ITS and SCORM Xiangen Hu, Andrew Olney, Eric Mathews, Art Graesser The University of Memphis

Agenda AutoTutor ADL and SCORM ITS and SCORM2004 Summary

AutoTutor

Tutoring Effective Tutoring Involves the Student: (Graesser, Person, and Magliano 1995; Chi 1996) –Taking an active role in knowledge construction –Asking questions –Generating their own explanations –Recognizing their misconceptions –Synthesizing information

Tutoring Untrained tutors are effective (Bloom 1984; Cohen, Kulik, and Kulik 1982; Graesser and Person 1994) Possible explanations for tutoring effectiveness: (Graesser, Person, and Magliano 1995) –Interactive dialog –Collaborative construction of knowledge –Explanations are generated –Concrete examples –Deep reasoning questions

AutoTutor A computer program that is designed to tutor students in computer literacy and conceptual physics. Simulates the tutoring strategies used by human tutors. AutoTutor interacts with students and covers topic material in the course of a conversation.

AutoTutor Language Extraction Speech act classifier Latent Semantic Analysis Curriculum Script Animated Agent Dialog Management Topic/Problem Selection

When a car without headrests on the seats is struck from behind, the passengers often suffer neck injuries. Why do passengers get neck injuries in this situation? Question Head Simulation Parameter Controls Describe what happens

ADL and SCORM

What is ADL? Advanced Distributed Learning

Advanced Distributed Learning: What’s New? Advanced Technologies –Advanced delivering technology –Advanced assessment methodologies Advanced Learning Paradigms –Cognitive theory of learning –Intelligent tutoring Advanced Standards –Shareable learning objects –Anyone, anywhere, anytime, any system

Distributed Learning Distributed Learning Embedded Training Embedded Training Distributed Simulation Distributed Simulation Performance Assessment Performance Assessment Digital Knowledge Libraries Digital Knowledge Libraries Office School Home Field In Transit

ADL Co-Labs and Partnership Labs An open collaborative environment for sharing learning technology research, development, and assessments.

ADL Vision ADL STRATEGY Any Time Any Where Learning Right Time Right Place Learning Classroom Electronic Classroom CBT/CD-ROMs Distributed Learning web-based modular content intelligent tutors interoperability and reuse wide spread collaboration Distance Learning web-based Classroom video tele-training

Strategy Exploit existing network-based technologies Create platform-neutral, reusable courseware and content to lower costs Promote wide spread collaboration to satisfy common needs Enhance performance with emerging and next- generation learning technologies Develop common framework that drives COTS product cycle Establish a coordinated implementation process Explore the technology for “learning objects”

Functional Requirements for “learning objects” –Accessibility: access instructional components from one remote location and deliver them to many other locations –Interoperability: use instructional components developed in one location, with one set of tools or platform, in another location, with a different set of tools or platform –Adaptability: tailor instruction to individual and situational needs –Reusability: incorporate instructional components into multiple applications –Durability: operate instructional components when base technology changes, without redesign or recoding –Affordability: increase learning effectiveness significantly while reducing time and costs

ADL “SCORM” –Need of standards Best practice in all other industries –Proven methodology Object oriented –Cutting edge technology xml based –“SCORM” Sharable Content Object Reference Model –Innovated Strategy ADL Co-Labs PlugFest

ITS and SCORM2004

ITS basics Two Levels of questions –What material does the tutor want to cover with the student? Knowledge of the domain Teacher’s model Student’s Model –How does the tutor present the material during the session? Teaching knowledge Tactics Theory driven

SCORM2004 SN Sequencing and Navigation –Activity Tree Smallest unit is SCO –Clustering Allows structuring to implement knowledge structure –Rollup Rollover Dynamic sequencing adaptive to the users Capable of answering the first question of ITS –Organize knowledge Not a standard for the second level question –Theory neutral

Formal Models Need of formal model –Having a standard, one needs a model An ITS model that model Teacher/Student Interaction –ITS contains A set of items A relation among the items –ITS Presents a stimulus to students Receive a response from students –ITS Assign (numerical) values to any combination of stimulus/response pair Store interaction history Select next item as stimulus based on probability distribution that is conditional to the prior interaction history.

Formal Models Two types of Models for ITS –knowledge based REDEEM (Ainsworth and Wood 2004): Advanced Planning –uncertainty based Markov Decision Processes (Matsuda & Van Lehn, 2001): Based on interaction between tutor and student

Summary

ITS are theory driven in nature –Teaching tactics emphasize effective micro dialog/interaction between tutor and student –Highly individualized, tailored to user learning style –Smallest unit may be simple feedback such as hint or prompt –Probability of selecting next item is determined by specific teaching tactics

Summary SCORM SN emphasize higher level knowledge structure –Theory neutral –Provide basic selection mechanism at the level of knowledge structure –Have difficulty covering all teaching tactics as standard –The concept of assets allow ITS objects handle micro interactions, but not capable capture detailed interaction at the asset level

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