Issue No. 02 - April-June (2009 vol. 2)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TLT.2009.21
Davide Fossati , University of Illinois at Chicago, Chicago
Barbara Di Eugenio , University of Illinois at Chicago, Chicago
Christopher W. Brown , United States Naval Academy, Annapolis
Stellan Ohlsson , University of Illinois at Chicago, Chicago
David G. Cosejo , University of Illinois at Chicago, Chicago
Lin Chen , University of Illinois at Chicago, Chicago
We developed two versions of a system, called iList, that helps students learn linked lists, an important topic in computer science curricula. The two versions of iList differ on the level of feedback they can provide to the students, specifically in the explanation of syntax and execution errors. The system has been fielded in multiple classrooms in two institutions. Our results indicate that iList is effective, is considered interesting and useful by the students, and its performance is getting closer to the performance of human tutors. Moreover, the system is being developed in the context of a study of human tutoring, which is guiding the evolution of iList with empirical evidence of effective tutoring.
Computer-assisted instruction, computer science education, education, evaluation/methodology, constraint-based modeling, intelligent tutoring systems.
S. Ohlsson, D. Fossati, C. W. Brown, D. G. Cosejo, L. Chen and B. Di Eugenio, "Supporting Computer Science Curriculum: Exploring and Learning Linked Lists with iList," in IEEE Transactions on Learning Technologies, vol. 2, no. , pp. 107-120, 2009.