Mining Student Behavior Models in Learning-by-Teaching Environments

This paper discusses our approach to building models and analyzing student behaviors in different versions of our learning by teaching environment where students learn by teaching a computer agent named Betty using a visual concept map representation. We have run studies in fifth grade classrooms to compare the different versions of the system. Students' interactions on the system, captured in log files represent their performance in generating the causal concept map structures and their activities in using the different tools provided by the system. We discuss methods for analyzing student behaviors and linking them to student performance. At the core of this approach is a hidden Markov model methodology that builds students' behavior models from data collected in the log files. We discuss our modeling algorithm and the interpretation of the models.

• Type: Conference
• Year: 2008
• Where: EDM
• Authors: Hogyeong Jeong, Gautam Biswas
• Keywords: Concept Map, Data Mining, EDM 2008, Log Files, Student Behaviors