DB Seminar [Fall 2014]: Nobu Furukawa
Improving student productivity in online learning depends on designing learning environments based on principles derived from learning science research into how people learn. Students master a skill by solving the sequence of practice exercises related to the skill. The initial development of a skills model on a course, defining skills and associate them with exercises, heavily relies on human intuition, thus it might have a discrepancy which leads to differences between expected and actual student performance.
Learning Factors Analysis (LFA) is an approach for improvement of a skills model by introducing difficulty factors which split a skill. Although LFA is a powerful tool, difficulty factors need to be defined by domain experts. This talk will start with a short introduction to LFA and evaluating method of skills models. Then we will talk about our ongoing research for automatic difficulty factors mining.