Teaching evaluation using data mining on moodle LMS forum
Chakrit Pong-inwong, Wararat Songpan · International Conference on New Trends in Information Science, Service Science and Data Mining · 2012
Recently, teaching evaluation is defined the main part of quality in education. The students normally make answers on questionnaire that are divided into types; close-end question and open-end question. The close-end question is simple answer as multi-choices that are easily processed by statistical evaluation. On the other hand, open-end question gives the person answering in phrases or statements that are recommended their teacher. The problem is mostly LMS ignored these open-end questions to overall analysis. Therefore, analysis and processing of these open-end questions are very importance and determined teaching. This research presents analysis model for teaching evaluation from answering and posting a comment to discussion in form of open-end question obtained from moodle LMS forum using data mining techniques. The techniques extract classification of attitudes that are defined positive and negative attitude from students to instructor for improvement of learning and teaching. These classification models are compared three algorithms; ID3, BFTree and Naive Bayes. The experimental results, the decision tree is achieved correctly classifier 80% compared with others.