以學習分析初探線上學習者之學習動機對其線上學習行為模式之影響:以校園學術研究倫理課程為例

Abstract

本研究旨在應用學習分析探討學習動機與線上學習行為模式之影響,以臺 灣北部地區某三所國立大學便利取樣 161 位研究生為樣本。研究者自行架設具有 行為追蹤記錄功能之學術研究倫理線上課程,蒐集登入次數、教材閱讀次數、測 驗失敗次數、教材閱讀時間與測驗時間並與學習動機問卷及使用者投入度問卷進 行統計分析。接著將以學習動機與線上教材閱讀時間為學習者進行階層式群集分 析,並將行為追蹤記錄編碼為認真閱讀、隨意閱讀、多工閱讀、測驗成功、測驗 失敗,暫離六個編碼,以序列分析深入探討各群集之線上學習行為模式差異。 本研究發現學習動機與實際閱讀時間並無顯著關聯,且學習者僅帄均閱讀一 半的教材即通過本課程,但經過本課程後顯著提升學習者之學習動機。然而,高 動機學習者在多工情境中表現出相對認真的學習模式,且線上教材閱讀時間為顯 著認真進行線上課程之指標。分析亦顯示學習者偏好以少量多次方式進行線上學 習,使用者投入度與實際行為投入並無顯著關聯,且遭遇測驗失敗等負面回饋與 使用投入度呈負相關。因此,本研究認為線上學習者普遍而言傾向被動學習,但 學習動機仍是一個影響學習行為之因素。 本研究建議,未來線上學習帄臺或教學設計應設法提高學習動機,例如可結 合有趣的多媒體動畫;且應縮短課程單元長度、避免給予負面回饋。此外,線上 教材閱讀時間可作為衡量線上學習者認真學習的標準,未來線上學習帄臺應設計 學習分析功能,供線上課程管理者或教師給予學習者引導與回饋。此研究成果希 望能作為從事線上帄臺設計或課程管理之開發人員、教師與研究者之參考。

The purpose of this study was to explore how online learners’ motivation influences their online learning behavioral patterns. Learning analytics was applied to analyze the learning behaviors in an online academic research course. Participants were 161 graduate students at three national universities in northern Taiwan. A self-developed learning management system was used to track the usage data, including the frequencies of logins, online reading, and failing exams, as well as the duration of reading and exam. The instruments included the learning motivation scale and the user engagement scale. Learners were clustered into three groups based on their learning motivation and online reading duration using the hierarchical cluster analysis. In order to understand the differences in online learning behaviors among these three groups, system logs were transformed into six codes for lag sequential analysis: intensive reading, skimmed reading, multi-tasking reading, passing exam, failing exam, and offline. The results showed that even though the learners completed the task after reading only half of the course materials, the online course still significantly increased learners’ motivation. Students in the high-motivation group showed intensive reading behaviors in the multi-tasking reading situation. Online reading duration was a significant predictor of the serious learning behavior. In addition, user engagement was not correlated with behavior engagement, online learners preferred to learn IIfragmentally, and negative feedback, such as failing the exam, was negatively correlated with the user engagement. The findings showed that online learners tended to be passive, while learning motivation was still a key factor which facilitated the learning behavior. This study suggests that online learning platforms should be designed to increase learning motivation, for examples, incorporating interesting multimedia, decreasing the learning duration for each unit, and avoiding negative feedback. Furthermore, online reading duration could be used as a key indicator to evaluate how seriously the students study online. Future online learning platforms could collect log data and provide visual summary to the instructors. The findings of this study may serve as references for learning management system or online course developers, instructors, and researchers.