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Analysis of Student Activity and Its Effect Utilizing Programming Education Support Tool pgtracer

発表形態:
原著論文
主要業績:
その他
単著・共著:
共著
発表年月:
2018年07月
DOI:
10.1109/IIAI-AAI.2018.00057
会議属性:
国際会議(国内開催を含む)
査読:
有り
リンク情報:
7th International Conference on Learning Technologies and Learning Environments (LTLE2018)

日本語フィールド

著者:
Miyuki Murata, Naoko Kato, Tetsuro Kakeshita
題名:
Analysis of Student Activity and Its Effect Utilizing Programming Education Support Tool pgtracer
発表情報:
7th International Conference on Learning Technologies and Learning Environments (LTLE2018) ページ: pp. 261-267
キーワード:
Learning Analytics (LA), computer programing education; e-learning; Moodle; fill-in-the-blank question
概要:
抄録:
In this paper, we analyze learning activity of students and its effect when we utilize the programming education support tool pgtracer to provide homework for their programming course. We assigned homework utilizing pgtracer to the students and incorporated its learning achievement to their evaluation of the course. As a result, this method improved the learning activity of the students. Their understanding of the trace table was related to understanding of the programming. Their answering processes to reach to a correct answer varied according to their programming skill. As for their understanding of the program, those who continuously did their homework understood a program better than those who only prepared for the exam in a short term. Therefore, we can conclude that providing homework utilizing pgtracer is effective for students’ centered learning of programming.

英語フィールド

Author:
Miyuki Murata, Naoko Kato, Tetsuro Kakeshita
Title:
Analysis of Student Activity and Its Effect Utilizing Programming Education Support Tool pgtracer
Announcement information:
7th International Conference on Learning Technologies and Learning Environments (LTLE2018) Page: pp. 261-267
Keyword:
Learning Analytics (LA), computer programing education; e-learning; Moodle; fill-in-the-blank question
An abstract:
In this paper, we analyze learning activity of students and its effect when we utilize the programming education support tool pgtracer to provide homework for their programming course. We assigned homework utilizing pgtracer to the students and incorporated its learning achievement to their evaluation of the course. As a result, this method improved the learning activity of the students. Their understanding of the trace table was related to understanding of the programming. Their answering processes to reach to a correct answer varied according to their programming skill. As for their understanding of the program, those who continuously did their homework understood a program better than those who only prepared for the exam in a short term. Therefore, we can conclude that providing homework utilizing pgtracer is effective for students’ centered learning of programming.


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