探討在電子書學習系統中學生的學習經驗、線上學習行為與學業成績之間的關聯性—以微積分課程為例

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/86716

Title:	探討在電子書學習系統中學生的學習經驗、線上學習行為與學業成績之間的關聯性—以微積分課程為例
Authors:	李宜庭;Li, Yi-Ting
Contributors:	數學系
Keywords:	學習經驗;自我調節效能;滿意度;線上學習行為;學業成績;Learning experience;Self-regulatory efficacy;Satisfaction;Online learning behavior;Learning outcomes
Date:	2021-07-20
Issue Date:	2021-12-07 13:09:19 (UTC+8)
Publisher:	國立中央大學
Abstract:	本研究主要在探討微積分課程學生的「學習經驗」、「線上學習行為」與「學業成績」之間的關聯性；以及探討學生在課後的「自我評估」與前三者之關係。學生的「學習經驗」包含課程內容設計、學生與講師的互動、同學之間的互動、線上學習環境和個人化學習過程；而「自我評估」包含自我調節效能、滿意度和學習成果自評。本研究根據相關的期刊文獻資料，編製出一份用於測量學生課程學習經驗與自我評估之問卷，並於會考時間進行施測。研究對象為中央大學 109 學年度修習微積分課程之學生，共計 423 人，以學生施測之問卷結果為主要資料，結合學生在 BookRoll 線上電子書學習系統的瀏覽紀錄資料，與學生的學業成績進行相關統計數據分析。透過實證分析與研究，運用 SEM 結構方程模型，並經過修正與調整後，統整出學生課程學習經驗、自我評估、線上學習行為與學業成績之間的相互關係。研究結果發現，學生的課程學習經驗會影響學生的線上學習行為；學生的線上學習行為又對於學生的學業成績有非常強的影響力。即學生的學習經驗和線上學習行為皆會影響學業成績。而學生的自我調節效能與線上學習行為也有顯著相關，並影響學業成績。因此，學生的課程學習經驗以及學生在 BookRoll 線上電子書學習系統的線上學習行為，皆可作為預測學生學業成績之指標，並且可以學生的自我調節效能作為參考輔助。 ;The main purpose of this study is to explore the relationship between the " learning experience ", " online learning behavior " and " learning outcomes " of students in calculus courses; and to explore the relationship between students′ "self-assessment" and the first three items. Student’s "learning experience" includes course design, student-instructor interaction, interaction between students, online learning environment and individual learning process; while "self-assessment" includes self-regulatory efficacy, satisfaction and academic performance. Based on relevant journal literature, this study compiled a questionnaire to measure students′ course learning experience and self-assessment. The questionnaire has been tested during the examination time. The subjects of this study are 423 students who have taken the Calculus course in the 109th academic year of National Central University. Use the results of the questionnaire, the browsing record data in BookRoll system, and the learning outcomes of the students for statistical analysis. Through correlation analysis, SEM structural equation model, and after adjustment, the interrelationships among student’s learning experience, self-assessment, online learning behavior and learning outcomes are organized. It was found that students′ learning experience will affect online learning behavior. And students′ online learning behavior has a strong influence on learning outcomes. In addition, the self-regulation efficiency of students is also related to online learning behaviors and affects learning outcomes. Therefore, student’s "learning experience" and student’s "online learning behavior" in BookRoll system can be used to predict student’s "learning outcomes", and student’s "self-regulatory efficacy" can be used as an auxiliary reference.
Appears in Collections:	[Graduate Institute of Mathematics] Electronic Thesis & Dissertation

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