Immediate Elaborated Feedback Personalization in Online Assessment

Providing a student with feedback that is timely, most suitable and useful for her personality and the performed task is a challenging problem of online assessment within Web-based Learning Systems (WBLSs). In our recent work we suggested a general approach of feedback adaptation in WBLS and through a series of experiments we demonstrated the possibilities of tailoring the feedback that is presented to a student as a result of her response to questions of an online test, taking into account the individual learning styles (LS), certitude in a response and correctness of this response. In this paper we present the result of the most recent experimental field study where we tested two feedback adaptation strategies in real student assessment settings (73 students had to answer 15 multiple-choice questions for passing the midterm exam). The first strategy is based on the correctness and certitude of the response, while the second strategy takes student LS into account as well. The analysis...

• Type: Conference
• Year: 2008
• Where: ECTEL
• Authors: Ekaterina Vasilyeva, Paul De Bra, Mykola Pechenizkiy
• Keywords: ECTEL 2008, Feedback Adaptation, Feedback Adaptation Strategies, Machine Learning, Student