Archives for January 2020

Abstract—This research focuses on understanding student performance by giving automatic feedback after writing freestyle comment data in each lesson. Writing comments express students’ learning activities, tendencies, attitudes, and situations involved with the lesson. Random Forest and Support Vector Machine were applied to analyze the students’ prediction results. Also, a Majority Vote (MV) method is employed in consecutive lessons during the semester to the predicted results. The proposed system tracks student’s learning activities and attitudes with different courses and provides valuable feedback to improve educational performance.

Keywords—Automatic feedback, Comment data, SVM, RF, MV

I. INTRODUCTION

Improving the performance of students, determining their actual progress, and enhancing their learning process can be extremely valuable in the educational environment. To achieve a high level of student performance, we have to find ways to measure their current progress and predict the results of the learning process at the earliest stages. Read the full article here “The Effect of An Automatic Feedback System on Students’ Comments to Improve their Performance”