Reciprocal tutoring using cognitive tools

Reciprocal tutoring, where peers take turns to tutor each other, is an interesting style of social learning. In the Reciprocal Tutoring System (RTS), three computational cognitive tools were designed to facilitate reciprocal tutoring of Lisp programming on the network. The first is a Petal-style of code-chunk interface, with which a tutee can enter Lisp code without making syntactic errors. The second tool is Diagnosis- Hint Tree, with which a tutor can diagnose and comment on the errors in the tutee's program. The third one is a list of dialogue templates, with which the tutee and the tutor can communicate during the tutoring process. A three-phase experiment was conducted, with each phase using different cognitive tools. In addition, with the help of the cognitive tools, RTS provides a virtual learning companion that can play tutor or tutee. Evaluation results reveal both the strengths and weaknesses of peer-based learning and intelligent tutoring, with supports of different cognitive tools. Peer-based learning supported by cognitive tools is a practical and attractive alternative to intelligent tutoring systems. Exactly which type of tutor is preferred depends on the tutee's cognitive, communication, and emotional needs in the tutorial context.

[1]  R. Slavin.  Cooperative Learning: Theory, Research and Practice , 1990 .

[2]  Albert T. Corbett,et al.  Intelligent Tutoring Systems , 1985, Science.

[3]  Ann L. Brown,et al.  Reciprocal teaching of comprehension-monitoring activities , 1983 .

[4]  Kurt VanLehn,et al.  Repair Theory: A Generative Theory of Bugs in Procedural Skills , 1980, Cogn. Sci..

[5]  Mark L. Miller.  A structured planning and debugging environment for elementary programming , 1979 .

[6]  David W. Johnson,et al.  Learning Together and Alone , 1999 .

[7]  James C. Lester,et al.  Achieving Affective Impact: Visual Emotive Communication in Lifelike Pedagogical Agents , 1999 .

[8]  Johan de Kleer,et al.  A Qualitative Physics Based on Confluences , 1984, Artif. Intell..

[9]  S. Fernberger.  The language and thought of the child. , 1927 .

[10]  Jaime R. Carbonell,et al.  AI in CAI : An artificial intelligence approach to computer-assisted instruction , 1970 .

[11]  Lev Vygotsky.  Mind in society , 1978 .

[12]  A. Baskin,et al.  Studying with the prince: The computer as a learning companion , 1988 .

[13]  Mikhail V. Matz.  A process model for high school algebra errors , 1982 .

[14]  Elliot Soloway,et al.  MENO-II: An AI-Based Programming Tutor. , 1983 .

[15]  Judith D. Wilson,et al.  Artificial Intelligence and Tutoring Systems , 1990 .

[16]  Ann L. Brown,et al.  Reciprocal Teaching of Comprehension-Fostering and Comprehension-Monitoring Activities , 1984 .

[17]  Gordon I. McCalla,et al.  Learning Recursion Through the Use of a Mental Model-Based Programming Environment , 1992, Intelligent Tutoring Systems.

[18]  Tom Routen,et al.  Intelligent Tutoring Systems , 1996, Lecture Notes in Computer Science.

[19]  Stellan Ohlsson,et al.  Automated Cognitive Modeling , 1984, AAAI.

[20]  Allan Collins,et al.  Misconceptions in student's understanding , 1979 .

[21]  Chi-Jen Lin,et al.  An approach to developing computational supports for reciprocal tutoring , 2002, Knowl. Based Syst..

[22]  Derek H. Sleeman.  Inferring (Mal) Rules from Pupil's Protocols , 1982, ECAI.

[23]  Tak-Wai Chan,et al.  Exploring the Design of Computer Supports for Reciprocal Tutoring , 1997 .

[24]  James C. Lester,et al.  Generating Context-Sensitive Explanations in Interactive Knowledge-BasedSystems , 1991 .

[25]  William J. Clancey,et al.  Intelligent Computer-Aided Instruction for Medical Diagnosis , 1979 .

[26]  Kurt VanLehn,et al.  Human Procedural Skill Acquisition: Theory, Model and Psychological Validation , 1983, AAAI.

[27]  Elliot Soloway,et al.  PROUST: An automatic debugger for Pascal programs , 1985 .