政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/141352
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  全文筆數/總筆數 : 113325/144300 (79%)
造訪人次 : 51156010      線上人數 : 944
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/141352


    題名: 程式理解教學樣式:教學策略與學習任務
    Pedagogical Patterns for Program Comprehension: Teaching Strategies and Tasks
    作者: 林雅雯
    貢獻者: 廖峻鋒
    陶亞倫

    林雅雯
    關鍵詞: Block Model
    Notional Machine
    教學樣式
    程式理解
    程式教育
    Block Model
    Notional Machine
    pedagogical patterns
    program comprehension
    program education
    日期: 2022
    上傳時間: 2022-08-01 18:50:34 (UTC+8)
    摘要:   程式理解是理解一段由程式語言構成的程式碼片段的能力,其要素包含理解程式執行的過程、閱讀和解釋程式語意的能力、理解程式以維護或修改現有程式的能力、理解基本程式結構如迴圈和判斷式的能力,以及對程式應用目的的理解。近幾年的許多研究指出,程式理解通常被目前程式設計教育所忽略,而現有的程式理解研究大多還處於實驗階段,缺乏高質量程式理解教學的可靠指引,同時,教學樣式已被證明是交流教學經驗的有效方法。
    本文參考現有的程式理解研究,以Block Model和Notional Machine為理論基礎,提出可應用於教學的程式理解教學樣式系統。這些樣式描述了程式理解策略、程式理解任務以及呈現Notional Machine的方式,並以範例說明具體內容,分析應用這些樣式的結果,期盼這些樣式能作為教師設計課程的指南,並鼓勵教師進行相關的教學活動。
    為使教學樣式更貼近實際教學樣貌,本研究在提出教學樣式後,採質性研究之深度訪談法,以程式設計教師與助教為研究對象,蒐集其對樣式的看法與應用情境,整理分析訪談資料,修改樣式內容並提出樣式改善建議,供予未來樣式研究者參考。
    研究結果顯示,教學者進行教學活動時通常會應用到與樣式類似的概念,但依據教學現場的狀況會有相異的解讀與運用方式,而本研究整理的教學樣式能提供教學者更多教學上的選擇,統整性的內容能讓教學的順序更清晰,此外,研究結果中的應用情境與建議也能作為後續樣式的修改依據。本研究認為以教學樣式的方式呈現程式理解策略與工具有助於教師快速取用教學方法,減少嘗試與錯誤的時間,本文的研究結果可以作為教授程式設計課程的教師依據學生不同的理解需求和知識基礎來規劃程式理解課程的指引。
    Program Comprehension (PC) is the ability to understand a segment of code written in a computer programming language. The ingredients of PC include understanding the process of program execution, the ability to read and interpret program semantics, the ability to understand programs to maintain or modify an existing program, the ability to understand basic program structures such as loops and conditional expressions, and the understanding of program purposes. Many recent studies point out that PC is usually ignored in current programming education. Most of the existing practices of PC are still in the experimental stage, lacking reliable guidelines for conduction high-quality PC teaching. Meanwhile, Pedagogical Patterns have been proven as an effective approach for communicating empirical teaching experiences.
    Based on existing PC researches, this research proposes a system of pedagogical patterns for PC in education and uses the Block Model and the Notional Machine for program execution as two major theoretical foundations. The purpose of these patterns is to describe the PC strategies, PC tasks, and the method of representing Notional Machine, to illustrate the specific contents with examples, and to analyze the consequences of applying the patterns, hoping that they will serve as a basis for teachers to design their courses and encourage them to carry out related teaching activities.
    In addition, to make the pedagogical patterns close to the real teaching situation, this research adopts in-depth interviews and targets programming teachers and teaching assistants to collect the application situation of patterns. Then analyze the interview data, revise the patterns, and organize suggestions for future reasearch.
    The results indicate that teachers usually apply concepts similar to the patterns in class, but there will be different interpretation and application methods according to the teaching context, and the pedagogical patterns can provide teachers with more teaching alternatives. Besides, the application situations and suggestions in the research results can also be used as the basis for the revision of subsequent patterns. This study suggests that a system of pedagogical patterns for PC in education can help teachers quickly adopt teaching methods and reduce the time for trial and error. The results of this research can be used as a guide for programming teachers to plan programming comprehension courses with students’ different comprehension needs and knowledge bases.
    參考文獻: Alexander, C. (1977). A pattern language: towns, buildings, construction: Oxford university press.
    Alexander, C. (1979). The timeless way of building (Vol. 1): New york: Oxford university press.
    Bell, T., Witten, I. H., Fellows, M., Adams, R., & McKenzie, J. (2005). Computer Science Unplugged: An enrichment and extension programme for primary-aged children.
    Ben-Ari, M. (2001). Constructivism in computer science education. Journal of Computers in Mathematics and Science Teaching, 20(1), 45-73.
    Bennedsen, J., & Caspersen, M. E. (2007). Failure rates in introductory programming. SIGCSE Bull., 39(2), 32–36. doi:10.1145/1272848.1272879
    Bergin, J. (2000). Fourteen Pedagogical Patterns. Paper presented at the EuroPLoP.
    Bergin, J., Eckstein, J., Manns, M. L., & Wallingford, E. (2001). Patterns for gaining different perspectives. Paper presented at the Proceedings of PLoP.
    Bergin, J., Eckstein, J., Volter, M., Sipos, M., Wallingford, E., Marquardt, K., . . . Manns, M. L. (2012). Pedagogical Patterns: Advice for Educators: Joseph Bergin Software Tools.
    Bergin, J., Marquardt, K., Manns, M. L., Eckstein, J., Sharp, H., & Wallingford, E. (2004). Patterns for experiential learning. Learning Nov, 25(2002), 477.
    Bergin, J., Proulx, V. K., Brady, A. F., Hartley, S., Kelemen, C., Klassner, F., . . . Ross, R. (1999). Resources for next generation introductory CS courses: report of the ITiCSE`99 working group on resources for the next generation CS 1 course. Paper presented at the Working group reports from ITiCSE on Innovation and technology in computer science education, Cracow, Poland. https://doi.org/10.1145/349316.349555
    Bernard, H. R. (2017). Research methods in anthropology: Qualitative and quantitative approaches: Rowman & Littlefield.
    Bower, M. (2008). The" instructed-teacher" a computer science online learning pedagogical pattern. Paper presented at the Proceedings of the 13th annual conference on Innovation and technology in computer science education.
    Boyce, C., & Neale, P. (2006). Conducting in-depth interviews: A guide for designing and conducting in-depth interviews for evaluation input.
    Brooks, R. (1983). Towards a theory of the comprehension of computer programs. International journal of man-machine studies, 18(6), 543-554.
    Bruce-Lockhart, M. P., & Norvell, T. S. (2000). Lifting the hood of the computer: Program animation with the teaching machine. Paper presented at the 2000 Canadian Conference on Electrical and Computer Engineering. Conference Proceedings. Navigating to a New Era (Cat. No. 00TH8492).
    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.
    Buschmann, F., Henney, K., & Schmidt, D. C. (2007). Pattern-oriented software architecture, on patterns and pattern languages (Vol. 5): John wiley & sons.
    Buschmann, F., Meunier, R., Rohnert, H., Sommerlad, P., & Stal, M. (1996). Pattern-Oriented Software Architecture - Volume 1: A System of Patterns: Wiley Publishing.
    Busjahn, T., & Schulte, C. (2013). The use of code reading in teaching programming. Paper presented at the Proceedings of the 13th Koli Calling international conference on computing education research.
    Carney, T. F. (1990). Collaborative Inquiry Methodology: Division for Instructional Development, University of Windsor.
    Chi, M. T., & Wylie, R. (2014). The ICAP framework: Linking cognitive engagement to active learning outcomes. Educational psychologist, 49(4), 219-243.
    Cockburn, A. (1998). Surviving object-oriented projects: a manager`s guide: Addison-Wesley Longman Publishing Co., Inc.
    Coplien, J. O., & Alexander, A. W. O. (1996). Software patterns.
    Corney, M., Lister, R., & Teague, D. (2011). Early relational reasoning and the novice programmer: swapping as the`hello world`of relational reasoning. Paper presented at the Proceedings of the Thirteenth Australiasian Computing Education Conference.
    Corritore, C. L., & Wiedenbeck, S. (1991). What do novices learn during program comprehension? International Journal of Human‐Computer Interaction, 3(2), 199-222.
    Craik, K. J. W. (1952). The nature of explanation (Vol. 445): CUP Archive.
    Cross II, J. H., Hendrix, T. D., & Barowski, L. A. (2011). Combining dynamic program viewing and testing in early computing courses. Paper presented at the 2011 IEEE 35th Annual Computer Software and Applications Conference.
    DeLano, D. E., & Rising, L. (1997). Patterns for system testing. In Pattern languages of program design 3 (pp. 403-503).
    Dickson, P. E., Brown, N. C., & Becker, B. A. (2020). Engage Against the Machine: Rise of the Notional Machines as Effective Pedagogical Devices. Paper presented at the Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education.
    Du Boulay, B. (1986). Some difficulties of learning to program. Journal of Educational Computing Research, 2(1), 57-73.
    du Boulay, B., O`Shea, T., & Monk, J. (1981). The black box inside the glass box: presenting computing concepts to novices. International journal of man-machine studies, 14(3), 237-249.
    Eckerdal, A., & Thuné, M. (2005). Novice Java programmers` conceptions of" object" and" class", and variation theory. ACM Sigcse Bulletin, 37(3), 89-93.
    Eckstein, J., Bergin, J., & Sharp, H. (2002a). Feedback Patterns. Paper presented at the EuroPLoP.
    Eckstein, J., Bergin, J., & Sharp, H. (2002b). Patterns for active learning. Paper presented at the Proceedings of PloP.
    Eranki, K. L., & Moudgalya, K. M. (2014). Application of program slicing technique to improve novice programming competency in spoken tutorial workshops. Paper presented at the 2014 IEEE Sixth International Conference on Technology for Education.
    Fincher, S. (1999). Analysis of design: An exploration of patterns and pattern languages for pedagogy. Journal of Computers in Mathematics and Science Teaching, 18(3), 331-348.
    Fincher, S., Jeuring, J., Miller, C. S., Donaldson, P., Du Boulay, B., Hauswirth, M., . . . Mühling, A. (2020). Notional Machines in Computing Education: The Education of Attention. In Proceedings of the Working Group Reports on Innovation and Technology in Computer Science Education (pp. 21-50).
    Fincher, S., & Utting, I. (2002). Pedagogical patterns: their place in the genre. Paper presented at the Proceedings of the 7th annual conference on Innovation and technology in computer science education.
    Fleury, A. E. (1991). Parameter passing: The rules the students construct. ACM Sigcse Bulletin, 23(1), 283-286.
    Fowler, M. (1997). Analysis patterns: reusable object models: Addison-Wesley Professional.
    Fred Paas, Alexander Renkl, & Sweller, J. (2003). Cognitive Load Theory: A Special Issue of educational Psychologist: Routledge.
    Gamma, E., Helm, R., Johnson, R., Vlissides, J., & Patterns, D. (1995). Elements of reusable object-oriented software (Vol. 99): Addison-Wesley Reading, Massachusetts.
    Gao, P., Lu, M., Zhao, H., & Li, M. (2019). A New Teaching Pattern Based on PBL and Visual Programming in Computational Thinking Course. Paper presented at the 2019 14th International Conference on Computer Science & Education (ICCSE).
    Gomes, A., & Mendes, A. J. (2007). Learning to program-difficulties and solutions. Paper presented at the International Conference on Engineering Education–ICEE.
    Guo, P. J. (2013). Online python tutor: embeddable web-based program visualization for cs education. Paper presented at the Proceeding of the 44th ACM technical symposium on Computer science education.
    Harrison, N. B. (1999). The language of shepherding. Pattern languages of program design, 5, 507-530.
    Hebig, R., Ho-Quang, T., Jolak, R., Schröder, J., Linero, H., Ågren, M., & Maro, S. H. (2020). How do Students Experience and Judge Software Comprehension Techniques? Paper presented at the Proceedings of the 28th International Conference on Program Comprehension.
    Helminen, J., & Malmi, L. (2010). Jype - a program visualization and programming exercise tool for Python. Paper presented at the Proceedings of the 5th international symposium on Software visualization, Salt Lake City, Utah, USA. https://doi.org/10.1145/1879211.1879234
    Hermans, F. (2021). The Programmer’s Brain: What every programmer needs to know. United States of America: Manning Publications
    Hidalgo-Céspedes, J., Marín-Raventós, G., & Lara-Villagrán, V. (2016). Learning principles in program visualizations: a systematic literature review. Paper presented at the 2016 IEEE frontiers in education conference (FIE).
    Holland, S., Griffiths, R., & Woodman, M. (1997). Avoiding object misconceptions. Paper presented at the Proceedings of the twenty-eighth SIGCSE technical symposium on Computer science education.
    Howe, K., & Berv, J. (2000). Constructing constructivism, epistemological and pedagogical. Teachers College Record, 102(7), 19-40.
    Iba, T. (2014). A Journey on the Way to Pattern Writing: Designing the Pattern Writing Sheet. PLoP 2014 proceedings.
    Izu, C., Schulte, C., Aggarwal, A., Cutts, Q., Duran, R., Gutica, M., . . . Weeda, R. (2019). Fostering Program Comprehension in Novice Programmers - Learning Activities and Learning Trajectories. Paper presented at the Proceedings of the Working Group Reports on Innovation and Technology in Computer Science Education, Aberdeen, Scotland Uk. https://doi.org/10.1145/3344429.3372501
    Jiang, Z., Fernandez, E. B., & Cheng, L. (2011). P2N: a pedagogical pattern for teaching computer programming to non-CS majors. Paper presented at the Proceedings of the 18th Conference on Pattern Languages of Programs, Portland, Oregon, USA. https://doi.org/10.1145/2578903.2579163
    Johnson-Laird, P., & Khemlani, S. S. (2013). Toward a unified theory of reasoning. In Psychology of learning and motivation (Vol. 59, pp. 1-42): Elsevier.
    Johnson, J. D., McDuff, S. G., Rugg, M. D., & Norman, K. A. (2009). Recollection, familiarity, and cortical reinstatement: a multivoxel pattern analysis. Neuron, 63(5), 697-708.
    Köppe, C., & Pruijt, L. (2014). Improving students` learning in software engineering education through multi-level assignments. Paper presented at the Proceedings of the Computer Science Education Research Conference.
    Kahney, H. (1983). What do novice programmers know about recursion. Paper presented at the Proceedings of the SIGCHI conference on Human Factors in Computing Systems.
    Krishnamurthi, S., & Fisler, K. (2019). 13 Programming Paradigms and Beyond. The Cambridge Handbook of Computing Education Research, 377.
    Lahtinen, E., Ala-Mutka, K., & Järvinen, H.-M. (2005). A study of the difficulties of novice programmers. ACM Sigcse Bulletin, 37(3), 14-18.
    Letovsky, S. (1987). Cognitive processes in program comprehension. Journal of Systems and software, 7(4), 325-339.
    Linn, M. C., & Clancy, M. J. (1992). The case for case studies of programming problems. Commun. ACM, 35(3), 121–132. doi:10.1145/131295.131301
    Lister, R., Adams, E. S., Fitzgerald, S., Fone, W., Hamer, J., Lindholm, M., . . . Thomas, L. (2004). A multi-national study of reading and tracing skills in novice programmers. Paper presented at the Working group reports from ITiCSE on Innovation and technology in computer science education, Leeds, United Kingdom. https://doi.org/10.1145/1044550.1041673
    Markman, A. B. (1999). Knowledge representation.
    McDermott, R., Eccleston, G., & Brindley, G. (2008). More than a good story—can you really teach programming through storytelling? Innovation in Teaching and Learning in Information and Computer Sciences, 7(1), 34-43.
    Miljanovic, M. A., & Bradbury, J. S. (2016). Robot on! A serious game for improving programming comprehension. Paper presented at the Proceedings of the 5th International Workshop on Games and Software Engineering.
    Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological review, 63(2), 81.
    Moreno, A., & Myller, N. (2003). Producing an educationally effective and usable tool for learning, the case of the jeliot family. ACM Trans. Program. Lang. Syst, 15(5), 795-825.
    Moreno, A., Myller, N., Sutinen, E., & Ben-Ari, M. (2004). Visualizing programs with Jeliot 3. Paper presented at the Proceedings of the working conference on Advanced visual interfaces.
    Murphy, L., McCauley, R., & Fitzgerald, S. (2012). `Explain in plain English`questions: implications for teaching. Paper presented at the Proceedings of the 43rd ACM technical symposium on Computer Science Education.
    Murray, A., & Lethbridge, T. C. (2005a). On generating cognitive patterns of software comprehension. Paper presented at the Proceedings of the 2005 conference of the Centre for Advanced Studies on Collaborative research.
    Murray, A., & Lethbridge, T. C. (2005b). Presenting micro-theories of program comprehension in pattern form. Paper presented at the 13th International Workshop on Program Comprehension (IWPC`05).
    Naps, T. L., Rößling, G., Almstrum, V., Dann, W., Fleischer, R., Hundhausen, C., . . . Rodger, S. (2002). Exploring the role of visualization and engagement in computer science education. In Working group reports from ITiCSE on Innovation and technology in computer science education (pp. 131-152).
    Nelson, G. L., Xie, B., & Ko, A. J. (2017). Comprehension first: evaluating a novel pedagogy and tutoring system for program tracing in CS1. Paper presented at the Proceedings of the 2017 ACM Conference on International Computing Education Research.
    Nishida, T., Kanemune, S., Idosaka, Y., Namiki, M., Bell, T., & Kuno, Y. (2009). A CS unplugged design pattern. ACM Sigcse Bulletin, 41(1), 231-235.
    Norman, D. A. (1983). Some observations on mental models. Human-Computer Interaction, 241-244.
    Pennington, N. (1987). Stimulus structures and mental representations in expert comprehension of computer programs. Cognitive psychology, 19(3), 295-341.
    Perkins, D. N., Hancock, C., Hobbs, R., Martin, F., & Simmons, R. (1986). Conditions of Learning in Novice Programmers. Journal of Educational Computing Research, 2(1), 37-55. doi:10.2190/gujt-jcbj-q6qu-q9pl
    Rising, L. (1998). The patterns handbook: techniques, strategies, and applications (Vol. 13): Cambridge University Press.
    Robins, A., Rountree, J., & Rountree, N. (2003). Learning and teaching programming: A review and discussion. Computer science education, 13(2), 137-172.
    Schulte, C. (2008). Block Model: an educational model of program comprehension as a tool for a scholarly approach to teaching. Paper presented at the Proceedings of the Fourth international Workshop on Computing Education Research, Sydney, Australia. https://doi.org/10.1145/1404520.1404535
    Schulte, C., Clear, T., Taherkhani, A., Busjahn, T., & Paterson, J. H. (2010). An introduction to program comprehension for computer science educators. Paper presented at the Proceedings of the 2010 ITiCSE working group reports, Ankara, Turkey. https://doi.org/10.1145/1971681.1971687
    Schumacher, R. M., & Czerwinski, M. P. (1992). Mental models and the acquisition of expert knowledge. In The psychology of expertise (pp. 61-79): Springer.
    Shargabi, A. A., Aljunid, S. A., Annamalai, M., & Zin, A. M. (2020). Performing Tasks Can Improve Program Comprehension Mental Model of Novice Developers: An Empirical Approach. Paper presented at the Proceedings of the 28th International Conference on Program Comprehension.
    Sharp, H., Manns, M. L., & Eckstein, J. (2003). Evolving pedagogical patterns: The work of the pedagogical patterns project. Computer science education, 13(4), 315-330.
    Sharp, H., Manns, M. L., McLaughlin, P., Prieto, M., & Dodani, M. (1996). Pedagogical patterns—successes in teaching object technology: a workshop from oopsla`96. ACM SIGPLAN Notices, 31(12), 18-21.
    Shiffrin, R. M., & Schneider, W. (1977). Controlled and automatic human information processing: II. Perceptual learning, automatic attending and a general theory. Psychological review, 84(2), 127.
    Shneiderman, B., & Mayer, R. (1979). Syntactic/semantic interactions in programmer behavior: A model and experimental results. International Journal of Computer & Information Sciences, 8(3), 219-238.
    Simon. (2011). Assignment and sequence: why some students can`t recognise a simple swap. Paper presented at the Proceedings of the 11th Koli Calling International Conference on Computing Education Research, Koli, Finland. https://doi.org/10.1145/2094131.2094134
    Soloway, E., Bonar, J., & Ehrlich, K. (1983). Cognitive strategies and looping constructs: An empirical study. Communications of the ACM, 26(11), 853-860.
    Soloway, E., & Ehrlich, K. (1984). Empirical studies of programming knowledge. IEEE Transactions on software engineering(5), 595-609.
    Sonmez, J. Z. (2017). The Complete Software Developer`s Career Guide: How to Learn Programming Languages Quickly, Ace Your Programming Interview, and Land Your Software Developer Dream Job: Simple Programmer, LLC.
    Sorva, J. (2012). Visual program simulation in introductory programming education: Aalto University.
    Sorva, J. (2013). Notional machines and introductory programming education. ACM Trans. Comput. Educ., 13(2), Article 8. doi:10.1145/2483710.2483713
    Storey, M.-A. (2006). Theories, tools and research methods in program comprehension: past, present and future. Software Quality Journal, 14(3), 187-208.
    Strauss, A. L. (1998). Basics of qualitative research : techniques and procedures for developing grounded theory (2nd ed ed.).
    Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive science, 12(2), 257-285.
    Teague, D., Corney, M., Ahadi, A., & Lister, R. (2012). Swapping as the`Hello World`of relational reasoning: Replications, reflections and extensions. Paper presented at the Proceedings of the Fourteenth Australasian Computing Education Conference (ACE2012): Conferences in Research and Practice in Information Technology, Volume 123.
    Teif, M., & Hazzan, O. (2006). Partonomy and taxonomy in object-oriented thinking: junior high school students` perceptions of object-oriented basic concepts. SIGCSE Bull., 38(4), 55–60. doi:10.1145/1189136.1189170
    Thota, N., Berglund, A., & Clear, T. (2012). Illustration of paradigm pluralism in computing education research.
    Venables, A., Tan, G., & Lister, R. (2009). A closer look at tracing, explaining and code writing skills in the novice programmer. Paper presented at the Proceedings of the fifth international workshop on Computing education research workshop.
    Von Mayrhauser, A., & Vans, A. M. (1996). Identification of dynamic comprehension processes during large scale maintenance. IEEE Transactions on software engineering, 22(6), 424-437.
    Waite, J., Maton, K., Curzon, P., & Tuttiett, L. (2019). Unplugged computing and semantic waves: Analysing crazy characters. Paper presented at the Proceedings of the 1st UK & Ireland Computing Education Research Conference.
    Watson, C., & Li, F. W. (2014). Failure rates in introductory programming revisited. Paper presented at the Proceedings of the 2014 conference on Innovation & technology in computer science education.
    Weinberg, G. M. (1971). The psychology of computer programming (Vol. 29): Van Nostrand Reinhold New York.
    Westbrook, L. (2006). Mental models: a theoretical overview and preliminary study. Journal of Information Science, 32(6), 563-579.
    Wood, D., Bruner, J. S., & Ross, G. (1976). The role of tutoring in problem solving. Journal of child psychology and psychiatry, 17(2), 89-100.
    丁振豐(2000)。近側發展區。教育大辭書。[Online]. Available:http://terms.naer.edu.tw/detail/1306998/ (2021-11-24)
    Babbie, E.(2021)。社會科學研究方法(林秀雲譯)。臺北市:雙葉書廊。
    王令宜 (2017)。 教育訊息:美國推動電腦科學(Computer Science)教育對我國之啟示。教育脈動(10),頁 13。
    林生傳(2003)。教育研究法:全方位的統整與分析。臺北市:心理。
    胡幼慧(2009)。質性研究:理論、方法及本土女性研究實例。台灣:巨流圖書。
    張芬芬 (2010)。 質性資料分析的五步驟: 在抽象階梯上爬升。初等教育學刊(35),頁 87-120。
    張瀞文、賓靜蓀、程遠茜(2016)。教育下一波:程式設計開啟孩子的未來。親子天下,76。
    陳昺麟 (2001)。 社會科學質化研究之紮根理論實施程序及實例之介紹。勤益學報, No. 19,頁 327-342。
    程尚文(2009)。使用樣板教學於初階程式設計課程之探討。國立中山大學資訊管理學系研究所,高雄市。
    萬文隆 (2004)。 深度訪談在質性研究中的應用。生活科技教育月刊, 37(4),頁 17-23。
    蔡木景(2021)。JavaScript概念三明治:基礎觀念、語法原理一次帶走!。新北市:博碩文化股份有限公司。
    描述: 碩士
    國立政治大學
    數位內容碩士學位學程
    109462002
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0109462002
    資料類型: thesis
    DOI: 10.6814/NCCU202200903
    顯示於類別:[數位內容碩士學位學程] 學位論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    200201.pdf6088KbAdobe PDF21檢視/開啟


    在政大典藏中所有的資料項目都受到原著作權保護.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回饋