An automated cognitive analysis model for online asynchronous discussion

Abstract

Evaluation of students’ cognitive abilities needs to be done as part of evaluating student learning outcomes. This evaluation must not only be done in conventional learning, but this must also be done in online learning. Evaluation of students’ cognitive abilities can be done through cognitive evaluation of messages posted by students in online asynchronous discussion. There are several studies that have addressed the problem of evaluating students ‘cognitive abilities in on-line learning, but the process of identifying students’ cognitive abilities in these studies has not been fully automated. There are parts of the identification process still carried out by humans. This study proposes a model that can produce classification automation of cognitive levels of messages posted by students in online asynchronous discussion. The messages used in this study are messages written in Indonesian. The proposed model consists of four main processes, namely the process of creating corpus, extraction and selection of features, classifier and training development, and testing. This model can help lecturers to identify cognitive levels of messages. The proposed model is expected to improve the performance of evaluation systems of e-learning learning.