Does Self-Efficacy Correlate with Positive Emotion and Academic Performance in Collaborative Learning?

被引:2
|
作者
Dehbozorgi, Nasrin [1 ]
Maher, Mary Lou [2 ]
Dorodchi, Mohsen [3 ]
机构
[1] Kennesaw State Univ, Dept Software Engn, Marietta, GA 30060 USA
[2] UNC Charlotte, Dept Software Informat Syst, Charlotte, NC USA
[3] UNC Charlotte, Dept Comp Sci, Charlotte, NC USA
关键词
self-efficacy; social skill; computer science; emotion mining; sentiment analysis; NLP; collaborative active learning; BELIEFS; SCIENCE;
D O I
10.1109/FIE49875.2021.9637471
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This full research paper studies the correlation of self-efficacy in computer science as well as learning and social skills with students' academic performance and their emotions in collaborative learning environments. Self-efficacy is an essential part of social cognitive theory and provides the foundation for analyzing human thoughts, motivations, and actions. Studies show that students' successful performance and accomplishment are directly affected by the level of self-efficacy. Therefore, analyzing self-efficacy in engineering education is important since it can impact the learning process in academic settings as well as provide a metric to track for improvement. Social cognitive theories also emphasize that students' interaction with each other affects their learning process and how they perform in educational settings. In previous work [5], we analyzed students' conversations in low-stake teams in an introductory programming course (CS1) and observed a strong positive correlation between students' positive emotions while interacting with each other with their performance in the course. In this study, we focus on the correlation of self-efficacy with learner's emotion and performance. We measure students' self-efficacy with a standard instrument called "Student Attitudes Toward STEM (S-STEM) Survey". For this purpose, we asked the participants to self-report on a 5-point Likert-scaled survey including 20 questions. These 20 questions are grouped into 2 main categories of computer science and learning/social skills. Students' emotions were extracted from their speeches in teams by applying natural language processing (NLP) methods. The result of data analysis shows a statistically significant correlation between overall self-efficacy and performance in the course and positive emotions during the teamwork. We further investigate which category of self-efficacy questions most correlate with students' performance. The result shows self-efficacy in interpersonal skills and learning ability most impact students' performance.
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收藏
页数:8
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