Kazumasa Goda

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To grasp a student's lesson attitude and learning situation and to give a feed back to each student are educational foundations. Goda et al. proposed the PCN method to estimate a learning situation from a comment freely written by students[6, 7]. The PCN method categorizes comments into three items of P (previous), C(current) and N(next). They pointed out(More)
In this paper we propose a new approach based on text mining techniques for predicting student performance using LSA (latent semantic analysis) and K-means clustering methods. The present study uses free-style comments written by students after each lesson. Since the potentials of these comments can reflect student learning attitudes , understanding of(More)
Continuously tracking students during a whole semester plays a vital role to enable a teacher to grasp their learning situation , attitude and motivation. It also helps to give correct assessment and useful feedback to them. To this end, we ask students to write their comments just after each lesson , because student comments reect their learning attitude(More)
Assessment of learning progress and learning gain play a pivotal role in education fields. New technologies like comment data mining promote the use of new types of contents; student comments highly reflect student learning attitudes and activities compared to more traditional methods and they can be a powerful source of data for all forms of assessment. A(More)