Work in progress: Application of unsupervised learning method toward student's metacognition assessment

There has been awareness of the importance of metacognitive skill in learning processes, especially for university students, who are required to be more self-regulated. Therefore, monitoring the development of such skill is needed to ensure student's achievements. Currently, in classroom learning environments, student's metacognition can be observed conventionally by using interview or think-aloud procedures, however, the tasks are tedious and impractical for big number of students. Therefore, an automatic student's metacognition assessment/modeling is in progress. This paper proposes a partly automatic metacognition assessment, which is an implementation of unsupervised learning method. This proposed method is proven using a case study in which the dataset was gathered by administering Metacognitive Awareness Inventory (MAI) questionnaire to undergraduate students in our department. Experiment shows that the proposed method could be utilized for automatic assessment of student's metacognition. Two groups of students are identified, one that does well in their metacognitive awareness and the other one that needs further guidance and advisory to help them achieve better results and avoid failures.