藉由電子書學習系統探討學生線上學習準備度、線上學習行為與學習成果之間的關係－以微積分課程為例

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题名:	藉由電子書學習系統探討學生線上學習準備度、線上學習行為與學習成果之間的關係－以微積分課程為例
作者:	鄭兆傑;Jheng, Jhao-Jie
贡献者:	數學系
关键词:	線上學習準備度;線上學習行為;自主學習;Learning readiness;Online learning behavior;Self-directed learning
日期:	2021-07-26
上传时间:	2021-12-07 13:09:36 (UTC+8)
出版者:	國立中央大學
摘要:	本研究主要透過電子書學習系統探討學生的「線上學習準備度」、「線上學習行為」、「學習成果」與「自我評估」之間的相互關係，「線上學習準備度」中包含了電腦／網路的自我效能、自主學習、學習者控制、線上學習的動機、線上交流的自我效能等五個項目。本研究挑選了中央大學 109 學年度選修微積分課程的部分學生共 429 人作為研究對象，擬制了一份問卷來測量學生的線上學習準備度與自我評估，並於本學期第二次會考時施策。另外結合 BookRoll線上學習系統的後台數據與問卷的回饋結果，透過統計軟體 SPSS 統整出線上學習準備度、線上學習行為、學習成果與自我評估之間的相互關係。並運用結構方程模型（Structural Equation Modeling, SEM）分析學生的線上學習準備度、線上學習行為與學習成果三者之間的架構與關聯性。研究結果發現，學生的線上學習準備度對於學生的學習成果，為顯著正相關；學生的線上學習行為對於學業成績，為顯著正相關。因此我們可以藉由學生的線上學習準備度以及在 BookRoll學習系統上的學習行為來預測學生的學習成效。;The purpose of the research was to identify the relationship among students’ “online learning readiness”, “online learning behavior”, “learning outcomes” and “self-assessment” through the e-book learning system. "Online learning readiness" includes five items: computer/internet self-efficacy, self-directed learning, learner control, motivation for online learning, and online communication self-efficacy. In this study, the 429 students who took the calculus course in the 109th academic year of Central University were selected as the subjects. A questionnaire was drawn up to measure students′ online learning readiness and self-assessment, and the questionnaire was sent during the second examination of this semester. In addition, combined with the back-end data of the BookRoll online learning system and the feedback from the questionnaire, the correlation between online learning readiness, online learning behavior, learning outcomes and self-assessment was summarized through the statistical software SPSS. And use structural equation modeling (SEM) to analyze the structure and correlation between students′ online learning readiness, online learning behavior, and learning outcomes. The results of the study were that students’ online learning readiness is significantly positively correlated with students’ learning outcomes; students’ online learning behaviors are significantly positively correlated with academic performance. Therefore, we can predict students′ learning effectiveness based on their online learning readiness and their learning behavior on the BookRoll learning system. academic year of Central University were selected as the subjects. A questionnaire was drawn up to measure students′ online learning readiness and self-assessment, and the questionnaire was sent during the second examination of this semester. In addition, combined with the back-end data of the BookRoll online learning system and the feedback from the questionnaire, the correlation between online learning readiness, online learning behavior, learning outcomes and self-assessment was summarized through the statistical software SPSS. And use structural equation modeling (SEM) to analyze the structure and correlation between students′ online learning readiness, online learning behavior, and learning outcomes. The results of the study were that students’ online learning readiness is significantly positively correlated with students’ learning outcomes; students’ online learning behaviors are significantly positively correlated with academic performance. Therefore, we can predict students′ learning effectiveness based on their online learning readiness and their learning behavior on the BookRoll learning system.
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