基於文本型程式編寫紀錄之自我調節儀表板於程式設計學習成效探究;A Study of Applying Self-Regulation Dashboard Based on Text-based Programming Log to Enhance rogramming Learning

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题名:	基於文本型程式編寫紀錄之自我調節儀表板於程式設計學習成效探究;A Study of Applying Self-Regulation Dashboard Based on Text-based Programming Log to Enhance rogramming Learning
作者:	羅健瑋;Lo, Chien-Wei
贡献者:	網路學習科技研究所
关键词:	自我調節;社會調節;問題導向學習;學習分析儀表板;程式設計學習;Self-regulation;Social regulation;Problem-based learning;Learning analytic dashboards;Programming learning
日期:	2022-07-27
上传时间:	2022-10-04 12:07:08 (UTC+8)
出版者:	國立中央大學
摘要:	程式設計能力已成為影響學生未來競爭力的必備技能之一，程式教育的需求也隨之遽增。以數位學習系統蒐集分析學生學習歷程資料，有助於學生了解監控學習進度，增強自我調節能力。而探索程式編寫行為紀錄可供教師在學期中預測學生學習表現，有效給予學習輔助。此外，在程式設計中使用問題導向教學可促進學生技能和態度的發展，培養學生具備問題解決能力。因此，本研究開發自我調節儀表板融入學習環境中，設計問題導向的任務作業促使學生主動參與學習，課程中使用Moodle學習平台與Jupyter Notebook專用伺服器上撰寫程式和自我調節儀表板。系統中社會調節功能包含：高分觀摩、學習建議等，學生可透過系統觀看同儕的學習成果能作為參考與目標，修正自己的學習策略提升程式技能，實踐自我學習和培養問題解決能力。研究對象為台灣北部某大學19名研究生，課程共計18週，前後測評估學生的知識掌握程度，問卷包括與程式態度和自我調節有關的項目。本研究探討學生在學習分析儀表板對自我調節的影響與問題導向提高社會調節，主要結果分為以下四點：(1)使用自我調節儀表板幫助下學生時間管理上有顯著提升。(2)通過問題導向式學習方法，學生表示希望有更多的分組討論學習機會與提升同儕之間的互動學習行為，觀摩優秀作品提高學生對自己和他人學習過程的認識，提高共同調節與社會共享調節的互動。(3)程式編寫行為預測結果顯示，使用累計至第七週的資料來預測程式能力成績，結果有達0.70準確率的表現，可判斷這些特徵有學習預警的潛能。(4)學生常見的錯誤類型進行分群分析，發現成績較高的學生名稱錯誤次數普遍較低，可作為教學方向的改善參考依據。因此，本研究證實基於文本型程式編寫紀錄之自我調節儀表板可提高程式設計學習成效有效促進學生社會調節學習，本研究之系統與教學策略可作為將來研究者參照實行。 ;Programming skills have become one of the essential skills that affect students′ future competitiveness, and the demand for programming learning has increased dramatically. The learning system can collect and analyze students′ learning portfolio data to help them understand and monitor their learning progress and enhance their self-regulation. Exploring students’ programming logs allows teachers to predict student performance during the semester and effectively support students’ learning. In addition, using problem-based learning instruction in programming provides context to facilitate the development of students′ skills and attitudes and the development of problem-solving skills. Therefore, this study developed a self-regulation dashboard, integrated it into the learning environment, and designed problem-based tasks to motivate students to participate in learning actively. The course applies the Moodle system, the self-regulation dashboard, and a server for Jupyter Notebook to write programs. In addition, students can use the system to observe their peer′s learning results and use them as a reference and target to modify their learning strategies to improve their programming skills, practice self-learning, and develop problem-solving skills. There are 19 graduate students from a university in northern Taiwan who participated in this study for 18 weeks. The pre/post-test and questionnaires were executed to assess the students′ learning performance and self-regulation perceptions. In this study, we investigate the impact of students′ learning analytic dashboard on the self-regulated and problem-based improvement of social regulation. The results indicate that (1) Students showed significant improvement in time management with the self-regulation dashboard′s help. (2) Students desire more group discussions and interactive learning behaviors among peers through the problem-based learning approach. They also observed excellent work from peers to improve their learning and the interaction for co-regulation and socially shared regulation. (3) The results of the prediction of programming behaviors showed that the cumulative data up to week 7 were used to predict the learning performance with an accuracy of 0.70, which can be potential as a learning early warning. (4) The name error seldom happened to students with higher scores after analyzing the general type of error. This study confirms that the self-regulation dashboard based on text-based programming records can improve the effectiveness of programming learning and effectively facilitate students′ socially-regulated learning.
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