Prediction of Students’ Grades Based on Free-Style Comments Data

  • Shaymaa E. Sorour
  • Tsunenori Mine
  • Kazumasa Goda
  • Sachio Hirokawa
Conference paper

DOI: 10.1007/978-3-319-09635-3_15

Volume 8613 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Sorour S.E., Mine T., Goda K., Hirokawa S. (2014) Prediction of Students’ Grades Based on Free-Style Comments Data. In: Popescu E., Lau R.W.H., Pata K., Leung H., Laanpere M. (eds) Advances in Web-Based Learning – ICWL 2014. ICWL 2014. Lecture Notes in Computer Science, vol 8613. Springer, Cham

Abstract

In this paper we propose a new approach based on text mining technique to predict student’s performance using LSA (latent semantic analysis) and K-means clustering method. The present study uses free style comments written by students after each lesson. Since the potentials of these comments can reflect students’ learning attitudes, understanding and difficulties to the lessons, they enable teachers to grasp the tendencies of students’ learning activities.To improve this basic approach, overlap method and similarity measuring technique are proposed. We conducted experiments to validate our proposed methods. The experimental results illustrated that prediction accuracy was 73.6% after applying the overlap method and that was 78.5% by adding the similarity measuring.

Keywords

Comments Data Overlap method Similarity measuring 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Shaymaa E. Sorour
    • 1
    • 2
  • Tsunenori Mine
    • 2
  • Kazumasa Goda
    • 3
  • Sachio Hirokawa
    • 4
  1. 1.Kafr Elsheik UniversityKafr ElsheikhEgypt
  2. 2.Kyushu UniversityFukuokaJapan
  3. 3.Kyushu Institute of Information ScienceFukuokaJapan
  4. 4.Kyushu UniversityFukuokaJapan