簡易檢索 / 詳目顯示

研究生: 蔡宗霖
論文名稱: 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
指導教授: 陳明溥
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: 2010
畢業學年度: 98
語文別: 中文
論文頁數: 74
中文關鍵詞: 程式設計教學策略電腦自我效能
英文關鍵詞: programming, instructional strategy, computer self-efficacy
論文種類: 學術論文
相關次數: 點閱:100下載:30
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
  • 本研究藉由教學實驗驗證使用Scratch程式設計軟體教導六年級學生學習程式設計的可行性,探討不同的教學策略(演練範例、問題導向)及電腦自我效能(高電腦自我效能、低電腦自我效能),對國小學生學習程式設計的學習表現與電腦學習態度之影響。本研究採因子設計之準實驗研究法,研究對象為六年級學生。研究結果顯示:(1)演練範例的教學策略有助於學生程式設計的學習表現;(2)高電腦自我效能有助於學生在知識應用上的學習表現;(3)兩種教學策略及高、低電腦自我效能的學生在使用Scratch進行遊戲設計創作上均有正向的電腦學習態度與感受,特別是高電腦自我效能的學生。整體而言,使用Scratch實施於程式設計教學課程是可行的,學生也對此課程持正向的學習態度,而使用演練範例的教學策略有助於程式設計初學者的表現。

    The purpose of this study was to examine the effects of instructional strategy on learners’ performance and attitude of programming. One hundred and nine sixth grade students participated in the programming project of this study. Participants received worked-out examples and problem-based learning by class, respectively. Participants were identified as the high computer self-efficacy group and the low computer self-efficacy group by the mean score of the computer self-efficacy inventory. The quasi-experimental design was applied in this study. The result revealed that: (a) worked-out examples enhanced students’ learning performance of programming; (b) learners with high computer self-efficacy achieved higher performance on knowledge application; (c) regardless of the instructional strategies, both self-efficacy students held positive attitudes toward the integration of scratch in the programming project, especially in high computer self-efficacy. Overall, the use of scratch in the programming course was feasible. Students held positive attitudes toward this course, and worked-out examples enhanced beginners’ performance of programming.

    附表目錄…………………………………………………vi 附圖目錄…………………………………………………vii 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…………………………5 第三節 研究範圍與限制………………………………6 第四節 重要名詞釋義…………………………………7 第二章 文獻探討………………………………………9 第一節 程式設計教學…………………………………9 第二節 教學策略………………………………………17 第三節 自我效能與電腦自我效能……………………21 第三章 研究方法………………………………………25 第一節 研究對象………………………………………25 第二節 研究設計………………………………………27 第三節 研究工具………………………………………29 第四節 研究程序………………………………………37 第五節 資料分析………………………………………40 第四章 結果與討論……………………………………42 第一節 程式設計學習表現分析………………………42 第二節 電腦學習態度分析……………………………48 第三章 結論與建議……………………………………53 第一節 結論……………………………………………53 第二節 建議……………………………………………56 參考書目…………………………………………………58 附錄一 電腦自我效能量表……………………………63 附錄二 演練範例組學習單……………………………65 附錄三 問題導向組學習單……………………………67 附錄四 Scratch簡介…………………………………72 附錄五 電腦學習態度問卷……………………………73 附錄六 遊戲設計創作評分量表………………………74

    中文部分
    王春展(1997)。專家與生手間問題解決能力的差異及其在教學上的啟示。教育研究資訊,80-92。
    王曉璿、王麒富、林建伸(2009)。應用直觀式Scratch軟體輔助國小學童問題解決合作學習教學設計初探。GCCCE 2009,5/25-28,國立台灣師範大學,台北。
    阮惠嵐(2008)。應用電腦輔助學習鷹架於國中自然與生活科技之學習成效與態度探討。未出版碩士論文,國立臺灣師範大學,臺北市。
    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。
    洪榮昭(2001)。 PBL教學策略。技術及職業教育雙月刊,第61期,10-12。
    陳明溥(2003)。網際網路與問題解決學習。台大教與學期刊電子報,第20期,2003年12月10日。
    教育部(2003)。國民中小學九年一貫課程綱要。取自:http://teach.eje.edu.tw/9CC/index_new.php.
    康嫻純(2005)。運用作曲軟體創作音樂之個案研究。未出版碩士論文,國立臺灣師範大學,臺北市。
    麥孟生(2000)。個人心理類型、自我效能及態度對電腦學習成效之影響。未出版碩士論文,國立中央大學,桃園縣。
    張春興(1997)。心理學原理。台北市:東華書局。
    詹秀美、吳武典(1991)。問題解決測驗指導手冊。台北:心理出版社。
    單文經(1997)。設計電腦化家教系統的可能性評估。視聽教育雙月刊,39(2),1-13。
    楊坤原(1999)。問題解決在科學學習成就評量上的應用。科學教育月刊,第216期,3-16。

    英文部分
    Andre, T. (1986). Problem and education. In G. D. Phye & T. Andre (Eds.), Cognitive classroom learning: Understanding, thinking, and problem solving (pp. 169-204). Orlando: Academic Press.
    Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice Hall.
    Bandura, A. (2001). Social cognitive theory of mass communication. Media Psychology, 3(3), 265-299.
    Bencze, J. L. (2008). Constructivism. Retrieved on April 23, 2010 from http://webspace.oise.utoronto.ca/~benczela/Constructivism.html.
    Biggs, J. (2000). Teaching for quality learning at university. Buckingham, UK: Open University Press.
    Boud, D., & Feletti, G. (1997). The challenge of problem based learning. London: Kogan Page.
    Bouffard-Bouchard, T. (1990). Influence of self-efficacy on performance in a cognitive task. The Journal of Social Psychology, 130(3), 353-363.
    Brooks, R. (1999). Towards a theory of the cognitive processes in computer programming. International Journal of Human Computer Studies, 51, 197-211.
    Bransford, J. D. & Stein, B. S. (1984). The IDEAL problem solver: A guide for improving thinking, learning, and creativity. New York: Freeman.
    Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121-152
    Coffin, R. J., & MacIntyre, P. D. (1999). Motivational influences on computer-related affective states. Computer in Human Behavior, 15, 549-569.
    Cooke, N. J., & Schvaneveldt, R. W. (1988). Effects of computer programming experience on network representations of abstract programming concepts. International Journal of Man-Machine Studies, 29, 407-427.
    Cooper, G., & Sweller, J. (1987). The effects of schema acquisition and rule automation on mathematical problem-solving transfer. Journal of Educational Psychology, 79, 347-362.
    Darabi, A., & Nelson, D. W. (2004). Training and transfer of complex cognitive skills: Effects of worked examples and conventional problem-solving. Proceedings of 27th Association for Educational Communications and Technology (AECT) Conference, Chicago, IL.
    de Kereki, I. F. (2008). Scratch: Applications in computer science 1. 38th ASEE/IEEE Frontiers in Education Conference, Saratoga Springs, NY, October 22-25, 2008.
    Eckerdal, A. (2009). Novice programming students’ learning of concepts and practise. Dissertation presented at mathematics and computer science, department of information technology, Upsalla University, Sweeden, March 6, 2009.
    Ericsson, K. A., & Lehmann, A. C. (1996). Expert and exceptional performance.: Evidence of maximal adaptation to task constraints. Annual Review Psychology, 47, 273-305.
    Fernaeus, Y., Kindborg, M., & Scholz, R. (2006). Programming and tools: Rethinking children's programming with contextual signs. Conference on Interaction Design and Children IDC '06, June 7-9, Tampere, Finland. ACM Press.
    Gagné, R. M. (1985). The Conditions of learning and theory of instruction. Orlando, Florida: Holt, Rinehart and Winston Inc.
    Gist, M. E., Schwoerer, C., & Rosen, B. (1989). Effects of alternative training methods on self-efficacy and performance in computer software training. Journal of Applied Psychology, 74(6), 884-891.
    Govender, I. & Grayson, D. (2006). Learning to program and learning to teach programming: A closer look. Proceedings of the ED-MEDIA 2006-World Conference on Educational Multimedia, Hypermedia & Telecommunications, 1687-1693.
    Guzdial, M. (2004). Programming environments for novices. S. Fincher, & M. Petre (Eds.), Computer Science Education Research. Taylor & Francis Group, London, UK.
    Hill, T., Smith, N. D., & Mann, M. F. (1987). Role of efficacy expectations in predicting the decision to use advanced technologies: The case of computers. Journal of Applied Psychology, 72(2), 307-313.
    Hadjerrouit, S. (2008). Towards a blended learning model for teaching and learning computer programming: A case study. Informatics in Education, 7(2), 181-210.
    Hohn, R. L., & Moraes, I. (1997). Use of rule-based elaboration of worked examples to promote the acquisition of programming plans. The Journal of Computer Information Systems, 38(2), 35-40.
    Hummel, H. G.-K. (2006). Feedback model to support designers of blended-learning courses. International Review of Research in Open and Distance Learning, 7(3), 1-16.
    Kelleher, C., & Pausch, R. (2005). Lowering the barriers to programming: A taxonomy of programming environments and languages for novice programmers. ACM Computing Surveys, 37(2), 83-137.
    Kolfschoten, G., Lukosch, S., Verbraeck, A., Valentin, E., & de Vreede, G. J. (2010). Cognitive learning efficiency through the use of design patterns in teaching. Computers & Education, 54(3), 652-660.
    Lahtinen, E., Ala-Mutka, K., & Järvinen, H. (2005). A study of the difficulties of novice programmers. ACM SIGCSE Bulletin, Proceedings of the 10th annual SIGCSE conference on Innovation and technology in computer science education ITiCSE '05, 37(3), 14-18.
    Malan, D. J., & Leitner, H. H. (2007). Scratch for budding computer scientists. ACM SIGCSE Bulletin, 39(1), 223-227.
    Maloney, J. H., Peppler, K., Kafai, Y., Resnick, M. & Rusk, N. (2008). Programming by choice: Urban youth learning programming with scratch. ACM SIGCSE Bulletin, 40(1), 367-371.
    Martocchio, J. J., & Dulebohn, J. (1994). Performance feedback effects in training: The role of perceived controllability. Personnel Psychology, 47(2), 357-373.
    Mayer, R. E. (1992). Thinking, problem solving, cognition (2nd ed.). NY: W. H. Freeman and Company.
    Murphy, C. A., Coover, D., & Owen, S. V. (1989). Development and validity of the computer self-efficacy scale. Educational and Psychological Measurement, 49, 893-899.
    Naharro-Berrocal, F., Pareja-Flores, C., Urquiza-Fuentes, J., & Velazquez-Iturbide, J. A. (2002). Approaches to comprehension-preserving graphical reduction of program visualizations. Paper presented at the Proceedings of the 2002 ACM symposium on Applied computing.
    Nilssona, B., & Folkestad, G. (2005). Children's practice of computer-based composition. Music Education Research, 7(1), 21-37.
    Norman, G. R., & Schmidt, H. G. (1992). The psychological basic of problem-based learning: a review of the evidence. Acad Med, 67(9), 557-565.
    Paas, F. G. W. C. (1992). Training strategies for attaining transfer of problem solving skill in statistics: A cognitive load approach. Journal of Educational Psychology, 84, 429-434.
    Paas, F. G. W. C., & van Merrriënboer, J. J. G. (1994). Variability of worked examples and transfer of geometrical problem-solving skills: A cognitive load approach. Journal of Educational Psychology, 86, 122-133.
    Pintrich, P. R. & Schunk, D. H. (2002) Motivation in education: Theory, research and applications (2nd edn) (Englewood Cliffs, NJ, Prentice Hall Merrill).
    Robins, A., Rountree, J., & Rountree, N. (2003). Learning and teaching programming: A review and discussion. Computer Science Education,13(2), 137-172.
    Salomon, G., & Perkins, D. N. (1987). Transfer of cognitive skills from programming: When and how? Journal of Educational Computing Research, 3, 149-170.
    Schollmeyer, M. (1996). Computer programming in high school vs. college. ACM SIGCSE Bulletin, 28(1), 378-382.
    Schunk, D. H., & Hanson, A. R. (1985). Peer Models: Influence on children’s self-efficacy and achievement. Journal of Educational Psychology, 77, 313-322.
    Schunk, D. H. (2000). Learning theories: An educational perspective (3rd ed.). Upper Saddle River, NJ: Prentice Hall.
    Seidman, R. H. (1988). New directions in educational computing research. In R. E. Mayer (Ed). Teaching and learning computer programming: Multiple research perspectives (pp. 299-308). Hillsdale, NJ: Lawrence Erlbaum.
    Sengupta, A. (2009). CFC(comment-first-coding)- A simple yet effective method for teaching programming to information systems students. Journal of Information Systems Education, 20(4), 393-399.
    Shaw, D. G. (1986). Effects of learning to program a computer in BASIC or Logo on problem-solving abilities. AEDS Journal, 19, 176-189.
    Skinner, E. A. Wellborn, J. G., & Connell, J. P. (1990). What it take to do well in school and whether I've got it: A process model of perceived control and children’s engagement and achievement in school. Journal of Educational Psychology, 82(1), 22-32.
    Slack, S.J., & Stewart, J. (1990). High school students' problem-solving performance on realistic genetics problems. Journal of Research in Science Teaching, 27, 55-67.
    Smith, P. L., & Ragan, T. J. (1999). Instructional design (2nd ed.). NY: John Wiley & Sons.
    Soloway, E., & Spohrer, J. C. (1989). Studying the novice programmer. Hillside, NJ: Erlbaum.
    Spohrer, J. C., & Soloway, E. (1986). Novice mistakes: Are the folk wisdoms correct? Communication of the ACM, 29(7), 624-632.
    Sweller, J., & Cooper, G. A. (1985). The use of worked examples as a substitute for problem solving in learning algebra. Cognition and Instruction, 2, 59-89.
    Sweller, J. (1988.) Cognitive load during problem solving: Effects on learning. Cognitive Science, 12, 257-285.
    Sweller, J., van Merrienboer, J. G., & Paas, F. G. W. C. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251-296.
    Sweller, J. (2004). Instructional design consequences of an analogy between evolution by natural selection and human cognitive architecture. Instructional Science 32(1), 9-31.
    Tuovinen, J. E., & Sweller, J. (1999). A comparison of cognitive load associated with discovery learning and worked examples. Journal of Education Psychology,91(2), 334-341.
    Van Tassel, D. (1978). Programming style, design, efficiency, debugging and testing. Englewood Cliffs. NJ: Prentice Hall.
    Woolfolk, A. E., & Hony, W. K. (1990). Prospective teachers’ sense of efficacy and beliefs about control. Journal of Educational Psychology, 82(1), 81-91.
    Zimmerman, B. J. (2000). Attaining self-regulation: A social cognitive perspective. In M. Boekaerts, P. R. Pintrich, & M. Zeidner, Handbook of self-regulation. (pp. 13-39). San Diego: Academic Press.

    下載圖示
    QR CODE