Earticle

초록

영어

Universities have been trying hard in order to help students learn more effectively. However, students' learning outcomes do not look like increasing accordingly. As we observe how students learn, we presume the main reason is not on lack of professors' teaching neither skills nor students' learning abilities, but rather on lack of students' attitudes to learning. In order to make sure if our assumption holds or not, we have been investigating the students' attitude by taking the approach of analyzing the lecture data and trying to find out useful knowledge. In this paper, we investigate correlations of students' achievements and their learning attitudes by analyzing the usage of words of students which appear in the answer-texts of their looking-back self/class-evaluation questionnaire. Precisely, we classify the words into 4 types based on the students' attitudes to learning, represented by the words. As a result of the study, we found that the students in the middle-achievement group have differences in their word-usages, whereas the high- and low-achievement students rather use ordinary words.

목차

Abstract
 1. Introduction
 2. Findings in the Analysis So Far
  2.1. Target Data
  2.2. Correlation between Self-Evaluation Score and Achievement
  2.3. Analysis of Looking-Back Evaluation Texts with KH Coder
 3. Word-Type Analysis for Investigating How Word-Usage Correlates to Achievement
  3.1. Word-Types and Type-Based Analysis of Achievement
  3.2. Weighting the Types of Used Words so as to Represent Amount of Contribution to Student's Achievement
  3.3. Grade Estimation of Student Based on the Types of Words
 4. Comparison of Used Words of High and Low Achievement Students
 5. Concluding Remarks
 Acknowledgements
 References

키워드

저자

• Toshiro Minami [ Kyushu Institute of Information Sciences 6-3-1 Saifu, Dazaifu, Fukuoka, 818-0117 Japan ]
• Yoko Ohura [ Kyushu Institute of Information Sciences 6-3-1 Saifu, Dazaifu, Fukuoka, 818-0117 Japan ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605