Feedback Micro-engineering in EER-Tutor

Although existing educational systems are based on various learning theories, these theories are rarely used when developing feedback. Our research is based on the theory of learning from performance errors, which suggests that feedback should provide long and short-term learning advantages through revision of faulty knowledge in the context of learners' errors. We hypothesized that principled, theory-based feedback would have a positive impact on learning. To test the hypothesis we performed an experiment with EER-Tutor, an intelligent tutoring system that teaches database design. The results of the study support our hypothesis: the students who learned from theory-based feedback had a higher learning rate than their peers. We conclude that learning theories should be used to formulate design guidelines for effective feedback.

[1]  John Self Bypassing the intractable problem of student modelling , 1988 .

[2]  Antonija Mitrovic,et al.  An Intelligent Tutoring System for Entity Relationship Modelling , 2004, Int. J. Artif. Intell. Educ..

[3]  Antonija Mitrovic,et al.  KERMIT: A Constraint-Based Tutor for Database Modeling , 2002, Intelligent Tutoring Systems.

[4]  A. Grafstein MIT Encyclopedia of the Cognitive Sciences , 2000 .

[5]  Antonija Mitrovic,et al.  DB-Suite: Experiences with Three Intelligent, Web-Based Database Tutors. , 2004 .

[6]  John R. Anderson,et al.  Rules of the Mind , 1993 .

[7]  Stellan Ohlsson,et al.  Learning from Performance Errors. , 1996 .

[8]  Antonija Mitrovic,et al.  NORMIT: a Web-enabled tutor for database normalization , 2002, International Conference on Computers in Education, 2002. Proceedings..

[9]  Reva Freedman Atlas: A Plan Manager for Mixed-Initiative, Multimodal Dialogue , 1999 .

[10]  Antonija Mitrovic,et al.  A Comparative Analysis of Cognitive Tutoring and Constraint-Based Modeling , 2003, User Modeling.

[11]  Mia Stern,et al.  Applications of AI in education , 1996, CROS.

[12]  Kenneth R. Koedinger,et al.  An Empirical Assessment of Comprehension Fostering Features in an Intelligent Tutoring System , 2002, Intelligent Tutoring Systems.

[13]  Guy L. Steele,et al.  Common Lisp the Language , 1984 .

[14]  Brent Martin Intelligent tutoring systems: The practical implementation of constraint-based modelling , 2002 .

[15]  Ramez Elmasri,et al.  Fundamentals of Database Systems , 1989 .

[16]  Susanne P. Lajoie,et al.  Apprenticeship training in the workplace: computer-coached practice environment as a new form of apprenticeship , 1989 .

[17]  Tanja Mitrovic,et al.  Constraint-based tutors: a success story , 2001, AIED.

[18]  Steven Brodhead,et al.  Java XML Programmer's Reference , 2001 .

[19]  Vinod Goel,et al.  Motivating the Notion of Generic Design within Information-Processing Theory: The Design Problem Space , 1989, AI Mag..

[20]  Stephen J. Payne,et al.  Algebra Mal-Rules and Cognitive Accounts of Error , 1990, Cogn. Sci..

[21]  Antonija Mitrovic,et al.  Evaluation of a Constraint-Based Tutor for a Database Language , 1999 .

[22]  Cristina Conati,et al.  Building and evaluating an intelligent pedagogical agent to improve the effectiveness of an educational game , 2004, IUI '04.

[23]  Ralph Johnson,et al.  design patterns elements of reusable object oriented software , 2019 .

[24]  Antonija Mitrovic,et al.  An Intelligent SQL Tutor on the Web , 2003, Int. J. Artif. Intell. Educ..

[25]  Marlene Jones,et al.  The State of Student Modelling , 1994 .

[26]  B. Bloom The 2 Sigma Problem: The Search for Methods of Group Instruction as Effective as One-to-One Tutoring , 1984 .

[27]  Ramez Elmasri,et al.  Fundamentals of Database Systems, 5th Edition , 2006 .

[28]  Carolyn Penstein Rosé,et al.  Fading and Deepening: The Next Steps for Andes and other Model-Tracing Tutors , 2000, Intelligent Tutoring Systems.

[29]  Stephen J. Payne,et al.  Algebra Mal‐Rules and Cognitive Accounts of Error , 1990 .

[30]  Gerhard Weber,et al.  User Modeling and Adaptive Navigation Support in WWW-Based Tutoring Systems , 1997 .

[31]  C. Lebiere,et al.  The Atomic Components of Thought , 1998 .

[32]  Deborah A. Lapeyre XSLT: programmer's reference, 2nd edition , 2001 .

[33]  Allen and Rosenbloom Paul S. Newell,et al.  Mechanisms of Skill Acquisition and the Law of Practice , 1993 .

[34]  Stellan Ohlsson,et al.  Constraint-Based Student Modeling , 1994 .

[35]  John R. Anderson,et al.  Cognitive Tutors: Lessons Learned , 1995 .

[36]  Chris R. Jesshope Computers as Tutors: Solving the Crisis in Education , 1999, J. Educ. Technol. Soc..

[37]  Antonija Mitrovic,et al.  Using Evaluation to Shape ITS Design: Results and Experiences with SQL-Tutor , 2002, User Modeling and User-Adapted Interaction.

[38]  Jean McKendree,et al.  Effective Feedback Content for Tutoring Complex Skills , 1990, Hum. Comput. Interact..