簡易檢索 / 詳目顯示

研究生: 許書毓
Shu, Hsu-Yu
論文名稱: 程式設計迷思概念診斷與矯正
Programming instruction with misconception diagnosis and correction
指導教授: 林育慈
Lin, Yu-Tzu
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: 2016
畢業學年度: 104
語文別: 中文
論文頁數: 110
中文關鍵詞: 程式設計迷思概念教學回饋教學平台
英文關鍵詞: programming misconception, feedback, learning platform
DOI URL: https://doi.org/10.6345/NTNU202203850
論文種類: 學術論文
相關次數: 點閱:195下載:37
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 本研究希望利用迷思概念診斷與矯正來輔助學生建立正確的程式設計概念、或減少迷思概念的產生。我們研究發展了一個迷思概念診斷與矯正的程式設計輔助學習平台,學生可於平台上撰寫並編譯程式,平台並提供迷思概念診斷機制,並可於診斷出可能的迷思概念時,給予學生迷思概念的矯正回饋,學生亦必須在撰寫程式的過程中針對重要概念進行反思以避免迷思概念的產生。研究利用準實驗研究法檢驗所發展教學模式的效益,實驗參與者為67位高中二年級的學生(實驗組32人,控制組31人),實驗結果發現:透過本研究提出的迷思概念診斷與矯正的教學平台與策略,包含對程式執行的順序、變數、判斷式、迴圈、函式的概念,學生的程式設計成就顯著提升(程式實作、學習單、期中期末測驗),此即由於學生經過迷思概念矯正回饋的引導與圖文概念的強調釐清,可針對容易產生迷思概念的程式結構,進行深度的思考與練習,以了解程式結構的概念與應用方式,進而促進程式設計能力。

    This study intends to study the design and development of programming instruction with misconception diagnosis and correction, and its effectiveness on students’ programming learning. We have implemented a programming learning platform with misconception diagnosis and correction functions, by which students can write and compile programs, and get misconception correction feedbacks once their programs are diagnosed with possible misconception. During writing programs, students are also required to carry out reflection for critical programming concepts to avoid misconception. A quasi-experimental study was conducted to examine the effectiveness of the proposed instructional methodology. The participants are 67 senior high school students. The experiment results show that the proposed instructioanl strategies and programming learning platform based on misconception diagnosis and correction, students’ programming achievement can be significantly enhanced. With the guidance of misconception correction feedbacks provided by the learning platform and reflective learing activities, students can easily carry out in-depth thinking in various programming conception and constructs during practicing program implementation; thus, contributing to programming conception development and programming ability.

    目錄 第一章 緒論 1 第一節 研究背景與動機 1 第二節 研究目的 3 第二節 名詞釋義 4 第二章 文獻探討 7 第一節 迷思概念 7 第二節 程式設計迷思概念 10 第三節 教學回饋 15 第三章 研究方法 19 第一節 研究設計與架構 19 第二節 研究實驗參與者 20 第三節 研究程序 21 第四節 研究工具 23 第五節 JSLA輔助教學工具 29 第六節 資料蒐集與分析方法 36 第四章 分析結果與討論 38 第一節 分析結果 38 第二節 討論 51 第五章 結論與建議 66 第一節 結論 66 第二節 建議 67 參考文獻 68 附錄一 程式設計迷思概念蒐集表格 72 附錄二 運算思維測驗題目 79 附錄三 每週課堂學習單 95 附錄四 期中期末測驗題目 106

    中文部份

    陳建偉. (2008). 高三學生液體界面現象迷思概念之研究 A Study of Misconceptions of Liquid Interface Phenomenon of the 12th Graders (pp. 1–120).
    彭泰源, & 張惠博. (1999). 國小五年級學童力與運動概念學習之研究.
    廖焜熙. (2001). 理化科學概念及過程技能之研究回顧與分析.

    英文部份

    0zdener, N. (2008). A comparison of the misconceptions about the time-efficiency of algorithms by various profiles of computer-programming students. Computers and Education, 51(3), 1094–1102. http://doi.org/10.1016/j.compedu.2007.10.008
    Akbaş, Y., & Gençtürk, E. (2011). The effect of conceptual change approach to eliminate 9th grade high school students’ misconceptions about air pressure. Kuram ve Uygulamada Egitim Bilimleri, 11(4), 2217–2222.
    Anseel, F., Lievens, F., & Schollaert, E. (2009). Reflection as a strategy to enhance task performance after feedback. Organizational Behavior and Human Decision Processes, 110(1), 23–35. http://doi.org/10.1016/j.obhdp.2009.05.003
    Baker, B. S. (1992). A Program for Identifying Duplicated Code. Computing Science and Statistics, 24, 49–57.
    Bayman, P., & Mayer, R. E. (1983). A diagnosis of beginning programmers’ misconceptions of BASIC programming statements. Communications of the ACM, 26(9), 677–679. http://doi.org/http://doi.acm.org/10.1145/358172.358408
    Bonar, J., & Soloway, E. (1985). Preprogramming Knowledge: A Major Source of Misconceptions in Novice Programmers. Human-Computer Interaction, 1(2), 133–161. http://doi.org/10.1207/s15327051hci0102_3
    Booth, J. L. (2011). Why Can’t Students Get the Concept of Math ?, (October), 31–35.
    Branch, W. T., & Paranjape, A. (2002). Feedback and Reflection: Teaching Methods for Clinical Settings. Academic Medicine : Journal of the Association of American Medical Colleges, 77(12 Pt 1), 1185–1188. http://doi.org/10.1097/00001888-200212000-00005
    Brandt, C. (2008). Integrating feedback and reflection in teacher preparation. ELT Journal, 62(1), 37–46. http://doi.org/10.1093/elt/ccm076
    Brinko, K. T. (2008). The Practice of Giving Feedback to Improve Teaching. The Journal of Higher Education, 64(5), 574–593.
    Britos, P., Rey, E. J., Rodríguez, D., & García-martínez, R. (2008). Work in Progress - Programming Misunderstandings Discovering Process Based On Intelligent Data Mining Tools, 1–2.
    Chen, C.-L., Cheng, S.-Y., & Lin, J. M.-C. (2012). A study of misconceptions and missing conceptions of novice Java programmers, 1–7. Retrieved from http://worldcomp-proceedings.com/proc/p2012/FEC2866.pdf
    Chen, M.-P. (2007). The Effects of Instructional Approach and Programming Tools on Novices’ Learning Computer Programming. Journal of Taiwan Normal University: Science Education, 52(1&2), 1–21. http://doi.org/10.6300/JNTNU.2007.52.01
    Chick, H. L., & Baker, M. (2005). Investigating Teachers’Responses To Student Misconceptions. Psychology of Mathematics Education, 2, 249–256. Retrieved from http://www.emis.ams.org/proceedings/PME29/PME29CompleteProc/PME29Vol2Adl_Fre.pdf#page=255
    Danielsiek, H., Paul, W., & Vahrenhold, J. (2012). Detecting and Understanding Students’ Misconceptions Related to Algorithms and Data Structures. ACM Technical Symposium on Computer Science Education (2012), 21–26. http://doi.org/10.1145/2157136.2157148
    Du Boulay, B. (1986). Some Difficulties of Learning to Program. Journal Of Educational Computing Research, 2(1), 57–73. http://doi.org/10.2190/3LFX-9RRF-67T8-UVK9
    Eckerdal, A., & Thuné, M. (2005). Novice Java programmers’ conceptions of “object” and “class”, and variation theory. ACM SIGCSE Bulletin, 37(3), 89. http://doi.org/10.1145/1151954.1067473
    Goldman, K., Gross, P., Heeren, C., Herman, G., Kaczmarczyk, L., Loui, M. C., & Zilles, C. (2008). Identifying important and difficult concepts in introductory computing courses using a delphi process. ACM SIGCSE Bulletin, 40(1), 256. http://doi.org/10.1145/1352322.1352226
    Hancock, C. H. (1940). An evaluation of certain popular science misconceptions. Science Education, 24(4), 208–213. http://doi.org/10.1002/sce.3730240409
    Hattie, J., & Timperley, H. (2007). The Power of Feedback. Review of Educational Research, 77(1), 81–112. http://doi.org/10.3102/003465430298487
    Holland, S., Griffiths, R., Woodman, M., Hall, W., Keynes, M., & Kingdom, U. (1997). Avoiding Object Misconceptions. SIGCSE Technical Symposium on Computer Science Education, 29 Issue 1, 131–134.
    Hwang, W. Y., Shadiev, R., Wang, C. Y., & Huang, Z. H. (2012). A pilot study of cooperative programming learning behavior and its relationship with students’ learning performance. Computers and Education. http://doi.org/10.1016/j.compedu.2011.12.009
    Kaczmarczyk, L. C., Petrick, E. R., East, J. P., & Herman, G. L. (2010). Identifying student misconceptions of programming. Proceedings of the 41st ACM Technical Symposium on Computer Science Education - SIGCSE ’10, 107–111. http://doi.org/10.1145/1734263.1734299
    Lahtinen, E., Ala-Mutka, K., & Järvinen, H.-M. (2005). A study of the difficulties of novice programmers. ACM SIGCSE Bulletin, 37(3), 14. http://doi.org/10.1145/1151954.1067453
    Lwo, L. S., Chang, C. C., Tung, Y. P., & Yang, W. C. (2013). Marine science literacy and misconceptions among senior high school students. Journal of Research in Education Sciences, 58(3), 51–83. http://doi.org/10.6209/JORIES.2013.58(3).03
    Moons, J., & De Backer, C. (2013). The design and pilot evaluation of an interactive learning environment for introductory programming influenced by cognitive load theory and constructivism. Computers & Education, 60(1), 368–384. http://doi.org/10.1016/j.compedu.2012.08.009
    Morales, Z. A. (2014). Analysis of Students ’ Misconceptions and Error Patterns in Mathematics : The Case of Fractions, 1–10.
    Perkins, D., & Martin, F. (1986). Fragile knowledge and neglected strategies in novice programmers. In Empirical studies of programmers (pp. 213–229). Retrieved from http://books.google.com/books?hl=en&lr=&id=sswoYivNQVUC&oi=fnd&pg=PA213&dq=Fragile+Knowledge+and+Neglected+Strategies+in+Novice+Programmers&ots=afQcU6lc_F&sig=z1XL1J_F7uXpWMQ6dATyayoRwao
    Perkins, D. N., & Simmons, R. (1988). Patterns of Misunderstanding: An Integrative Model for Science, Math, and Programming. Review of Educational Research, 58(3), 303–326. http://doi.org/10.3102/00346543058003303
    Putnam, R. T., Sleeman, D., Baxter, J. A., & Kuspa, L. K. (1986). A Summary of Misconceptions of High School Basic Programmers. Journal of Educational Computing Research, 2(4), 459–472. http://doi.org/10.2190/FGN9-DJ2F-86V8-3FAU
    Ragonis, N., & Ben-Ari, M. (2005). A long-term investigation of the comprehension of OOP concepts by novices. Computer Science Education, 15(February 2015), 203–221. http://doi.org/10.1080/08993400500224310
    Revival, G. (2014). What is a misconception? Common Misconceptions in Basic Mathematics, 1–46. http://doi.org/10.1038/sj.embor.7400842
    Rittle-Johnson, B., & Schneider, M. (2015). Developing conceptual and procedural knowledge of mathematics. Oxford Handbook of Numerical Cognition, 1118–1134. http://doi.org/10.1093/oxfordhb/9780199642342.013.014
    Running, D. M., Ligon, J. B., & Miskioglu, I. (2016). Individual Differences in Perception of Applied Music Teaching Feedback. Journal of Composite Materials, 33(10), 928–940. http://doi.org/0803973233
    Rutar, N. (University of M., Almazan, C. (University of M., & Foster, J. (University of M. (2004). A comparison of bug finding tools for Java. International Symposium on Software Reliability Engineering (ISSRE), 245–256. http://doi.org/10.1109/ISSRE.2004.1
    Sanders, K., & Thomas, L. (2007). Checklists for grading object-oriented CS1 programs. ACM SIGCSE Bulletin, 39(3), 166. http://doi.org/10.1145/1269900.1268834
    Sekiya, T., & Yamaguchi, K. (2013). Tracing quiz set to identify novices’ programming misconceptions. Proceedings of the 13th Koli Calling International Conference on Computing Education Research, 87–95. http://doi.org/10.1145/2526968.2526978
    Sirkiä, T., & Sorva, J. (2012). Exploring programming misconceptions: An analysis of student mistakes in visual program simulation exercises. Proceedings - 12th Koli Calling International Conference on Computing Education Research, Koli Calling 2012, 19–28. http://doi.org/10.1145/2401796.2401799
    Spohrer, J. C., & Soloway, E. (1986). Novice Mistakes : Are the Folk Wisdoms Correct ? Communications of the ACM, 29(7), 10.
    Taylor, A. K., & Kowalski, P. (2012). Students ’ misconceptions in Psychology : How you ask matters … sometimes. Journal of the Scholarship of Teaching and Learning, 12(3), 62–77. Retrieved from http://search.proquest.com/docview/1314328305?accountid=13042
    Treagust, D. F. (1988). Development and use of diagnostic tests to evaluate students’ misconceptions in science. International Journal of Science Education, 10(2), 159–169. http://doi.org/10.1080/0950069880100204
    Van Den Boom, G., Paas, F., Van Merriënboer, J. J. G., & Van Gog, T. (2004). Reflection prompts and tutor feedback in a web-based learning environment: Effects on students’ self-regulated learning competence. Computers in Human Behavior, 20(4), 551–567. http://doi.org/10.1016/j.chb.2003.10.001

    下載圖示
    QR CODE