簡易檢索 / 詳目顯示

研究生: 林映慈
Lin, Ying-Tzu
論文名稱: 探討STEM導向程式設計課程對於運算思維傾向、程式自我效能與創意自我效能之影響
Exploring the impact of STEM-oriented programming curriculum on computational thinking, programming self-efficacy and creative self-efficacy
指導教授: 李文瑜
Lee, Silvia Wen-Yu
口試委員: 梁至中
Liang, Jyh-Chong
王嘉瑜
Wang, Chia-Yu
李文瑜
Lee, Silvia Wen-Yu
口試日期: 2023/07/21
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: 2023
畢業學年度: 111
語文別: 中文
論文頁數: 78
中文關鍵詞: STEM導向課程運算思維傾向程式自我效能創意自我效能
英文關鍵詞: STEM-oriented curriculum, computational thinking disposition, programming self-efficacy, creative self-efficacy
研究方法: 準實驗設計法
DOI URL: http://doi.org/10.6345/NTNU202301639
論文種類: 學術論文
相關次數: 點閱:115下載:49
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
  • STEM教育模式,是一種跨領域的教學方式,其核心科目為科學、科技、工程與數學,有別於傳統的課堂授課以教師講述為中心,STEM教育則以學生為中心,引導學生思考並解決問題。然而,過去研究中對於運算思維和創造力幾乎是以試題和圖形的測驗方式評估學生的運算思維能力與創造力,鮮少探討個人的情意面向。本研究藉由STEM課程以培養學生的運算思維,使用積木程式編輯平台輔助STEM導向的課程教學,並結合環境議題,課程共為期10週。研究對象為臺灣中部地區國小六年級學生,男生57人、女生47人,共104人。本研究採用單一組前後測設計,並蒐集學生的運算思維傾向、程式與創意自我效能問卷,以成對樣本 t 檢定、獨立樣本t檢定、皮爾森積差相關與多元迴歸分析。了解學生藉由STEM導向程式設計課程,其運算思維傾向、創意自我效能與程式自我效能的改變情形以及各變項對程式自我效能的預測情形。此外,本研究亦針對完成之作品進行評分,探討作品表現與程式自我效能、創意自我效能以及運算思維傾向的關聯。研究結果顯示學生在STEM導向課程前後其創意自我效能與程式自我效能總量以及程式自我效能中的邏輯、獨立、鷹架、自律學習與複雜任務均獲得顯著提升,然而在運算思維傾向上沒有顯著提升。多元回歸結果顯示創意自我效能、運算思維傾向中的模式一般化、抽象化、問題評估能預測學生程式自我效能。作品評分中的評分項目與程式自我效能的構面、運算思維傾向的構面達正向低度相關。因此,學生除了學習程式設計的技能外也透過作品的創作提高他們的創意信心,進而能提升對於程式設計的信心。對此,建議未來課程中可以多鼓勵學生發揮創意進行創作,以提升學生對撰寫程式的信心。

    STEM education model is an interdisciplinary instructional approach with a core focus on Science, Technology, Engineering, and Mathematics. Unlike traditional classroom lectures centered around teacher-led instruction, STEM education places students at the center, guiding them to think critically and solve problems. However, past research has predominantly assessed students' computational thinking and creativity through test questions and graphical assessments, often overlooking the affective aspects. This study utilizes a STEM curriculum to cultivate students' computational thinking, employing a block-based programming platform to facilitate STEM-oriented course instruction, combined with environmental issues. The course spans a duration of 10 weeks and targets sixth-grade students (104 participants; 57 males and 47 females) from the central region of Taiwan. The study employs a single-group pretest-posttest design and collects data through Computational Thinking Disposition, Programming, and Creative Self-Efficacy questionnaires. Data analysis involves paired-sample t-tests, one-sample t-tests, Pearson correlation coefficients, and multiple regression analysis. The study aims to understand the changes in students' computational thinking disposition, creative and programming self-efficacy through a STEM-oriented programming design course, as well as predicting the effects of various variables on programming self-efficacy. Furthermore, the study assesses completed projects and explores the associations between project performance and programming self-efficacy, creative self-efficacy, and computational thinking disposition. The findings reveal significant improvements in students' overall creative and programming self-efficacy, as well as specific facets of programming self-efficacy including logical thinking, independence, scaffolding, self-directed learning, and handling complex tasks, after participating in the STEM-oriented course. However, there is no significant improvement observed in computational thinking disposition. Multiple regression results indicate that creative self-efficacy and specific computational thinking disposition aspects such as pattern generalization, abstraction, and problem assessment can predict students' programming self-efficacy. Project scoring correlates positively and moderately with programming self-efficacy dimensions and computational thinking disposition facets. Therefore, students not only enhance their programming skills but also boost their creative confidence through project creation, subsequently increasing their confidence in programming. In light of these findings, it is recommended that future curricula encourage students to exercise creativity in their projects to enhance their confidence in programming.

    第一章 緒論 1 第一節 研究背景與動機 1 第二節 研究目的與問題 4 第三節 名詞釋義 5 第四節 研究範圍與限制 7 第二章 文獻探討 8 第一節 程式設計課程 8 第二節 運算思維傾向 12 第三節 自我效能 17 第三章 研究方法 22 第一節 研究對象 22 第二節 研究設計與流程 22 第三節 學習環境與教學設計 24 第四節 研究工具 29 第五節 分析方法 38 第四章 研究結果 40 第一節 程式自我效能、運算思維傾向與創意自我效能改變情形 40 第二節 作品評分情形與各變項之間的相關性 43 第三節 高低創意自我效能對於運算思維傾向與程式自我效能之影響 46 第四節 各變項對程式自我效能的預測情形 49 第五章 結論與建議 50 第一節 結論與討論 50 第二節 建議 55 參考文獻 58 附錄 70

    王曉璿(2022)。運算思維課程關鍵與學習策略設計探究。台灣教育,736,1-7。
    李隆盛、楊秀全(2019)。 範例引導學習與問題導向學習之教學策略對國小學生機器人程式學習的影響.。數位學習科技期刊, 11(4), 77-104。
    林育慈、吳正己(2016)。運算思維與中小學資訊科技課程。教育脈動,6,5-20。
    林依婷、李文瑜(2023年3月9-10日)。探討心智圖融入程式編輯和性別對國中生運算思維傾向與程式自我效能之影響。第十八屆台灣數位學習發展研討會,屏東縣,臺灣。
    林坤誼(2018)。STEM 教育在台灣推行的現況與省思。青年研究學報,21(1), 1-9。
    邱皓政(2021)。量化研究法(二)統計原理與分析技術。雙葉書廊。
    胡秋帆、吳正己 、林育慈、游志弘(2021)。高中生運算思維測驗發展。數位學習科技期刊,13(1), 1-21。
    國家教育研究院(2015)。十二年國教科技領域「資訊科技」科目課程綱要草案。作者。
    張基成、陳怡靜 (2018)。機器人跨領域 STEM 主題式統整課程與任務導向式教學的設計及評鑑。科學教育學刊,26(4), 305-331。
    教育部(2014)。十二年國民基本教育課程綱要總綱。作者。
    陳家騏、古建國(2017)。STEM 教學應用於高中探究與實作課程之行動研究—以摩擦力為例。物理教育學刊,18(2), 17-38。
    楊立萱(2021)。國小學童創意自我效能與創造力之相關研究—以學習心流經驗及幸福感為中介變項(未出版之碩士論文)。國立臺灣師範大學。
    楊書銘、賴阿福、蔡俊明(2008)。兒童 Scratch 程式設計課程之開發與研究。載於臺北市97 年度資訊教育人員國際交流參訪團教師論壇作品集(頁128-143)。
    鄭瑞洲、楊敏、陳君瑜(2022)。不插電程式設計教學促進偏鄉國小生對程式設計的情境興趣與概念理解。科技博物,26(2), 83-115。
    羅希哲、陳柏豪、石儒居、蔡華齡、蔡慧音(2009)。STEM 整合式教學法在國民中學自然與生活技術領域之研究。人文社會科學研究,3(3), 42-66。
    Adams, R., Evangelou, D., English, L., De Figueiredo, A. D., Mousoulides, N., Pawley, A. L., Schiefellite, C., Stevens, R., Svinicki, M., Trenor, J. M., & Wilson, D. M. (2011). Multiple perspectives on engaging future engineers. Journal of Engineering Education, 100(1), 48–88.
    Addido, J., Borowczak, A. C., & Walwema, G. B. (2023). Teaching Newtonian physics with LEGO EV3 robots: An integrated STEM approach. Eurasia Journal of Mathematics, Science and Technology Education, 19(6), em2280.
    Addido, J., Borowczak, A. C., & Walwema, G. B. (2023). Teaching Newtonian physics with LEGO EV3 robots: An integrated STEM approach. Eurasia Journal of Mathematics, Science and Technology Education, 19(6), em2280.
    Angeli, C., Voogt, J., Fluck, A., Webb, M., Cox, M., Malyn-Smith, J., & Zagami, J. (2016). A K-6 computational thinking curriculum framework: Implications for teacher knowledge. Journal of Educational Technology & Society, 19(3), 47-57.
    Atmatzidou, S., & Demetriadis, S. (2016). Advancing students’ computational thinking skills through educational robotics: A study on age and gender relevant differences. Robotics and Autonomous Systems, 75, 661-670.
    Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychological review, 84(2), 191.
    Bandura, A. (1997) Self-Efficacy: The Exercise of Control. W.H. Freeman and Company, New York.
    Bers, M. U. (2008). Blocks to robots learning with technology in the early childhood classroom. Teachers College Press.
    Biskjaer, M. M., Iversen, O. S., & Dindler, C. (2021). Cultivating Creativity in Computing Education: A Missed Opportunity?. In Creativity and Learning: Contexts, Processes and Support (pp. 89-113). Cham: Springer International Publishing.
    Brown, N. C., Sentance, S., Crick, T., & Humphreys, S. (2014). Restart: The resurgence of computer science in UK schools. ACM Transactions on Computing Education (TOCE), 14(2), 1-22.
    Buitrago Flórez, F., Casallas, R., Hernández, M., Reyes, A., Restrepo, S., & Danies, G. (2017). Changing a generation’s way of thinking: Teaching computational thinking through programming. Review of Educational Research, 87(4), 834-860.
    Chang, Y. S., Chen, M. Y. C., Chuang, M. J., & Chou, C. H. (2019). Improving creative self-efficacy and performance through computer-aided design application. Thinking Skills and Creativity, 31, 103-111.
    Chen, G., Shen, J., Barth-Cohen, L., Jiang, S., Huang, X., & Eltoukhy, M. (2017). Assessing elementary students’ computational thinking in everyday reasoning and robotics programming. Computers & education, 109, 162-175.
    Cheng, L., Wang, M., Chen, Y., Niu, W., Hong, M., & Zhu, Y. (2022). Design my music instrument: a project-based science, technology, engineering, arts, and mathematics program on the development of creativity. Frontiers in Psychology, 12, 763948.
    Chiang, F. K., Zhang, Y., Zhu, D., Shang, X., & Jiang, Z. (2022). The Influence of Online STEM Education Camps on Students’ Self-Efficacy, Computational Thinking, and Task Value. Journal of science education and technology, 31(4), 461-472.
    Chookaew, S., Howimanporn, S., & Hutamarn, S. (2020). Investigating Students’ Computational Thinking through STEM Robot-Based Learning Activities. Advances in Science, Technology and Engineering Systems, Journal Vol. 5(No. 6), 1366–1371
    Cohen, J. (2013). Statistical power analysis for the behavioral sciences. Academic press.
    Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. psychometrika, 16(3), 297-334.
    Csizmadia, A., Curzon, P., Dorling, M., Humphreys, S., Ng, T., Selby, C., & Woollard, J. (2015). Computational thinking-A guide for teachers. Computing At School.
    Dagienė, V., Futschek, G., & Stupurienė, G. (2019). Creativity in solving short tasks for learning computational thinking. Constructivist Foundations, 14(3), 382-396.
    Durak, H. Y., Yilmaz, F. G. K., & Yilmaz, R. (2019). Computational thinking, programming self-efficacy, problem solving and experiences in the programming process conducted with robotic activities. Contemporary Educational Technology, 10(2), 173-197.
    Erdoğan, N., Navruz, B., Younes, R., & Capraro, R. M. (2016). Viewing how STEM project-based learning influences students’ science achievement through the implementation lens: A latent growth modeling. EURASIA Journal of Mathematics, Science & Technology Education, 12(8), 2139–2154.
    Erdoğan, N., Navruz, B., Younes, R., & Capraro, R. M. (2016). Viewing how STEM project-based learning influences students’ science achievement through the implementation lens: A latent growth modeling. EURASIA Journal of Mathematics, Science & Technology Education, 12(8), 2139–2154.
    Erdoğan, N., Navruz, B., Younes, R., & Capraro, R. M. (2016). Viewing how STEM project-based learning influences students’ science achievement through the implementation lens: A latent growth modeling. EURASIA Journal of Mathematics, Science & Technology Education, 12(8), 2139–2154.
    Fernaeus, Y., Kindborg, M., & Scholz, R. (2006, June). Rethinking children's programming with contextual signs. In Proceedings of the 2006 conference on Interaction design and children (pp. 121-128).
    Geng, Z. (2023). Environmental design as a component of block‐based programming. Computer Applications in Engineering Education, 31(2), 408-420.
    Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field. Educational researcher, 42(1), 38-43.
    Guven, G., Kozcu Cakir, N., Sulun, Y., Cetin, G., & Guven, E. (2022). Arduino-assisted robotics coding applications integrated into the 5E learning model in science teaching. Journal of Research on Technology in Education, 54(1), 108-126.
    Hill-Briggs, F. (2003). Problem solving in diabetes self-management: a model of chronic illness self-management behavior. Annals of Behavioral Medicine, 25(3), 182-193.
    Hsiao, H. S., Lin, Y. W., Lin, K. Y., Lin, C. Y., Chen, J. H., & Chen, J. C. (2022). Using robot-based practices to develop an activity that incorporated the 6E model to improve elementary school students’ learning performances. Interactive Learning Environments, 30(1), 85-99.
    https://www.computingatschool.org.uk/resources/2014/june/cas-computational-thinking-a-guide-for-teachers
    Israel-Fishelson, R., Hershkovitz, A., Eguíluz, A., Garaizar, P., & Guenaga, M. (2021). A log-based analysis of the associations between creativity and computational thinking. Journal of Educational Computing Research, 59(5), 926-959.
    Israel-Fishelson, R., Hershkovitz, A., Eguíluz, A., Garaizar, P., & Guenaga, M. (2021). The associations between computational thinking and creativity: The role of personal characteristics. Journal of Educational Computing Research, 58(8), 1415-1447.
    Johnson, D. M., Pate, M. L., Estepp, C. M., Wardlow, G. W., & Hood, G. T. (2022). Designing Arduino Instruction for Novice Agriculture Students: Effects on Interest, Self-Efficacy, and Knowledge. Applied Engineering in Agriculture, 38(5), 753-761.
    Karwowski, M. (2012). Did curiosity kill the cat? Relationship between trait curiosity, creative self-efficacy and creative personal identity. Europe’s Journal of Psychology, 8, 547‒558
    Kelley, T. R., & Knowles, J. G. (2016). A conceptual framework for integrated STEM education. International Journal of STEM Education, 3, 1-11.
    Kelley, T. R., & Knowles, J. G. (2016). A conceptual framework for integrated STEM education. International Journal of STEM Education, 3, 11.
    Kim, B., Kim, T., & Kim, J. (2013). and-pencil programming strategy toward computational thinking for non-majors: Design your solution. Journal of Educational Computing Research, 49(4), 437-459.
    Kong, S. C. (2016). A framework of curriculum design for computational thinking development in K-12 education. Journal of Computers in Education, 3, 377-394.
    Kong, S. C. (2017, July). Development and validation of a programming self-efficacy scale for senior primary school learners. In Proceedings of the International Conference on Computational Thinking Education (pp. 97-102).
    Kong, S. C., Chiu, M. M., & Lai, M. (2018). A study of primary school students' interest, collaboration attitude, and programming empowerment in computational thinking education. Computers & education, 127, 178-189.
    Korkmaz, Ö., & Altun, H. (2014). Adapting Computer Programming Self-Efficacy Scale and Engineering Students’ Self-Efficacy Perceptions. Participatory Educational Research, 1(1), 20-31.
    Korkmaz, Ö., Çakir, R., & Özden, M. Y. (2017). A validity and reliability study of the computational thinking scales (CTS). Computers in human behavior, 72, 558-569.
    Kumar, J. A. (2021). Educational chatbots for project-based learning: investigating learning outcomes for a team-based design course. International journal of educational technology in higher education, 18(1), 1-28.
    Kwon, K., Ottenbreit-Leftwich, A. T., Brush, T. A., Jeon, M., & Yan, G. (2021). Integration of problem-based learning in elementary computer science education: effects on computational thinking and attitudes. Educational Technology Research and Development, 69, 2761-2787.
    Lai, A. F., & Yang, S. M. (2011, September). The learning effect of visualized programming learning on 6 th graders' problem solving and logical reasoning abilities. In 2011 International Conference on Electrical and Control Engineering (pp. 6940-6944). IEEE.
    Lee, S. W. Y., Liang, J. C., Hsu, C. Y., & Tsai, M. J. (2023). Students’ beliefs about computer programming predict their computational thinking and computer programming self-efficacy. Interactive Learning Environments, 1-21.
    Lindstrøm, C., & Sharma, M. D. (2011). Self-efficacy of first year university physics students: Do gender and prior formal instruction in physics matter?. International Journal of Innovation in Science and Mathematics Education (formerly CAL-laborate International), 19(2), 1-19.
    Ling, H. C., Hsiao, K. L., & Hsu, W. C. (2021). Can students’ computer programming learning motivation and effectiveness be enhanced by learning python language? a multi-group analysis. Frontiers in psychology, 11, 600814.
    Liu, C. C., Wu, L. Y., Chen, Z. M., Tsai, C. C., & Lin, H. M. (2014). The effect of story grammars on creative self‐efficacy and digital storytelling. Journal of Computer Assisted Learning, 30(5), 450-464.
    Liu, X., Cong, L., & Xu, J. (2022, December). The Influence of Problem Solving Based Practice on Pupils' Computational Thinking. In Proceedings of the 2022 5th International Conference on Education Technology Management (pp. 298-304).
    Lye, S. Y., & Koh, J. H. L. (2014). Review on teaching and learning of computational thinking through programming: What is next for K-12? Computers in Human Behavior, 41, 51-61.
    Moreno-León, J., Robles, G., & Román-González, M. (2015). Dr. Scratch: análisis automático de proyectos Scratch para evaluar y fomentar el pensamiento computacional. Revista de Educación a Distancia (RED), (46).
    Negrini, L., & Giang, C. (2019). How do pupils perceive educational robotics as a tool to improve their 21st century skills?. Journal of e-Learning and Knowledge Society, 15(ARTICLE), 77-87.
    Noh, J., & Lee, J. (2020). Effects of robotics programming on the computational thinking and creativity of elementary school students. Educational technology research and development, 68, 463-484.
    Ntourou, V., Kalogiannakis, M., & Psycharis, S. (2021). A study of the impact of Arduino and Visual Programming In self-efficacy, motivation, computational thinking and 5th grade students’ perceptions on Electricity. Eurasia Journal of Mathematics, Science and Technology Education, 17(5), em1960.
    Nugent, G., Barker, B., Lester, H., Grandgenett, N., & Valentine, D. (2019). Wearable textiles to support student STEM learning and attitudes. Journal of Science Education and Technology, 28, 470-479.
    Orton, K., Weintrop, D., Beheshti, E., Horn, M., Jona, K., & Wilensky, U. (2016). Bringing computational thinking into high school mathematics and science classrooms. Singapore: International Society of the Learning Sciences.
    Park, K. M., & Hong, T. J. (2009). A study on object-oriented programming education for improving logical thinking ability of elementary school students. Journal of Digital Contents Society, 10(2), 367-373.
    Ramalingam, V., & Wiedenbeck, S. (1998). Development and validation of scores on a computer programming self-efficacy scale and group analyses of novice programmer self-efficacy. Journal of Educational Computing Research, 19(4), 367-381.
    Resnick, M., Maloney, J., Monroy-Hernández, A., Rusk, N., Eastmond, E., Brennan, K., Silverman, B. (2009). Scratch: programming for all. Communications of the ACM, 52(11), 60-67.
    Román-González, M., Pérez-González, J. C., & Jiménez-Fernández, C. (2017). Which cognitive abilities underlie computational thinking? Criterion validity of the Computational Thinking Test. Computers in human behavior, 72, 678-691.
    Romero, M., Lepage, A., & Lille, B. (2017). Computational thinking development through creative programming in higher education. International Journal of Educational Technology in Higher Education, 14(1), 1-15.
    Sáez-López, J. M., Román-González, M., & Vázquez-Cano, E. (2016). Visual programming languages integrated across the curriculum in elementary school: A two year case study using “Scratch” in five schools. Computers & Education, 97, 129–141.
    Seiter, L., & Foreman, B. (2013, August). Modeling the learning progressions of computational thinking of primary grade students. In Proceedings of the ninth annual international ACM conference on International computing education research (pp. 59-66).
    Selby, C., & Woollard, J. (2013). Computational thinking: The developing definition.
    Souza, M., & Rodrigues, P. (2015). Investigating the effectiveness of the flipped classroom in an introductory programming course. The New Educational Review, 40(1), 129-139.
    Sternberg, R. J., & Williams, W. M. (1996). How to develop student creativity. ASCD.
    Su, Y. S., Shao, M., & Zhao, L. (2022). Effect of mind mapping on creative thinking of children in scratch visual programming education. Journal of Educational Computing Research, 60(4), 906-929.
    Sun, L., Hu, L., & Zhou, D. (2021). Improving 7th-graders’ computational thinking skills through unplugged programming activities: A study on the influence of multiple factors. Thinking skills and creativity, 42, 100926.
    Sutaphan, S., & Yuenyong, C. (2019, October). STEM education teaching approach: Inquiry from the context based. In Journal of Physics: Conference Series (Vol. 1340, No. 1, p. 012003). IOP Publishing.
    Tierney, P., & Farmer, S. M. (2002). Creative self-efficacy: Its potential antecedents and relationship to creative performance. Academy of Management journal, 45(6), 1137-1148.
    Torrance, E. P. (1974). Torrance tests of creative thinking. Scholastic Testing Service.
    Tsai, L. T., Chang, C. C., & Cheng, H. T. (2021). Effect of a STEM-Oriented Course on Students' Marine Science Motivation, Interest, and Achievements. Journal of Baltic Science Education, 20(1), 134-145.
    Tsai, M. J., Chien, F. P., Wen-Yu Lee, S., Hsu, C. Y., & Liang, J. C. (2022). Development and validation of the computational thinking test for elementary school students (CTT-ES): Correlate CT competency with CT disposition. Journal of Educational Computing Research, 60(5), 1110-1129.
    Tsai, M.-J., Liang, J.-C., Lee, S. W.-Y., & Hsu, C.-Y. (2021). Structural validation for the developmental model of computational thinking. Journal of Educational Computing Research, 1-18.
    Wang, C., Shen, J., & Chao, J. (2022). Integrating computational thinking in STEM education: A literature review. International Journal of Science and Mathematics Education, 20(8), 1949-1972.
    Weese, J. L. (2017). Bringing computational thinking to K12 and higher education (Dissertation). Kansas State University.
    Weintrop, D., Beheshti, E., Horn, M. S., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2014, April). Defining computational thinking for science, technology, engineering, and math. In Poster presented at the Annual Meeting of the American Educational Research Association (AERA 2014). Philadelphia. USA. Retrieved from http://ccl. northwestern. edu/2014/CT-STEM_AERA_2014. pdf.
    Werner, L., Denner, J., Campe, S., & Kawamoto, D. C. (2012, February). The fairy performance assessment: Measuring computational thinking in middle school. In Proceedings of the 43rd ACM technical symposium on Computer Science Education (pp. 215-220).
    Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35.
    Wing, J. M. (2008). Computational thinking and thinking about computing. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 366(1881), 3717-3725.
    Yildiz Durak, H. (2018). Digital story design activities used for teaching programming effect on learning of programming concepts, programming self‐efficacy, and participation and analysis of student experiences. Journal of Computer Assisted Learning, 34(6), 740-752.
    Yildiz Durak, H. (2020). The effects of using different tools in programming teaching of secondary school students on engagement, computational thinking and reflective thinking skills for problem solving. Technology, Knowledge and Learning, 25, 179-195.
    Zhang, L., & Nouri, J. (2019). A systematic review of learning computational thinking through Scratch in K-9. Computers & Education, 141, 103607.
    Zimmerman, B. J. (2000). Self-efficacy: An essential motive to learn. Contemporary educational psychology, 25(1), 82-91.

    下載圖示
    QR CODE