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研究生: 劉冠緯
Liu, Guan-Wei
論文名稱: 除錯策略與引導策略對國中八年級學習者以擴增實境輔助程式除錯學習成效、動機及態度之影響
Types of Debugging Strategies and Learning Guidance on Junior High School Students' Learning of Program Debugging through AR-Based Learning
指導教授: 陳明溥
Chen, Ming-Puu
口試委員: 陳明溥
Chen, Ming-Puu
游光昭
Yu, Kuang-Chao
楊凱翔
Yang, Kai-Hsiang
口試日期: 2022/08/22
學位類別: 碩士
Master
系所名稱: 資訊教育研究所
Graduate Institute of Information and Computer Education
論文出版年: 2022
畢業學年度: 110
語文別: 中文
論文頁數: 159
中文關鍵詞: 程式除錯擴增實境問題解決除錯策略引導策略
英文關鍵詞: program debugging, augmented reality, problem-solving, debugging strategies, learning guidance
研究方法: 準實驗設計法
DOI URL: http://doi.org/10.6345/NTNU202201814
論文種類: 學術論文
相關次數: 點閱:95下載:0
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  • 本研究旨在探討除錯策略(邏輯導向、功能導向)及引導策略(程序引導、問題引導)對國中八年級學習者以擴增實境輔助程式除錯之學習成效、學習動機及學習態度的影響。研究對象為新北市某國中八年級學習者159人,有效樣本為108人。本研究採因子設計之準實驗研究法,自變項為除錯策略及引導策略,除錯策略根據學習者分析問題的方法,分為「邏輯導向」與「功能導向」;引導策略則依照引導學習者解題的方式,分為「程序引導」與「問題引導」。依變項為程式設計學習成效(知識理解、知識應用)、程式設計學習動機(價值成份、期望成份、科技接受度)與程式設計學習態度(學習自信心、學習喜好、學習焦慮、學習過程、學習方法、有用性)。
    研究結果發現:就程式設計學習成效而言,(1)在「知識理解」面向,邏輯導向組的表現優於功能導向組;(2)在「知識應用」面向,學習者使用邏輯導向除錯時,程序引導組表現顯著優於問題引導組;而學習者接受問題引導策略時,功能導向組的表現顯著優於邏輯導向組。其次,就程式設計學習動機而言,(3)各實驗組學習者對於程式設計學習皆保持正向動機,其中在工作價值、控制信念、自我效能、期望成功與科技有效性方面,邏輯導向組顯著優於功能導向組;(4)在外在目標導向方面,學習者使用功能導向除錯時,問題引導組顯著優於程序導向組;(5)而接受程序引導組的學習者,邏輯導向組顯著優於功能導向組。最後,就程式設計學習態度而言,(6)各實驗組學習者對於程式設計學習皆抱持正向態度,其中在學習自信心方面,問題引導組顯著優於程序引導組;(7)在學習喜好、學習方法與有用性方面,邏輯導向組顯著優於功能導向組。

    The purpose of this study was to explore the effects of types of debugging strategies and learning guidance on junior high school students’ learning performance, motivation, and attitude in learning of program debugging through AR-Based learning activity. The participants were 159 eighth-graders from a junior high school in the northern part of Taiwan. The effective sample size was 108. A quasi-experimental design was adopted. The independent variables were type of debugging strategies (“logic-oriented” vs. “function-oriented”) and type of learning guidance (“question-guidance” vs. “procedure-guidance”). The dependent variables included students’ learning performance, motivation, and attitude.
    The results manifested that (a) for the knowledge comprehesion performance, the logic-oriented group outperformed the function-oriented group; (b) for knowledge application performance, while receiving the logic-oriented, the procedure-guidance group outperformed the question-guidance group; and while receiving the question-guidance, the function-oriented group outperformed the logic-oriented group. For learning motivation, (c) participants showed positive motivation, and the logic-oriented group revealed a higher degree of motivation than the function-oriented group; (d) while receiving the function-oriented, the question-guidance group revealed a higher degree of motivation than the procedure-guidance group; (e) while receiving the procedure-guidance, the logic-oriented group revealed a higher degree of motivation than function-oriented group. (f) As for learning attitude, participants showed positive attitude and the question-guidance group revealed higher degree of attitude than the procedure-guidance group; (g) the logic-oriented group revealed higher degree of attitude than the function-oriented group.

    第一章 緒論 1 第一節 研究背景與動機 1 第二節 研究目的與待答問題 4 第三節 研究範圍與限制 5 第四節 重要名詞釋義 7 第二章 文獻探討 9 第一節 程式設計學習 9 第二節 程式除錯 11 第三節 擴增實境 14 第四節 問題解決歷程 17 第五節 除錯策略 20 第六節 引導策略 23 第三章 研究方法 27 第一節 研究對象 27 第二節 研究設計 28 第三節 實驗流程 40 第四節 研究工具 41 第五節 資料處理與分析 47 第四章 結果與討論 53 第一節 程式設計學習成效分析 53 第二節 程式設計學習動機分析 58 第三節 程式設計學習態度分析 73 第五章 結論與建議 80 第一節 結論 80 第二節 建議 82 參考文獻 84 附錄一、邏輯導向—問題引導組學習單 89 附錄二、邏輯導向—程序引導組學習單 102 附錄三、功能導向—問題引導組學習單 115 附錄四、功能導向—程序引導組學習單 128 附錄五、程式設計學習成效測驗(前測) 140 附錄六、程式設計學習成效測驗(後測) 143 附錄七、程式設計學習動機量表(前測) 146 附錄八、程式設計學習動機量表(後測) 150 附錄九、程式設計學習態度量表(前測) 154 附錄十、程式設計學習態度量表(後測) 157

    中文部分
    吳正已、林凱胤(1997)。問題解決導向的程式語言教學。資訊教育雜誌創刊十年特刊,75-83。
    宋錦圓(2007)。遊戲學習中問題導向學習策略之應用研究—以模擬黑面琵鷺生態的遊戲系統為例(未出版碩士論文)。國立臺南大學數位學習科技學系,台南市。
    李彩鳳(2018)。鷹架策略與提示策略對不同先備知識國中生程式設計課程學習成效與動機之探討。國立臺灣師範大學資訊教育研究所,台北市。
    阮丞安(2015)。高低互動擴增實境融入程式設計課程對國小學生學習之影響(未出版碩士論文)。國立臺灣科技大學數位學習與教育研究所,台北市。
    洪文東(2003)。創造性問題解決化學單元教學活動設計與評估。科學教育學刊,11(4),407-430。
    張春興(2000)。教育心理學:三化取向的理論與實踐。台北市:東華書局。
    張春興、林清山(1997)。教育心理學。台北:東華書局。
    張順原(2015)。學習態度、學習動機、激勵因素與學習成效關係之研究-以消防特考班學員為例(未出版碩士論文)。南華大學企業管理學系管理科學碩博士班,嘉義縣。
    張德明(2017)。應用Rubric於程式設計學習評量與教學策略之改進(未出版碩士論文)。朝陽科技大學資訊工程系,台中市。
    張曉瑀(2018)。目標設定與引導策略對不同先備知識國中生以智慧眼鏡輔助機器人程式設計學習之成效及動機探討(未出版碩士論文)。國立臺灣師範大學資訊教育研究所,台北市。
    教育部(2008)。十二年國民基本教育課程綱要國民中學暨普通型高級中等學校科技領域。台北:教育部。
    許祐群(2018)。DebugamO:遊戲式偵錯學習系統及其對程式學習動機影響之研究(未出版碩士論文)。國立臺灣大學電機工程學研究所,台北市。
    郭家禎(2020)。教學方式與引導策略對國小四年級學習者micro:bit程式設計學習成效及態度之影響。國立臺灣師範大學資訊教育研究所碩士論文,台北市。
    黃信溢(2020)。運用問題解決策略於程式除錯學習之研究(未出版碩士論文)。國立暨南國際大學課程教學與科技研究所,南投縣。
    黃茂在、陳文典(2004)。「問題解決」的能力。科學教育月刊,273,21-41。
    蔡宗霖(2010)。不同問題解決教學策略對國小生程式設計學習表現及學習態度之影響(未出版碩士論文)。國立臺灣師範大學資訊教育學系,台北市。
    鄭佳淵(2018)。應用擴增實境與積木視覺化程式設計技術於虛擬教育機器人系統之實作(未出版碩士論文)。健行科技大學資訊管理系碩士班,桃園縣。
    鄭昭明(1993)。認知心理學—理論與實踐。台北:桂冠圖書。

    英文部分
    Ahmadzadeh, M., Elliman, D., & Higgins, C. (2005). An analysis of patterns of debugging among novice computer science students. Proceedings of the 10th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education (pp. 84-88).
    Alfieri, L., Brooks, P. J., Aldrich, N. J., & Tenenbaum, H. R. (2011). Does discovery-based instruction enhance learning? Journal of Educational Psychology, 103(1), 1.
    Azuma, R. T. (1997). A survey of augmented reality. Presence: Teleoperators & Virtual Environments, 6(4), 355-385.
    Bayman, P. & Mayer, R. E. (1988). Using conceptual models to teach BASIC computer programming. Journal of Educational Psychology, 80(3), 291.
    Beaubouef, T. & Mason, J. (2005). Why the high attrition rate for computer science students: Some thoughts and observations. ACM SIGCSE Bulletin, 37(2), 103-106.
    Brusilovsky, P., Calabrese, E., Hvorecky, J., Kouchnirenko, A., & Miller, P. (1997). Mini-languages: A way to learn programming principles. Education and Information Technologies, 2(1), 65-83.
    Carver, S. M. & Klahr, D. (1986). Assessing children's LOGO debugging skills with a formal model. Journal of Educational Computing Research, 2(4), 487-525.
    Cheah, C. S. (2020). Factors contributing to the difficulties in teaching and learning of computer programming: A literature review. Contemporary Educational Technology, 12(2), 272.
    Chen, M. P. & Tsai, C. C. (2016). Augmented-reality as a scaffolding tool for learning geometry. Proceesings of EdMedia 2016—World Conference on Educational Media and Technology (pp. 1531-1535).
    Chen, M. W., Wu, C. C., & Lin, Y. T. (2013). Novices' debugging behaviors in VB programming. Learning and Teaching in Computing and Engineering (pp. 25-30).
    Chin, K. Y., Wang, C. S., & Chen, Y. L. (2019). Effects of an augmented reality-based mobile system on students’ learning achievements and motivation for a liberal arts course. Interactive Learning Environments, 27(7), 927-941.
    Chmiel, R. & Loui, M. C. (2003). An integrated approach to instruction in debugging computer programs. Proceedings of the 33rd Annual Frontiers in Education, 3, S4C1-S4C6.
    Chung, C. Y. & Hsiao, I. H. (2020). Computational thinking in augmented reality: An investigation of collaborative debugging practices. Proceedings of IEEE 6th International Conference of the Immersive Learning Research Network (iLRN) (pp. 54-61).
    Clark, R. E. (2009). How much and what type of guidance is optimal for learning from instruction? Constructivist Instruction (pp. 170-195).
    Corney, M., Lister, R., & Teague, D. (2011). Early relational reasoning and the novice programmer: Swapping as the 'hello world' of relational reasoning. Proceedings of the 13th Australiasian Computing Education Conference (pp. 95-104).
    Davis, D., Burry, J., & Burry, M. (2011). Understanding visual scripts: Improving collaboration through modular programming. International Journal of Architectural Computing, 9(4), 361-375.
    Decasse, M. & Emde, A. M. (1988). A review of automated debugging systems: Knowledge, strategies and techniques. Proceedings of the 11th International Conference on Software Engineering (pp. 162-163).
    Deek, F., Kimmel, H., & McHugh, J. A. (1998). Pedagogical changes in the delivery of the first‐course in computer science: Problem solving, then programming. Journal of Engineering Education, 87(3), 313-320.
    Dewey, J. (1933). How we think: a restatement of the relation of reflective thinking to the educative process. Boston, MA: D.C. Heath & Co Publishers.
    Fitzgerald, S., Lewandowski, G., McCauley, R., Murphy, L., Simon, B., Thomas, L., & Zander, C. (2008). Debugging: Finding, fixing and flailing, a multi-institutional study of novice debuggers. Computer Science Education, 18(2), 93-116.
    Gagné, R. (1985). The conditions of learning and theory of instruction. New York, NY: Holt, Rinehart, & Winston.
    Gomes, A. & Mendes, A. J. (2007). Learning to program-difficulties and solutions. International Conference on Engineering Education–ICEE (Vol. 7).
    Guay, F., Ratelle, C. F., & Chanal, J. (2008). Optimal learning in optimal contexts: The role of self-determination in education. Canadian Psychology/Psychologie Canadienne, 49(3), 233.
    Gugerty, L. & Olson, G. (1986). Debugging by skilled and novice programmers. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 171-174).
    Hacker, M., Barden, R. A., Rutherford, M. A., & Rye, K. J. (1988). Living with technology. Delmar Publishers.
    Hanus, M. D. & Fox, J. (2015). Assessing the effects of gamification in the classroom: A longitudinal study on intrinsic motivation, social comparison, satisfaction, effort, and academic performance. Computers & Education, 80, 152-161.
    Hatch, L. (1988). Problem solving approach. Instructional Strategies for Technology Education, 37, 89.
    Heikkilä, M. & Mannila, L. (2018). Debugging in programming as a multimodal practice in early childhood education settings. Multimodal Technologies and Interaction, 2(3), 42.
    Hill, J. R. & Hannafin, M. J. (2001). Teaching and learning in digital environments: The resurgence of resource-based learning. Educational Technology Research and Development, 49(3), 37-52.
    Huang, T. C., Chen, C. C., & Chou, Y. W. (2016). Animating eco-education: To see, feel, and discover in an augmented reality-based experiential learning environment. Computers & Education, 96, 72-82.
    Iqbal, S. & Harsh, O. K. (2013). A self review and external review model for teaching and assessing novice programmers. International Journal of Information and Education Technology, 3(2), 120.
    Jonassen, D. H. & Hung, W. (2006). Learning to troubleshoot: A new theory-based design architecture. Educational Psychology Review, 18(1), 77-114.
    Kao, G. Y. M. & Ruan, C. A. (2022). Designing and evaluating a high interactive augmented reality system for programming learning. Computers in Human Behavior, 132, 107245.
    Katz, I. R. & Anderson, J. R. (1987). Debugging: An analysis of bug-location strategies. Human-Computer Interaction, 3(4), 351-399.
    Ke, F. & Hsu, Y. C. (2015). Mobile augmented-reality artifact creation as a component of mobile computer-supported collaborative learning. The Internet and Higher Education, 26, 33-41.
    Kinnunen, P. & Simon, B. (2010). Experiencing programming assignments in CS1: The emotional toll. Proceedings of the 6th International Workshop on Computing Education Research (pp. 77-86).
    Kirschner, P., Sweller, J., & Clark, R. E. (2006). Why unguided learning does not work: An analysis of the failure of discovery learning, problem-based learning, experiential learning and inquiry-based learning. Educational Psychologist, 41(2), 75-86.
    Lapidot, T. & Hazzan, O. (2005). Song debugging: Merging content and pedagogy in computer science education. ACM SIGCSE Bulletin, 37(4), 79-83.
    Lazonder, A. W. & Harmsen, R. (2016). Meta-analysis of inquiry-based learning: Effects of guidance. Review of Educational Research, 86(3), 681-718.
    Leppink, J., Broers, N. J., Imbos, T., van der Vleuten, C. P., & Berger, M. P. (2014). The effect of guidance in problem-based learning of statistics. The Journal of Experimental Education, 82(3), 391-407.
    Lin, P. H. & Chen, S. Y. (2020). Design and evaluation of a deep learning recommendation based augmented reality system for teaching programming and computational thinking. IEEE Access, 8, 45689-45699.
    Linn, M. C. & Clancy, M. J. (1992). The case for case studies of programming problems. Communications of the ACM, 35(3), 121-132.
    Liu, Z., Zhi, R., Hicks, A., & Barnes, T. (2017). Understanding problem solving behavior of 6–8 graders in a debugging game. Computer Science Education, 27(1), 1-29.
    Loksa, D., Ko, A. J., Jernigan, W., Oleson, A., Mendez, C. J., & Burnett, M. M. (2016). Programming, problem solving, and self-awareness: Effects of explicit guidance. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (pp. 1449-1461).
    Lönnberg, J., Malmi, L., & Berglund, A. (2008). Helping students debug concurrent programs. Proceedings of the 8th International Conference on Computing Education Research (pp. 76-79).
    Luxton-Reilly, A., McMillan, E., Stevenson, E., Tempero, E., & Denny, P. (2018). Ladebug: An online tool to help novice programmers improve their debugging skills. Proceedings of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education (pp. 159-164).
    Malik, S. I. & Coldwell-Neilson, J. (2018). Gender differences in an introductory programming course: New teaching approach, students’ learning outcomes, and perceptions. Education and Information Technologies, 23(6), 2453-2475.
    Matlen, B. J. & Klahr, D. (2013). Sequential effects of high and low instructional guidance on children’s acquisition of experimentation skills: Is it all in the timing? Instructional Science, 41(3), 621-634.
    Mayer, R. E. (2001). Multimedia learning. New York, USA: Cambridge University Press.
    Mayer, R. E. & Wittrock, M. C. (2006). Problem solving. Handbook of Educational Psychology, 2, 287-303.
    Medeiros, R. P., Ramalho, G. L., & Falcão, T. P. (2018). A systematic literature review on teaching and learning introductory programming in higher education. IEEE Transactions on Education, 62(2), 77-90.
    Michaeli, T. & Romeike, R. (2017). Addressing teaching practices regarding software quality: Testing and debugging in the classroom. Proceedings of the 12th Workshop on Primary and Secondary Computing Education (pp. 105-106).
    Michaeli, T. & Romeike, R. (2019). Improving debugging skills in the classroom: The effects of teaching a systematic debugging process. Proceedings of the 14th Workshop in Primary and Secondary Computing Education (pp. 1-7).
    Milgram, P. & Kishino, F. (1994). A taxonomy of mixed reality visual displays. IEICE TRANSACTIONS on Information and Systems, 77(12), 1321-1329.
    Nanja, M. & Cook, C. R. (1987). An analysis of the on-line debugging process. Empirical Studies of Programmers: Second Workshop (pp. 172-184). Norwood, NJ: Ablex.
    Pea, R. D. & Kurland, D. M. (1984). On the cognitive effects of learning computer programming. New Ideas in Psychology, 2(2), 137-168.
    Perez-Sanagustin, M., Hernández-Leo, D., Santos, P., Kloos, C. D., & Blat, J. (2014). Augmenting reality and formality of informal and non-formal settings to enhance blended learning. Proceeding of the IEEE Transactions on Learning Technologies, 7(2), 118-131.
    Perkins, D. N. & Martin, F. (1986). Fragile knowledge and neglected strategies in novice programmers. Proceeding of the First Workshop on Empirical Studies of Programmers on Empirical Studies of Programmers (pp. 213-229).
    Renumol, V. G., Janakiram, D., & Jayaprakash, S. (2010). Identification of cognitive processes of effective and ineffective students during computer programming. ACM Transactions on Computing Education (TOCE), 10(3), 1-21.
    Santos, M. E. C., Chen, A., Taketomi, T., Yamamoto, G., Miyazaki, J., & Kato, H. (2013). Augmented reality learning experiences: Survey of prototype design and evaluation. Proceeding of the IEEE Transactions on Learning Technologies, 7(1), 38-56.
    Simon, B., Bouvier, D., Chen, T. Y., Lewandowski, G., McCartney, R., & Sanders, K. (2008). Common sense computing (episode 4): Debugging. Computer Science Education, 18(2), 117-133.
    Sittiyuno, S. & Chaipah, K. (2019). Arcode: Augmented reality application for learning elementary computer programming. Proceeding of the 16th International Joint Conference on Computer Science and Software Engineering (JCSSE) (pp. 32-37).
    Stephenson, C., Gal-Ezer, J., Haberman, B., & Verno, A. (2005). The new educational imperative: Improving high school computer science education. Final Report of the CSTA Curriculum Improvement Task Force.
    Sweller, J. (2010). Element interactivity and intrinsic, extraneous, and germane cognitive load. Educational Psychology Review, 22(2), 123-138.
    Teng, C. H., Chen, J. Y., & Chen, Z. H. (2018). Impact of augmented reality on programming language learning: Efficiency and perception. Journal of Educational Computing Research, 56(2), 254-271.
    Theodoropoulos, A. & Lepouras, G. (2021). Augmented reality and programming education: A systematic review. International Journal of Child-Computer Interaction, 30, 100335.
    Treffinger, D. J. & Isaksen, S. G. (1992). Creative problem solving: an introduction. Center of creative learning Inc..
    Vessey, I. (1985). Expertise in debugging computer programs: A process analysis. International Journal of Man-Machine Studies, 23(5), 459-494.
    Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35.
    Winslow, L. E. (1996). Programming pedagogy—a psychological overview. ACM Sigcse Bulletin, 28(3), 17-22.
    Wu, H. K., Lee, S. W. Y., Chang, H. Y., & Liang, J. C. (2013). Current status, opportunities and challenges of augmented reality in education. Computers & Education, 62, 41-49.
    Wu, P. H., Hwang, G. J., Yang, M. L., & Chen, C. H. (2018). Impacts of integrating the repertory grid into an augmented reality-based learning design on students’ learning achievements, cognitive load and degree of satisfaction. Interactive Learning Environments, 26(2), 221-234.

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