A Method Detecting Student’s Flow Construct during School Tests through Electroencephalograms (EEGs): Factors of Cognitive Load, Self-Efficacy, Difficulty, and Performance

构造(python库) 认知负荷 考试(生物学) 认知 心理学 脑电图 逻辑回归 认知心理学 计算机科学 机器学习 生物 精神科 古生物学 神经科学 程序设计语言
作者
Shu-Fen Wu,Chieh-Hsin Kao,Yu-Ling Lu,Chi-Jui Lien
出处
期刊:Applied sciences [MDPI AG]
卷期号:12 (23): 12248-12248 被引量:2
标识
DOI:10.3390/app122312248
摘要

This study gathers and examines information about the flow state’s emergence during tests and its factors using an electroencephalogram (EEG) to establish a method and reveal an individual student’s flow construct. Through a single-case experimental design and 766 test items, multiple measurements were performed on a 14-year-old junior high school science-gifted student. During the test, self-efficacy, item difficulty, cognitive load, and test performance (long-term test performance [LT-tp] and short-term test performance [ST-tp]) were examined to establish the construct of EEG-detected, real-time flow states (EEG-Fs). Based on the chi-square test of independence results, the EEG-F had a significant correlation with the student’s cognitive load, self-efficacy, LT-tp, and item difficulty. Furthermore, a J48 decision tree analysis and logistic regression revealed four inhibiting and two inducing conditions affecting the emergence of EEG-Fs. The two inducing conditions included (1) high self-efficacy with a low cognitive load (odds ratio (OR) = 3.7) and (2) high cognitive load when combined with high self-efficacy and LT-tp for low-difficulty items (OR = 3.5). The established method and findings may help teaching designers or automated teaching applications detect the individual student’s flow construct to select appropriate test tasks accordingly, resulting in an optimal experience and better achievements.
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