臺灣博碩士論文加值系統

本研究旨在探討問題導向之程式設計教學對雲林地區國中生運算思維及設計思考表現的影響。隨著數位科技的快速發展，α世代的學生高度依賴科技產品，容易分心且面臨科技成癮的風險。為了適應這一特點，教育研究者開始尋求新的教學方法，其中問題導向學習（Problem-Based Learning, PBL）被認為是一種有效的策略。PBL強調學生主動參與、解決實際問題，並通過合作學習和反思提升運算思維及設計思考能力。
本研究選取雲林地區國中一年級兩個班級共46名學生，分為實驗組和控制組。實驗組接受問題導向的程式設計教學，控制組則接受傳統教學。課程活動設計包括四個單元，涵蓋流程圖、心智圖及小遊戲專案製作，旨在培養學生的解決問題能力和設計思考與運算思維。
研究結果顯示，接受問題導向程式設計教學的學生在設計思考能力自評上有顯著提升，而對照組則無明顯變化。在運算思維能力方面，實驗組學生的自評成績雖有有顯著提升，但運算思維測驗成績未達顯著水準，與對照組相比無顯著差異。學生普遍認為分組合作和問題導向學習方式能提高學習動機與興趣，主要是透過增加互動、培養解決問題的能力和成就感。但對於本身缺乏興趣的學生，這些教學方法的影響可能有限。

This study aims to investigate the impact of problem-based programming instruction on the computational thinking and design thinking performance of junior high school students in Yunlin County. With the rapid development of digital technology, Generation α students highly rely on technological products, are easily distracted, and face the risk of technology addiction. To adapt to these characteristics, educational researchers have started seeking new teaching methods, among which Problem-Based Learning (PBL) is considered an effective strategy. PBL emphasizes students' active participation, solving real-world problems, and enhancing computational thinking and design thinking skills through collaborative learning and reflection.
This study selected two first-grade classes in Yunlin County junior high schools, totaling 46 students, and divided them into an experimental group and a control group. The experimental group received problem-based programming instruction, while the control group received traditional instruction. The course activities included four units, covering flowcharts, mind maps, and small game project creation, aiming to cultivate students' problem-solving skills, design thinking, and computational thinking.
The results showed that students who received problem-based programming instruction had significant improvement in their self-assessed design thinking abilities, whereas the control group showed no significant change. In terms of computational thinking, the experimental group's self-assessment scores significantly improved, but their computational thinking test scores did not reach a significant level, showing no significant difference compared to the control group. Students generally believed that group collaboration and problem-based learning methods could enhance learning motivation and interest, mainly by increasing interaction, fostering problem-solving abilities, and providing a sense of achievement. However, for students who lack interest, the impact of these teaching methods may be limited.

中文摘要 ………………………………………………………….. i
英文摘要 ………………………………………………………….. ii
誌謝 ………………………………………………………….. iii
目錄 ………………………………………………………….. iv
表目錄 ………………………………………………………….. vi
圖目錄 ………………………………………………………….. viii
第一章 緒論…………………………………………………....... 1
1.1 研究背景與動機………………………………………... 1
1.2 研究目的與問題………………………………………... 4
第二章 文獻探討………………………………………………... 5
2.1 問題導向學習…………………………………………... 5
2.1.1 問題導向學習的特徵…………………………………... 5
2.1.2 問題導向學習的優缺點與挑戰………………………... 6
2.2 運算思維………………………………………………... 6
2.2.1 運算思維的定義………………………………………... 7
2.2.2 運算思維的應用………………………………………... 7
2.2.3 關於運算思維的待解問題……………………………... 7
2.3 設計思考………………………………………………... 8
2.3.1 設計思考的定義與內涵………………………………... 8
2.3.2 設計思考與運算思維…………………………………... 9
2.4 心智圖…………………………………………………... 10
2.4.1 心智圖的運作原理……………………………………... 11
2.4.2 心智圖與問題導向學習………………………………... 11
2.5 Bebras國際運算思維挑戰賽…………………………... 12
第三章 研究方法………………………………………………... 13
3.1 研究架構………………………………………………... 13
3.2 研究對象………………………………………………... 14
3.3 實驗設計與實施………………………………………... 15
3.4 課程介入設計與實驗實施……………………………... 16
3.5 研究工具………………………………………………... 20
3.6 資料處理與分析………………………………………... 21
3.6.1 前測信效度分析………………………………………... 22
3.6.2 後測信效度分析………………………………………... 31
第四章 實驗結果………………………………………………... 39
4.1 量化分析………………………………………………... 39
4.1.1 學生背景調查分析……………………………………... 39
4.1.2 實驗組與對照組之前測自評分數比較………………... 44
4.1.3 各量表之成對樣本t檢定…………………………….... 47
4.1.4 ARCS學習動機量表獨立樣本t檢定…………………. 50
4.2 質性分析………………………………………………... 54
4.3 討論……………………………………………………... 58
第五章 結論與建議……………………………………………... 59
5.1 結論……………………………………………………... 60
5.2 限制與建議……………………………………………... 61
參考文獻 …………………………………………………………... 63
附錄A …………………………………………………………... 67
附錄B …………………………………………………………... 77
附錄C …………………………………………………………... 99
英文簡要 …………………………………………………………... 101

[1]兒童福利聯盟. (2023年7月). 2023臺灣兒少網路安全暨網路識讀現況調查. https://www.children.org.tw/publication_research/research_report/2611
[2]台灣傳播調查資料庫. (2020). 青少年上網行為概況2020. https://crctaiwan.dcat.nycu.edu.tw/epaper/%E7%AC%AC274%E6%9C%9F20220128.htm
[3]Ziatdinov, R., & Cilliers, J. (2021). Generation Alpha: Understanding the Next Cohort of University Students. ArXiv, abs/2202.01422.
[4]Ward, A. F., Duke, K., Gneezy, A., & Bos, M. W. (2017). Brain drain: The mere presence of one’s own smartphone reduces available cognitive capacity. Journal of the association for consumer research, 2(2), 140-154.
[5]Stefan, I., Barkoczi, N., Todorov, T., Peev, I., Pop, L., Marian, C., ... & Morales, L. (2023, June). Technology and Education as Drivers of the Fourth Industrial Revolution Through the Lens of the New Science of Learning. In International Conference on Human-Computer Interaction (pp. 133-148). Cham: Springer Nature Switzerland.
[6]Organisation for Economic Co-operation and Development (OECD). (2018). The future of education and skills: Education 2030. OECD education working papers.
[7]Misirli, A., & Komis, V. (2023). Computational thinking in early childhood education: The impact of programming a tangible robot on developing debugging knowledge. Early Childhood Research Quarterly, 65, 139-158..
[8]Zeng, Y., Yang, W., & Bautista, A. (2023). Teaching programming and computational thinking in early childhood education: a case study of content knowledge and pedagogical knowledge. Frontiers in Psychology, 14, 1252718.
[9]Lu, J. J., & Fletcher, G. H. (2009, March). Thinking about computational thinking. In Proceedings of the 40th ACM technical symposium on Computer science education (pp. 260-264).
[10]十二年國民基本教育課程綱要國民中小學暨普通型高級中 等學校──科技領域（2018）。https://www.k12ea.gov.tw/files/class_schema/ /課綱/13-科技/13-1/十二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.pdf
[11]Marra, R. M., Jonassen, D. H., Palmer, B., & Luft, S. (2014). Why problem-based learning works: Theoretical foundations. Journal on Excellence in College Teaching, 25(3&4), 221-238.
[12]Yew, E. H., & Goh, K. (2016). Problem-based learning: An overview of its process and impact on learning. Health professions education, 2(2), 75-79.
[13]Moust, J., Bouhuijs, P., & Schmidt, H. (2021). Introduction to Problem-Based Learning (4th ed.). Routledge. https://doi.org/10.4324/9781003194187
[14]Dolmans, D. H., De Grave, W., Wolfhagen, I. H., & Van Der Vleuten, C. P. (2005). Problem‐based learning: Future challenges for educational practice and research. Medical education, 39(7), 732-741.
[15]Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35.
[16]Wing, J. M. (2010). Computational Thinking: What and Why?.
[17]Shute, V. J., Sun, C., & Asbell-Clarke, J. (2017). Demystifying computational thinking. Educational research review, 22, 142-158.
[18]Brennan, K., & Resnick, M. (2012, April). New frameworks for studying and assessing the development of computational thinking. In Proceedings of the 2012 annual meeting of the American educational research association, Vancouver, Canada (Vol. 1, p. 25).
[19]Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12: What is involved and what is the role of the computer science education community?. ACM inroads, 2(1), 48-54.
[20]Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field. Educational researcher, 42(1), 38-43.
[21]Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of science education and technology, 25, 127-147.
[22]Simon, H. A. (1969). The sciences of the artificial. MIT Press.
[23]Rowe, P. G. (1987). Design thinking. MIT Press.
[24]Brown, T., & Katz, B. (2011). Change by design. Journal of product innovation management, 28(3), 381-383.
[25]Kelly, N., & Gero, J. S. (2021). Design thinking and computational thinking: A dual process model for addressing design problems. Design Science, 7, e8.
[26]Buzan, T., & Buzan, B. (1993). The mind map book: how to use radiant thinking to maximize your brain's untapped potential. New York, Plume.
[27]Hidayati, N., Zubaidah, S., Suarsini, E., & Praherdhiono, H. (2020). Cognitive learning outcomes: Its relationship with communication skills and collaboration skills through digital mind maps-integrated PBL. International Journal of Information and Education Technology, 10(6), 433-448.
[28]Dagienė, V., & Futschek, G. (2008). Bebras international contest on informatics and computer literacy: Criteria for good tasks. In Informatics Education-Supporting Computational Thinking: Third International Conference on Informatics in Secondary Schools-Evolution and Perspectives, ISSEP 2008 Torun Poland, July 1-4, 2008 Proceedings 3 (pp. 19-30). Springer Berlin Heidelberg.
[29]Dagienė, V., Sentance, S., & Stupurienė, G. (2017). Developing a two-dimensional categorization system for educational tasks in informatics. Informatica, 28(1), 23-44.
[30]Izu, C., Mirolo, C., Settle, A., Mannila, L., & Stupuriene, G. (2017). Exploring bebras tasks content and performance: a multinational study. Informatics in Education, 16(1), 39-59.
[31]Tang, X., Yin, Y., Lin, Q., Hadad, R., & Zhai, X. (2020). Assessing computational thinking: A systematic review of empirical studies. Computers & Education, 148, 103798.
[32]Creswell, J. W. (2014). Research Design: Qualitative, Quantitative and Mixed Methods Approaches (4th ed.). Thousand Oaks, CA: Sage.
[33]Johnson, R. B., & Onwuegbuzie, A. J. (2004). Mixed methods research: A research paradigm whose time has come. Educational researcher, 33(7), 14-26.
[34]Garrison, D. R. (2016). E-learning in the 21st century: A community of inquiry framework for research and practice. Routledge.
[35]Kvale, S. (1994). InterViews: An introduction to qualitative research interviewing. Sage Publications, Inc.
[36]Miller, M.D., Linn, R.L. and Gronlund, N.E. (2000) Measurement and Assessment in Teaching. 10th Edition, Pearson Education Ltd., Upper Saddle River.
[37]Keller, J. M. (2009). Motivational design for learning and performance: The ARCS model approach. Springer Science & Business Media.