政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/152569

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/152569

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政大機構典藏 > 資訊學院 > 資訊科學系 > 學位論文 > Item 140.119/152569

請使用永久網址來引用或連結此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/152569

題名:	運用學習管理系統資料進行學生學習行為之資料探勘 Data Mining of Student Learning Behaviors using Learning Management System Data
作者:	林侑萱 Lin, Yu-Hsuan
貢獻者:	江玥慧 Chiang, Yueh-hui 林侑萱 Lin, Yu-Hsuan
關鍵詞:	學習管理系統教育資料探勘程式碼分群學習行為模式學習成效 Learning Management System Educational Data Mining Program Code Grouping Learning Behavior Learning Effectiveness
日期:	2024
上傳時間:	2024-08-05 12:45:17 (UTC+8)
摘要:	除了在教學現場能夠觀察到學生在課堂上的學習情形，數位教學平台中的日誌資料也隱含了學生學習行為的相關訊息。而本研究希望使用Moodle平台所蒐集的資料，從三種角度探討基礎程式設計課程的學生學習狀況，首先，透過學生的程式作業來觀察學生的共同撰寫模式，以幫助教學者了解學生可能會出現的程式錯誤以及有哪些寫法，再來，透過日誌資料，找尋程式撰寫及小組合作需要協助的學生，在課程上的行為模式，透過這些行為模式能幫助教學者找到這些學生，並多加關注這些學生在程式撰寫上及小組活動上是否需要幫助，最後，找出學習管理系統上可能影響學生學習成效的因素，幫助教學者提前觀察到學生後續可能的學習成效。這些研究結果可以協助教學者了解學生在學習上的行為，以提供學生更適合的幫助。 In addition to observing students' learning in the classroom at the teaching site, the log data in learning management system also contains information about students' learning behaviors. This study analyzes data collected from the Moodle platform to achieve three objectives: to explore the differences in programming approaches among students in programming courses, to examine the behavior patterns of students who need assistance with programming and group work, and to identify the factors that influence worksheet performance. These findings can help educators understand student learning behaviors better and provide more suitable support for students.
參考文獻:	[1]N.Ademi, S.Loshkovska and S.Kalajdziski, "Prediction of Student Success Through Analysis of Moodle Logs: Case Study ", ICT Innovations 2019. Big Data Processing and Mining. Communications in Computer and Information Science, vol 1110. Springer, Cham, 2019. [2]A.Namoun and A.Alshanqiti, "Predicting Student Performance Using Data Mining and Learning Analytics Techniques: A Systematic Literature Review ". Applied Sciences.11(1):237, 2021 [3]G.Yang et al., "ComFormer: Code Comment Generation via Transformer and Fusion Method-based Hybrid Code Representation", 8th International Conference on Dependable Systems and Their Applications (DSA), Yinchuan, China, 2021, pp. 30-41, 2021 [4]P.Wang,L.Zhu,Q.Wang,O.Jaiteh and C.Guo,"An Empirical Understanding of Code Clone Detection by ChatGPT", 2023 6th International Conference on Data Science and Information Technology (DSIT), Shanghai, China, pp. 78-83, 2023 [5]林世唐, "學生程式碼相似度之研究—以抄襲偵測之應用為例",〔碩士論文，淡江大學〕,華藝線上圖書館,2005 [6]H.Aldriye, A.AlKhalaf and M.Alkhalaf, "Automated Grading Systems for Programming Assignments: A Literature Review " .International Journal of Advanced Computer Science and Applications .2019 [7]蔡明志、陳思豪、曾宣瑜、胡俊之,"程式抄襲源頭偵測之研究"。《輔仁管理評論》 26卷3期 p. 27-50,2019 [8]R.Maertens,C.V.Petegem,N.Strijbol,T.Baeyens,A.C.Jacobs,P.Dawyndt and B.Mesuere, "Dolos: Language-agnostic plagiarism detection in source code ", Journal of Computer Assited learning,Volume38, Issue4,2022 [9]F.Nielsen,"Hierarchical Clustering ",Introduction to HPC with MPI for Data Science pp 195–211,2016 [10]M.Valle Torre, C.Oertel and M.Specht,"The Sequence Matters in Learning-A Systematic Literature Review",In Proceedings of the 14th Learning Analytics and Knowledge Conference, Pages 263-272, March,2024 [11]A.Tlili,T.Sun,M.Denden,Kinshuk,S.Graf,C.Fei and H.Wang, "Impact of personality traits on learners’ navigational behavior patterns in an online course: a lag sequential analysis approach ",Frontiers in psychology, 14, 1071985,2023 [12]K.Stefanova and D.Kabakchieva, "Educational data mining perspectives within university big data environment", 2017 International Conference on Engineering, Technology and Innovation (ICE/ITMC), Madeira, Portugal, pp. 264-270, 2017 [13]V.Mandalapu, et al. "Student-Centric Model of Login Patterns: A Case Study with Learning Management Systems", International Educational Data Mining Society ,2021 [14]J.W.You, "Identifying significant indicators using LMS data to predict course achievement in online learning", The Internet and Higher Education,Volume 29, April 2016, Pages 23-30,2015 [15]A.S.Aljaloud ,D.M. Uliyan, A.Alkhalil, M.Abd Elrhman, A. F.M.Alogali, Y.M.Altameemi and P.Kwan, "A Deep Learning Model to Predict Student Learning Outcomes in LMS Using CNN and LSTM", IEEE Access, vol. 10, pp.85255-85265, 2022 [16]P.Resta, C.Awalt and M.Menchaca, "Self and peer assessment in an online collaborative learning environment ", E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 682-689), Association for the Advancement of Computing in Education (AACE),2002 [17]M.J.Tsai, C.Y.Wang and P.F.Hsu, "Developing the computer programming self-efficacy scale for computer literacy education ", Journal of Educational Computing Research, 56(8), 1345-1360,2019
描述:	碩士國立政治大學資訊科學系 111753121
資料來源:	http://thesis.lib.nccu.edu.tw/record/#G0111753121
資料類型:	thesis
顯示於類別:	[資訊科學系] 學位論文

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