Limitations of Student Control: Do Students Know When They Need Help?

Intelligent tutoring systems often emphasize learner control: They let the students decide when and how to use the system's intelligent and unintelligent help facilities. This means that students must judge when help is needed and which form of help is appropriate. Data about students' use of the help facilities of the PACT Geometry Tutor, a cognitive tutor for high school geometry, suggest that students do not always have these metacognitive skills. Students rarely used the tutor's on-line Glossary of geometry knowledge. They tended to wait long before asking for hints, and tended to focus only on the most specific hints, ignoring the higher hint levels. This suggests that intelligent tutoring systems should support students in learning these skills, just as they support students in learning domain-specific skills and knowledge. Within the framework of cognitive tutors, this requires creating a cognitive model of the metacognitive help-seeking strategies, in the form of production rules. The tutor then can use the model to monitor students' metacognitive strategies and provide feedback.

[1]  D. Wood,et al.  Help seeking, learning and contingent tutoring , 1999, Comput. Educ..

[2]  Alan M. Lesgold,et al.  Sherlock 2: An Intelligent Tutoring System Built on the LRDC Tutor Framework , 2020 .

[3]  C. Hirsch.  Curriculum and Evaluation Standards for School Mathematics , 1988 .

[4]  John R. Anderson,et al.  Skill Acquisition and the LISP Tutor , 1989, Cogn. Sci..

[5]  Kurt VanLehn,et al.  A model of the self-explanation effect. , 1992 .

[6]  Kevin A. Gluck,et al.  Individual Differences in Patterns of Spontaneous Online Tool Use , 1996 .

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

[8]  Daniel D. Suthers,et al.  Automated Advice-Giving Strategies for Scientific Inquiry , 1996, Intelligent Tutoring Systems.

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

[10]  John Seely Brown,et al.  An Investigation of Computer Coaching for Informal Learning Activities. , 1978 .

[11]  Matthew W. Lewis,et al.  Self-Explonations: How Students Study and Use Examples in Learning to Solve Problems , 1989, Cogn. Sci..

[12]  Mimi Recker,et al.  Student Strategies for Learning Programming from a Computational Environment , 1992, Intelligent Tutoring Systems.

[13]  K. VanLehn,et al.  Teaching Meta-cognitive Skills: Implementation and Evaluation of a Tutoring System to Guide Self- Explanation While Learning from Examples , 1999 .

[14]  Vincent Aleven,et al.  Tutoring Answer Explanation Fosters Learning with Understanding , 1999 .