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WO1997044767A1 - Systeme et procede d'enseignement assiste par agent - Google Patents

Systeme et procede d'enseignement assiste par agent Download PDF

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Publication number
WO1997044767A1
WO1997044767A1 PCT/US1997/008687 US9708687W WO9744767A1 WO 1997044767 A1 WO1997044767 A1 WO 1997044767A1 US 9708687 W US9708687 W US 9708687W WO 9744767 A1 WO9744767 A1 WO 9744767A1
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WO
WIPO (PCT)
Prior art keywords
student
εaid
materials
agent
information
Prior art date
Application number
PCT/US1997/008687
Other languages
English (en)
Other versions
WO1997044767A9 (fr
Inventor
Donald A. Cook
George Lukas
Andrew V. Lukas
David J. Padwa
Original Assignee
Agent Based Curricula, Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from US08/651,422 external-priority patent/US5727950A/en
Application filed by Agent Based Curricula, Inc. filed Critical Agent Based Curricula, Inc.
Priority to AU31383/97A priority Critical patent/AU3138397A/en
Publication of WO1997044767A1 publication Critical patent/WO1997044767A1/fr
Publication of WO1997044767A9 publication Critical patent/WO1997044767A9/fr

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Classifications

    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B5/00—Electrically-operated educational appliances
    • G09B5/06—Electrically-operated educational appliances with both visual and audible presentation of the material to be studied
    • G09B5/065—Combinations of audio and video presentations, e.g. videotapes, videodiscs, television systems
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B19/00—Teaching not covered by other main groups of this subclass
    • G09B19/06—Foreign languages
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B5/00—Electrically-operated educational appliances
    • G09B5/08—Electrically-operated educational appliances providing for individual presentation of information to a plurality of student stations
    • G09B5/14—Electrically-operated educational appliances providing for individual presentation of information to a plurality of student stations with provision for individual teacher-student communication
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B7/00—Electrically-operated teaching apparatus or devices working with questions and answers
    • G09B7/02—Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by a student
    • G09B7/04—Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by a student characterised by modifying the teaching programme in response to a wrong answer, e.g. repeating the question, supplying a further explanation

Definitions

  • This invention relates to a system and method for interactive, adaptive, and individualized computer-assisted instruction of students, preferably implemented on network connected computers. More particularly the system and method includes for each student an agent adapted to that student
  • the viewable on ⁇ screen aspect of the agent includes customizable multimedia
  • CAI the computer acts as a teaching machine.
  • a program presents instructional displays, accepts student responses, edits and judges those responses, branches on the basis of student responses, gives feedback to the student, and records and stores the student's progress.
  • Examples of CAI systems include those of Carbonell, 1970, Al in CAI, an artificial intelligence approach to computer- assisted instruction, IEEE Transactions on Man -machine Systems, 11:190-202; Osin, 1984, CAI on a national scale, Proc . 4 th Jerusalem Conf . on Information Technology, pp 418- 424; Seidel 1971; Koffman et al. , 1975, Artificial intelligence and artificial programming in CAI, Artifi cial Intelligence 6.:215-234.
  • Effective CAI instructional materials for a limited number of specific topics have been developed, as have special "authoring languages," which assist instructional developers on the tasks of designing instructional materials.
  • U.S. Patent No. 5,310,349 is exemplary of such CAI systems.
  • CAI systems do not adapt to their students. These systems merely sequence students through educational materials, based only on student performance during a current lesson and using only parameters such as recent responses and pre-requisite patterns. These systems do not gather or use information on more comprehensive student characteristics, such as past student performance, student performance on other courses, student learning styles, and student interests.
  • CAI systems do not recognize characteristics of their individual students. They cannot be individualized or made responsive to their students styles. Thereby, these system ignore those roles of a human tutor that can be of unparalleled significance in the education of an individual.
  • the human tutor assists in scheduling and prioritizing and in maintaining interest through proper reinforcement and knowledge of student abilities and preferences.
  • a human tutor observes and addresses patterns of errors and maintains a consistent manner of interaction across a broad range of subject matters and activities.
  • a human tutor effectively integrates the cognitive, personal and social aspects of the instructional situation. In other words the human tutor provides a level of individualization based on student styles and on requirements of the instructional task.
  • the human tutor provides an equally effective interaction with the teacher by accepting individualized instructions, collecting data and providing detailed reports.
  • the integrated learning system is a dedicated installation that is used in schools to teach basic strands of reading, mathematics and related topics, spelling, writing, and other language arts, from grades one to six, or perhaps to eight or nine (EPIE, 1990, In tegra ted
  • agents can operate in the client, the server, or both.
  • adaptive and personalized agent based systems have begun to be developed.
  • Systems with adaptive agents agents which learn from experience, has made gains with new techniques continually identified.
  • Adaptive agents have permitted new commercially viable adaptive systems implemented across networks.
  • an agent is a "go-between, " mediating relations in a manner whose function is understood with details being left to the agent itself.
  • the agent acts as a "stand-in” for its user, who is thus freed from direct manipulation of the network.
  • instructional applications there is an unmet need for an agent who serves two users: the school system and the individual student. This is the well-known role of the teaching assistant/tutor.
  • Agents can learn by a mixture of methods: observation, receiving feedback from its user, receiving instructions from the user, and consulting other agents concerning "similar problems.”
  • Approaches to the creation of agents with personal characteristics have begun to be explored. In this work, relevant techniques are found in the tradition of film animators who, through the portrayal of emotions, gave their characters the illusion of life.
  • Client-server architectures have emerged as the principal architecture of distributed computer systems.
  • Client systems running under sophisticated windowing operating systems, can support advanced object based software applications, including high speed graphics, animation and audio output.
  • Servers can store gigabytes of data and programs at central or distributed locations at quite reasonable cost.
  • Object oriented database systems have been developed to store structured data on servers.
  • Client systems in a striking change from only several years ago, now virtually all have multimedia capabilities, including high quality graphics, sound, and at least limited video playback capability. Text-to-speech software is presently available for use with these systems, and speech recognition software is on brink of widespread commercial acceptability on low cost platforms.
  • New authoring tools support graphical methods for generation of multimedia presentations and computer based instructional materials having corresponding sequencing logic.
  • Clients and servers can be linked remotely with increasing convenience and decreasing cost.
  • the Internet has emerged as a means of providing an inexpensive means of connecting computers to provide effective communications and access to information and other resources such as software. Further Internet developments that made the Internet truly universal include the HTML and the HTTP protocols, which provide platform independent access to hyperlinked multimedia information, and the JavaTM programming language, which provides platform independent software for Internet applications programming. Subsets of the Internet -- intranets -- have become an increasingly important means for disseminating information and enabling communication within constrained domains, such as a single school system or corporate enterprise.
  • ABSI Agent Based Instruction
  • An important object of this invention is to provide the student with a virtual tutor, by having agent software
  • agent adapted to each student that offers a high quality of individualized student interaction and that manages or controls instruction in a manner approximating a real tutor.
  • the agent exercises management or control over the computer- assisted instruction materials and provides information and help to the student, both synchronously and asynchronously to particular instructional materials. Agent behaviors are sensitive to both the educational context and to the history of student behavior.
  • the agent integrates data from several sources. From computer-assisted instructional materials, it accepts data on the methods of instruction adopted by particular materials and on student performance in the instruction. From the student, it accepts direct interactions as well as using the history of previous student performance stored in a student data object. From the teacher, it accepts data on customization and student assignments. From the school, it accepts data on assigned courses, data on analysis of student body performance, and educational standards and criteria. In a preferred embodiment, these inputs allow individualization of agent interaction. Alternative embodiments are responsive to additional data types and sources.
  • diverse agent behaviors are handled uniformly by a single means.
  • the diverse behaviors include encouragement and feedback, providing meta-cognitive help on ongoing instruction, managing or controlling and individualizing computer based instruction to the student's learning modes, and assistance with assignment management .
  • These diverse behaviors are selected from a set of potentially appropriate candidate behaviors. This set of candidate behaviors is ordered and the highest ranked behaviors are chosen.
  • the diverse agent behaviors adapt to the student based on a variety of information about the student.
  • the agent modifies its behavior on the basis of a growing history of interactions with the student over time, as this history of student performance is stored in the student data object.
  • the agent can also modify its behavior on the basis of teacher and school system supplied information.
  • Another important object of this invention is that the agent presents itself on-screen to the student with integrated, and optionally, animated multimedia persona, or preferably a plurality of persona (hereinafter called "personae”) .
  • the on-screen agent can appear as living entities, which in grade school can be comfortable "Study
  • the on-screen agent can be dramatized by a single character or by a cast of interacting characters.
  • the interaction between these actors can be individualized to reflect the pedagogical response of the agent.
  • story lines continuing across materials or session can be used.
  • the voices, gestures and motions of the personae are derived from the chosen behaviors, student personae preferences, and the history of recent behavior by selection from tables containing a rich variety of alternative sound and visual display objects. All elements of the on-screen agent display are then synthesized in an integrated display script calling for graphics, animation, video, or sound as appropriate. These scripts are then bundled into applets, run-time program fragments that represent a complete element of performance. This display is highly configurable by the student, the teacher, or the system administrator.
  • elements of the display objects can be created by artists, animators, singers, and so forth, as data snips.
  • Pluralities of data snips can be stored in libraries of dynamic clip art and then installed in an implementation of this invention. In this manner the on-screen agent personae have an appropriately contemporary, realistic, and engaging manner.
  • Data snips are, in general, short clips of sound, voice, graphics, animation or video, or combinations of these used to construct the on-screen agent.
  • a data snip can also be a complete prefor ⁇ natted animated sequence, perhaps in the format of a talking animated daily cartoon strip.
  • the method and system cf this invention is adapted to implementation on a variety of networks.
  • the interactive, adaptive, and self-paced computer-assisted instruction and homework provided by this invention is available to geographically dispersed students and from geographically dispersed schools.
  • an implementation of this invention as a "Homework NetworkTM" can make computer assisted homework available to students of all levels at home.
  • the student can also access homework materials at computers located in youth centers, libraries, schools and other locations.
  • the network on which this invention is implemented as an intranet configured of appropriate links and utilizing the known TCP/IP protocol suite, and as appropriate, ATM technologies, including World Wide Web, associated browsers, and mail format extensions. Implementation over the public Internet is equally preferred in cases where extensive connectivity is needed.
  • a further important object of this invention is to utilize augmented computer-assisted instruction materials which present to students a variety of interactive, adaptive, and self-paced computer-assisted instruction and homework materials in a manner which informs the agent of a student's progress and performance and which permits the agent to manage or control the materials to the student's pedagogic characteristics. Thereby, the ABI system can effectively guide and engage students in their educational tasks.
  • these instructional and homework materials are composed of materials data presented by a materials engine.
  • the materials data includes display objects containing the substance of the instruction, logic to sequence the display according to student input, and notations.
  • Notations are augmented definitions that serve to pass information to the agent concerning the materials and the student. For example, notations classify key sections of materials which are educationally significant student actions.
  • authoring tools assist in developing these augmented instructional materials.
  • Materials tasks and sequences are created and entered by instructional designers and subject experts. Notations are usually entered by instructional designers and can be customized by teachers.
  • the information passed in the notations is standardized according to an instruction materials interface standard.
  • This standard establishes a uniform way the materials independent data relating to student performance are to be provided to the agent and a uniform way for the agent to guide the student in a materials independent manner.
  • a further important object of this invention is to provide to the student a range of tools which are integrated with the agent in a manner similar to the instructional materials. These tools include general tools helpful to assigned instructional tasks, and special tools for group work and communication and for student scheduling.
  • the general tools include at least a calculator, an encyclopedia, a dictionary, a thesaurus, each appropriate to the several levels of students, which can access an ABI implementation.
  • the group work and communication materials allow, when permitted, message exchange, student linking into groups for joint work, and student linking into groups for structured work such as contests.
  • the student scheduling tool records assigned student activities and their priorities. In an embodiment, this tool can be consulted by the student to view schedules. It can be consulted by the system to prescriptively schedule required activities, to permit student choice, or to permit a mixed scheduling initiative. Finally, it can be consulted by the agent to offer scheduling advice to the student. Typically, student assignments are set by a teacher.
  • An object of this invention is reporting of student performance to students, teachers, parents, administration, or to other appropriate individuals in a business enterprise or other commercial versions. These reports include the unique data on the student's pedagogic performance accumulated and analyzed by the agent, as well as all the usuc.l and expected performance data on specific materials available in existing computer-assisted instruction systems. In a preferred embodiment this data is derived from the student data object, where all permanent student data is stored. These data objects are preferably stored in an object oriented database system against which are run reports of this data. It is an advantage of this invention in a school context that parents can have access to current data on their children, and thereby play a more informed role in their children's education.
  • NCs are low cost computers specifically designed to access intranets or the public Internet.
  • this invention is adaptable to multimedia PCs for some students, and to such special interaction technologies as can be advantageous to special students or students with special needs.
  • Typical interactive devices include keyboards, mice or other pointing devices, voice recognition, joy-sticks, touch activated devices, light-pens, and so forth.
  • Other devices, such as virtual reality devices, can be added as they become commercialized.
  • Fig. 1 illustrates in overview fashion the principal functional components of and parties in the ABI system
  • Figs . 2A and 2B illustrate in overview fashion an implementation of the functional components of Fig. 1
  • Fig. 3 illustrates an exemplary student display screen of the implementation of Fig. 2;
  • Fig. 4 illustrates in more detail exemplary screen interaction between the on-screen agent and the instructional materials of the implementation of Fig. 2;
  • Fig. 5 illustrates an exemplary interaction of a student with the ABI system implementation of Fig. 2 ,-
  • Fig. 6 illustrates in more detail the software components and hierarchy in the implementation of Fig. 2
  • Fig. 7 illustrates exemplary message flow through the implementation of Fig. 2;
  • Fig. 8 illustrates agent action processing of Fig. 7 in more detail ;
  • Fig. 9 illustrates agent behavior processing of Fig. 7 in more detail
  • Figs. 10A and 10B illustrate the structure of student data object of Fig. 7 in more detail
  • Fig. 11 illustrates exemplary processing of the student data object of Fig. 7 ;
  • Fig. 12 illustates an exemplary sequence of student metarequests and agent metare ⁇ ponses .
  • Sec. 5.1 presents a general overview of the Agent Based Instruction system.
  • Sec. 5.2 describes the preferred hardware and operating software configurations.
  • Sec. 5.3 describes details of the instructional interface between the ABI system and its users.
  • Sec. 5.4 describes in a general fashion the software structure of the ABI system with subsequent sections describing each component in a more detailed fashion.
  • Sac. 5.5 describes the instructional materials and the tools in a more detailed fashion and
  • Sec. 5.6 describes the agent in a more detailed fashion.
  • Sec 5.6 includes detailed description of the preferred interface between the agent and the materials in the ABI system.
  • this invention is described in the context of a school system, with examples drawn primarily from elementary education. This invention is not so limited. It will be apparent to one of skill in the relevant arts that this invention can be applied at all levels of public and private education, from pre-school through university, and to all forms of commercial or corporate education. In all these contexts, this invention has particular utility in making education and training available at school, at the office, at home, at schools with geographically dispersed students and to students at geographically dispersed schools, and at other types of locations. Further, it will be apparent that this invention can be applied in contexts other than education where monitored interactivity and individualization are to be provided, as in child care or weight loss.
  • Agent agent software together with the data it references executing in an ABI system.
  • ABSI Agent Based Instruction
  • Agent Software software modules that generate responsive, adaptive, and individualized behavior in the ABI system, preferably implemented according to methods from artificial intelligence.
  • Applet an executable program fragment advantageously downloaded to a client across the network, in the ABI system applets are particularly used to represent a complete element of on-screen agent actions, or performance, ( e . g. , a character scratching its head and saying an utterance) and can reference various data snips of animation, sound, and scripting information.
  • Authoring Tools programs used by instructional designers to develop materials data, such development includes inserting notations.
  • Cast a plurality of persona ("personae") representing the on-screen agent.
  • Character an individual persona in the cast of the on ⁇ screen agent .
  • Concept Coach a possible alternative name for a persona in the cast of an on-screen agent that is suitable for high school and adult students.
  • Data Snip an elementary piece of sound, voice, animation, video, or a graphic,- data snips can be combined, preferably by an applet, to represent a complete element of on-screen agent action.
  • ELF Electronic Learning Friend
  • Instructional Materials the components of a course of instruction, such components are selected according to the course and can include prerequisite tests, pre ⁇ tests, lessons, and unit tests.
  • Materials Data the content of instructional materials.
  • Materials Engine software modules that reference instructional materials data and tools data to present the instruction and the tools to the student.
  • Meta-request a student request directly to the on-screen agent, an exemplary request is 'asking for a hint.
  • Meta-response all responses to a student produced by the agent software, as distinguished from presentations by instructional materials, tools and communications.
  • Network the hardware and software connecting student client computers to school servers in an ABI system,- the network connections can comprise fiber optic links, wired links, or terrestrial or satellite wireless links.
  • interface information inserted into materials data that causes the materials engine to send and receive messages from the agent software create standardized interface messages between the agent and the materials .
  • On-screen Agent presentation by the agent software on the student's display using such media as sound, voice, graphics, animation, video, or other multimedia modality; this presentation preferably displays one or more life-like personae.
  • Persona a character in the cast of an on-screen agent.
  • Personae the collective plural of persona.
  • Student Data Object data about each student which the agent software references in order to provide responsive, adaptive, and individualized instruction to that student; this data is updated during course of each lesson and is advantageously stored as one object, or alternatively a few linked objects, in the ABI system.
  • Study BuddiesTM a possible alternative name for personae in the cast of an on-screen agent that is suitable for elementary school students.
  • Tools Data the content of tools supporting particular instructional materials,- tools can include a dictionary a calculator, or an encyclopedia,- and so forth, and tools data are the content of the dictionary, the calculator, or the encyclopedia.
  • Utterance a text or voiced response by on-screen agent.
  • Virtual Tutor the ABI system components acting together to emulate a human tutor,- from an individual student's perspective, the Study BuddiesTM, ELF, or Concept Coach appears as his or her personal tutor.
  • Fig. 1 illustrates the principal actors and the principal functional components in an ABI System. These include, generally, materials engine 102, agent software 108, and student data object 109, all of which interact with student 101 and with teachers and administrators 106 via a computer network described below in conjunction with Fig. 2 to create a virtual tutor of student 101.
  • Student 101 is typically one of many students enrolled in a school or similar institution.
  • the virtual tutor Central to the ABI System is the virtual tutor individualized to each student, which formed by the functioning of agent software 108 with student data object 109, which stores characteristics of student 101 and assignments and standards set by teachers and administrators 106.
  • Other actors not shown in Fig. 1 can be relevant in particular applications, for example, parents in the case of primary and secondary education.
  • Materials engine 102 presents educational content such as instructional units, homework assignments, and testing to student 101.
  • the educational content includes instructional materials data 114, communications materials data 104, and tools data 115.
  • instructional materials data 114 include computer based instructional materials similar to those known in the art but, importantly, augmented with notations for use in this invention.
  • the materials also include various tools 115 appropriate to particular instructional materials, such as a calculator for mathematics, a dictionary for writing, access to on-line reference sources for research, and so forth.
  • materials can also include communication materials data 104, which define and provide communication with other students 105 for instructional purposes . Such purposes can provide, for example, the tutoring of one student by another more advanced student, joint work of several students on one instructional materials lesson as permitted, and educational contests, such as spelling bees.
  • this invention is equally adaptable to other forms of materials that function in the framework of Fig. 1, in particular interfacing to the agent software as indicated by arrow 111, and that are useful in a particular application of this invention.
  • materials appropriate for child care contexts can differ from the above three classes by, perhaps, having different paradigms of interactivity.
  • the structure and course of interactions 103 between the student and the materials is preferably governed by paradigms of educational psychology and sound educational practice, such as are described in the exemplary reference Englemann et al . , 1982, Theory of instruction: principles and applications, New York: Irvington Publisher.
  • student 101 can make requests and receives responses from materials engine 102 and, in turn, materials engine 102 can make requests and receive responses from student 101.
  • the " materials engine can adjust its sequence of presentation in response to student responses.
  • the requests and responses exchanged between the student and the materials engine can follow several patterns known in the arts of computer based instruction and which, for example, include the following.
  • the student can respond to questions presented by the materials engine, and in the course of responding, can ask for advice or hints, the use of a tool such as a calculator, or other relevant assistance.
  • the student can advance to the next item, lesson, or unit upon successful completion of the present item, lesson, or unit.
  • the student in case of error, can request, or automatically be presented with, appropriate repeat, review, or remediation materials.
  • these patterns of interactions can be analyzed to provide more adaptive responses from the system.
  • Teachers and administrators 106 also interact with materials engine 102 for several purposes, as represented by arrow 107.
  • teachers can customize existing materials by adding additional items, modifying existing items, altering the order of item presentation, changing the notations (see infra . ) governing agent interaction, and so forth.
  • a teacher can create particular instances of materials suitable for one class, a group, or even one student.
  • the materials engine can directly report student progress to teachers and administrators. For example, this can be done by entering notations that generate messages for the teachers .
  • instructional designers can create, or "author, " materials for use in this invention. Such materials can be original or can be derived from existing textbooks, workbooks or media material.
  • Authoring instructional materials in a course suitable for interactive instruction typically comprises several steps, including decisions about the objects to display to the student, the sequencing of these objects, and the interactions with the agent.
  • the first step is the selection of objects which carry the education content for presentation to a student.
  • Objects can include visual display items, such as text, graphics, animation or movies, audible display items, such as voice, audio and so forth.
  • They can include input items known in the computer arts, such as buttons to select, selections to chose from, text to enter, hypertext and hypermedia links, functions to perform with student input, and so forth.
  • the second step is the selection of the sequencing logic for the ordered display of the objects to the student and the educationally appropriate reaction to student requests and responses .
  • the sequencing logic can reference instructional controls set by agent software 108, such as a command to increase example density, and preferably is chosen in light of principles of educational psychology and practice as detailed above.
  • the third step is the specification of interactions with a student's agent or virtual tutor, a key component of the ABI system. This specification is made by augmenting the sequencing logic with "notations,” which are referenced, called, or executed by the sequencing logic during object presentation and that communicate with the agent, in a preferred embodiment by exchanging messages .
  • the agent builds an adaptive model of its student's pedagogic characteristics, in other words the student's cognitive styles, by monitoring the course of the student's interactive instruction.
  • the notations are the means for this monitoring.
  • the authored materials are indexed and stored in the files of the ABI system, preferably on materials server systems .
  • ABI authoring tools differ from authoring conventional instructional materials in that notations are present in these materials to enable the agent software to update the student data object, to monitor and modify the instruction, student's use of a tool, or a communication task.
  • ABI authoring tools support and facilitate the conversion of existing materials to the ABI instructional format.
  • agent software 108 is comprised of agent software 108 in conjunction with a student data object 109 unique to each student.
  • agent software monitors its student's instruction, it builds an adaptive model of its student in student data object 109.
  • agent software 108 acts, first, to manage or control the student's instruction, and second, to directly guide the student in order that the total ABI system can present education to each student in an optimal fashion best adapted to the student's evolving abilities, skills, and preferences.
  • the agent becomes a virtual tutor by acting as a student's personal and individualized tutor.
  • the agent manages or controls instruction of student 101 by directly controlling materials engine 102 in its presentation of materials data 104, 114, and 115 through interaction with the materials engine, as represented by arrow 111.
  • the agent preferably manages or controls the materials engine in two manners, synchronous with materials data presentation, such as when the materials engine encounters an appropriate notation in the data, makes an agent request, and waits for an agent response, and asynchronous with the presentation, such as when the agent software adjusts control parameters which the materials engine references at decision points.
  • Examples of synchronous control are an ' instructional material asking the agent for permission to allow the student to use a tool, to receive a hint, or to be given remediation, or a communications material asking the agent for permission to permit the student to engage in a particular type of communication with certain other students.
  • An example of asynchronous control is the agent setting of pedagogic parameters, such as coaching parameters that the materials engine uses to adjust its presentation, according to the pedagogic characteristics of the student.
  • Exemplary coaching parameters include the time pacing of exercises, the new concept seeding rate and the density of examples.
  • the materials can present interactive instruction according to optimal values of the pedagogic characteristics or cognitive styles of each student as determined from the agent's observation of its student.
  • agent software 108 directly guides the student by exchanging communication with the student, as represented by arrow 112.
  • Student communication also preferably occurs in two manners, synchronously, in which the student directly makes meta-requests of the agent tutor and receives meta- responses and second, asynchronously, in which the agent tutor itself generates a meta-response in response to some instructional event.
  • requests and responses are prefixed with "meta" when they are exchanged directly with the agent.
  • Meta-requests include student questions to the agent - for example: How am I doing? What should I do next? Can you say that another way? - or student requests - for example: I need a hint,- I need help. The agent responds to each student question or request.
  • Agent meta-response ⁇ can be generated, for example, when the student takes too long to complete an exercise, when the student makes a series of repeated errors, or when the student achieves good performance. Agent meta-responses can be drawn from such categories as reminders, encouragements, reinforcements, paraphrases, jokes, progress summaries, and so forth. Communication with the agent, represented by arrow 112, include direct student meta-requests that generate agent meta-responses . Other communications derive from instructional event messages generated and communicated by augmented notations in materials 104, 114, and 115. An event received by the agent can generate no meta-response at all or alternatively can generate an asynchronous type agent meta- response.
  • the materials sequencing logic presents display objects to the student and receives inputs from the student
  • the materials data author places one or more notations.
  • these notation are referenced, called, or executed, important variables and parameters educationally relevant at this significant point are gathered into a message, along with an indication of the type of the educational event.
  • These messages are events which are then sent to the agent.
  • an educationally significant point is the beginning of a new instructional sequence.
  • the corresponding event message can include an indication of the topic to be covered, the expected level of difficulty, the expected time to complete, and the educational paradigm adopted.
  • Another educationally significant point is the receipt of a wrong answer.
  • the materials can generate several messages: a first message can include the time required to make the answer, an indication of the type of error, and an indication of whether the answer is completely wrong or only a near miss,- a second message can include text parameters ("say-it” type message) if the agent chooses to make a specific text or spoken comment about the error,- finally, a third message can include the screen location best representing the error ("point-it" type message) to use if the on-screen agent chooses to point to the error or move to the location of the error.
  • Another educationally significant point can be a long delay in receiving the next student input, at which point the materials engine can send an asynchronous message indicating the time elapsed.
  • Tools data 115 generate events similar to messages from instructional materials.
  • Communications materials 104 can generate events recording a communication request or an initiation of communication with certain other students for a certain task.
  • communications materials can generate events recording how this student in progressing with the shared materials,- in the case of a contest such as a spelling bee, events recording how this student is progressing in the contest with respect to other contestants .
  • agent software 108 also receives messages describing the progress of the student through specific instructional materials.
  • messages can include information that the student is making errors in problems requiring finding common denominators .
  • event message should preferably all information that can be of interest to teachers and administrators for tracking student progress and tracking course adequacy.
  • Agent communication preferably utilizes all the modalities of input and output available in a particular implementation of this invention, including text, audio displays such as voice and sound, and video displays such as graphics, animation, and realistic movie clips.
  • the agent can select the display of sound and video clips, from a data snips library, that the student finds pleasing.
  • the agent can further make reward graphics available on the student's screen for a period of time.
  • the agent can point to the screen location of the error.
  • the on-screen agent can assume various display personae during student communication.
  • persona means the effect conveyed to the student of the combined and coherent presentation of multiple display modalities to emulate a particular, apparently living, personality. For example, in the case of elementary education, this can be the selection of tone and animation to emulate a pleasant animal or a known cartoon character.
  • characteristics of the display persona can be selectable by the student according to the student's preferences.
  • the personae can be specified by the instructional materials, the teacher or the administrator overriding student persona preferences.
  • Personae for an elementary school student can be selected from well-known cartoon characters and can perhaps be called “Study BuddiesTM.”
  • Persona for commercial or corporate education can be adapted to the organizational ethos and can perhaps be called a "Concept Coach.”
  • Presentations for intermediate levels can be called an Electronic Learning Friend (“ELF”) .
  • ELF Electronic Learning Friend
  • the ABI system through its network, software and database acts as the student's virtual tutor, from the elementary school students point of view, the "Study BuddiesTM" are his/her personal tutor. Realism in voice, gestures and movement reinforce this relationship.
  • Agent software 108 in the ABI system builds an adapting pedagogic or cognitive model of its student in student data object 109 that is independent of the specific materials.
  • Event messages to the agent software from the materials engine preferably include the information from which this model is built. In general, event messages must include such content as is necessary to describe and parametrize the pedagogic or cognitive style models adopted by the materials in an implementation of the ABI system.
  • the student data object 109 collects all the permanent data about the student maintained by the ABI system.
  • the data objects for all the students are collected for permanent storage in a database system.
  • this is an object oriented database, although this data can be advantageously stored in standard relational databases.
  • the various subtypes of student data in the student data object can be separated into separate objects and stored in separate databases.
  • the materials specific progress data separately from the materials independent global student data.
  • the student data object is stored as one structured object.
  • it can be stored as a plurality of objects, each object of the plurality perhaps storing only one subtype of data.
  • the student data objects are accessed not only by the agent software 108, but also by teachers and administrators 106.
  • the data object is referenced by the agent in order to generate its actions and is updated by the agent as it processes events and student meta- requests.
  • the data object is referenced by teachers and administrators in order to track the student progress and to generate reports concerning the students and materials in the ABI system. Teachers also update the data object to enter schedule information for the student's assignments. Administrators update the object in order to enter the courses and materials the student must master and specify standards and criteria the student must meet .
  • FIGs. 2A and 2B illustrate an exemplary preferred structure implementing the principal conceptual and functional components of the ABI system as illustrated in Fig. 1.
  • a preferred implementation of this invention is based on a plurality of computers interconnected by a network.
  • certain computers are specialized for certain functions, such as student client systems for providing student access or system servers for storing system software resources. Therefore, an exemplary preferred ABI system includes one or more student client systems 201, at which student 202 receives instructional presentations including homework. Other student clients are generally indicated at 203 and can be located at school, at home, or at the office.
  • the system further includes one or more servers 204, at which teachers and administrators 205 gain access to the system.
  • a network which consists of transmission medium 206 and local attachments 207.
  • the network illustrated in Fig. 2A is of a bus-type configuration, as in a local area network perhaps using collision detection or token passing protocols or both, this invention is adaptable to all forms of networks which support adequate transmission protocols, such as those that are functionally similar to the TCP/IP protocol suite, and as appropriate, ATM technology.
  • the invention is adaptable to networks constructed from switched or non- switched links to a central server, which can be configured of several LAN attached server systems, to networks including CATV cable or optical links, to networks including radio links either terrestrial or satellite, and to public or private packet switching networks.
  • a preferred public packet switching network to which this invention is adaptable is the Internet.
  • ABI system nodes can be linked to the Internet in any convenient manner known to those skilled in the art and can include security boundaries (known a firewalls) to prevent unauthorized access.
  • an ABI system implementation can be an "intranet,” that is a network constructed according to TCP/IP protocols but using private links of the types enumerated above, and as appropriate, ATM technologies.
  • student client system 201 includes memory 208, which is RAM type real memory or a virtual memory based on RAM type memory and a backing store.
  • the client system has no permanent disk storage.
  • a preferable student client can be a low cost network computer ("NC") .
  • a NC is a computer with processor, RAM, and network interfaces sufficient to access intranets or the Internet.
  • a NC is preferable in cases when high-bandwidth network access is available.
  • the client system can have one or more disc drives 209 which can be used as a pre-fetch buffer or a read-only cache.
  • the " disks preferably are magnetic, although in a less preferable embodiment they can also include CDROMs . This optional capability serves to enhance communications efficiency in cases where the network has relatively low bandwidth.
  • Large files can be downloaded in advance of a student session or the student client can cache read-only data across sessions obviating the need for downloading such files. Such caching requires the operating system components to maintain some form of version control of the read-only data.
  • the student data object which contains all permanent and read-write student data, is stored between sessions on a server. This permits a student to access the ABI system services from any available client system at any time by simply downloading the student data object to that client system.
  • I/O interactive input/output
  • standard devices include pointing devices, such as mouse 211 or a trackball, age appropriate keyboards, optionally speech recognition, and so forth. Speech recognition will permit brief conversations with the "Study BuddiesTM,” or other personae, in limited areas.
  • the invention is adaptable to special input devices appropriate for particular groups, such as the handicapped, and to devices yet to be constructed.
  • Virtual reality (“VR”) interface devices such as VR gloves and VR display helmets can have immediate applications for special needs students.
  • preferable devices include computer display 212, for displaying objects such as text, graphics, animation, and video, and audio output devices for voice and sound clips.
  • Fig. 2A also shows an exemplary screen layout for a student client that exemplifies the principal functions of this invention.
  • the screen is preferably partitioned so that principal components of this invention are displayed; and important student actions are represented by icons or buttons.
  • the screen includes materials and tools area 220 to the left, agent area 215 to the right, and a system toolbar 218, which includes a student customization area 221 at the top.
  • the size of the 1 screen partitions illustrated preferably change from time to time in response to student customization or display requirements.
  • either the materials area or the agent area can enlarge, perhaps up to the entire screen as needed.
  • Materials area 220 is for the instructional materials, tools, and communication materials to present visual display objects and for these components to receive interactive input. This area is further subdivided into display region 213 and a materials specific toolbar 214.
  • On-screen agent area 215 is for the on-screen agent to receive meta-requests and to display synchronous and asynchronous meta-responses .
  • an exemplary on-screen agent consisting of a single persona 216 and a meta-request icon 217. The persona can move to other screen areas as required.
  • the system area at top includes toolbar 218 for selecting particular available system components.
  • selection icons 219 for the calendar and scheduling tool.
  • Part 221 of the system area can be reserved for student customization, for example for the display of reward graphics "given" to the student by the agent or virtual tutor.
  • Functionally illustrated in Fig. 2A is an exemplary memory organization of a student client system when a session is in progress with materials being presented.
  • Layer 222 comprises operating software and network communications.
  • This software provides, among other services, support for I/O devices attached to the client, a file system with cache control, lower level network protocols, such as TCP/IP and ATM, and higher-level network protocols, such as HTTP V2.0.
  • Basic shared ABI system capabilities are provided by executive software 223.
  • the executive software verifies student identity and access authority, establishes communications sessions with the system servers as required during client start-up, downloads from the student object database the student data object corresponding to the student in session at this client system, downloads instructional materials scheduled for this student, and download executable software required from the systems servers as-needed.
  • the instructional material and the software are read-only and are not changed.
  • the student model is updated by the agent during the student session and modified parts are uploaded to the student database on a server for storage Such downloading can utilize higher level network transfer protocols, or alternatively, directly use lower level network protocols
  • Agent software 225 certain parts of student data object 226, and certain instructional materials software 224 have already been downloaded
  • the materials are displaying CDject ⁇ m screen area 220, forwarding events to the agent and receiving agent management or controls, as indicated by arrow 227
  • the agent is displaying its persona(e) in screen area 215, interacting with the materials, as represented by arrow 227, and is referencing and updating data in student data model 226, as represented by arrow 228
  • the student client system further includes standard components not shown, such as a microprocessor and input/output interfaces.
  • standard components such as a microprocessor and input/output interfaces.
  • Alternative implementations of the student client system are within the scope of this invention.
  • student client system function can reside on a server system.
  • the client system can be implemented as two machines, wherein a first machine performs substantially all the computations and a second machine is for student interaction and sends student input and receives display instructions from the first machine
  • the ABI system further includes one or more server systems 204 of Fig. 2B with sufficient large capacity discs 230 for storing all student data objects in the student database, all instructional materials, and all software used in the system.
  • the network is used to distribute the software, student data objects and instructional materials form the servers.
  • the server can be a central host system.
  • servers preferably have increased performance and higher speed network connections 231 in order to make this stored data quickly available to the one or more student client systems. Access to the body of student data allows teachers and administrators to track student performance by class, grade, subject, school and so forth. This statistical data is also input into agent processing.
  • the server systems are preferably configured as shown in Fig. 2B and are loaded with software 232 providing the following function.
  • First there is operating system, network services, and file server layer 233.
  • layer 233 also provides a file server facility including file backup and version control.
  • System manger 234 includes facilities for access control, authenticating student access requests and limiting file access to authorized users. For example, students can be limited to only their personal files,- parents to their children's files and curricular related data; teachers to files and student data objects for their classes,- while certain administrators have unlimited access.
  • the system manager can also maintain any necessary system logs.
  • Student data object database 235 is explicitly illustrated Student data objects reside on the server systems when the associated student is not in session.
  • These objects contain the data which is the source of all teacher and administrator reports, data by which these staffs schedule student courses and assignments, and data representing the pedagogic model of the student used by the agent software.
  • Instructional materials databases 240 and directories of executable software also reside on the server systems. When group communications is in use, agents and communication tasks monitoring the groups can reside on the servers.
  • the servers also contain areas 237 for administrative data and for reports and report software of interest to the administrative staff.
  • the servers contain teacher areas 238 for data and report software of interest to teachers.
  • certain instructional materials can be made available specifically for the teaching staff, along with an individualized teacher agent acting as a virtual tutor for the teachers.
  • the facilities of the ABI system can be used to simplify teacher familiarization and system training.
  • teacher training can be user instruction in the ABI system itself, or can be teacher versions of student materials designed to assist the teacher in his/her use and customization (in the nature of today's teacher versions of textbooks) .
  • teacher specific tools for example, to assist in generating student reports and class management.
  • the server system contains special instructional materials and associated teacher data objects 236 for performing this instruction.
  • Client systems for teacher access have agents unique to individual teachers .
  • the flexible server structure of the system permits administrative and teaching staff to perform their specific tasks on any computer system with enough computing resources to support these tasks .
  • necessary system components are downloaded from servers to these temporary client systems. Thereby, these personnel are not limited to sessions on server systems.
  • materials authoring can be done on server systems, client systems, or on separate systems not interconnected with a given ABI system. To make authored materials available, they are transferred to and indexed in the appropriate server system databases.
  • Figs. 2A and 2B can be constructed on standard hardware platforms meeting the requirements discussed in this section.
  • ABI ABI system
  • Networks permit students and teachers to participate at more than one school, and, further, permit delivery of homework and instruction to remote locations.
  • the client system must access student data objects, instructional materials, and ABI software from the network.
  • Access to all system components is typically provided from ABI system servers attached to the network. It is preferable, to use a single large network server in place of several smaller network servers. In all cases, it is preferable to store the updatable student model objects on server systems, in order that they can be downloaded to whatever client system a student accesses.
  • Networks suitable for an ABI system can be of any configuration and protocol that meets the system's client- server communication and object transfer requirements, where the client is either a PC or a network computer ("NC") . Suitable networks can be private or public.
  • the preferred ABI network in the case of PC clients is an intranet running the TCP/IP protocol suite and utilizing ATM technologies as appropriate.
  • utilizing a single large server such a server can be directly connected to the intranet or Internet.
  • these servers can be connected into a cluster by a LAN, preferably an Ethernet LAN.
  • the ABI network is built from a local Ethernet LAN with remote connections to telephone lines using 28.8 Kbps modems, or other network links.
  • the network can by visible to the public Internet if adequate security systems (firewalls) prevent unauthorized access. This can make wider access available at lower cost than by switched telephone remote connections .
  • the ABI LAN can be further connected to other ABI LAN's and to other networks, such as the Internet, by standard use of routers and gateways.
  • An exemplary protocol for an ABI System network is TCP/IP supplemented with a client-server protocol such as HTTP and object transfer protocol, such as a multi-format mail protocol.
  • client-server protocol such as HTTP
  • object transfer protocol such as a multi-format mail protocol.
  • ATM technologies are used as appropriate .
  • Remote clients are expected to be indirectly connected to the ABI network. These connections can consist of routing over a public network cr direct dial-in connections. These connections can be of either low-speed or high speed.
  • the ABI system can be implemented on networks such as @Home (Mountain View, CA) , which use a combination of ATM, cable modems, TCP/IP and other technologies.
  • the ABI system can also be hierarchically configured on new network topologies for distance learning in areas with limited communications infrastructure.
  • Primary central servers with ABI software and instructional materials communicate with remote secondary servers over broadband satellite communication systems.
  • Student clients connect to the local secondary servers through wired or wireless means .
  • the client hardware consists of client input/output ("I/O") , client CPU and memory, and client network access.
  • client I/O client input/output
  • standard input devices such as keyboard and mouse, or other pointing device
  • Color graphics output capability adequate to support partial screen animations is preferred. Sound generation and output are preferable on ABI client systems.
  • Text-to-speech conversion can be done either in software or in hardware. When economically available, full video capability, for example by providing video decompression hardware such as MPEG decoders, and speech recognition, for example with hardware assists, are also preferable.
  • the ABI system is also adaptable to special I/O devices appropriate to special student groups, such as the very young or the handicapped. These include, for example, simplified keyboards, touch panels, VR devices, and so forth.
  • Client memory must be sufficient to contain resident operating system components, resident ABI executive software, and dynamically loaded segments of the student data object, instructional materials, and code.
  • High performance CPU's together with high performance graphics hardware and memory is preferable to enable more advanced presentation effects.
  • ABI software In embodiments where part or all of the ABI software is implemented in special languages, hardware or software assists for these language are preferable. For example, where such a special language is JAVATM (Sun Microsystems, Mountain View, CA) , JAVATM chips, which enhance performance of the JAVATM interpreter, are preferable.
  • the ABI client node in certain embodiments can be a JAVATM enhanced network appliance adapted to Internet communication access and the HTTP V2.0, or equivalent client-server protocol.
  • Client communication hardware can be adapted for either local or remote attachment.
  • Local access requires network access hardware,- remote access requires a communication capability.
  • This invention is adaptable to lower speed access over switched telephone line services, preferably using 28.8 Kbps modems or ISDN interfaces (64 or 128 Kbps) . These bandwidths are adequate for sessions with materials using only voice and limited animations. Prefetching and caching can be required to make fullest use of other materials at this bandwidth.
  • This invention is also adaptable to high speed access over any available high speed links, such as Tl (1.5 Mbp ⁇ ) , T3, ADSL telephone lines, or cable modems (several Mbps) , or other means of high speed access. These bandwidths permit full access to materials without limitation. If economically available, high speed - access is preferred. With greater communications bandwidth, the on-screen agent can appear more life-like.
  • Standard client software includes an operating system and communication software.
  • the operating system preferably has interfaces to client I/O devices including communications capability and network access, such as a TCP/IP stack.
  • ATM interfaces are present if necessary.
  • it also has means for establishing sessions with servers, for providing file server services, and means for security as specified shortly.
  • the implementation language or languages of this invention preferably have several features related to the implementability, maintainability, and extensibility of ABI.
  • the implementation language preferably provides a degree of modularity similar to that provided by object-oriented programming languages . It preferably provides means of dynamically loading acros ⁇ a network and executing additional software segments during program execution. It preferably provides means of accessing all input devices and of controlling the output devices in a high level display object fashion. It preferably provides a threaded or multiprocessing capability. Less preferably, this invention can be implemented in any computer language, including a ⁇ sembly language.
  • a currently preferred client system is a IBM type PC with a PentiumTM 120 Mhz processor, 16 MB memory, a 1 GB disk drive, a Soundblaster compatible sound card with speakers, a medium performance graphics card such as a Diamond Stealth card with 2 MB of graphics memory, an Ethernet card or a communication card and a 28.8 Kbp ⁇ modem, and standard keyboard and pointing device such as mouse.
  • the operating system is WindowsTM 95 with network services provided by a World Wide Web browser equivalent to Netscape 2.0 or better and capable of running JavaTM applets. JavaTM together with standard system and graphics classes is the implementation language.
  • the primary function of the server systems of this invention is to store databases of executable software elements, of student data objects, and of instructional materials .
  • the latter two consist of heterogeneous and structured elements .
  • the ⁇ e elements can be stored in a relational database such as supplied by the Oracle Corp. or the Sybase Corp.; they can be stored a ⁇ specialized data files,- or they can be stored in an object-oriented database system such as ObjectStore (Object Design Inc., Burlington, MA) .
  • the operating system of the server nodes must support whatever database systems are selected as well as network and application server software to access the databases.
  • Application database server software of this invention preferably provides database access and version control and downloads database elements on client request .
  • the preferred server hardware and software can vary widely depending on the number of clients to be simultaneously served. This number can vary from 20 at one school to more than 5000 across an entire school system. The number of servers and database distribution across 'a server cluster can be adjusted by means known in the art to satisfy projected peak loads.
  • a suitable medium performance server system can be configured on a high end INTEL Pentium or DEC Alpha system with adequate memory and disk space. WindowsTM NT is an adequate server operating system, and Internet server software similar to that from Netscape is adequate for network access.
  • the preferred database is an object oriented database such as ObjectStore.
  • application database access uses a common gateway interface ("CGI") program also providing database access and version control.
  • the CGI access program can be implemented in C++, a suitable object oriented programming language capable of accessing interfaces to ObjectStore databases.
  • ABI System Security Security and access control present additional client and server requirements which are importantly part of an implementation of this invention. Security and access control can be maintained by careful selection of management policies, security software, and security hardware. These elements are described in this section in the order of authorizing and controlling access, operating system and network security requirements, and implementation language issues.
  • the primary means for authorizing and controlling access are pas ⁇ word ⁇ .
  • Sy ⁇ tem management of passwords preferably includes ensuring that user passwords are secure, not easily guessed, and are periodically changed.
  • This invention is also adaptable to any other means of access control, including for example, pas ⁇ ive and active identification cards and recognition of certain personal characteristics, such as voice.
  • Access protection can be preferably provided by limiting access to system resources - database and file - based on a user's password. For example, access protection can be implemented in the CGI application access programs .
  • the operating system in clients and server ⁇ of this invention is preferably of a tested security level.
  • This base security can be enhanced by a variety of techniques and tools that can provide increased levels of security for additional investments.
  • Such techniques and tools include firewall machines, that is dedicated network gateways than filter incoming and outgoing packets according to content criteria, and monitoring software, such as tripwires, that observe system events for suspicious combinations.
  • encryption can help protect sensitive and valuable data from illegitimate access by those without the key. Encryption in hardware and software can be provided according to methods known in the art, such as the Rivest-Shamir-Adelman (RSA) public key algorithm or the data encryption standard private key algorithm.
  • RSA Rivest-Shamir-Adelman
  • the implementation language importantly should address the security exposures thereby created.
  • a malevolent and knowledgeable user can create or modify the downloaded code to perform illegitimate operations within the client system or access restricted information from the server.
  • the JavaTM language is preferable in these embodiment because it now significantly addresses these problems and further improvements are constantly being made.
  • Examples of JavaTM security measures include limiting access to client system resources, particularly the file system and network connections, preventing downloaded software from 'spoofing' local software, and providing byte-code verification to test code for possible security violations.
  • Any implementation language for an ABI system preferably offers similar or improved security features .
  • Each student receiving ABI instruction on a specific topic is presented with a combination of instruction, utilities, and on-screen agent interaction. Because the ABI System provides individualized interactions, each such presentation comprises a unique mixture of visual, audio, and software elements. Also, each user's consumption of hardware and communications resources differs .
  • the ABI System therefore preferably incorporates metering technology to track the utilization of the different elements of the ABI Sy ⁇ tem. Such information can be used to determine payments tc the creators or providers of these elements and/or as a basis of charges to the user. Further, this information can be used by ABI System providers to determine absolute and relative usage of various components of the system. Parties interested in such information include providers of server hardware, application software, networks, instructional and tool content, authoring tools and on-screen agent animations, scripts and utterances. Finally, this information can be used to monitor system performance and utilization.
  • the ABI sy ⁇ tem comprises hardware elements, standard software elements, special application software elements, and content elements typically supplied by different providers.
  • Hardware elements include networks and other communications links, server CPUs, and disks.
  • Standard software elements include operating systems, database packages, and communications software.
  • Application software includes instructional playback engines, schedulers, and agent software.
  • Content includes instructional materials, utilities such as dictionaries and encyclopedias, and on ⁇ screen agent animation and utterances .
  • ABI metering comprises the elements of the metering utility software, of tagging of all ABI component elements, and of the preferred methods of monitoring.
  • the pricing and compensation model is preferably provided by sy ⁇ tem administrators.
  • the ABI Metering Utility Software measures usage and maintains usage data in a 'multidimensional usage model' during each student session.
  • the MUS is resident at run-time on the student clients and the system server(s) .
  • the MUS is a component function of the Session Manager with inputs derived from the Executive Software, Agent Software and the Materials Engine.
  • MUS is a component function of the System Manager Software.
  • each ABI element is tagged with an ownership identification code similar to a product barcode.
  • the first digits indicate ownership and subsequent digits indicate the specific component.
  • a ⁇ the elements move through the ⁇ y ⁇ tem from server to client and within the client, the use of the ⁇ e elements is metered.
  • the Materials Engine uses materials ownership tags to meter content.
  • the agent utterance generation and visual display generation uses tags of the data snips to track ownership of on-screen agent actions.
  • the ses ⁇ ion and ⁇ creen manager keep ⁇ track of which element of the screen is active.
  • This invention is adaptable to any method for measuring usage appropriate to the particular component elements. In particular, four preferred methods of measuring usage are by- time, by-interaction, by-unit and by-packets.
  • the by-packet method is performed at each server to track usage of communications resources. This method is preferably implemented by using a count of the number of bytes transferred in order to estimate the number of packets transferred.
  • the ABI application software keeps track of counting the number of bytes transmitted to the user according to content type (i.e. system packets, instructional materials, or elf animations) . Then based on the network transfer protocol used, the byte count may be converted to a roughly equivalent packet count. Alternatively, the byte count may be used directly as a measure.
  • each server sends a summary of packet transmission information to a unique metering utility server.
  • the by-elapsed-time method is performed at the client.
  • the Screen Manager at the student client keeps track of the multiple simultaneous on-screen activities such as instructional materials, the elf, and the dictionary.
  • This method preferably further monitors the active element of presentation, that is, the element performing an action or the focus for student input.
  • the connect time of the student may simply be measured at the server.
  • the System Manager application at the server additionally periodically obtains session statistics during a user session, either by polling the student client or from timed client downloads.
  • the by-units method is preferably implemented either at the server or at the client.
  • This method measures the content accessed by the client. For example in the case of instructional materials, the server records the ⁇ pecific lesson accessed while the client records the completion of exercises. In the case of on-screen agent actions, this method records each completed display or animation sequence or utterance.
  • the by-interaction method is preferably performed at the client and records both fine-grained interactions, such a ⁇ clicks and keystrokes, and the medium grained interactions, such as completed responses and metarequests .
  • This method when combined with the by-time or by-units methods provides an indication of the relative level of interactivity of the instruction. For example, during use of instructional materials, the by-interaction methods measures the actual usage of each resource such as agent processing. Usage of the different ABI elements is preferably metered by an appropriate method.
  • the methods described abcve are not uniformly advantageous to different types of presentation. A graphics designer might seek compensation based on the amount of time a design is on the ⁇ creen, while the instructional designer might seek compensation based on the fraction of the les ⁇ on completed.
  • the by- elapsed-time method is preferred for graphics designers, while the by-units methods is preferably used to record the publisher and lesson for instructional materials, the type and author for tool ⁇ material, and the creators of the animation and utterance for on-screen agent actions.
  • the by- packet method is preferably used to record the source of the network traffic such as access to the student object database or downloading of application software, in ⁇ tructional materials, or animation data snips.
  • the preferred metering methods provide information needed for the typical owner compensation and user pricing models.
  • system administrators provide pricing and compensation models.
  • This invention is adaptable to many alternative such models.
  • One user pricing model is a flat rate based on the type of instruction being made available, similar to pricing in the cable industry.
  • Another is based on connect time, as frequently done for Internet acces ⁇ , or on type and quantity of information retrieved, a ⁇ i ⁇ common for on-line database access.
  • TABLE 1A illustrate ⁇ an exemplary model for compen ⁇ ating provider ⁇ of ABI ⁇ ystem elements. Compensation i ⁇ based on metering data and an allocation model . The four metering methods are applied selectively to different providers. The allocation amounts 'a', 'b', 'C and 'd' are externally determined.
  • the Instructional Interface The ABI system has interfaces for students, teachers, and administrative staff . Materials and software developers can have specific ABI system interfaces. Alternatively, such development can occur on separate sy ⁇ tem ⁇ followed by indexing and loading of the developed components into the appropriate databases.
  • Student-System Interface This section describes the structure and design of the student-system interface. This description is directed to the currently preferred implementation of this interface by a series of visual display screens. However, this invention is not so limited, and adequate alternative technologies, for example voice output with speech-recognition input, can be used to implement this design. 5.3.1.1. Exemplary Student Screens
  • screens are structured as a hierarchy of areas and subareas with text, graphical, animation, and perhaps video object ⁇ displayed in the subareas.
  • Objects can either be for display only or permit student input or interaction.
  • Task screens are used for materials presentation task ⁇ such as homework assignments including problems, programmed steps, mastery quizzes, and drills.
  • Table 1 and Fig. 3 illustrate exemplary components of a task screen appropriate for elementary education. Reference numbers in Table 1 are from Fig. 3.
  • the ⁇ ession manager presents objects visualized as icons permitting the student to easily access ABI sy ⁇ tem facilities.
  • materials area 304 object presentation including description, placement and movement, is ⁇ pecified by the material ⁇ de ⁇ igner in the pre ⁇ entational and sequencing sections of the materials data.
  • the materials engine interprets the ⁇ e ⁇ pecification at run time to send display object ⁇ for display.
  • agent area 303 agent behavior processing formats predefined parametrizable objects, including resolution of object parameters, representing selected agent personae. The output from all selected and formatted display objects is sent to the executive software and operating system for ultimate display to a student .
  • buttons, etc . filling in text, dragging, drawing
  • the task screen of Fig. 3 includes in system area 302 student customization area 305.
  • the student can display objects given by the agent as rewards for student accomplishment. These objects can include text, as illustrated here, graphics, or animations.
  • file system toolbar 306 displaying accessible files as icons in a "book- Gr.-shelf" metaphor.
  • This invention is adaptable to other reasonable file system display metaphors.
  • the book icons represent a file personal to the student, a file holding ongoing instructional materials, a file of e- mail, and files for tools such as a dictionary and group activity.
  • Below file system toolbar 306 i ⁇ toolbar 310 for tools the student ha ⁇ access to.
  • Illustrated here are icons for a calculator, a word processor, communications, and starfish, a general purpose language tool.
  • "Starfi ⁇ h” are a vi ⁇ ualization tool for semantic networks that can be available in an ABI System.
  • a semantic network typically consi ⁇ ts of nodes linked to other nodes by semantically significant and named links.
  • a starfish tool visualizes such a network for a student by displaying the node centrally in the body of the starfi ⁇ h with the node' ⁇ links di ⁇ played as arms of the starfish.
  • a dictionary represented as a semantic network might include a node for each word with links to similar words, opposite words, root words, and so forth.
  • a dictionary ⁇ tarfish displays a word in its body.
  • the scheduling/calendar tool is an important tool that is always available.
  • Exemplary icon 309 illustrated for this tool has calendar part 307 and clock part 308. Selection of each of these parts brings up daily and monthly scheduling functions. These function can either prescribe the student's next activity or permit choice where the student ha ⁇ exce ⁇ s time or demonstrated personal scheduling ability.
  • materials area 304 instructional materials, tools, and communications materials display their content. Illustrated in Fig. 3 is page 3 of an exemplary mathematics homework.
  • Instructional materials are advantageously 5 structured as a book of exercises and items, emulating current textbook and workbook practice.
  • section tabs 312 permit the student to navigate the homework book by sections
  • page buttons 321 permit the student to navigate the homework book by page.
  • toolbar
  • An exemplary standardization has header information 314, presentation 315, and interactive input area
  • On-screen Agent area 303 allows the student entry of meta-requests and allows the agent to display synchronous or asynchronous meta-respon ⁇ e ⁇ .
  • This exemplary area illustrated in Fig. 3 comprises meta-request button 320 which the student
  • Student metarequests are generally allowed by the ABI ⁇ y ⁇ tem at any time. Requests may occur at the beginning, middle or end of instructional sequences, in choice screens, in tools, in group communications, or in the calendar. Agent
  • 25 metarespon ⁇ e ⁇ are individualized and context dependent. Typical metarequests are illustrated in Table IB. As an example of context dependence, if the request 'Where am I?' occurs within a le ⁇ on, a graphic repre ⁇ entation of ⁇ the le ⁇ on will be shown,- whereas if the same request is made
  • the agent software attempts to respond based on the user's intention and uses the context and previous request ⁇ to infer the reason for the current request .
  • the instructional materials notations provide a framework for the agent software to keep track of the relative position of the student in the lesson. This same information is also available to the teacher for lesson preview and annotation.
  • the remainder of area 303 is for agent meta-responses, which importantly have multi-media structured into personae. Illustrated are text mes ⁇ age 318 and visual persona 319 that typically includes animation. Also possible is audio output, either text-to-speech or generated from audio files.
  • Fig. 4 further illustrate ⁇ an exemplary ⁇ creen interaction between the materials and the agent. Fig. 4 shows only the content of materials area .501 and on-screen agent area 502 of the complete display screen of Fig. 3. A mathematic ⁇ homework material is displaying item presentation 503 with input selection buttons. The student has selected wrong input button 504. At this educationally significant event, the materials send to the agent several messages generated by notations in the materials data.
  • the student's agent has chosen to act a ⁇ illustrated.
  • the agent software integrates speech utterances, visualization, display of text and graphics, and animation into a persona display for highlighting an educational event that the agent determined important based its processing of the current input, past student inputs in this le ⁇ son, and the student's pedagogic model generated over several sessions .
  • Choice screens can be used at the tran ⁇ ition ⁇ between in ⁇ tructional sequences . They summarize what instructional material ⁇ have ju ⁇ t been completed, announce status information, and list any material ⁇ choices now available to the student . These choices can related to instructional materials to be undertaken next or to optional, non- instructional materials, such as exchanging credits for time in a game room, acces ⁇ to e-mail, and so forth, that can be available to the student.
  • the inputs of a student or other user of the ABI System are preferably classified as request ⁇ , meta-reque ⁇ t ⁇ , or data.
  • a student request is an input directed to materials or to the system seeking a specific action.
  • Student data i ⁇ an input responding to a sy ⁇ tem reque ⁇ t for information.
  • student requests include an input to the system to start the calculator is a reque ⁇ t, or an input to certain materials to submit completed homework to the teacher.
  • input of numbers into the calculator is data.
  • This invention is adaptable to a further particular type of data input, termed semiotic, in which the student selects certain signs or symbols to provide input.
  • Semiotic input is particularly advantageous when the agent requests the student to report his feeling or appreciation for a particular educational event.
  • Meta-requests are inputs directed to the agent seeking specific actions. For example, student input to the agent seeking hints during the current materials i ⁇ a meta-request .
  • Displays produced by this invention are preferably classified as applications, response ⁇ , meta-response ⁇ , or que ⁇ tion ⁇ .
  • Application display occurs upon sy ⁇ tem initiation of an available material, for example, an in ⁇ tructional material or a tool.
  • the agent can request the system to make a tool available to the ⁇ tudent.
  • Response ⁇ are all displays produced by materials or by the system.
  • responses include material ⁇ pre ⁇ entation di ⁇ play and di ⁇ play on the adequacy or correctne ⁇ of student input.
  • Meta-responses are all displays produced by the agent.
  • Que ⁇ tions are a particular form of response or meta-response which seek further student input. Que ⁇ tions engage the ⁇ tudent in a form of a dialogue which i ⁇ an integral :omponent of the tutoring interaction.
  • Fig. 5 illustrates an exemplary segment of the interaction of the student and the system that can occur during a mathematics homework. It illustrates both how response ⁇ and requests are distinguished from meta-responses, and meta-requests and also how the agent, through its observation of the ⁇ tudent' ⁇ current ⁇ ituation and it ⁇ contact with past student history, is able to guide the student better than the materials alone, which are only aware of the current context.
  • This display is individualized to the student' ⁇ current and pa ⁇ t performance and preferably 5 u ⁇ es realistic, life-like on-screen personae to engage the student. Display ⁇ from the ABI System directed to the student are indicated generally on the right; inputs from the student directed to the ABI system are indicated generally on the left,- and time increases downward.
  • the following general principles preferably guide system and materials responses and agent meta-responses.
  • 35 some display is to be made on every user input, if only to echo a character or mouse click.
  • a user is never to be left in doubt about the status of current task ⁇ .
  • the system preferably provides task specific hints or suggestion ⁇ if no user input is received in a time period adaptively determined.
  • all responses reflect the current context .
  • aspects of system response ⁇ ⁇ hould be adapted to the particular student audience, from elementary to adult education and including special classes of students. This tailoring can be set by the teaching or administrative staff.
  • One adaptable aspect is the language level and the language of system responses - for example, the vocabulary and language of help services, messages, and tutorials - is preferably adjustable.
  • Another important adaptable aspect is the type of personae of the on-screen agent is preferably adjustable.
  • the types of encouragement, level of joke ⁇ , and so forth, depend closely on the intended student population and are advantageously adjustable.
  • tools are also adaptable. Each tool is also advantageously enabled or disabled for each student .
  • Mail and communications tools for example, can be made unavailable for the lower grades.
  • File creation and deletion can require strict controls. Also, certain tools can have differing complexity levels suitable for differing student levels .
  • meta-respon ⁇ e selection is preferably shaped in view of the student' ⁇ pa ⁇ t baselines of speed, performance accuracy, modality, as specific to the type of materials. Moving average functions, in which recent values are given higher weight than earlier values, can be used advantageously to generate baselines of performance and timing.
  • the timing of meta-responses is preferably based on student data object fields that record the amount of help asked for in the past and past performance provided. Further, the pacing of meta-responses is advantageously context ⁇ en ⁇ itive.
  • remediation should be offered only in case of repeated error or hints offered asynchronously only after a relatively long period without an answer. Also, previous student interactions should be utilized. Repeated requests for hints should be noted and dealt with perhaps not with another hint but with remediation. The rate of prompts, advice, and hints should be adaptively adjusted on the basis of ongoing performance ' records .
  • the actual content of a meta-response can be adjusted to the current situation by filling in parameters from event messages sent from the materials. See infra .
  • IMIS Instructional Materials Interface Standard
  • Marker requests use general notations for the type of lessons and specific notations for prerequi ⁇ ite ⁇ .
  • Temporal requests use notations of expected time together with profile informatioi on individual performance on that type of material .
  • Typical predefined graphical response templates include roadmaps (perhaps in the form of a train and subway map) , charts, table, graphics and icon flowcharts. Colors can be used to the show relative levels of performance, urgency or dependency of elements. In respon ⁇ e to a 'How am I doing' request, green might indicate good performance,- yellow, adequate performance,- and red, needs immediate attention. Similarly, the shape of the icon might indicate its function such as a diamond for caution or a hexagon for stop.
  • Figure 12 illustrates an exemplary dialogue starting with the ⁇ tudent metarequest 'where am I?' .
  • the on-screen agent then make a metaresponse containing a ⁇ ummary of the ⁇ tudent' ⁇ progress, for example "You are one quarter through the lesson on adding fractions.”
  • the student might request further information.
  • the on-screen agent will point to the location on the diagram and say "You are here.” If the ⁇ tudent then clicks on an element of the chart, the agent will provide further information. For example, clicking on the Practice Box will provide a metaresponse containing a flowchart of this upcoming activity, a ⁇ generally illustrated.
  • the calendar scheduler is advantageously capable of providing the following response ⁇ . These are controlled by schedule data contained in the student data object and are proces ⁇ ed by the calendar/ ⁇ chedule tool .
  • Schedule reminder responses which remind the student of deadlines for materials task ⁇ in the system or for external activities, such as getting a parent's approval for a clas ⁇ outing.
  • Ta ⁇ k sequencing ⁇ ugge ⁇ tion responses, which suggest an order of assigned task ⁇ based on student history and on the as ⁇ igned priority and deadline.
  • Timing e ⁇ timate re ⁇ ponses which estimate how long a task will take based on timing information entered as part of task in the instructional materials and on pa ⁇ t relative performance for this student.
  • the ABI system provides for of scheduling initiative to be divided between the ⁇ tudent and the sy ⁇ tem.
  • Settable task schedule parameters permit, at one extreme, the student to have complete scheduling control, able to initiate and to exit any activity at will, and limit, at the other extreme, the student to work on only those materials that the sy ⁇ tem schedules .
  • schedule parameters include those controlling the tools and option ⁇ available to the ⁇ tudent while performing a given task and those requiring the student to perform background reading or remediation.
  • Important initiative parameters include the scheduling values of task priority value and deadline. If the priority and date are not both "off", those tasks with greater priority and earlier deadline are automatically scheduled for the student. If these values are "off", the student has control of task scheduling.
  • the sy ⁇ tem of thi ⁇ invention also includes a central list of timed activities, perhaps stored on the server ⁇ y ⁇ tems, to be performed by the sy ⁇ tem.
  • the ⁇ e can include regular time ⁇ for the generation and printing of ⁇ tandard reports or for the broadcasting mes ⁇ ages concerning group activities such a ⁇ spelling bees.
  • the ⁇ e timed activitie ⁇ can be performed by ⁇ cheduling ⁇ oftware which compiles the timed activity li ⁇ t ⁇ and initiate ⁇ the listed activities at their listed time ⁇ .
  • Such ⁇ cheduling ⁇ oftware can be ⁇ imilar to the "at" utility in UNIX operating ⁇ ystems .
  • the teacher use ⁇ the ⁇ y ⁇ tem to perform ⁇ uch function ⁇ a ⁇ entering initial profile ⁇ in ⁇ tudent data object ⁇ , assigning ⁇ tudent ⁇ to subgroups, previewing, annotating and scheduling a ⁇ ignments, reviewing and commenting on completed homework as ⁇ ignment ⁇ , and reviewing summary reports .
  • the agent of the student is also an agent of the student's teacher in that the student' ⁇ teacher control ⁇ key parameter ⁇ in the ⁇ tudent data object, which in turn control ⁇ agent actions.
  • the teacher customizes the ABI system by setting student data object parameters, assigning and prioritizing as ⁇ ignment ⁇ , and customizing materials. Important teacher activities are included in the following list .
  • the teacher initializes and exercises continuing control over important data in the student data object, and in this manner ⁇ upervi ⁇ es the student's use of the system. For example, the teacher controls the access and level of tools available to the student and limits the extent to which the student can alter agent personae.
  • the teacher controls the student's use of the ABI system by assigning, scheduling, and prioritizing the student' ⁇ access to the materials. This is accomplished by teacher control over the schedule subtype in the student model object. For example, the teacher can schedule task ⁇ that must be completed on the ABI sy ⁇ tem, ⁇ chedule non- ⁇ ystem tasks, remove task ⁇ or modify their priorities.
  • the teacher can customize materials available to the student ⁇ .
  • the extent of routine customization includes modifying sequencing of instructional les ⁇ ons, elements, and items, choosing the homeworks the ⁇ tudent mu ⁇ t complete, specifying the formats of homework assignments having some student discretion, such as reports, sending message ⁇ to ⁇ tudent ⁇ .
  • the teacher's class management is aided by a facility to send mes ⁇ ages, reminders, hints, etc. to students using the ABI ⁇ y ⁇ tem e-mail facilitie ⁇ .
  • the system can advantageously as ⁇ i ⁇ t the teacher in homework management. Once the ⁇ tudent completes and submit ⁇ a homework a ⁇ signment, a printed copy can be made for the teacher and the student .
  • the homework assignment can be graded by the ABI system, if answers were provided as part of homework material .
  • the teacher can add comments for the student, if homework is viewed online by teacher.
  • the system can advantageously also provide the teacher with summary and detail reports for each student and class .
  • These reports can be immediately available online or printed for later review.
  • reports can contain both current and cumulative data on instructional progress and homework assignments.
  • the reports can also flag patterns of deficiency in a student's homework and problems in a student's in ⁇ tructional progress.
  • these reports are generated from the database of student data objects on the server systems.
  • the teacher can be a student.
  • a teacher can benefit from training in the use of the ABI system in general, in the procedures to customize materials, and in the characteristics of the particular material ⁇ used in that teacher's class.
  • This training can advantageously be packaged as instructional materials directed to the teacher which are otherwise similar to student instructional materials.
  • the teacher like the student, has accessible material ⁇ , a teacher data object recording the teacher's progress and pedagogical characteristics, and an agent using this data object to guide the teacher's training and guide the teacher in the use of the system.
  • Administrative staff can have privileged access to certain data items in the ⁇ tudent and teacher data objects and other system data, which permits them to assign students to course ⁇ , to a ⁇ ign students to teachers, and to establish instructional performance ⁇ tandard ⁇ and criteria which the ⁇ tudent ⁇ mu ⁇ t meet to complete their material ⁇ .
  • This staff can also receive online or paper reports on the progress of students in the schools, the effectiveness of teachers, and the usefulnes ⁇ of the particular materials assigned.
  • parents can also be actors in an embodiment of the ABI system.
  • a student's parents can be given access to certain fields in their student' ⁇ data object in order that they can receive rapid information on their 5 child' ⁇ assignment ⁇ and performance.
  • Thi ⁇ information can be made available at home on the ⁇ ame client system that their student receives instruction and homework.
  • educational researcher ⁇ can receive certain acce ⁇ to ABI ⁇ ystem ⁇ in order to re ⁇ earch the effectiveness 0 of educational theories and methods. For example, they can efficiently compare the effectivene ⁇ of various educational paradigms in certain instructional contexts by receiving reports relating to students pursuing materials constructed according to the paradigms of interest . 5
  • Materials in particular instructional materials, are authored by instructional designers. Authoring of materials can be done on the ⁇ y ⁇ tem on which the materials are to be
  • an instructional designer authors materials including, for example, computer as ⁇ i ⁇ ted in ⁇ truction a ⁇ known in the art, computer assisted exercise ⁇ such a homework or simulation, , c and computer managed student instructional tasks which can involve work with several materials. For all materials, the student' ⁇ agent mu ⁇ t be informed of the sections completed and skills acquired in standard formats.
  • the ABI system provides an environment in which the student's agent i ⁇ available to con; rol materials presentation and guide the ⁇ tudent to improve educational outcomes.
  • This environment includes facilities to present assignments, assess responses, probe for prerequisites, offer as ⁇ i ⁇ tance with tools such as dictionaries, and score unit mastery quizzes.
  • the system can advantageously include conventional forms of homework, such as worksheets, as well as new types of homework, such as group-based homework, and formats previously too time consuming for teachers, such as criterion based rather than fixed length or interactive rather than prescriptive.
  • the system structure can accommodate existing forms of computer assisted instruction by embedding such existing instruction in materials of this invention which contain notations and generate agent event messages.
  • the instructional designer advantageously provides information including initial instructions for the entire task in a written and preferably also a spoken format with alternative wordings as neces ⁇ ary for special clas ⁇ e ⁇ of ⁇ tudent ⁇ .
  • the de ⁇ igner al ⁇ o provides materials sequencing in accord with the education paradigm chosen. Instructional sequencing i ⁇ appropriate for interactive in ⁇ truction with feedback.
  • Homework ⁇ equencing can include a fixed order,- a student defined order; a student defined order as ⁇ isted by teacher prioritization into ⁇ uch priority group ⁇ a ⁇ e ⁇ ential, important, or optional; and sequencing defined by performance to criterion on individual item subtype ⁇ .
  • the instructional designer advantageously provides information including the following.
  • the designer chooses names for this task and exercise, its prerequisites, and the skills to be acquired in accordance with school sy ⁇ tem ⁇ tandards so that the agent can meaningfully track student performance and provide helps, hints, and remediation.
  • the de ⁇ igner provides student instructions for the exercise, preferably in both spoken and written formats.
  • the designer specifies the presentation of the exercise by creating graphics and text for the exercise and by specifying their display attributes.
  • the designer defines allowable user inputs, the data type of input, and the display areas in which input is allowed.
  • the instructional designer advantageously provides information including the following.
  • the designer defines standard ⁇ for the completene ⁇ s of requested inputs and actions, possibly none, in case of incomplete inputs.
  • An exemplary such action i ⁇ suggesting the completion of omitted inputs.
  • the designer select ⁇ how inputs are to be judged and the possible judgements, for example, correct, near mis ⁇ , incorrect, and ⁇ o forth.
  • the designer select ⁇ error re ⁇ pon ⁇ e ⁇ to individual input elements or an entire exercise. These responses can be uniform or can reflect the specific wrong answer. Error responses include retry policies and selection of remediation paths. Remediation can be item sequencing options given on the basi ⁇ of retry outcome.
  • a first step in input judging can be, where appropriate, checking the data type and perhaps range of an input. For example, checking that a fraction is entered in response to a fraction addition problem. Appropriate feedback can be given if the wrong data type or range is input.
  • Single student inputs can include entry of a single text or numeric element, movement of a single display object, selection of a single di ⁇ play object, or drawing-a line or curve perhaps encircling a display object.
  • a second step in input judging can be classification of a suitable input in standard error categories. In an exemplary embodiment, this can be performed by providing a pattern corresponding to a correct answer.
  • the patterns can be a template appropriate to the suitable input, such as a text template or a spatial template.
  • a pattern matching procedure selected from a system library of such procedures can be executed to match the input to the pattern.
  • the output of the system matching procedure is advantageously selected from a limited number of standard judgements of correctnes ⁇ and partial correctness. This judgement is then communicated to the agent in an event me ⁇ sage in order for it to guide its student and adapt its pedagogic model.
  • Thi ⁇ invention i ⁇ adaptable to templates and pattern matching procedures known in the art.
  • Patterns can include one or more parametrized text templates, spatial templates defining the relative positions of objects to be moved by the student, selection templates ⁇ pecifying pattern ⁇ of ⁇ election ⁇ . Further, spatial templates can include outlining area ⁇ of the ⁇ creen, ⁇ hape ⁇ of drawn object ⁇ , maze traver ⁇ al, and tool inputs.
  • the instructional designer advantageou ⁇ ly provides information including standards for input, exercise, and task completion.
  • the materials can require a certain minimum completion before allowing homework submission to the teacher.
  • the final authoring step is augmenting the materials with additional notations for the agent.
  • These notations concern task and exercise subject, skill clas ⁇ ification ⁇ , and definition of the educational paradigm embodied in the sequencing logic. It is performed by instructional designers or knowledgeable teachers, and i ⁇ expre ⁇ ed a ⁇ notation ⁇ in the material ⁇ that generate event messages for the agent and that reference control parameters set by the agent for control of materials sequencing.
  • the notations so entered communicate variou ⁇ types of information to the agent.
  • Exemplary types include characterization of assignment by type of task, subject, elements of subject covered by task; comparison between exercises in same assignment by similarity and difficulty; the subject matter prerequisites to determine what the student may or may not have mastered based on which exercises are answered correctly,- system knowledge prerequisites,- and scheduling information such as average and expected time to complete.
  • Thi ⁇ section describe ⁇ in a more detailed fa ⁇ hion an exemplary ⁇ tructure for the software components previously described in a more general fashion with reference to Fig. 2. Subsequent section ⁇ de ⁇ cribe particular component ⁇ in an even more detailed fashion.
  • the structure described here is exemplary. This invention is adaptable to other structure ⁇ with other allocation of the function ⁇ of thi ⁇ invention to different module ⁇ .
  • Such alternative ⁇ tructure ⁇ are ea ⁇ ily designed by those of skill in the arts.
  • This section first describe ⁇ the principal client software and data component ⁇ and the conceptual hierarchy which reflect ⁇ their interaction. Next, the ⁇ tructure of the executive software is described. Finally, the flow and processing of events through the system are described.
  • Fig. 6 illustrates the principal client software and data components and the conceptual hierarchy which reflects their interaction.
  • the links illustrated represent principal procedure cal or class dependencies among the component ⁇ .
  • OS operating system
  • ES executive ⁇ oftware
  • Thi ⁇ software collects a number of components which customize the operating system to the requirements of this invention and also extend it, if needed. For example, ail OS task creation i ⁇ processed through an ES task control facility to insure that the student accesses only permitted materials.
  • the ES ⁇ oftware also provides a preferred animation facility and controls client startup.
  • Session and screen manager 603 is always present on a client system.
  • This component partitions the screen into the areas for the principal sy ⁇ tem components, as has been generally illustrated by the exemplary screen of Fig. 3, and controls the system area, area 302 in Fig. 3.
  • schedule/calendar 607 upon student selection of an icon presented in the system are'a requesting the ES to start the function represented, it turn checks with schedule/calendar 607 whether the ⁇ tudent is currently permitted to access this function before continuing with OS task creation.
  • the system manager also presents whatever reward graphics and animation the ⁇ tudent has been granted access.
  • These functions are performed by calling the object level I/O facilities of the OS and ES. Also always present on a client system i ⁇ student data object 611 for the student in session on the client.
  • This object preferably containing all the permanent read-write data in the ABI sy ⁇ tem relating to the ⁇ tudent, is downloaded from the server student database when the student logs onto the client.
  • this object is divided into subtype ⁇ , and tho ⁇ e only tho ⁇ e subtypes referenced are downloaded as required.
  • each object is downloaded from its database as required.
  • various ABI sy ⁇ tem component ⁇ reference and update data item ⁇ in the ⁇ tudent data object is indicated by double headed arrows 608 and 614.
  • Schedule/calendar component 607 is important for management of the student by other system actors, such as teachers and administrators. It is a tool that is always active whether or not it has a screen presence. Activities for the ⁇ tudent, represented by activity description, priority, and deadline, are entered into the schedule/calendar data ⁇ ubtype of the ⁇ tudent data object by teacher ⁇ or administrators. Optionally prerequisite information can also be entered into the schedule/calendar subtype. This component uses this schedule/calendar subtype data as well as the time expected for the student to complete an activity, as determined from the student's past performance also stored in the student data object, in order to determine whether certain activities, ⁇ uch a ⁇ particular instructional materials, should be automatically started by the ES without any student intervention.
  • the schedule/calendar can permit OS task creation reque ⁇ ted by the ⁇ tudent, a ⁇ by ⁇ electing an icon.
  • Thi ⁇ component al ⁇ o provides, on request, prioritized li ⁇ t ⁇ of ta ⁇ k ⁇ for the agent to present to its student when the student asks for advice on what to do next. It uses priority and deadline information and time-for-completion data computed u ⁇ ing data in the in ⁇ tructional material ⁇ and student data object.
  • the materials are represented in the ABI System by materials engine 604 and materials data 605.
  • the materials data comprise ⁇ object ⁇ for display output or ⁇ tudent input, ⁇ equencing logic controlling object display, and notations which when referenced by the sequencing logic during object presentation generate event mes ⁇ age ⁇ for the agent.
  • Material ⁇ data i ⁇ advantageou ⁇ ly grouped into "entries” comprising tho ⁇ e object ⁇ , logic sections, and notations related to the display of a single screen or a few screens related to a single educational item.
  • the materials data also preferably include a special header or initialization entry wii.h important notations that communicate to the agent the educational paradigm adopted by these materials and can inform the agent of the control variables to which it is responsive. Such header or initialization messages are also preferably sent to the agent if the material ⁇ change their education paradigm.
  • there is one common materials engine 6C4 which presents a plurality of materials data 605.
  • Materials engine 604 downloads the entries of materials daca 605, interprets the sequencing logic, display ⁇ objects a ⁇ requested, and reference ⁇ embedded notation ⁇ generating the requested event messages to the agent.
  • Standard facilities of the OS and ES are used for object presentation and for routing any input to the materials. Input is processed according to specifications in the sequencing logic.
  • the agent controls the materials by setting shared global variables which the sequencing logic checks.
  • shared global variables can be made available by OS interprocess communication ("ipc") facilities, such as shared memory.
  • the materials engine can be any program implementing these requirements, in particular an extension of available commercial authoring tools and engines, ⁇ uch as Macromedia's Authorware.
  • the materials are not separated into an engine and a data component but consist of one unitary component for each material.
  • a proces ⁇ similar to compiling creates a single executable material ⁇ component.
  • Thi ⁇ invention is equally adaptable to otner implementations of the material ⁇ that generate agent messages and are respon ⁇ ive to agent control according to the requirements outlined herein.
  • Agent processing is divided into two component ⁇ , agent action processing 609, which determines agent display actions in respon ⁇ e to event ⁇ , and agent behavior processing 612, which transform ⁇ display actions into display ⁇ of per ⁇ onae to the student.
  • agent action processing is rule based and event driven. Rules in rules tables 610 are evaluated using parameters both communicated in event messages from the material ⁇ or the ⁇ tudent and retrieved form the ⁇ tudent data object. These rules propose candidate actions and then weigh and select a final set of agent actions from the candidate ⁇ , which are communicated to sub ⁇ equent agent behavior processing 612. Agent processing also sets global variables for materials sequencing and control. A side effect of this processing is the updating the student data object with information from the materials event message.
  • Agent behavior processing 612 constructs an on-screen agent display based on the actions determined in agent action proce ⁇ sing. In a preferred embodiment, this proces ⁇ mg i ⁇ ba ⁇ ed on behavior table ⁇ 613. Utterances, text or voice, and affects are selected from tables based on the determined final actions and refined with parameters included with the actions. The utterances and actions are sent to the selected agent persona object, which creates the agent display of the selected personae using the utterances and effect selected. Data is referenced and updated in the student data object by this processing, in particular fields reflecting the student's agent personalization choices, ⁇ uch a ⁇ the de ⁇ ired per ⁇ onae, and fields reflecting recent agent behavior ⁇ .
  • Al ⁇ o illustrated is communication materials 615. These materials manage and provide resource ⁇ for variou ⁇ group activities, such as student tutoring, group work with particular materials, and group contests.
  • ES software collects together a number of component ⁇ which customize the operating ⁇ y ⁇ tem to the requirement ⁇ of thi ⁇ invention and, if needed, also extend it.
  • ES software implements common and special facilities. Exemplary common facilities include task control, communications, and I/O facilities,- exemplary ⁇ pecial facilitie ⁇ include a preferred animation fa ility and a client logon and startup facility.
  • ES software is built as frontends, wrappers, or extensions to available OS software components. For example, certain facilities can be implemented in C or C++ and directly call OS interfaces, such as the Window ⁇ TM graphics device interface or its extension ⁇ .
  • Other facilitie ⁇ can be built as classes using available implementation language libraries, such as the packages in JavaTM 1.0. Yet other facilities can be provided directly a ⁇ part of software packages, such as the display I/O functions present in commercially available authoring packages .
  • the task control facility manages the startup of system components. First, it verifies that the student is permitted to activate a requested component by checking schedules and priorities with the schedule/calendar tool. Indirectly, the student's agent can be queried to determine if this activation is reasonable. Next, if permitted, this facility manages the loading of required software and data objects from server system ⁇ . Finally, task control then starts up the component by making any neces ⁇ ary OS call ⁇ . Task control also notifies other system components at task terminations.
  • the communications facility manages network communications and provides whatever client-server or file server protocols are not present in the OS. Such protocols might include HTTP V2.0 with URL name resolution.
  • thi ⁇ facility handle ⁇ all remote acce ⁇ reque ⁇ t ⁇ for information including reque ⁇ t ⁇ for downloading and uploading.
  • the I/O facilitie ⁇ includes input and output display handlers for object level display I/O.
  • the display handlers receive object level requests for text, graphics, video and audio and translate them into whatever interface is supported by the OS.
  • the input handler receives low-level inputs from the OS input handlers and processes them according to the current screen format. In certain cases, it can directly call the output handler to perform immediate feedback actions, such as highlighting or dragging an object. In other cases, it can pass I/O event messages in an appropriate format to the system component owning that screen object, for example, the on-screen agent.
  • the output handler receives object presentation specification ⁇ , such as system owner, position, characteristic ⁇ , ⁇ ize, any animation information, and whether the object is an input focus, then updates any necessary screen mapping, and generates OS request ⁇ to display the object.
  • object presentation specification ⁇ such as system owner, position, characteristic ⁇ , ⁇ ize, any animation information, and whether the object is an input focus
  • OS request ⁇ to display the object.
  • An example of such an object specification includes a selectable text field object with specified contents, perhaps ⁇ crollable, di ⁇ played by a particular instructional material.
  • Exemplary specialized ES facilities are animation and client startup. It is preferable that the client sy ⁇ tem ⁇ upport animation, which i ⁇ a connected and timed sequence of display ⁇ potentially calling on all di ⁇ play modalitie ⁇ available, and other timed presentations. Although this invention is adaptable to any suitable animation facility, a preferred facility presents a script based interface.
  • the inputs to an animation facility are scripts which comprise object display commands, the timing of the object di ⁇ play ⁇ , an input ⁇ pecification of how any permitted u ⁇ er inputs are to be handled, and the types of events to be returned to the initiating sy ⁇ tem component.
  • Example ⁇ of display events include user input causing script branching and termination or interruption.
  • the animation facility receives a script from another system component, request ⁇ downloading of nece ⁇ ary di ⁇ play object ⁇ , for example from data ⁇ nip librarie ⁇ , interpret ⁇ the timing ⁇ pecification, and ⁇ end ⁇ reque ⁇ t to the input and output handler ⁇ .
  • the ES ⁇ tartup facility is described herein with respect to a student client to run on a network attached computer. Startup i ⁇ similar for other client system ⁇ , including teacher and instructional designer clients. Each component of the ABI system must be downloaded from a server when needed, if as is typical, no component of the sy ⁇ tem is resident on a client prior to ⁇ tartup.
  • the initial ⁇ tep involves the student accessing any client attached to an ABI network. Accessing can involve as little as powering-on the computer and requesting startup of the system on this client.
  • accessing by a student user begins by acces ⁇ ing the ⁇ erver with the ⁇ y ⁇ tem manager, for example, using a standard intranet browser which can be resident on the client or downloaded by a power-on bootstrap process.
  • the student logs on to the system manager, which then performs authentication, for example, by means such as password or identification card.
  • the system manager downloads and starts the ES
  • the ES then initiates necessary communication sessions, including those with the system servers, and then downloads the session manager software, subtype ⁇ of the student data object, the agent software, and the scheduler/calendar tool software.
  • the session manager presents the ⁇ tudent di ⁇ play m a form depending on student preferences in the student data object and receives input from the sy ⁇ tem area of the display
  • the schedule/calendar in cooperation with the agent then determines what material ⁇ the ⁇ tudent is to be presented with or can select from Finally, the materials data and engine are then downloaded and the substance of the student session commences
  • Presentation ⁇ of personae or merely appropriate coherent response ⁇ can be created from audio and video display objects downloaded from a server and referenced upon demand These display objects, or data snips, can be linked into groups corresponding to the particular presentations Further, these linked groups can include small pieces of code that allow for a branching and interactive short meta-response. Thus, one meta-respon ⁇ e can include opportunities for ⁇ tudent input with the next di ⁇ play object being chosen in respon ⁇ e to that input. Each of these groups is catalogued and referenced as that persona behaving in a particular manner 5.4.3. System Event Processing
  • the ABI System on the student client, and on other clients, is advantageously organized to wait for student and timer input events and then to respond appropriately to these events.
  • This is common current practice for constructing interactive systems.
  • this invention is adaptable t ' o practices that might be developed in the future for constructing interactive systems as long as the principal system components and their mutual interactions as previously described can be represented in such a future practice.
  • thi ⁇ section sequentially describe ⁇ the ⁇ ystem processing of an input event and its consequences from initial input until the sy ⁇ tem wait ⁇ for the next event. This description provides detail of how the ⁇ ystem components communicate with each other and of how information and control flows through the system. More detailed description of the individual components appears in following sections.
  • Fig. 7 conceptually illustrates control flow and event processing in a student client.
  • data at the left of this figure is relevant data,- in the center is proce ⁇ sing steps,- and at the right are I/O events.
  • the arrows in this diagram represent either data references or control flow.
  • the control flow is at times implemented by information bearing mes ⁇ age ⁇ and at other time ⁇ effected by ⁇ tandard ES and OS ⁇ ystem call ⁇ .
  • thi ⁇ figure is directed to the processing of those components that interact with the student's agent.
  • Those component ⁇ , such as the session manager, which do not interact with the agent can be constructed according to standard interactive techniques (see, e . g. , Petzold, 1996, Programming " Windows ® 95. Microsoft Press, Redmond WA) .
  • wait point 701 the system waits for the next student input or timer event.
  • This wait commences at wait points 707, 713 and 717 after the system completes processing of the previous event, or possibly after sy ⁇ tem startup.
  • ES I/O handlers 702 decide whether the event represents an action without significance for other sy ⁇ tem component ⁇ .
  • the event can be a student action causing only the highlighting of an object or a timer event directing an animation.
  • Such events can be entirely processed by the I/O handlers, and ⁇ ystem waiting resumes at 701.
  • the I/O handler ⁇ format it appropriately and communicate ⁇ it to the correct component owning that input object. If the event repre ⁇ ents a time interval set by one of the material ⁇ engines or by the agent, it is formatted and passed to the requesting component. In the case of group work, the event can be generated on a remote computer sy ⁇ tem and tran ⁇ mitted over a network link in order to reach the local I/O handler ⁇ .
  • the I/O handler ⁇ format event message ⁇ into the format expected by the component they are directed to. They include in each me ⁇ age an indication of the type of ⁇ tudent action or time interval along with any input information from the action. One input event can generate ⁇ everal events messages .
  • message ⁇ directed to material ⁇ engine ⁇ 703 are considered first; me ⁇ ages directed to agent action processing 711 are considered second.
  • Fig. 7 illu ⁇ trates two materials engines, one engine or more than two engines are pos ⁇ ible on a system from time to time. Regardless of the number of materials engines present, event messages are communicated to the correct engine.
  • the material ⁇ engines 703 process a plurality of read-only materials data 704 representing instructional materials, tools, and communication materials. As indicated by arrow 725, these engines also access control information determined by agent action processing 711. This control information can be accessed in any convenient manner, such a ⁇ by an exchange of messages or by referencing parameters stored in a shared memory region. This information controls the materials engines at educationally significant points during their materials presentation.
  • materials engines 703 can also acces ⁇ remote databa ⁇ es 705 and other remote resources available through the sy ⁇ tem network.
  • the engines use these two sources, and optionally three sources, of input to cause presentation 706 to the student of, for example, an instructional lesson, a homework exercise, an instructional tool, or a joint educational contest.
  • This presentation uses the I/O handler of the ES and OS to generate actual student display.
  • the materials engines also generate message ⁇ directed to agent action processing 711.
  • notations m the materials cause the engines to format a mes ⁇ age to the agent
  • the ⁇ e me ⁇ ages also include an indication of event type and relevant data, perhaps including timing data
  • One student input can generate several agent messages.
  • the system can wait again for the next ⁇ tudent action at wait point 707 if the previou ⁇ ⁇ tudent action had either no input significance for the materials or agent or no educational significance for the agent
  • agent action proce ⁇ sing 711 is activated
  • this processing is table based Rules from policy filter table 708 are evaluated in view of the data included m an incoming event mes ⁇ age and in view of data on the student' ⁇ past performance and the student' ⁇ pedagogic model in ⁇ tudent data object 712. For example, comparisons with student history are needed to determine re_at ⁇ ve performance These rules propose candidate agent action ⁇ .
  • rules in decision weight table 709 and m selection criteria table 710 filter the proposed actions into a final list of agent actions.
  • These final actions can cause the update of the information in student data object 712 with data on the student' ⁇ current performance and behavior, as indicated by double headed arrow 728 They can also make available control information for the materials, as indicated by arrow 725.
  • the actions can include display actions for causing visible agent behavior.
  • Agent behavior proce ⁇ sing 716 processes the final list of display actions communicated from agent action processing 711 in view of utterance tables 714, display behavior tables 715, preferences and the record of recent agent behavior in student data object 712 in order to generate a coherent display of the on-screen agent personae reacting to the previous actions.
  • the final actions select utterance templates which are completed with parameter ⁇ contained in the action ⁇ .
  • the per ⁇ onae from the di ⁇ play behavior table ⁇ elected according to the student preferences use these complete utterances to generate display object ⁇ , and perhaps animation script ⁇ or applet ⁇ , which are sent to the I/O facilities of the ES for final display 718.
  • Agent behavior proces ⁇ ing also updates the student data object with information concerning this current behavior.
  • the system now waits at wait point 717 for the next ⁇ tudent action or time interval .
  • the material ⁇ have a uniform ⁇ tructure, being defined by material ⁇ data which i ⁇ u ⁇ ed by the materials engine to appropriately generate display ⁇ and perform functions. This uniform structure permits a uniform handling of the interface between all the materials and the agent.
  • certain tools and the group communication materials can be advantageously separately implemented as separate programs that themselves maintain the necessary agent interface. Such certain tools include a calculator, a dictionary, an encyclopedia, and group communications.
  • each in ⁇ tructional material could be a separate program that also maintained the necessary agent interface.
  • This section first describes the general structure of the instructional materials and then describes the tools typically available on an ABI sy ⁇ tem.
  • a common material ⁇ engine interpret ⁇ ⁇ pecific material ⁇ data to perform instructional and tools functions. These are described with reference to instructional materials with adaptations needed for the other materials noted.
  • the materials data includes three principal sections for presentation items, sequencing logic, and notations.
  • the presentation items include whatever is displayed, preferably represented as display objects, which can be parametrized. These display object ⁇ can be packaged with the materials data or can be downloaded from a server on demand.
  • the notations contain additional data related to the materials display. These include, for example, prerequi ⁇ ite ⁇ , link ⁇ to related material, expected student performance, and help and hints.
  • the notations are preferably generated from template ⁇ referencing parameter ⁇ from the material ⁇ data and ⁇ tudent performance input ⁇ .
  • the material ⁇ engine u ⁇ e ⁇ notations to generate messages to the agent, which comprise one part of the agent interface.
  • the sequencing logic i ⁇ executable or interpreted code that animate ⁇ the particular material ⁇ . It reference ⁇ all data in the particular material ⁇ to cause the ordered display of the presentation items and to send mes ⁇ age ⁇ to the agent according to the notations.
  • the material ⁇ data i ⁇ advantageou ⁇ ly grouped into entrie ⁇ , each entry representing a minimum item of presentation, which can, however, involve several screens. These entries are preferably specialized at least into a header or initialization entry and the other entries.
  • Table 2A illustrates a typical materials header entry which is the first entry processed when the materials are initialized.
  • the sequencing logic for the header frame consi ⁇ ts largely of definitions of variables and function ⁇ .
  • the global variable ⁇ are ⁇ hared 5 between system components and include the control variables that the agent set ⁇ and that the ⁇ equencing logic references and te ⁇ t ⁇ in order to be guided by agent control. These variable ⁇ , which compri ⁇ e another part of the agent interface, for example, can control the time pacing of Q instruction, the new concept seeding rate, the density of new exampler, the time pacing, or the difficulty of discriminations .
  • Local variables are available to the sequencing logic during materials processing.
  • Global functions are those global system functions that can be 5 called by the sequencing logic. Also, dictionary lookup, spell checking, or encyclopedia lookup can " be globally implemented and shared.
  • the global functions can be DLLs.
  • local functions are available locally to the sequencing logic.
  • computation ⁇ can be local function ⁇ .
  • in ⁇ tructional material ⁇ the local functions are available for checking user inputs for correctness, scoring quizzes, and so forth.
  • the notations in the header entry generate materials initialization messages to the agent. These mes ⁇ ages inform the agent about these materials, about what global variables they respond to, about what helps, hints, and tools are useful, and importantly about the educational paradigm the materials use. Preferably, information about this paradigm is structured according to the instructional materials interface standard. See infra .
  • the notations can also contain additional information, such as prerequisite ⁇ for the whole material ⁇ and references to other material ⁇ and text ⁇ .
  • the pre ⁇ entation item can be, for example, an introductory ⁇ creen.
  • Table 2B illu ⁇ trate ⁇ a typical entry which is proces ⁇ ed during regular material ⁇ pre ⁇ entation.
  • the presentation items are those for the materials display.
  • the sequencing logic causes this display in view of the variables and other information in the materials data and any student input.
  • the notations result in agent message ⁇ reporting changes in any parameter ⁇ set at initialization, ⁇ tudent performance data, ⁇ tudent error ⁇ , and other educationally significant information.
  • the notations can also contain information specific to thi ⁇ frame, such as expected difficulty and timing.
  • the materials engine its first processing step is to request the executive software to download the requested materials data from the instructional materials server. It next processes the header entry, links to global variables and function ⁇ , and sends initialization event mes ⁇ age ⁇ to the agent.
  • pre ⁇ entation begin ⁇ it interprets or calls for execution the ⁇ equencing logic on the fir ⁇ t frame. From this frame it proceeds to activate other frames as directed by the sequencing logic.
  • the materials proce ⁇ ing end ⁇ any termination me ⁇ sages as directed by the notations are sent to the agent and the materials are deleted from the client.
  • the material ⁇ are all implemented ⁇ imilarly. Most differences between the instructional materials, tools, and communication material ⁇ are in the presentation items and the ⁇ equencing logic, including different global and local entities. All materials are expected to have notations for generating agent mes ⁇ age ⁇ that record materials initiation and termination and ⁇ tudent performance and error ⁇ . Preferably thi ⁇ information i ⁇ reported in a standardized manner according to an in ⁇ tructional material ⁇ ..nterface ⁇ tandard. See infra .
  • the ABI system is adaptable to a wide range of necessary and optional student and teacher tools tailored to the students and the courses of instructions.
  • the following preferable tools include certain general tools and the communication, or joint work, material ⁇ .
  • other tools can be preferable.
  • the schedule/calendar tool participates in permitting access to materials according to ⁇ tudent ⁇ chedule and is preferably found in all embodiments.
  • the discus ⁇ ion in the section is directed to an implementation for elementary education. It is not limiting in the tools that can be used in an implementation.
  • the general tools are preferably present in a range of forms selected according to data in the student data object, including grade level, and teacher permissions.
  • One general tool is a calculator, which can have forms varying from a simple four function calculator to a complex graphing calculator.
  • Other general tools include language tools, such as a spelling checker, a thesauru ⁇ , a word pronouncer, an encyclopedia, and a dictionary. Different level ⁇ of each language tool can be provided suitable for different grade levels.
  • the language tools can be integrated with a " ⁇ tarfi ⁇ h” tool, which allows the user to place the center of a "starfi ⁇ h” over a particular word, and then, by ⁇ electing the appropriate arm of the ⁇ tarfi ⁇ h to obtain the definition, a pronunciation of the word, a rhyming word, a ⁇ ynonym, or an antonym.
  • Another general tool is a word proces ⁇ or, perhap ⁇ with a drawing mode which can be provided a ⁇ a multi-level set of writing and drawing tools. The writing and drawing capabilities available to a student are selectable by the student or teacher.
  • a last general tool is a link-maker, which offers exercises in various types of memorization, such as paired c.ssociate ⁇ , serial learning, ordered serial learning, and mnemonics.
  • additional tools can be added to an implementation to meet specific educational needs. For example for geography lessons a map tool can be added. For student projects, an encyclopedia tool and a network search tool can be added. The Study BuddiesTM can provide instruction in operation of the tools ⁇ uch a ⁇ the use of keywords and operators. Specialized tools can be added for commercial or industrial training.
  • full view of and access to the sy ⁇ tem provided file ⁇ y ⁇ tem can be a disadvantage. Consequently this invention contemplates, providing a file system front end, or file system tool, that limits the student' ⁇ view of and access to the system file system.
  • This particular tool is advantageously implemented a ⁇ part of the ses ⁇ ion manager and not a ⁇ a material. With that implementation, customized iconic file representations are managed as part of the ⁇ y ⁇ tem area of the di ⁇ play.
  • One embodiment of ⁇ uch a file ⁇ y ⁇ tem tool pre ⁇ ent ⁇ a four level file system organized into shelves of books, each of which has section ⁇ , the sections having pages.
  • a book representing a directory of files is opened when a student user select ⁇ it ⁇ icon.
  • the ⁇ tudent navigate ⁇ around the directory book by ⁇ electing tab ⁇ or by moving page by page, by selecting nextpage, lastpage, or other buttons.
  • the student interacts with selected pages, or files, of the book, possibly creating new pages and sections.
  • the student can also close the book. For most needs of elementary purposes, a single shelf with a few prespecified book ⁇ i ⁇ adequate. More advanced students can be given permission to create and use multiple shelves with new books and to cut and paste pages and sections from book to book.
  • a page of a book, a file is preferably presented with the materials that proces ⁇ it.
  • materials that proces ⁇ it For example, u ⁇ er-created text or giaphics pages appear with the word proces ⁇ or active. Homework and instruction pages appear with the appropriate materials . 5.5.2.3.
  • the schedule/calendar is an important tool and is preferably always present. It is accessed when the ABI sy ⁇ tem initiates materials to verify the student is permitted and ⁇ cheduled for thi ⁇ material, and al ⁇ o invoked when the ⁇ y ⁇ tem terminate ⁇ materials to schedule new materials. It is accessed as a global function by the agent in response to a meta-request from the student seeking scheduling as ⁇ i ⁇ tance. Further, it can be directly acce ⁇ ed by the ⁇ tudent using the calendar tool icon appearing on the student desktop. When accessed, this tool displays a calendar book to the student, viewable in several ways .
  • the schedule/calendar data is a subtype of and contained in the student data object.
  • thi ⁇ data include ⁇ the following field ⁇ for each ⁇ cheduled ⁇ tudent activity:
  • Deadline date and time or a definition of a perpetual activity, which has periodic requirements but no completion date,- Link to material for the activity which in turn can specify activity completion criteria; for activity of a single student this is typically a particular instructional material; for group work activity a list of the students for the group and other communication information can also be in the calendar entry,-
  • Activity characteristic ⁇ for example whether thi ⁇ wa ⁇ entered by the student or teacher and whether this is to be marked complete by the student or system,- Activity status, completion statu ⁇ and ⁇ ubmission ⁇ tatu ⁇ of any required report ⁇ .
  • Thi ⁇ exemplary data, ⁇ ufficient to define a ⁇ cheduled activity, can alternatively be entered by the teacher or by the student. If entered by the teacher, it can be protected from modification by the student. Data entry is preferably as ⁇ i ⁇ ted by a teacher tool with a suitable screen format. Optional activities can be entered by the student if the teacher permits.
  • the schedule/calendar tool can be directed by the teacher to permit the student a range of scheduling initiatives. These initiatives can range from permitting the student freedom to schedule materials as desired to requiring the schedule/calendar tool to enforce a fixed order of student activities. In a preferred embodiment this is accomplished by the teacher's specifying initiative parameters including a deadline date/time, D, and a criterion priority, P, in the student data object. The schedule/calendar then schedules automatically all tasks with deadline less than or equal to D and with priority level greater than or equal to P. By varying D and P with respect to scheduled tasks the teacher can achieve the specified range of initiative ⁇ . Schedule/calendar proce ⁇ ing can be invoked by the executive software, by the student, or by the agent.
  • the executive software invokes schedule/calendar tool, fir ⁇ t, to mark the terminated ta ⁇ k complete, and then, to reference the calendar data in view of the initiative parameter ⁇ to find activitie ⁇ requiring ⁇ cheduling. If thi ⁇ tool find ⁇ only one activity in the calendar requiring scheduling, thi ⁇ required activity i ⁇ initiated. If multiple required activitie ⁇ are found, the tool can, alternately, initiate the required activity of highe ⁇ t priority or allow the student a choice of which required ta ⁇ k to initiate. If there are no required activities, the schedule/calendar tool allow ⁇ ⁇ tudent selection of the next task via the session manager.
  • the schedule/calendar tool can be invoked by the student by selecting the schedule/calendar icon in the system area of the display. When so invoked, the tool displays the student calendar and scheduled activities in various formats from a monthly overview to details of individual activities. If permitted, the student can enter optional items or mark items complete.
  • the schedule/calendar tool can al ⁇ o be invoked by the agent when it receives a student meta-request of the type "What do I do next?" The agent retrieves the required and scheduled activities from this tool and al ⁇ o determines an expected time to complete each task based on student performance from the student data object and the average time required for each task from the materials header. In view of this combined information, the agent can present to the student an ordered list of activitie ⁇ ⁇ cheduled according to their expected time to complete.
  • the ABI ⁇ y ⁇ tem includes communication, or group work, materials integrated with the remainder of the sy ⁇ tem.
  • a ⁇ for other tools and materials, access to communications materials is granted by the scheduler/calendar tool .
  • Communication work groups are assigned and scheduled in students' calendars with calendar entries preferably including the group members names and other communication parameters. When these materials are activated by the scheduler, the communication group is begun.
  • ⁇ tudent ⁇ can ⁇ pontaneou ⁇ ly reque ⁇ t the formation of a communication group by the selection of a communication material.
  • the scheduler/calendar tool can permit group activation if the ⁇ tudent ⁇ have no other required activitie ⁇ .
  • each particular communication material can also have specific acce ⁇ s controls preferably set by the teacher that control the types of communication permitted and with whom the communications is permitted.
  • the communication materials have an agent interface. Upon activation, they send initialization event messages to the agent specifying the global control variables they will be sensitive to, the educational paradigm adopted, and available hints, helps, and other communication parameters.
  • the instructional materials interface ⁇ tandards include special categories for communication based work that enable the agent to control these material ⁇ with specificity. During communication work, these materials generate event messages at educationally significant points. Thereby, communication materials are fully integrated into an ABI embodiment. Further, in a preferred embodiment, communication materials are implemented in a manner similar to other materials.
  • each communication material has a particular communication ta ⁇ k specific for that communication material or form of group work.
  • the communication task manages the network interface for that particular type of communication or group activity by using the network protocols provided by the OS and ES, and provides its communication functions as global functions for access through an ABI system.
  • these function ⁇ are made available to the student in a manner similar to other materials through particular materials data that includes presentation items, sequencing logic referencing these global communication functions, and notations generating event message ⁇ for the agent.
  • the communication materials can be programs, independent of the material ⁇ engine and perhap ⁇ part of the associated communication task, which internally generate the necessary agent event messages.
  • communication material ⁇ tasks can be written either in the ABI implementation languages, or in a special purpose communication scripting language.
  • the particular communication materials in a preferred embodiment provide forms of group work or communication including e-mail or message exchange, linking student groups for joint work on materials, and ⁇ tructured joint work ⁇ uch as contests with rules .
  • group work or communication is described in the remainder of this section.
  • a first form of group work implemented by communication materials is E-mail and newsgroups. These are useful for teachers to send information to their classes, such as schedule and materials changes and to communicate with absent students. Teachers can also exchange information with each other or obtain help for system and other issues. Students can use this form to obtain help and advice, especially from remote sources, communicate with their teachers, and share work or interests with other ⁇ tudent ⁇ . E-mail and newsgroups are easily incorporated as previously discussed.
  • Student linking i ⁇ another form of group work implemented by communication material ⁇ can link together for various exemplary activities including simply talking with each other by voice or text or for joint work on a particular material in which the students have either similar roles, as in developing a document using a word processor, or different roles, as in a simulation or game.
  • Another activity of linked student ⁇ include ⁇ group activities, in which position of participants within a virtual environment determines activity and role within activity.
  • student linking includes the following steps.
  • the first step is identification of other students with whom a given student can link.
  • the group can be defined by the teacher in the schedule/calendar entry for this activity, or alternatively, in a communication access control particular to this linked work activity.
  • links must be e ⁇ tabli ⁇ hed between the ⁇ tudent ⁇ to be linked. These links can be to a single server communication materials task that receives and distributes mes ⁇ ages.
  • Third, local and global actions must be determined. Local actions are those that result in output visible only to the user taking the action. Global actions are those that result in output visible to all the student ⁇ in the linked group. These global actions can include communicating each student' ⁇ input to all linked ⁇ tudent ⁇ , sharing information among all linked students, jointly creating information by student ⁇ in the linked group, and ⁇ toring jointly created information.
  • the fourth step in linking is orderly disconnection from the linked group.
  • Linking can be implemented in alternative fashions.
  • the communications tools and materials for linked activities are integrated with the other components of an ABI ⁇ y ⁇ tem in one of the way ⁇ previously described.
  • a simple implementation is to provide on each student's screen an icon and a message area for each linked student. Alternatively, one or more shared materials areas can be provided. Communication can be di ⁇ tributed through a single server task to which all linked ⁇ tudent ⁇ connect.
  • a more advanced implementation of linking employ ⁇ ⁇ oftware package ⁇ ⁇ imilar to multi-u ⁇ er dungeon ⁇ (“MUD ⁇ ") , which contain a collection of virtual shared traversable ⁇ pace ⁇ (called "room ⁇ ”) in which users can interact either with each other or with elements within the room.
  • MOD ⁇ multi-u ⁇ er dungeon ⁇
  • MUD ⁇ are especially preferable for student group work in which different student ⁇ have different role ⁇ with access to different ⁇ y ⁇ tem capabilitie ⁇ .
  • one ⁇ tudent can be a recorder, having write-acce ⁇ to the group's notebook, while another can be the database expert, having access to a body of relevant data.
  • MUDs are also be useful for teachers, communicating with each other within 'rooms' each set aside for a specific topic and forming a dynamic newsgroup.
  • Important example ⁇ of ⁇ tructured linking in which the students have different or structured roles are educational contests.
  • the server spelling bee task initiates a spelling bee by accumulating connections with students local spelling bee tasks, then mediates the spelling bee by controlling ⁇ tudent action ⁇ , and provide ⁇ for orderly termination of the spelling bee.
  • the local ⁇ pelling bee ta ⁇ ks provide the communication function ⁇ acce ⁇ ed or required by the ⁇ pelling bee materials data, which are scheduled or selected to invoke ⁇ pelling bee participation, on the client ⁇ ystems. These materials also send event mes ⁇ age ⁇ to the agent and are controlled by the student's agent.
  • the local spelling bee tasks can be programmed to communicate with the agent and perform the spelling bee without materials data.
  • the spelling bee task ⁇ carry out the following ⁇ tep ⁇ .
  • the ⁇ pelling bee ⁇ erver ta ⁇ k i ⁇ started at a teacher's request or automatically by the ⁇ y ⁇ tem.
  • a li ⁇ t of eligible ⁇ tudent ⁇ can be ⁇ elected by the teacher or automatically determined by the ⁇ erver task based on data in the student data objects, including class membership and a stated interest in ⁇ pelling bee ⁇ .
  • the ⁇ pelling bee activity can be scheduled for each individual student by the teacher or selected by the student. If a student desire ⁇ to enter the ⁇ pelling bee, the local spelling bee ta ⁇ k i ⁇ started by the ES and a message is returned to the s.erver. No re ⁇ pon ⁇ e within a ⁇ pecified amount of time is taken as indicating a desire not to join.
  • a student's data object shows that this is the first time in a spelling bee
  • an instructional and warm-up sequence can be authorized for the student by the agent in the server task. If enough eligible ⁇ tudent ⁇ join the spelling bee, the server task continues, otherwise it sends a termination message to those who have joined and terminate ⁇ .
  • Each local spelling bee task obtains space on the student display indicating the other players and their inputs. Next the spelling bee begins, and the server task broadcasts the word to be spelled selected from a graded word list and the name of user to spell the word.
  • Each local task echoes the word sent, preferably by requesting the on-screen agent voice the words as utterances with an appropriate affect.
  • the spelling bee materials inform the student's local agent of the student' ⁇ progre ⁇ and performance in the spelling bee materials.
  • the server task accepts input from designated user's local task and broadcasts it.
  • the server task judges and reports on correctne ⁇ s of completed responses and, if incorrect, eliminates the student from further spelling request ⁇ .
  • a ⁇ student leave the spelling bee the server task is notified and ⁇ end ⁇ messages to the local tasks of continuing players in order to update their workspaces.
  • the student preferences for further spelling bees are checked and preference data in the student' data object i ⁇ updated.
  • the server spelling bee task terminate ⁇ the game and reports result ⁇ .
  • the agent i ⁇ an important component of thi ⁇ invention and i ⁇ further de ⁇ cribed in thi ⁇ ⁇ ection with reference to the ⁇ tudent data object, the agent interface, agent proce ⁇ sing, and agent adaptivity.
  • the agent comprises the student data object which contains data on the student' ⁇ performance on the variou ⁇ material ⁇ and data on the ⁇ tudent' ⁇ pedagogic model.
  • the ⁇ tudent data object i ⁇ referenced and updated by other components of the system, for example, for report generation and for student scheduling.
  • Other system components preferably have an interface to the agent in order that the agent can control the materials and guide the student in a uniform manner.
  • Agent processing is divided into two phases, agent action proces ⁇ ing and agent behavior proce ⁇ ing. Finally, agent adaptivity in the preferred and in alternative embodiment ⁇ i ⁇ de ⁇ cribed. 5.6.1. Student Data Object
  • One student data object is created for each ⁇ tudent in the ABI ⁇ y ⁇ tem and is the only permanent repository of data concerning that ⁇ tudent.
  • the student data comprises fixed data defining the student as well as evolving data describing .:he student' ⁇ interaction with the system, the latter _ncluding current and past performance and data defining the agent's view of the student.
  • the student data object is stored on the server ⁇ ystem and is the source on the server system for all teacher and administrative reports concerning that student. Elements of the student data object are fetched to a client system as required once its a ⁇ sociated student logs on to that client and on that client ⁇ erve ⁇ to control the agent and provide for agent adaptivity. Figs.
  • FIGs. 10A, 10B and 11 illustrate the structure and operation of the student data object.
  • Figs. 10A and 10B conceptually illustrates an exemplary structure for student data object 1101. It is an object compri ⁇ ing ⁇ tructured student data 1102 and methods 1103 for acces ⁇ ing and updating the ⁇ tudent data.
  • Student data is divided into global data 1104, materials related data 1105, including tool related data 1106, current lesson data 1107, and log data 1108.
  • Global data that is all items meaningful across all ABI materials, includes such subtypes as sy ⁇ tem data, agent behavior preference data 1109, agent ⁇ tudent model data 1110, and ⁇ chedule data 1111.
  • Agent behavior preference data 1109 relate ⁇ to the multi-modal behaviors generated by the agent and includes student defined preferences for these behaviors as well as a summary of past agent behaviors.
  • Student preferences can include options relating to agent visual appearance - species, gender, dres ⁇ , or perhaps, no visual appearance - and similar options relating to audio behavior and text production.
  • the summary of past agent behaviors is used to aid in the selection of reasonably varied future multi-modal behaviors.
  • Agent student model data 1110 include ⁇ item ⁇ modeling the student's persistent behavior which the agent use ⁇ to individualize it ⁇ interactions with the student. Such data items can include material retention rate, hint effectiveness, and preferred rewards.
  • schedule data 1111 relate ⁇ to a ⁇ signment ⁇ ⁇ cheduled by the teacher and unchangeable by the ⁇ tudent and optional item ⁇ ⁇ cheduled by the student.
  • Data for each schedule item can include due dates, reminder alarms, and priorities.
  • this data subtype includes ⁇ tandard and criteria data, u ⁇ ually set by the school sy ⁇ tem, which include objective ⁇ and ⁇ tandard ⁇ the student must meet in the particular course, milestone data establi ⁇ hing objective ⁇ already met by the ⁇ tudent, data relating to the ⁇ tudent' ⁇ progress in the materials, data relating to the student's use of tools in the materials, and performance data.
  • Progres ⁇ data include ⁇ data nece ⁇ sary for the student to leave the material ⁇ and resume the materials at the prior point.
  • Performance data 1112 relate ⁇ to student's performance over several les ⁇ on ⁇ in the material ⁇ and can include mean performance, weighted moving average ⁇ of performance, pattern ⁇ of performance, u ⁇ e of hint ⁇ , use of retries, and needed remediation. Using such performance data, for example, means and weighted moving average ⁇ , permits the agent to determine whether ⁇ tudent performance i ⁇ improving or declining.
  • Tool data 1106 contains essentially similar but more abbreviated data about use of system tools such as the calculator, dictionary, and word processor. This data can only include milestones and performance information. The status of each lesson presented by instructional materials is accumulated in current lesson data 1107. This subtype is created upon lesson initiation and deleted upon les ⁇ on completion.
  • the agent includes short term measures of performance - such as error rates, weighted moving averages of error rates, and the use of hints and retries - short term measures of time latency - such as time to complete les ⁇ on ⁇ egment ⁇ and weighted moving average ⁇ of such times - work areas in which the agent can store information particular to the instructional materials - such as parameter ⁇ to u ⁇ e in forming multimedia presentations - and lesson coaching parameters 1113.
  • the lesson coaching parameters are used by the agent to provide feedback to the instructional materials so that their presentation can be individualized according to student performance. These parameters are governed by the instructional modalities employed by the particular in ⁇ tructional materials and can include values such as the seeding rate of new concepts, time pacing of the presentation, the density of examples, and the ratio of reinforcement .
  • the student data object has links to ⁇ tudent log 1108.
  • the log stores all mes ⁇ age ⁇ input to agent proce ⁇ ing and all action ⁇ from agent behavior processing. It can be used to create detailed audits of student behavior and system respon ⁇ e ⁇ , which can be of intere ⁇ t to in ⁇ tructional designers, in order to improve instructional materials, and to educational researcher ⁇ , in order to develop new modalitie ⁇ of instruction. With its carefully partitioned and functionally defined interface ⁇ , the ABI ⁇ y ⁇ tem i ⁇ ea ⁇ ily adaptable to new modalities of instruction as well as to merely installing new materials.
  • the ⁇ tudent data object also includes one or more data updating methods and one or more data accessing methods.
  • Exemplary updating method 1114 includes two components, triggering event type 1115 and action list 1116.
  • a component of agent processing updates the student data object, it sends a message to the object including an update event type and a list of relevant parameter ⁇ .
  • the updating methods are searched to find one with a triggering event type which matches the event type of the update event.
  • the one or more methods having matching event types are then executed by performing all the actions in the included action list using the parameters in the update event message.
  • Each action use ⁇ the supplied parameters to update data elements in the student data object.
  • a plurality of actions is generally associated with each method because it is typical for one event to cause changes in several student model data elements.
  • an update event related to the use of a tool cause ⁇ change ⁇ in the relevant tool data ⁇ ubtype a ⁇ well a ⁇ the associated instructional material subtype.
  • the method ⁇ executed appropriately ⁇ ummarize ⁇ tudent data from the current lesson ⁇ ubtype into all the permanent data subtypes.
  • parameters such as 'hint effectivene ⁇ ' in the agent ⁇ tudent model data 1110 are also updated.
  • One of the method ⁇ associated with the event type 'end of lesson' updates the parameter 'hint effectivene ⁇ ' in the following exemplary manner.
  • the performance parameter 1120 'u ⁇ e of hints' is accessed to determine if update is required. If hint ⁇ were provided to the ⁇ tudent, the 'current le ⁇ on log' 1108 i ⁇ used in calculating the two components of the parameter 'hint effectivene ⁇ ' - 'hint effectivene ⁇ -before-fir ⁇ t-try' and 'hint effectivenes ⁇ -after-fir ⁇ t-try' .
  • the ⁇ e two components each hold an array of values which are used to compute a weighted moving average.
  • a more complex formulation of this parameter can be used to provide a more detailed analysis of hint effectiveness - each of its two component ⁇ can be ⁇ eparated into ⁇ ubcomponents corr ⁇ sponding to subject area, hint types and other instructionally u ⁇ eful measures . It is further preferable, for data elements comparing a particular student to clas ⁇ peer ⁇ according to variou ⁇ mea ⁇ ure ⁇ be entered into the ⁇ tudent data object. Thi ⁇ can be done by executing appropriate update methods on the server system where such comparison data is available from reports generated from the student database including all the student data objects.
  • Fig. 11 is an exemplary illustration of how a typical student action update event updates the student data object.
  • Other update events include agent action update events.
  • Update message 1201 is ⁇ ent 1206 to the student data object from a component of agent processing to cause student model update.
  • the update event type is "exercise_done" and exemplary a ⁇ ociated parameter ⁇ are a ⁇ indicated at 1202.
  • “exercise_done” is executed by performing the four associated action ⁇ .
  • the fir ⁇ t action update ⁇ relevant data element ⁇ in tool data ⁇ ubtype 1106.
  • the ⁇ econd action update ⁇ the log 1108, a ⁇ i ⁇ done for all event ⁇ .
  • the third action update ⁇ timing latency data element ⁇ 1205 in current lesson ⁇ ubtype 1107.
  • the fourth action updates student performance data elements 1204 in current lesson subtype 1107.
  • Any component of the ABI sy ⁇ tem needing to determine the value of particular data element in the ⁇ tudent data object does so by sending an inquiry mes ⁇ age to the student data object requesting the desired data element.
  • the inquiry method for that data element retrieves and then returns the desired value.
  • Such inquiries are typically made by the agent on the student client sy ⁇ tem and by inquiry and report generating programs on the server systems .
  • the structure of the interface between the agent and the materials is important in the ABI system. It permits a single agent to control a wide range of materials through which it guides a ⁇ ingle ⁇ tudent. The agent achieves this by advantageou ⁇ ly maintaining a model of the student's pedagogic characteri ⁇ tic ⁇ , which it reference ⁇ in diver ⁇ e ⁇ ituation ⁇ to determine its actions.
  • This section describes the general procedural structure of this interface, and second, describes the preferred model for the content of the interface. This preferred model is structured according to the instructional material interface standard (herein called "IMIS")
  • IMIS instructional material interface standard
  • Event ⁇ containing parameter ⁇ are ⁇ ent to the agent by the material ⁇ at educationally significant occurrences.
  • the agent set ⁇ global parameter ⁇ controlling the materials and returns messages confirming actions proposed by the materials.
  • the materials In circumstances in which the materials needs to coordinate display ⁇ with the agent, it communicates synchronou ⁇ ly with the agent. For example, when the ⁇ tudent requests help or a hint, the materials can need to synchronou ⁇ ly obtain the agent's permission to offer the help or hint. In other circumstances, the materials can asynchronou ⁇ ly ⁇ end informational message ⁇ to the agent.
  • Such a ⁇ ynchronous agent input and pos ⁇ ible output can give the ⁇ y ⁇ tem the appearance of ⁇ pontaneity.
  • the agent/material ⁇ interface can be implemented in any convenient manner in a given OS. For example, it can be built on explicit me ⁇ aging, ⁇ hared memory area ⁇ , procedure call ⁇ to a ⁇ ocket interface, or other technology.
  • the global parameter ⁇ ⁇ et by the agent and which control the material ⁇ are preferably ⁇ tate variable ⁇ that the materials sequencing logic references in order to make educationally significant sequencing decisions.
  • the meanings of state variable ⁇ to which a particular material is sen ⁇ itive can be e ⁇ tablished at materials initialization according to specifications in a header material ⁇ data entry.
  • Examples of ⁇ uch variables range from simple flags, such as tho ⁇ e controlling the availability of help ⁇ and hint ⁇ , to more ⁇ ophisticated parameter ⁇ , ⁇ uch a ⁇ tho ⁇ e controlling the rate of new concept introduction, the den ⁇ ity of examples, or the speed of di ⁇ crimination exercises .
  • a notation includes an event type, parameter ⁇ a ⁇ ociated with the event, and the condition under which the event i ⁇ con ⁇ tructed and ⁇ ent.
  • Notation ⁇ are activated when they are encountered in sequencing logic in the materials data.
  • Notations vary according to the materials. Some materials, such a ⁇ simple e-mail, can contain no notations. Tool materials can contain notations indicating only correct or incorrect use of the tool. Mo ⁇ t instructional materials data contain several types of notations. Generally, the events generated by these notation ⁇ ⁇ end information ⁇ imilar to the following: number of retrie ⁇ , mea ⁇ ure ⁇ of rate in fluency drills, measures of performance such as percent correct and the number of tries, partition of exercise items into similarity set ⁇ , and mea ⁇ ure ⁇ of the relative difficulty of item ⁇ .
  • Table 2C illustrates exemplary types of notations generated by typical instructional materials.
  • IMIS in ⁇ tructional material ⁇ interface ⁇ tandard
  • the material ⁇ adopt one of a limited and defined set of educational paradigms contemplated in the standard.
  • the rules referenced by the agent in its a ⁇ ociated proce ⁇ ing tables and performance data in the student data object be similarly structured.
  • IMIS provide ⁇ the agent with a materials independent view of the student .
  • IMIS is not limited to a particular set of educational paradigms . Any standard set or set ⁇ of paradigms appropriate to the intended student ⁇ can be adopted for the interface standard. It i ⁇ preferable that the ⁇ tandard ⁇ adopted be ba ⁇ ed on principles of educational psychology and sound educational practice. In the following, thi ⁇ invention i ⁇ de ⁇ cribed according to an IMIS appropriate for elementary education. The paradigm ⁇ de ⁇ cribed below are not limiting.
  • Each of these educational paradigms is preferably handled differently by the agent in respon ⁇ e to differing de ⁇ criptive information and student performance data. For example, a sequence of correct respon ⁇ es in a fluency exercise is expected. On the other hand, a sequence of correct respon ⁇ e ⁇ in a paired a ⁇ ociates exercise can be worth while for the agent to comment on.
  • IMIS standardize ⁇ the ⁇ e educational paradigms according to three pieces of information: the instructional context, the instructional format, and most ⁇ pecifically, the ⁇ ubject area.
  • Materials nctations ⁇ hould preferably specify all pieces for maximum agent flexibility, although the ABI system is adaptable to the materials specifying any number or none. If none are specified, agent actions are independent of the educational paradigm.
  • the instructional context is the specific mode of instruction being presented to the student by the materials. Examples of instructional contexts are:
  • material ⁇ can adopt in ⁇ tructional format ⁇ , the second component of the IMIS specification.
  • instructional formats are:
  • student performance should preferably be stored relative to the subject area being worked on, as necessary -_ for course level reporting.
  • the third component of the exemplary IMIS is the subject area, such as mathematics or reading.
  • IMIS standardize ⁇ system tables and data relevant to agent action processing according to this triple of information -- instructional context, instructional format, subject area -- which characterize the education paradigm adopted by the materials.
  • 0 material adopts one of the standard set of educational paradigms, or modes of instruction.
  • the parameter ⁇ to be pa ⁇ ed to the agent in an event me ⁇ age are determined by the instructional context and each instructional format of thi ⁇ paradigm.
  • c Tne following table contain ⁇ an exemplary ⁇ equence of notations for a "prerequisite ⁇ review” education paradigm, and the parameters relevant to agent action processing that each notation send ⁇ to the agent.
  • Instructional Context Type Prerequi ⁇ ite ⁇ Review Sequence Entry Unit Name: Selecting Gender Pronoun ⁇ Header Subject Area: Grammar Average Time: 5 minute ⁇ Number of Exerci ⁇ e ⁇ .- 8
  • Exercise 1 Entry Format Type Multiple Choice Header Number of Option ⁇ : 2 Difficulty: 0.3 Hint: Available
  • Exercise k Entry Format Type Fill in Blank Header Subformat : Select from Words in
  • An aspect of these notations is to provide information about the quality of the ⁇ tudent response, which, in this example, is given by the a priori probability of a correct answer. For example, ⁇ electing the correct response from two choices has an a prior probability of 0.5 if the choice is made at random. Filling in a blank correctly is le ⁇ s likely by chance, if no cuing is provided in the exercise.
  • notations containing the parameters associated with a given instructional context and a given instructional format can be stored as templates in libraries Notations are available in the ⁇ e librarie ⁇ to generate necessary messages at materials initialization and during material ⁇ proce ⁇ ing. An instructional designer then need only consult these libraries to obtain the notation ⁇ appropriate to the educational paradigm of the material ⁇ bein ⁇ authored.
  • the standardization of the student data object according to this exemplary embodiment of IMIS for elementary education is simply achieved by storing student performance data according to instructional context, instructional format, and subject area. Thereby, these characteristics can be taken into account when comparing student pedagogic performance in general across subject matter area ⁇ .
  • IMIS ⁇ tandardi ⁇ ation i ⁇ that of the agent action proce ⁇ ing table ⁇ , the policy filter table, the deci ⁇ ion weight table, and the ⁇ election rule ⁇ .
  • Event me ⁇ age ⁇ from the material ⁇ inform the agent of current values for the in ⁇ tructional context and in ⁇ tructional format. Since the ⁇ e values are parameter ⁇ available to evaluate the conditions and functions contained m these tables, these tables can be, in effect, segmented into parts each corresponding to a particular instructional context and instructional format. Since there is considerable overlap between the parts of these tables, the number of rules does not proliferate.
  • the current ⁇ ubject area is also available to ⁇ egment the table ⁇ in the ca ⁇ es of those ⁇ ubject ⁇ that can require special treatment by agent action proces ⁇ ing.
  • the IMIS ⁇ tandardization permits a more systematic and effective use of the mechanism which the agent use ⁇ to ⁇ et global variables in the material ⁇ . These variables facilitate adaptive adjustments of instructional parameters, such as seeding rate and amount of prompting. These variables can be more effectively set in view of the current educational paradigm as indicated by the current values of the instructional context and format.
  • IMIS is also useful in providing information to the student in response to "Where am I?" inquiries. The system can use the information contained in the entities in the information triple to respond, "You are halfway through the drill and practice on fractions," for example.
  • the segmenting of the policy filter table and decision weight table which provides a simplified 'intelligent instructional agent' for each kind of in ⁇ tructional context, instructional format, can be augmented by other techniques from artificial intelligence.
  • the customized rules and functions contained in the action table can be augmented software modules, which extend the agent and are constructed based on such techniques as production rules systems with rule propagation or neural nets.
  • Such additional modules could, for example, find complex patterns of student error unanticipated by the in ⁇ tructional de ⁇ igner.
  • a ⁇ additional artificial intelligence method ⁇ are incorporated into the agent software, new materials notations can be added to the notation repertoire.
  • agent action proce ⁇ ing is rule based and event driven
  • agent behavior processing is table based. This and the succeeding section describe the preferred embodiments of these divi ⁇ ion ⁇ of agent proce ⁇ ing.
  • Fig. 8 illu ⁇ trate ⁇ in more detail agent action processing.
  • This processing is activated when event messages 801, representing either input events sent from the I/O handlers or educationally meaningful message ⁇ from the material ⁇ , are sent to the agent software. It transforms the input event messages into lists of display actions that activate the agent display and also has the important side effects of updating student data object 806, as indicated by arrow 815, and of setting materials control parameters, as indicated by arrow 816. It is pos ⁇ ible a particular input event can generate all or none of these outputs and side effects .
  • Agent action processing proceeds through three step ⁇ : event filtering, candidate action weighting, and display action selection.
  • event filtering In common, each of these ⁇ tep ⁇ reference ⁇ rules in an associated table of rules. These rules include relations, function ⁇ , and procedure ⁇ , all of which reference input parameter ⁇ .
  • Input parameter ⁇ can be any appropriate data carried in the input event me ⁇ age and any appropriate data stored in student data object 806.
  • fields from the following subtype ⁇ in the ⁇ tudent data model are referenced: the current le ⁇ son subtype, the materials specific subtypes, and the agent pedagogic student model ⁇ ubtype.
  • event input parameters include parameter ⁇ characterizing the current educational paradigm adopted by the material ⁇ .
  • the ⁇ e parameter ⁇ can be u ⁇ ed to ⁇ elect rules applicable only to this paradigm for reference and activation.
  • the first step is event filtering 807, referencing policy filter table 803. This step is described with reference to Table 7, an exemplary policy filter table.
  • the first row illustrates a generic policy filter rule, while subsequent rows illustrate exemplary filter rules.
  • the generic rule has a condition and a consequent .
  • the condition is boolean expres ⁇ ion, B() , of one or more conditions, p n , each of which i ⁇ a function of the available parameter ⁇ .
  • Default parameter ⁇ in a rule can be overwritten by parameter ⁇ from the input event.
  • the consequent is a list of an agent action type, "type, " an agent action subtype, "subtype, " and zero or more parameters, x r ..
  • the type is a major mode of agent behavior, for example, "congratulate the student," and the ⁇ ubtype modifie ⁇ that behavior, for example, "because of the ⁇ tudent' ⁇ rate.”
  • the parameter ⁇ provide additional information to be u ⁇ ed in con ⁇ tructing an utterance, for example the time that the ⁇ tudent took to complete an item or the name of the item.
  • Each rule can be marked active or inactive, possibly as a re ⁇ ult of ⁇ election during material ⁇ initialization or a ⁇ a re ⁇ ult of ⁇ election according to IMIS educational paradigm parameter ⁇ .
  • Proce ⁇ ing a filter rule con ⁇ ists, first, in evaluating each active boolean, and second, for each such active and true expres ⁇ ion, placing the con ⁇ equent and it ⁇ parameter ⁇ into the list of candidate actions.
  • the list of candidate actions is then pas ⁇ ed on to action weighing 808, the next proces ⁇ ing ⁇ tep.
  • the current lesson subtype and materials specific data subtype are updated, if neces ⁇ ary, with data from the input event message. For example, upon item completion, performance results need to be updated.
  • Action weighting 808 references decision weight table 804 and a ⁇ signs a numeric weight to each action in the input candidate action list. Thi ⁇ ⁇ tep i ⁇ de ⁇ cribed with reference to Table 8 an exemplary deci ⁇ ion weight table.
  • the fir ⁇ t row illu ⁇ trate ⁇ a generic policy filter rule, while ⁇ ub ⁇ equent row ⁇ illu ⁇ trate exemplary filter rule ⁇ .
  • the generic rule has an index and a weight function.
  • the index is a type and subtype pair, and the consequent is a weight function of zero or more parameters, x n , with a value between 0 and 1.
  • Each rule can also be marked active or inactive, pos ⁇ ibly a ⁇ a re ⁇ ult of ⁇ election during material ⁇ initialization or a ⁇ a re ⁇ ult of ⁇ election according to IMIS educational paradigm parameter ⁇ .
  • Action selection 809 references selection criteria table 805 to select a final set of action ⁇ from the input candidate 5 action list. This step is described with reference to Table 9, an exemplary selection criteria table.
  • the ⁇ election criteria table con ⁇ i ⁇ t ⁇ of a list of available method ⁇ for the candidate action ⁇ election proce ⁇ s.
  • a 0 selection criterion use ⁇ the computed weight and perhap ⁇ other parameters to select one or more final action ⁇ from the candidate weighted actions.
  • Exemplary ⁇ election criteria are illustrated in the last two rows. It is anticipated that one criteria is marked active a ⁇ a re ⁇ ult of ⁇ election during ⁇ material ⁇ initialization or as a result of selection according to IMIS educational paradigm parameters. The active criteria is applied to select zero or more final actions. Some final actions are executed locally to provide control to the materials by setting control parameter ⁇ , a ⁇ Q indicated by arrow 816.
  • final action ⁇ can cau ⁇ e update of field ⁇ on the ⁇ tudent data object, in particular in the agent pedagogic model ⁇ ubtype, as indicated by arrow 815.
  • the remaining final actions are display actions which are pas ⁇ ed to agent behavior proce ⁇ sing in display action list .. 802.
  • Action proce ⁇ ing is illustrated with reference to the exemplary rules in Tables 7, 8, and 9 by considering the result ⁇ of proce ⁇ ing two input event ⁇ , one of type "item done” with a "difficulty greater that LIM" and one of type “exerci ⁇ e done.”
  • Applying the exemplary filter rules from Table 7 results in two candidate actions, one being (congratulation, diff) and the other being (congratulations, done) .
  • No other exemplary boolean expression evaluates to true.
  • the exemplary weighting rules from Table 8 are simply applied by selecting and evaluating the correct weighting function.
  • the resulting exemplary candidate action weight ⁇ are taken to be 0.8 for (congratulation, diff) and 0.5 for (congratulations, done) .
  • the one active exemplary selection rule from Table 9 is applied which ⁇ elect ⁇ the one final action (congratulation, diff) .
  • rule propagation and general production rule sy ⁇ tem ⁇ could be u ⁇ ed to transform events to actions.
  • Other applicable techniques could involve neural nets, predicate logic, and so forth.
  • Agent behavior proces ⁇ ing transforms di ⁇ play action ⁇ into output di ⁇ play ⁇ to the ⁇ tudent.
  • agent behavior proce ⁇ ing select ⁇ from table ⁇ of possible display behaviors based on the input display action list and its parameters and on fields in the student data object describing student preferences and recent agent display behaviors.
  • agent behavior proces ⁇ ing generate ⁇ either display script ⁇ which are sent to the I/O handler, or scripts with as ⁇ ociated data snips of sound and animation that are embedded in applets.
  • intermediate scripts are not used and behavior processing generate ⁇ I/O handler commands in real time. This section describes agent behavior processing, first, with respect to the table data structures used, and second, with respect to the proces ⁇ ing step ⁇ .
  • agent behavior proces ⁇ ing include ⁇ two ⁇ tep ⁇ .
  • the message and its emotional affect which is to be displayed or spoken by the on-screen agent, called herein the "utterance” is ⁇ elected according to the input display actions.
  • the utterance and affect are sent to the preferred persona object where it is integrated into a complete display, including animation, graphics and audio.
  • the display is preferably represented as a script which is then ⁇ ent to the I/O handler ⁇ .
  • the selected affect m an important parameter. The affect further characterizes the intent of the utterance.
  • an utterance of a "congratulations" type is associated with a positive affect that can range from “happy, " in ca ⁇ e ⁇ of superior performance, to "encourage,” in cases of improving but still les ⁇ than average performance.
  • the di ⁇ play behavior of the on- ⁇ creen agent preferably represented as one or more personae interacting with each other and the ⁇ tudent, i ⁇ ⁇ trongly re ⁇ pon ⁇ ive to the affect parameter.
  • infusing an animation with an affect or emotion gives resulting images a human and life-like quality. Such a quality is important so that the virtual tutor aspect of the ABI sy ⁇ tem engage the ⁇ tudent in order to improve in ⁇ tructional results.
  • agent behavior processing can present a coherent and life-like imaje agreeable to the student over one instructional session or over several instructional sessions .
  • Affects are a ⁇ ociated with and further characterize the intent of utterance ⁇ . They are ⁇ elected a ⁇ part of utterance generation proce ⁇ ing for u ⁇ e in vi ⁇ ual display generation proces ⁇ ing. Utterance generation proce ⁇ sing depends on the type, ⁇ ubtype, and parameters of the current event as well as on the student data object, which contains the agent student mcdel, student pedagogic parameter ⁇ , and recently generated behavior ⁇ . Therefore, preferably, the ⁇ elected affect and generated visual displays are respon ⁇ ive to the student pedagogic characteristics or, alternatively, the student cognitive style.
  • utterances and associated affect are generated by selecting options from a hierarchy of tables. This hierarchy, having typically many choices for each level, provides variety in agent behavior. At the highest level of this hierarchy are the tables of utterance templates 908, which are indexed by action type and action ⁇ ubtype. Typically, there are many utterance template ⁇ and a ⁇ sociated affect for any given action type and subtype, and indexing is according to additional parameters that occur in action lists and additional parameters of student characteristics from the ⁇ tudent data object. For example, utterance ⁇ and affect ⁇ are further selected according to the educational paradigm employed, student grade level, and student preferences.
  • ⁇ lot ⁇ which are parametrized phra ⁇ e ⁇ , or in other word ⁇ , function ⁇ which use input parameters to return phrases .
  • Utterance templates contain named slots as well as invariable words and sounds.
  • ⁇ lot ⁇ with the specified name are selected from the slot table.
  • there are' many slots of a given name which are further indexed according to additional action list parameters and user characteristic ⁇ from the student data object. Wheu a slot is selected for use in the utterance template, slot parameters are passed from the utterance template.
  • Alternative embodiments of this invention are adaptable to hierarchies with additional levels of utterance generation table ⁇ or additional type ⁇ of table ⁇ at a given level in the hierarchy.
  • Table 10 is a small segment of the utterance template table for an action type of "congratulations” and an action subtype of "performance” and appropriate for a test type paradigm.
  • Table 10 illustrate ⁇ that the ⁇ tudent grade level, obtained from the student data object, is an additional indexing parameter for these utterance templates .
  • each illustrated template includes a slot named "performance-streak- ⁇ lot, " with parameters of grade level, number of problems answered correctly, and total number of problems .
  • the utterance template table have a large number of utterance templates appropriate to a large number of educations situations. Since the preferable number of type and subtype combinations is at least approximately 500, and since it is preferable to have 10 to 100 respon ⁇ ive utterances per pair, a preferable utterance template table has at lea ⁇ t 25,000 entries. A less preferable table has at least 5,000 entries and a more preferable table has at lea ⁇ t 50,000 entrie ⁇ . In an embodiment of the invention, le ⁇ u ⁇ ed utterance ⁇ have fewer candidate responsive utterance ⁇ without impairing the image of ⁇ ystem spontaneity. Thus this invention is adaptable to utterance tables of 1,000 entries.
  • Exemplary Table 11 is a small segment of the slot table for slot ⁇ named "performance- ⁇ treak- ⁇ lot, " any of which could be employed in the previou ⁇ template ⁇ .
  • the illu ⁇ trated ⁇ lot ⁇ evaluate their input parameters to result ⁇ in phrases. For example the last slot results in the phrase "90 percent" if numright is 9 and total is 10. Further, slots can contain a condition which control ⁇ their applicability. In this example it is the fifth component of each entry and only the first slot has an non-null condition.
  • slot tables have at least the same number of entries as the utterance template table.
  • a preferable slot has at least 25,000 entries.
  • a less preferable table has at least 5,000 entries, and a more preferable table ha ⁇ at lea ⁇ t 50,000 entries .
  • the final display of the preferred on-screen agent object is generated from Display Behavior Tables 904 with a similar hierarchical table data structure to that used in utterance generation.
  • On-screen agent actions which contain a cast of one or more personae.
  • persona types which the ⁇ tudent ⁇ elect ⁇ once, or at mo ⁇ t once per session.
  • associated with each persona type is a library of display behaviors indexed by affect.
  • Exemplary affect types include the following.- sad, objective, pleased, happy, disappointed, announce, remind, encourage, reinforce, model, prompt, hint, joke, and tutor.
  • each affect has many possible behaviors and the ⁇ e are further indexed, as for utterance generation, by parameters appearing in the action list and the student data object.
  • the display behaviors are structured as scripts containing named display objects. These named display objects can optionally involve voice, audio, graphics, or video display ⁇ , and they are contained in ⁇ cript ⁇ which can optionally specify a timed animated display or a branching display, where the branches are dependent on student reactions to the display. At the lowest level in the preferred embodiment are the individual named display objects. As for slot ⁇ , typically there are several parametrized instantiations of each named object. These instantiations are indexed according to the same parameters indexing the display behaviors and in turn use these parameters to generate di ⁇ play ⁇ .
  • Alternative embodiments of this invention are adaptable to hierarchies with additional levels of tables for display generation tables or additional types of table ⁇ at a given level in the hierarchy.
  • Exemplary Table 12 i ⁇ a ⁇ mall segment with personae type ⁇ adapted to elementary education.
  • a robot per ⁇ ona creakily waving it ⁇ arms and saying the congratulatory mes ⁇ age.
  • the cat ⁇ ays the general part of the encouragement message while pointing to his bird sidekick.
  • the bird then flies acros ⁇ the ⁇ creen while ⁇ aying the ⁇ pecific part of the message.
  • the on-screen agent have a richly varied and engaging behavior.
  • the persona types preferably include recognizable popular figures as well as a rich variety of specially created figures.
  • Per ⁇ ona type table ⁇ have a preferable selection of at least 100, and les ⁇ preferably at least 50 persona types.
  • the librarie ⁇ of di ⁇ play behavior ⁇ preferably have many behavior ⁇ for each affect. Since the preferable number of affect ⁇ i ⁇ at lea ⁇ t 50, and since it is preferable to have 50 to 100 responsive behaviors per affect, a preferable behavior libraries have at least 2,500 entries, and more preferably 5,000 entries, per persona type. A fully implemented ABI sy ⁇ tem can have preferable behavior libraries with approximately 125,000 entries.
  • This number can be les ⁇ in situations were more popular persona have fully configured behavior libraries while le ⁇ popular per ⁇ ona have more limited librarie ⁇ . Further, the number of per ⁇ ona type ⁇ can be advantageou ⁇ ly limited to only the mo ⁇ t popular or more appropriate for the type of ⁇ tudent. Thus this invention i ⁇ adaptable to librarie ⁇ with approximately 1,000 entrie ⁇ of re ⁇ ponsive behaviors .
  • this content is preferably created by artist ⁇ , animators, writers, and other creative talent.
  • These elements of sound, voice, animation, graphics and video are collected into libraries of data snips and stored in archives. Further, it is preferable that these tables have an extensive and varied content in order that agent displays repeat only infrequently.
  • the fir ⁇ t ⁇ tep i ⁇ utterance generation 906 which receives as input action li ⁇ t 901.
  • Utterance generation indexes the utterance template table in accord with action list parameters, in particular action type and subtype, and student preferences from the ⁇ tudent data object, to obtain candidate utterance template ⁇ re ⁇ pon ⁇ ive to the current ⁇ ituation. If no candidate ⁇ are found, the student preferences are relaxed in a preset order until at least one candidate is found.
  • a record of agent display behavior during the session is stored in the student data object.
  • the named slots of the selected template are resolved in a similar fashion, by finding candidate named slot ⁇ and selecting one at random that has not been recently used.
  • An utterance is then generated from the template, the named slot, and the input action list parameters. This utterance and its as ⁇ ociated affect is passed to visual di ⁇ play generation.
  • the ⁇ econd ⁇ tep of agent behavior proce ⁇ ing, vi ⁇ ual display generation 907 uses the input utterance and associated affect to select candidate respon ⁇ ive displays of that affect from the libraries as ⁇ ociated with the student's current personate) preference contained in the student data object 905 As with utterance generation, if no candidate is found, student preferences are relaxed until one l ⁇ found.
  • the utterance mes ⁇ age l ⁇ ⁇ ent to the ⁇ elected display and display object ⁇ contain performance method ⁇ that are called to generate and output di ⁇ play script
  • the script with references to data snip ⁇ 909 of voice, ⁇ ound, graphic ⁇ , video and animation is incorporated into an applet
  • An exemplary applet can be a program fragment representing a character scratching his head while saying the utterance and moving acros ⁇ the screen This output applet l ⁇ ⁇ ent to the I/O handler ⁇ in the ES for ⁇ tudent display 908.
  • a display action can also reference a preformatted animated sequence stored in the data snip library 909 in which voice, sound, graphics, animation and video have been already integrated.
  • portion ⁇ of utterance proce ⁇ ing 906 and vi ⁇ ual display proces ⁇ ing 907 can be bypa ⁇ sed
  • ⁇ election of utterance or per ⁇ ona candidates from the available content ⁇ can be done other than randomly.
  • agent behavior data saved during a se ⁇ ion m the ⁇ tudent data object can be used to 5 construct performances extending acro ⁇ in ⁇ tance ⁇ of student actions.
  • utterance templates and display object ⁇ can be ⁇ elected in a connected manner in order to give agent di ⁇ play the appearance of continuity and reali ⁇ m.
  • the ⁇ e method ⁇ can include advanced text to ⁇ peech techniques, 2-D and 3-D graphical generation, and VR effect ⁇ .
  • Continuing story line ⁇ cript ⁇ can be available from the ABI ⁇ ystem on a daily basis in a manner similar to a continuing plot in a daily comic strip. These story lines can be applicable to a group of student ⁇ and individualized
  • the student' ⁇ ⁇ elected per ⁇ ona can introduce a ⁇ tory line and m other ca ⁇ e ⁇ ⁇ everal personae are directly involved in an interaction.
  • the story line can be u ⁇ ed as the basis for a reward such as "We're off to the beach to play volleyball. Join us
  • the agent receives event messages, which describe the student' ⁇ learning and performance.
  • the agent update ⁇ the ⁇ tudent data object with data from these mes ⁇ age ⁇ .
  • the agent adapt ⁇ to the ⁇ tudent, and thereby the virtual tutor individualizes to the student. This adaptation is maintained acros ⁇ sessions with this student.
  • the data referenced and updated by the agent are averages or weighted moving averages, giving more weight to recent than past behavior.
  • the pedagogic model includes, for example, data weighted moving averages of the rates that the student learns discrimination of a certain complexity.
  • Materials specific performance includes, for example, weighted moving averages of data on the student's respon ⁇ e time and response latency.
  • agent adaptivity to its student can occur differently.
  • student model data include ⁇ not only average ⁇ or weighted moving average ⁇ , but al ⁇ o data on the statistical distribution of the parameters involved, such as standard deviations. With thi ⁇ data the agent can recognize the current situation as "normal" or "abnormal" for this student and thereby offer appropriate guidance.
  • this stati ⁇ tical data can optionally include correlation ⁇ between the agent data, such as between various pedagogic parameters and variou ⁇ material ⁇ parameter ⁇ .
  • educational ⁇ ituation ⁇ can be cla ⁇ ified more finely than "normal” or “abnormal” into, for example, “abnormally ⁇ low on thi ⁇ fluency drill in view of normal progre ⁇ s on other exercise ⁇ .
  • cla ⁇ ification of thi ⁇ ⁇ tati ⁇ tical data can be done by ⁇ pecial executable modules in the agent based on, for example, statistical classification ⁇ cheme ⁇ or neural network ⁇ .
  • agent action proce ⁇ ing can be implemented with more complicated techniques.
  • agent action processing is done by rules without rule propagation.
  • rule propagation and full rule based systems can be used to transform events into action ⁇ .
  • This invention is applicable to other techniques from artificial intelligence that can make thi ⁇ tran ⁇ formation ⁇ uch a ⁇ Baye ⁇ ian belief networks.
  • the ⁇ tudent data object has data modeling student interest ⁇ and preference ⁇ .
  • Such a model enable ⁇ the agent, for example, to monitor school events and suggest those appropriate to the user.
  • This model also enables the agent to provide reward ⁇ tailored to individual ⁇ tudent ⁇ , which enhances the system reinforcement and adds to perceived agent persona personality and to virtual tutor individualization.
  • this model of ⁇ tudent interests can be implemented simply a ⁇ a ⁇ et of approximately 200 party ⁇ , covering intere ⁇ t in ⁇ everal ⁇ ubdivi ⁇ ion ⁇ of each ⁇ chool subject area, as well as categories related to ⁇ ports, leisure time and other areas of student interest .
  • Intere ⁇ t in the ⁇ e instance ⁇ can be entered in ⁇ everal manner ⁇ .
  • Student u ⁇ e of the encyclopedia tool can be used to determine areas of current interest .
  • Interest can be directly entered by the student, parent, or teacher. Alternately, student interest in materials can inquired for when the materials terminate.
  • the ⁇ tudent could provide ⁇ emiotic feedback by ⁇ electing from a row of face ⁇ with different expres ⁇ ion ⁇ .
  • the ⁇ tudent can be quizzed on intere ⁇ t ⁇ in a po ⁇ ed branching manner.

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Abstract

La présente invention se rapporte à un système et à un procédé d'enseignement interactif, adaptatif et individualisé assisté par ordinateur. Cette invention comprend, pour chaque étudiant (101), un agent (108) qui s'adapte à son étudiant et qui assure l'encadrement individualisé de l'étudiant et la gestion du matériel didactique augmenté assisté par ordinateur. Le matériel didactique de la présente invention est augmenté afin que les résultats de l'étudiant et les caractéristiques pédagogiques du matériel soient communiqués à l'agent et que ce dernier puisse en assurer la gestion. De préférence, le contenu de la communication entre l'agent et le matériel est conforme à des normes d'interface déterminées de sorte que l'agent agit indépendamment du contenu d'un matériel particulier. De préférence également, l'agent peut projeter sur l'écran, au moyen de diverses modalités E/S, des personnages intégrés sympathiques et vivants adaptés au goût de son étudiant, et lui apparaître comme un professeur virtuel. Enfin, la présente invention est de préférence mise en application sur des ordinateurs reliés entre eux au sein d'un réseau.
PCT/US1997/008687 1996-05-22 1997-05-22 Systeme et procede d'enseignement assiste par agent WO1997044767A1 (fr)

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US60/022,844 1996-07-31

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Cited By (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1003141A1 (fr) * 1998-11-17 2000-05-24 Alcatel Procédé de génération automatique et de surveillance de l'exécution du plan de déroulement d'un cours de formation par un ordinateur
WO2000043972A1 (fr) * 1999-01-26 2000-07-27 Microsoft Corporation Systeme et procede de planification d'etudes
WO2001009864A1 (fr) * 1999-07-28 2001-02-08 Erudite, Llc Systeme et procede destines au tele-apprentissage multimode interactif
US6427063B1 (en) 1997-05-22 2002-07-30 Finali Corporation Agent based instruction system and method
WO2001093226A3 (fr) * 2000-06-01 2002-10-24 Cehub Com Inc Systeme complet, procede et article de fabrication permettant de fournir les requis d'une formation continue institutionnelle, reglementaire et individuelle, par l'intermediaire d'un reseau de communications
US7246315B1 (en) 2000-05-10 2007-07-17 Realtime Drama, Inc. Interactive personal narrative agent system and method
US7505921B1 (en) 2000-03-03 2009-03-17 Finali Corporation System and method for optimizing a product configuration
US7614014B2 (en) 2001-04-05 2009-11-03 Daniel Keele Burgin System and method for automated end-user support
US7844907B2 (en) 2002-10-16 2010-11-30 William Watler System and method for dynamic modification of web content
US7995735B2 (en) 2004-04-15 2011-08-09 Chad Vos Method and apparatus for managing customer data
US8096809B2 (en) 2001-04-05 2012-01-17 Convergys Cmg Utah, Inc. System and method for automated end-user support
CN110322098A (zh) * 2018-03-30 2019-10-11 Cae有限公司 交互式计算机模拟期间的标准操作程序反馈
USRE47908E1 (en) 1991-12-23 2020-03-17 Blanding Hovenweep, Llc Ergonomic man-machine interface incorporating adaptive pattern recognition based control system
USRE48056E1 (en) 1991-12-23 2020-06-16 Blanding Hovenweep, Llc Ergonomic man-machine interface incorporating adaptive pattern recognition based control system
US11107289B2 (en) 2011-04-08 2021-08-31 Nant Holdings Ip, Llc Interference based augmented reality hosting platforms

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5310349A (en) * 1992-04-30 1994-05-10 Jostens Learning Corporation Instructional management system

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5310349A (en) * 1992-04-30 1994-05-10 Jostens Learning Corporation Instructional management system

Cited By (22)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
USRE48056E1 (en) 1991-12-23 2020-06-16 Blanding Hovenweep, Llc Ergonomic man-machine interface incorporating adaptive pattern recognition based control system
USRE49387E1 (en) 1991-12-23 2023-01-24 Blanding Hovenweep, Llc Ergonomic man-machine interface incorporating adaptive pattern recognition based control system
USRE47908E1 (en) 1991-12-23 2020-03-17 Blanding Hovenweep, Llc Ergonomic man-machine interface incorporating adaptive pattern recognition based control system
US6606479B2 (en) 1996-05-22 2003-08-12 Finali Corporation Agent based instruction system and method
US6427063B1 (en) 1997-05-22 2002-07-30 Finali Corporation Agent based instruction system and method
US6790044B1 (en) 1998-11-17 2004-09-14 Alcatel Process for the automatic creation and monitoring of a progress plan for a training course by a computer
EP1003141A1 (fr) * 1998-11-17 2000-05-24 Alcatel Procédé de génération automatique et de surveillance de l'exécution du plan de déroulement d'un cours de formation par un ordinateur
AU754173B2 (en) * 1998-11-17 2002-11-07 Alcatel A process for the automatic creation and monitoring of a progress plan for a training course by a computer
US6353447B1 (en) * 1999-01-26 2002-03-05 Microsoft Corporation Study planner system and method
WO2000043972A1 (fr) * 1999-01-26 2000-07-27 Microsoft Corporation Systeme et procede de planification d'etudes
WO2001009864A1 (fr) * 1999-07-28 2001-02-08 Erudite, Llc Systeme et procede destines au tele-apprentissage multimode interactif
US7505921B1 (en) 2000-03-03 2009-03-17 Finali Corporation System and method for optimizing a product configuration
US7246315B1 (en) 2000-05-10 2007-07-17 Realtime Drama, Inc. Interactive personal narrative agent system and method
WO2001093226A3 (fr) * 2000-06-01 2002-10-24 Cehub Com Inc Systeme complet, procede et article de fabrication permettant de fournir les requis d'une formation continue institutionnelle, reglementaire et individuelle, par l'intermediaire d'un reseau de communications
US8096809B2 (en) 2001-04-05 2012-01-17 Convergys Cmg Utah, Inc. System and method for automated end-user support
US8636515B2 (en) 2001-04-05 2014-01-28 Convergys Customer Management Group Inc. System and method for automated end-user support
US7614014B2 (en) 2001-04-05 2009-11-03 Daniel Keele Burgin System and method for automated end-user support
US7844907B2 (en) 2002-10-16 2010-11-30 William Watler System and method for dynamic modification of web content
US7995735B2 (en) 2004-04-15 2011-08-09 Chad Vos Method and apparatus for managing customer data
US11107289B2 (en) 2011-04-08 2021-08-31 Nant Holdings Ip, Llc Interference based augmented reality hosting platforms
CN110322098A (zh) * 2018-03-30 2019-10-11 Cae有限公司 交互式计算机模拟期间的标准操作程序反馈
CN110322098B (zh) * 2018-03-30 2024-03-12 Cae有限公司 交互式计算机模拟期间的标准操作程序反馈

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