Interactive Concept Maps and Learning Outcomes in Guru

Concept maps are frequently used in K 12 educational settings. The purpose of this study is to determine whether students’ performance on interactive concept map tasks in Guru, an intelligent tutoring system, is related to immediate and delayed learning outcomes. Guru is a dialogue based system for high school biology that intersperses concept map tasks within the tutorial dialogue. Results indicated that when students first attempt to complete concept maps, time spent on the maps may be a good indicator of their understanding, whereas the errors they make on their second attempts with the maps may be an indicator of the knowledge they are lacking. This pattern of results was observed for one cycle of testing, but not replicated in a second cycle. Differences in the findings for the two testing cycles are most likely due to topic variations.

[1]  Jacqueline Bourdeau,et al.  Advances in Intelligent Tutoring Systems , 2010 .

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

[3]  Kathleen M. Fisher,et al.  Mapping Biology Knowledge , 2000 .

[4]  Susanne P. Lajoie,et al.  Intelligent Tutoring Systems, 9th International Conference, ITS 2008, Montreal, Canada, June 23-27, 2008, Proceedings , 2008, Intelligent Tutoring Systems.

[5]  Chen-Lin C. Kulik,et al.  Effectiveness of computer-based instruction: An updated analysis. , 1991 .

[6]  Martha W. Evens,et al.  CIRCSIM-Tutor: An Intelligent Tutoring System Using Natural Language Dialogue , 1997, ANLP.

[7]  J. Novak The Theory Underlying Concept Maps and How To Construct Them , 2004 .

[8]  K. VanLehn The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring Systems , 2011 .

[9]  Sidney K. D'Mello,et al.  Dialogue Modes in Expert Tutoring , 2008, Intelligent Tutoring Systems.

[10]  Eugene A. Jongsma Cloze Instruction Research: A Second Look. , 1980 .

[11]  J. Alderson THE CLOZE PROCEDURE AND PROFICIENCY IN ENGLISH AS A FOREIGN LANGUAGE , 1979 .

[12]  Arthur C. Graesser,et al.  A Revised Algorithm for Latent Semantic Analysis , 2003, IJCAI.

[13]  Olusola O. Adesope,et al.  Learning With Concept and Knowledge Maps: A Meta-Analysis , 2006 .

[14]  Betsy Williams Sanders,et al.  Examining the Role of Gestures in Expert Tutoring , 2010, Intelligent Tutoring Systems.

[15]  Michelene T. H. Chi,et al.  Active-Constructive-Interactive: A Conceptual Framework for Differentiating Learning Activities , 2009, Top. Cogn. Sci..

[16]  Gautam Biswas,et al.  LEARNING BY TEACHING: A NEW AGENT PARADIGM FOR EDUCATIONAL SOFTWARE , 2005, Appl. Artif. Intell..

[17]  J. Novak Concept mapping: A useful tool for science education , 1990 .

[18]  Wilson L. Taylor,et al.  “Cloze Procedure”: A New Tool for Measuring Readability , 1953 .

[19]  Andrew Olney,et al.  Generating Concept Map Exercises from Textbooks , 2011, BEA@ACL.

[20]  Arthur C. Graesser,et al.  Tutorial Dialog in Natural Language , 2010, Advances in Intelligent Tutoring Systems.

[21]  Joseph P. Magliano,et al.  Collaborative dialogue patterns in naturalistic one-to-one tutoring , 1995 .

[22]  A. Graesser,et al.  Computerized Learning Environments That Incorporate Research in Discourse Psychology, Cognitive Science, and Computational Linguistics. , 2005 .