學術產出-學位論文
文章檢視/開啟
書目匯出
-
題名 具虛擬互動之線上討論環境輔以拼圖法合作學習對於國小學生程式設計學習成效之影響研究
Effects of Jigsaw Collaborative Method with the Support of an Online Virtual-interaction Discussion Environment on Primary School Student’s Programming Learning Performance作者 黃銘彥
Huang, Ming-Yan貢獻者 陳志銘
Chen, Chih-Ming
黃銘彥
Huang, Ming-Yan關鍵詞 運算思維
程式設計學習
虛擬教室
合作拼圖法
傳統教師講述法
COVID-19疫情
線上學習
學習成效
學習態度
Computational thinking
Programming learning
Virtual classroom
Jigsaw collaborative method
Traditional teacher lecture
COVID-19 epidemic
Online learning
Learning performance
Learning attitudes日期 2022 上傳時間 1-八月-2022 19:05:33 (UTC+8) 摘要 運算思維（Computational Thinking, CT）被視為是一種可以廣泛應用於日常生活情境輔以培養批判性思考，以及解決複雜問題的能力。因此，許多學者將其視為國家教育發展的重要領域，並透過Scratch等積木式的程式設計課程來教授國小學童運算思維。而當前國小的程式設計課程中，課程設計多採傳統教師講述法，導致部分學生會產生過度依賴教師協助的現象，不僅無法達成促進運算思維能力的教學目標，也造成教師教學的負擔與降低教師的教學成就感。此外，自2020年COVID-19疫情爆發以來，線上學習成為學生在疫情期間接受教育的最重要管道，使得如何善用各式可用以輔助線上學習的平台成為重要的課題。因此，本研究使用「Gather Town虛擬教室輔以拼圖法」輔助國小學童進行Scratch程式設計學習，期望能改善傳統教師講述法之缺點，並且克服疫情造成的學習限制，進而促進學習者的Scratch程式設計學習成效、運算思維，以及學習態度。本研究採用準實驗研究法，以新北市某公立國小五年級兩個班級共48名學生為研究對象，將兩個班級隨機分派為實驗組與控制組，進行Scratch程式設計學習。其中一班24名學生被分派為使用「Gather Town虛擬教室輔以拼圖法」的實驗組；另一班24名學生被分派為使用傳統教師講述法的控制組，以探討使用「Gather Town虛擬教室輔以拼圖法」進行Scratch程式設計學習，在學習成效、運算思維，以及學習態度上是否顯著優於傳統教師講述法。此外，也透過半結構深度訪談探討兩組學習者的學習經驗與感受。研究結果發現，採用「Gather Town虛擬教室輔以拼圖法」進行Scratch程式設計學習的實驗組學習者，在學習成效與學習態度上均顯著優於採用傳統教師講述法。在運算思維上，則兩組學習者沒有達到統計上的顯著差異，但採用這兩種學習模式進行Scratch程式設計學習，皆能有效促進運算思維能力的提升。此外，訪談資料分析結果顯示，使用「Gather Town虛擬教室輔以拼圖法」進行Scratch程式設計學習，能克服COVID-19疫情的限制，達成良好的合作學習成效，並且能有效提升學習者的學習興趣。最後基於研究結果，本研究提出應用「Gather Town虛擬教室輔以拼圖法」於教學場域的教學建議，以及未來可以進一步探討的研究方向。整體而言，本研究結合Gather Town虛擬教室與拼圖法合作學習，提供一個Scratch程式設計學習之創新有效學習模式，對於促進Scratch程式設計學習具有貢獻。
Computational thinking (CT) has been considered as an important learning literacy that can be used in learning activity in a wide range of daily life contexts to develop critical thinking and complex problem-solving skills. Therefore, many scholars emphasize its importance to the development of education, and teach primary school students’ computational thinking through block-based coding languages such as Scratch. In the current primary school coding courses, the curriculum was frequently designed by using the traditional teacher lecture in a face-to-face way at a physical classroom, leading to some students relying too much on teacher’s assistance, which not only fails to achieve the teaching goal of promoting computational thinking skills, but also creates a burden on the teacher’s teaching and reduces the teacher’s sense of accomplishment. In addition, since the pandemic of COVID-19 happen since 2020, online learning has become the most important way for students to receive education during the period of epidemic spreading, how to make the best consideration use of the various learning platforms available for online learning is an important issue. Therefore, this study presents a Jigsaw collaborative method with the support of Gather Town virtual classroom to assist Scratch coding learning for primary school’s students, hoping to improve the shortcomings of the traditional teacher lecture and overcome the learning limitations caused by the epidemic, so as to promote the learning performance, computational thinking, and learning attitudes of the learners toward Scratch programming learning.With a quasi-experimental research method, a total of 48 G5 students who were recruited from two classes of a public primary school in New Taipei City were selected as the research participants and randomly assigned to the experimental group and control group with different learning methods to learn Scratch coding skills. Among them, 24 students from one class were randomly assigned to the experimental group using the proposed Jigsaw collaborative method with the support of Gather Town virtual classroom to assist Scratch coding learning, while the remaining class with 24 students was assigned to the control group using the traditional teacher lecture to assist Scratch coding learning. This study examined whether the use of the Jigsaw collaborative method with the support of Gather Town virtual classroom to assist Scratch coding learning is significantly better than the traditional teacher lecture in terms of learning performance, computational thinking, and learning attitudes.Analytical results show that the learners in the experimental group using the Jigsaw collaborative method with the support of Gather Town virtual classroom to assist Scratch coding learning had significantly better learning performance and learning attitudes than the control group using the traditional teacher lecture. However, there is no statistically significant difference in computational thinking, but the use of these two learning modes for Scratch coding learning are effective in promoting computational thinking skills. In addition, the analysis of the interview data shows that the use of the Jigsaw collaborative method with the support of Gather Town virtual classroom to assist Scratch coding learning could overcome the limitations of the COVID-19 epidemic, achieve good collaborative learning performance, and is effective in promoting learners’ learning interests.Based on the research results of this study, this research proposes several teaching suggestions for applying Jigsaw collaborative method with the support of Gather Town virtual classroom in the coding teaching field, and draws several valuable research directions for further investigation. In conclusion, this study successfully combines the Gather Town virtual classroom and Jigsaw collaborative method to propose an innovative and effective learning model for Scratch coding learning, which can contribute to the promotion of coding learning.參考文獻 一、中文文獻王文科（譯）（1991）。學習心理學：學習理論導論。台北市：五南。何政賢（2016）。不同學習模式對國中生學習Scratch程式計之問題解決能力、學習動機興趣及學習成效之影響（未出版之碩士論文）。國立臺灣海洋大學教育研究所。呂沂蓁（2020）。以小組合作學習進行Scratch程式設計對國中生運算思維的影響（未出版之碩士論文）。國立台中教育大學數位內容科技學系。李佳恩（2015）。合作學習對國中七年级生學習Scratch程式設計的學習態度與成效之影響（未出版之碩士論文）。國立臺南大學數位學習科技學系。張文奇（2009）。視覺化程式設計對國小兒童高層次思考能力之影響（未出版之碩士論文）。臺北市立教育大學自然科學教學碩士班。教育部（2018）。十二年國民基本教育課程綱要。台北市：教育部。廖振凱（2020）。發展「合作共筆視覺化互動網絡分析系統」促進線上合作編輯成效（未出版之碩士論文）。國立政治大學圖書資訊與檔案學研究所。二、英文文獻Alvarez, A. & Scott, T.A. (2010). Using student surveys in determining the difficulty of programming assignments. Journal of Computing Sciences in Colleges, 26(2), 157-163.Anderson, N. D. (2016). A call for computational thinking in undergraduate psychology. Psychology Learning & Teaching, 15, 226-234. doi:10.1177/1475725716659252Angeli, 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. Educational Technology & Society, 19(3), 47-58.Balanskat, A., & Engelhardt, K. (2015). Computing our future. Computer programming and coding.Priorities, school curricula and iniciatives across Europe. Brussels, Belgium.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, 48-54. doi:10.1145/1929887.1929905Basogain, X., Olabe, M.A., ´ Olabe, J. C., & Rico, M. J. (2018). Computational thinking in pre-university blended learning classrooms. Computers in Human Behavior, 80, 412-419. https://doi.org/10.1016/j.chb.2017.04.058Benakli, N., Kostadinov, B., Satyanarayana, A., & Singh, S. (2017). Introducing computational thinking through hands-on projects using R with applications to calculus, probability and data analysis. International Journal of Mathematical Education in Science and Technology, 48(3), 393-427.Bers, M. I., Flannery, L., Kazakoff, E. R., & Sullivan, A. (2014). Computational thinking and tinkering: Exploration of an early childhood robotics curriculum. Computers & Education, 72, 145-157.Bravo, C., Marcelino, M. J., Gomes, A., Esteves, M., & Mendes, A. J. (2005). Integrating educational tools for collaborative computer programming learning. Journal of Universal Computer Science, 11(9), 1505-1517.Brennan, K., & Resnick, M. (2012). Using artifact-based interviews to study the development of computational thinking in interactive media design. American Educational Research Association Meeting. Vancouver, BC: Canada. http://web.media.mit.edu/~kbrennan/files/Brennan_Resnick_ AERA2012_CT.pdf.Brinda, T., Puhlmann, H., & Schulte, C. (2009). Bridging ICT and CS: Educational standards for computer science in lower secondary education. ACM SIGCSE Bulletin, 41, 288-292. https://doi.org/10.1145/1562877.1562965.Brown, N. C. C., Kölling, M., Crick, T., Peyton Jones, S., Humphreys, S. & Sentance, S. (2013). Bringing computer science back into schools: Lessons from the UK. In Proceedings of the 44th ACM Technical Symposium on Computer Science Education, 269-274. https://doi.org/10.1145/2445196.2445277.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.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.Chiu, M. M. (2008). Flowing toward correct contributions during groups’ mathematics problem solving: a statistical discourse analysis. Journal of the Learning Sciences, 17(3), 415-463.Cohen, E. G. (1994). Restructuring the classroom: Conditions for productive small groups. Review of Educational Research, 64, 1-35.Colosi, J. C., & C. R. Zales. (1998). Jigsaw cooperative learning improves biology lab course. Bioscience, 48(2), 118-124.Cooper, S., Dann, W., & Pausch, R. (2003). Using animated 3D graphics to prepare novices for CSI. Computer Science Education, 13, 3-30.Denning, P. J. (2017). Remaining trouble spots with computational thinking. Communications of the ACM, 60(6), 33-39.Ebel, R.L.,& Frisbie, D.A.(1991). Essentials of educational measurement.（5th ed.）. Englewood Cliffs, NJ: Prentice-Hall.de la Hera, D., Zanoni, M., Sigman, M. & Calero, C. (2022). Peer tutoring of computer programming increases exploratory behavior in children. Journal of Experimental Child Psychology, 216. doi:10.1016/j.jecp.2021.105335.Ellia, A. K.（2007）. Teaching and learning elementary social studies（8th ed.）. Boston, MA :Pearson Allyn and Bacon.Evia, C., Sharp, M. R., & Pérez-Quiñones, M. A. (2015). Teaching structured authoring and DITA through rhetorical and computational thinking. IEEE Transactions on Professional Communication, 58(3), 328-343.Falkner, K., Vivian, R., & Falkner, N. (2014, January). The Australian digital technologies curriculum: Challenge and opportunity. Conferences in Research and Practice in Information Technology Series, 148, 3-12.Fedorenko, E., Ivanova, A., Dhamala, R., & Bers, M. U. (2019). The language of programming: A cognitive perspective. Trends in Cognitive Sciences, 23, 525-528.Fessakis, G., Gouli, E., & Mavroudi, E. (2013). Problem solving by 5-6 years old kindergarten children in a computer programming environment: A case study. Computers & Education, 63, 87-97.Gagné, R. M., Briggs, L. J., & Wager, W. W. (1988). Principles of instructional design. New York : Holt, Rinehart & Winston.Gandy, L., Bradley, S., Brookes D. A.& Allen, N. (2010). The use of LEGO Minstroms NXT Robots in the Teaching of Introductory Java Programming to Undergraduate Students. ITALICS, 9(1), 1-9.Garcia, M.B. Cooperative learning in computer programming: A quasi-experimental evaluation of Jigsaw teaching strategy with novice programmers. Education and Information Technologies, 26, 4839-4856. https://doi.org/10.1007/s10639-021-10502-6Grout, V., & Houlden, N. (2014). Taking computer science and programming into schools: The Glyndwˆ r/BCS Turing Project. Procedia - Social and Behavioral Sciences, 141(25), 680-685Grover, S., & Pea, R. (2013). Computational thinking in K-12 a review of the state of the field. Educational Researcher, 42(1), 38-43.Grover, S., Pea, R., & Cooper, S. (2015). Designing for deeper learning in a blended computer science course for middle school students. Computer Science Education, 25(2), 199-237.Gull, F., & Shehzad, S. (2015). Effects of cooperative learning on students’ academic achievement. Journal of Education and Learning, 9(3), 246-25.Hanks, B. (2008). Empirical evaluation of distributed pair programming. International Journal of Human-Computer Studies, 66(7), 530-544. https://doi.org/10.1016/j. ijhcs.2007.10.003Heintz, F., Mannila, L., & Färnqvist, T. (2016). A review of models for introducing computational thinking, computer science and computing in K-12 education. 2016 IEEE Frontiers in Education Conference (FIE), 1-9.Hergenhahn, B. R. (1982). An introduction to theories of learning (2nd ed.). Upper Saddle River, N.J.: Pearson/Prentice Hall.Howland, K, & Good,J. (2015). Learning to communicate computationally with flip: A bi-modal programming language for game creation. Computers & Education, 80, 224-240.Hsu, T.C., Chang, S.C. & Hung, Y.T. (2018). How to learn and how to teach computational thinking: Suggestions based on a review of the literature. Computers & Education, 126(1), 296-310.Hwang, W. Y., Wang, C. Y., Hwang, G. J., Huang, Y. M., & Huang, S. (2008). A web-based programming learning environment to support cognitive development. Interacting with Computers, 20, 524-534.Iskrenovic-Momcilovic, O. (2019). Pair programming with scratch. Education and Information Technologies, 24, 2943-2952. https://doi.org/10.1007/s10639-019-09905-3Sáez-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. doi:10.1016/j.compedu.2016.03.003Johnson, D. W., & Johnson, R. (1989). Cooperation and Competition: Theory and Research. Edina, MN: Interaction Book Company.Johnson, D. W., & Johnson, R. T. (1994). Learning together and alone: cooperative, competitive, and individualistic learning (4th ed.). Boston: Allyn and Bacon.Johnson, D. W., & Johnson, R. T. (2009). An educational psychology success story: Social interdependence theory and cooperative learning. Educational Researcher, 38, 365-379.Johnson, D., Johnson, R., & Stanne, M. (2000). Cooperative learning methods: A meta-analysis. University of Minnesota.Kaleliog˘lu, F. (2015). A new way of teaching programming skills to K-12 students: Code.org. Computers in Human Behavior, 52, 200-210.Kerr, N. L., & Bruun, S. E. (1983). Dispensability of member effort and group motivation losses: Free rider effects. Journal of Personality and Social Psychology, 44, 78-94.Kordaki, M. (2012). Diverse Categories of Programming Learning Activities could be Performed within Scratch. Procedia - Social and Behavioral Sciences, 46, 1162-1166.Lee, I., Martin, F., & Apone, K. (2014). Integrating computational thinking across the K-8 curriculum. ACM Inroad, 5(4), 64-71.Leiva, F. A. J., & Salas, C. A. C. (2013). Practices of advanced programming: Tradition versus innovation. Comput. Appl. Eng. Educ., 21, 237-244.https://doi.org/10.1002/cae.20465Lye, 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.Malan, D. J., & Leitner, H. H. (2007). Scratch for budding computer scientists. SIGCSE Bulletin, 39(1), 223-227.Maloney, J., Resnick, M., & Rusk, N. (2010). The Scratch programming language and environment. ACM Transactions on Computing Education, 10, 1-15.McDowell, C., Werner, L., Bullock, H., & Fernald, J. (2002). The effects of pair programming on performance in an introductory programming course. Proceedings of the 33rd SIGCSE technical symposium on computer science education. ACM SIGCSE Bulletin, 34(1), 38-42.National Research Council. (2010). Committee for the Workshops on Computational Thinking: Report of a workshop on the scope and nature of computational thinking. Washington, D.C: National Academies Press.Nijhot, W. & Kommers, P. (1985). An analysis of cooperation in relation to cognitive controversy. In R. Slavin et al. (Eds). Learning to cooperating to learn, 125-146.Nikou, S. A., & Economides, A. A. (2014). Transition in student motivation during a scratch and an app inventor course. 2014 IEEE Global Engineering Education Conference, 1042-1045.O’Reilly, D. (1998). School programming as literacy: The case for BOXER. Journal of Computer Assisted Learning, 14(1), 51-58.P´erez-Marín, D., Hijon-Neira, ´ R., Bacelo, A., & Pizarro, C. (2020). Can computational thinking be improved by using a methodology based on metaphors and scratch to teach computer programming to children? Computers in Human Behavior, 105, 105849.Papert, S. (1980). Mindstorms: Children, computer, and powerful ideas. New York: Basic Books.Papert, S. (1990). Epistemology and learning memo No. 2 . Cambridge MA: MIT.Artut, P. D., & Tarim, K. (2007). The effectiveness of jigsaw II on prospective elementary school teachers. Asia‐Pacific Journal of Teacher Education, 35(2), 129-141. doi : 10.1080/13598660701268551Perkins, D.V., & Saris, R.N. (2001). A “Jigsaw classroom” technique for undergraduate statistics courses. Teaching of Psychology, 28(2), 111-113.Levin, P. (2003). Running group projects: dealing with the free-rider problem. Planet, 9(1), 7-8. doi: 10.11120/plan.2003.00090007Piteira, M. & Costa, C. (2013). Learning computer programming: Study of difficulties in learning programming. 2013 International Conference on Information Systems and Design of Communication, 75-80. https://doi.org/10.1145/2503859.2503871Repenning, A. (2012). Programming goes back to school. Communications of the ACM, 55(5), 38-40.Resnick, M., Maloney, J., Monroy-Hernandez, A., Rusk, N., Eastmond, E., Brennan, K., et al. (2009). Scratch: Programming for all. Communications of the ACM, 52(11), 60-67.Rizvi, M., Humphries, T., Major, D., Jones, M., & Lauzun, H. (2011). A CSO course using scratch. Journal of Computing Sciences in Colleges, 26(3), 19-27.Robins, A., Rountree, J., & Rountree, N. (2003). Learning and teaching programming: A review and discussion. Computer Science Education, 13(2), 137-172.Rubinstein, A., & Chor, B. (2014). Computational thinking in life science education. PLoS Computational Biology, 10(11), e1003897.https://doi.org/10.1371/journal.pcbi.1003897Scherer, R. (2016). Learning from the past—The need for empirical evidence on the transfer effects of computer programming skills. Frontiers in Psychology, 7. https://doi.org/10.3389/fpsyg.2016.01390.Scherer, R., Siddiq, F., & Sánchez Viveros, B. (2019). The cognitive benefits of learning computer programming: A meta-analysis of transfer effects. Journal of Educational Psychology, 111, 764-792.Sharan, S. (1980). Cooperative learning in small groups: Recent methods and effects on achievement, attitudes, and ethnic relations. Review of Educational Research, 50(2), 241-271.Shen, H., Sun, C. (2000). RECIPE: a prototype for Internet-based real-time collaborative programming. 2nd International Workshop on Collaborative Editing Systems , 3-4.Slavin , R. E.( 1985 ) .Cooperative learning : Applying contact theory in desegregated schools. Joural of Social Issues, 43-62.Slavin, R. E. (1991). Synthesis of research on cooperative learning. Educational Leadership, 48, 71-82.Slavin, R. E. (1995). Cooperative learning: Theory, research, and practice. Boston: Allyn and Bacon.Snodgrass, M. R., Israel, M., & Reese, G. C. (2016). Instructional supports for students with disabilities in K-5 computing: Findings from a cross-case analysis. Computers & Education, 100, 1-17.Soloway, E. (1986). Learn to program = Learning to construct mechanisms and explanations. Comunications of the ACM, 28(9), 850-858.Nur Fitria, T. (2021). Creating sensation of learning in classroom: Using ’Gather Town’ platform video game-style for virtual classroom. Education and Human Development Journal, 6(2), 30-43. https://doi.org/10.33086/ehdj.v6i2.2106Tu, J. (2022). Meetings in the Metaverse: Exploring Online Meeting Spaces through Meaningful Interactions in Gather.Town [Unpublished master’s thesis]. University of Waterloo.Tucker, A., Deek, F., Jones, J., McCowan, D., Stephenson, C., & Verno, A. (2003). A Model Curriculum for K-12 Computer Science: Final Report of the ACM K-12 Task Force Curriculum Committee. The Association for Computing Machinery, New York.Voogt, J., Fisser, P., Good, J., Mishra, P., & Yadav, A. (2015). Computational thinking in compulsory education: Towards an agenda for research and practice. Education and Information Technologies, 20, 715-728.Walker, I., & Crogan, M. (1998). Academic performance, prejudice, and the jigsaw classroom: new pieces to the puzzle. Journal of Community & Applied Social Psychology, 8(6), 381-393.Webb, M., Davis, N., Bell, T., Katz, Y. J., Reynolds, N., Chambers, D. P., et al. (2017). Computer science in K-12 school curricula of the 2lst century: Why, what and when? Education and Information Technologies, 22(2), 445-468.Webb, N. M., Nemer, K. M., & Ing, M. (2006). Small-group reflections: parallels between teacher discourse and student behavior in peer-directed groups. The Journal of the Learning Sciences, 15(1), 63-119.Westcott, S. (2008). Effectiveness of using digital game playing in a first-level programming course [Unpublished doctoral dissertation]. USA: Pace University.Wijnstra, J. (2021). Making Great Onlin eSpaces: The influence of the online platform of GatherTown on the creativity of the students at the University of Groningen [Unpublished master’s thesis]. University of Groningen.Wing, J.M. (2006). Computational Thinking. Communications of the ACM, 49, 33-35.https://doi.org/10.1145/1118178.1118215Wing, J. M. (2008). Computational thinking and thinking about computing. Philosophical transactions of the royal society of London a: Mathematical, Physical and Engineering Sciences, 366, 3717-3725.Wolz, U., Leitner, H. H., Malan, D. J., & Maloney, J. (2009). Starting with scratch in CS1. SIGCSE Bulletin, 41, 2-3.Yu, A.T.W. (2017). Using jigsaw method to enhance the learning of research and consultancy techniques for postgraduate students. Engineering, Construction and Architectural Management, 24(6), 1081-1091. https://doi.org/10.1108/ECAM-03-2016-0080Zhong, B., Wang, Q., Chen, J., & Li, Y. (2016). An exploration of three-dimensional integrated assessment for computational thinking. Journal of Educational Computing Research, 53(4), 562-590. 描述 碩士
國立政治大學
圖書資訊學數位碩士在職專班
109913009資料來源 http://thesis.lib.nccu.edu.tw/record/#G0109913009 資料類型 thesis dc.contributor.advisor 陳志銘 zh_TW dc.contributor.advisor Chen, Chih-Ming en_US dc.contributor.author (作者) 黃銘彥 zh_TW dc.contributor.author (作者) Huang, Ming-Yan en_US dc.creator (作者) 黃銘彥 zh_TW dc.creator (作者) Huang, Ming-Yan en_US dc.date (日期) 2022 en_US dc.date.accessioned 1-八月-2022 19:05:33 (UTC+8) - dc.date.available 1-八月-2022 19:05:33 (UTC+8) - dc.date.issued (上傳時間) 1-八月-2022 19:05:33 (UTC+8) - dc.identifier (其他 識別碼) G0109913009 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/141416 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 圖書資訊學數位碩士在職專班 zh_TW dc.description (描述) 109913009 zh_TW dc.description.abstract (摘要) 運算思維（Computational Thinking, CT）被視為是一種可以廣泛應用於日常生活情境輔以培養批判性思考，以及解決複雜問題的能力。因此，許多學者將其視為國家教育發展的重要領域，並透過Scratch等積木式的程式設計課程來教授國小學童運算思維。而當前國小的程式設計課程中，課程設計多採傳統教師講述法，導致部分學生會產生過度依賴教師協助的現象，不僅無法達成促進運算思維能力的教學目標，也造成教師教學的負擔與降低教師的教學成就感。此外，自2020年COVID-19疫情爆發以來，線上學習成為學生在疫情期間接受教育的最重要管道，使得如何善用各式可用以輔助線上學習的平台成為重要的課題。因此，本研究使用「Gather Town虛擬教室輔以拼圖法」輔助國小學童進行Scratch程式設計學習，期望能改善傳統教師講述法之缺點，並且克服疫情造成的學習限制，進而促進學習者的Scratch程式設計學習成效、運算思維，以及學習態度。本研究採用準實驗研究法，以新北市某公立國小五年級兩個班級共48名學生為研究對象，將兩個班級隨機分派為實驗組與控制組，進行Scratch程式設計學習。其中一班24名學生被分派為使用「Gather Town虛擬教室輔以拼圖法」的實驗組；另一班24名學生被分派為使用傳統教師講述法的控制組，以探討使用「Gather Town虛擬教室輔以拼圖法」進行Scratch程式設計學習，在學習成效、運算思維，以及學習態度上是否顯著優於傳統教師講述法。此外，也透過半結構深度訪談探討兩組學習者的學習經驗與感受。研究結果發現，採用「Gather Town虛擬教室輔以拼圖法」進行Scratch程式設計學習的實驗組學習者，在學習成效與學習態度上均顯著優於採用傳統教師講述法。在運算思維上，則兩組學習者沒有達到統計上的顯著差異，但採用這兩種學習模式進行Scratch程式設計學習，皆能有效促進運算思維能力的提升。此外，訪談資料分析結果顯示，使用「Gather Town虛擬教室輔以拼圖法」進行Scratch程式設計學習，能克服COVID-19疫情的限制，達成良好的合作學習成效，並且能有效提升學習者的學習興趣。最後基於研究結果，本研究提出應用「Gather Town虛擬教室輔以拼圖法」於教學場域的教學建議，以及未來可以進一步探討的研究方向。整體而言，本研究結合Gather Town虛擬教室與拼圖法合作學習，提供一個Scratch程式設計學習之創新有效學習模式，對於促進Scratch程式設計學習具有貢獻。 zh_TW dc.description.abstract (摘要) Computational thinking (CT) has been considered as an important learning literacy that can be used in learning activity in a wide range of daily life contexts to develop critical thinking and complex problem-solving skills. Therefore, many scholars emphasize its importance to the development of education, and teach primary school students’ computational thinking through block-based coding languages such as Scratch. In the current primary school coding courses, the curriculum was frequently designed by using the traditional teacher lecture in a face-to-face way at a physical classroom, leading to some students relying too much on teacher’s assistance, which not only fails to achieve the teaching goal of promoting computational thinking skills, but also creates a burden on the teacher’s teaching and reduces the teacher’s sense of accomplishment. In addition, since the pandemic of COVID-19 happen since 2020, online learning has become the most important way for students to receive education during the period of epidemic spreading, how to make the best consideration use of the various learning platforms available for online learning is an important issue. Therefore, this study presents a Jigsaw collaborative method with the support of Gather Town virtual classroom to assist Scratch coding learning for primary school’s students, hoping to improve the shortcomings of the traditional teacher lecture and overcome the learning limitations caused by the epidemic, so as to promote the learning performance, computational thinking, and learning attitudes of the learners toward Scratch programming learning.With a quasi-experimental research method, a total of 48 G5 students who were recruited from two classes of a public primary school in New Taipei City were selected as the research participants and randomly assigned to the experimental group and control group with different learning methods to learn Scratch coding skills. Among them, 24 students from one class were randomly assigned to the experimental group using the proposed Jigsaw collaborative method with the support of Gather Town virtual classroom to assist Scratch coding learning, while the remaining class with 24 students was assigned to the control group using the traditional teacher lecture to assist Scratch coding learning. This study examined whether the use of the Jigsaw collaborative method with the support of Gather Town virtual classroom to assist Scratch coding learning is significantly better than the traditional teacher lecture in terms of learning performance, computational thinking, and learning attitudes.Analytical results show that the learners in the experimental group using the Jigsaw collaborative method with the support of Gather Town virtual classroom to assist Scratch coding learning had significantly better learning performance and learning attitudes than the control group using the traditional teacher lecture. However, there is no statistically significant difference in computational thinking, but the use of these two learning modes for Scratch coding learning are effective in promoting computational thinking skills. In addition, the analysis of the interview data shows that the use of the Jigsaw collaborative method with the support of Gather Town virtual classroom to assist Scratch coding learning could overcome the limitations of the COVID-19 epidemic, achieve good collaborative learning performance, and is effective in promoting learners’ learning interests.Based on the research results of this study, this research proposes several teaching suggestions for applying Jigsaw collaborative method with the support of Gather Town virtual classroom in the coding teaching field, and draws several valuable research directions for further investigation. In conclusion, this study successfully combines the Gather Town virtual classroom and Jigsaw collaborative method to propose an innovative and effective learning model for Scratch coding learning, which can contribute to the promotion of coding learning. en_US dc.description.tableofcontents 第一章 緒論 1第一節 研究背景與動機 1第二節 研究目的 4第三節 研究問題 5第四節 研究範圍與限制 6第五節 重要名詞解釋 6第二章 文獻探討 9第一節 程式設計學習 9第二節 運算思維 13第三節 合作學習 17第三章 研究設計與實施 22第一節 研究架構 22第二節 研究方法 24第三節 研究對象 26第四節 實驗設計與流程 26第五節 研究工具 32第六節 資料處理與分析 39第七節 研究實施步驟 41第四章 實驗結果分析 43第一節 兩組學習者Scratch程式設計學習成效差異分析 44第二節 兩組學習者運算思維之差異分析 46第三節 兩組學習者學習態度之差異分析 50第四節 訪談質性資料分析 53第五節 綜合討論 60第五章 結論與建議 63第一節 結論 63第二節 教學建議 66第三節 未來研究方向 68參考文獻 70附錄一 Scratch學習成效測驗第一次預試題目 78附錄二 Scratch學習成效測驗 83附錄三 Scratch學習成效測驗第一次預試 84附錄四 Scratch學習成效測驗第二次預試題目 85附錄五 Scratch學習成效測驗 90附錄六 Scratch學習成效測驗第二次預試 91附錄七 運算思維測驗 92附錄八 Scratch學習態度問卷 108附錄九 訪談大綱 110 zh_TW dc.format.extent 6588743 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0109913009 en_US dc.subject (關鍵詞) 運算思維 zh_TW dc.subject (關鍵詞) 程式設計學習 zh_TW dc.subject (關鍵詞) 虛擬教室 zh_TW dc.subject (關鍵詞) 合作拼圖法 zh_TW dc.subject (關鍵詞) 傳統教師講述法 zh_TW dc.subject (關鍵詞) COVID-19疫情 zh_TW dc.subject (關鍵詞) 線上學習 zh_TW dc.subject (關鍵詞) 學習成效 zh_TW dc.subject (關鍵詞) 學習態度 zh_TW dc.subject (關鍵詞) Computational thinking en_US dc.subject (關鍵詞) Programming learning en_US dc.subject (關鍵詞) Virtual classroom en_US dc.subject (關鍵詞) Jigsaw collaborative method en_US dc.subject (關鍵詞) Traditional teacher lecture en_US dc.subject (關鍵詞) COVID-19 epidemic en_US dc.subject (關鍵詞) Online learning en_US dc.subject (關鍵詞) Learning performance en_US dc.subject (關鍵詞) Learning attitudes en_US dc.title (題名) 具虛擬互動之線上討論環境輔以拼圖法合作學習對於國小學生程式設計學習成效之影響研究 zh_TW dc.title (題名) Effects of Jigsaw Collaborative Method with the Support of an Online Virtual-interaction Discussion Environment on Primary School Student’s Programming Learning Performance en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 一、中文文獻王文科（譯）（1991）。學習心理學：學習理論導論。台北市：五南。何政賢（2016）。不同學習模式對國中生學習Scratch程式計之問題解決能力、學習動機興趣及學習成效之影響（未出版之碩士論文）。國立臺灣海洋大學教育研究所。呂沂蓁（2020）。以小組合作學習進行Scratch程式設計對國中生運算思維的影響（未出版之碩士論文）。國立台中教育大學數位內容科技學系。李佳恩（2015）。合作學習對國中七年级生學習Scratch程式設計的學習態度與成效之影響（未出版之碩士論文）。國立臺南大學數位學習科技學系。張文奇（2009）。視覺化程式設計對國小兒童高層次思考能力之影響（未出版之碩士論文）。臺北市立教育大學自然科學教學碩士班。教育部（2018）。十二年國民基本教育課程綱要。台北市：教育部。廖振凱（2020）。發展「合作共筆視覺化互動網絡分析系統」促進線上合作編輯成效（未出版之碩士論文）。國立政治大學圖書資訊與檔案學研究所。二、英文文獻Alvarez, A. & Scott, T.A. (2010). Using student surveys in determining the difficulty of programming assignments. Journal of Computing Sciences in Colleges, 26(2), 157-163.Anderson, N. D. (2016). A call for computational thinking in undergraduate psychology. Psychology Learning & Teaching, 15, 226-234. doi:10.1177/1475725716659252Angeli, 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. Educational Technology & Society, 19(3), 47-58.Balanskat, A., & Engelhardt, K. (2015). Computing our future. Computer programming and coding.Priorities, school curricula and iniciatives across Europe. Brussels, Belgium.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, 48-54. doi:10.1145/1929887.1929905Basogain, X., Olabe, M.A., ´ Olabe, J. C., & Rico, M. J. (2018). Computational thinking in pre-university blended learning classrooms. Computers in Human Behavior, 80, 412-419. https://doi.org/10.1016/j.chb.2017.04.058Benakli, N., Kostadinov, B., Satyanarayana, A., & Singh, S. (2017). Introducing computational thinking through hands-on projects using R with applications to calculus, probability and data analysis. International Journal of Mathematical Education in Science and Technology, 48(3), 393-427.Bers, M. I., Flannery, L., Kazakoff, E. R., & Sullivan, A. (2014). Computational thinking and tinkering: Exploration of an early childhood robotics curriculum. Computers & Education, 72, 145-157.Bravo, C., Marcelino, M. J., Gomes, A., Esteves, M., & Mendes, A. J. (2005). Integrating educational tools for collaborative computer programming learning. Journal of Universal Computer Science, 11(9), 1505-1517.Brennan, K., & Resnick, M. (2012). Using artifact-based interviews to study the development of computational thinking in interactive media design. American Educational Research Association Meeting. Vancouver, BC: Canada. http://web.media.mit.edu/~kbrennan/files/Brennan_Resnick_ AERA2012_CT.pdf.Brinda, T., Puhlmann, H., & Schulte, C. (2009). Bridging ICT and CS: Educational standards for computer science in lower secondary education. ACM SIGCSE Bulletin, 41, 288-292. https://doi.org/10.1145/1562877.1562965.Brown, N. C. C., Kölling, M., Crick, T., Peyton Jones, S., Humphreys, S. & Sentance, S. (2013). Bringing computer science back into schools: Lessons from the UK. In Proceedings of the 44th ACM Technical Symposium on Computer Science Education, 269-274. https://doi.org/10.1145/2445196.2445277.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.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.Chiu, M. M. (2008). Flowing toward correct contributions during groups’ mathematics problem solving: a statistical discourse analysis. Journal of the Learning Sciences, 17(3), 415-463.Cohen, E. G. (1994). Restructuring the classroom: Conditions for productive small groups. Review of Educational Research, 64, 1-35.Colosi, J. C., & C. R. Zales. (1998). Jigsaw cooperative learning improves biology lab course. Bioscience, 48(2), 118-124.Cooper, S., Dann, W., & Pausch, R. (2003). Using animated 3D graphics to prepare novices for CSI. Computer Science Education, 13, 3-30.Denning, P. J. (2017). Remaining trouble spots with computational thinking. Communications of the ACM, 60(6), 33-39.Ebel, R.L.,& Frisbie, D.A.(1991). Essentials of educational measurement.（5th ed.）. Englewood Cliffs, NJ: Prentice-Hall.de la Hera, D., Zanoni, M., Sigman, M. & Calero, C. (2022). Peer tutoring of computer programming increases exploratory behavior in children. Journal of Experimental Child Psychology, 216. doi:10.1016/j.jecp.2021.105335.Ellia, A. K.（2007）. Teaching and learning elementary social studies（8th ed.）. Boston, MA :Pearson Allyn and Bacon.Evia, C., Sharp, M. R., & Pérez-Quiñones, M. A. (2015). Teaching structured authoring and DITA through rhetorical and computational thinking. IEEE Transactions on Professional Communication, 58(3), 328-343.Falkner, K., Vivian, R., & Falkner, N. (2014, January). The Australian digital technologies curriculum: Challenge and opportunity. Conferences in Research and Practice in Information Technology Series, 148, 3-12.Fedorenko, E., Ivanova, A., Dhamala, R., & Bers, M. U. (2019). The language of programming: A cognitive perspective. Trends in Cognitive Sciences, 23, 525-528.Fessakis, G., Gouli, E., & Mavroudi, E. (2013). Problem solving by 5-6 years old kindergarten children in a computer programming environment: A case study. Computers & Education, 63, 87-97.Gagné, R. M., Briggs, L. J., & Wager, W. W. (1988). Principles of instructional design. New York : Holt, Rinehart & Winston.Gandy, L., Bradley, S., Brookes D. A.& Allen, N. (2010). The use of LEGO Minstroms NXT Robots in the Teaching of Introductory Java Programming to Undergraduate Students. ITALICS, 9(1), 1-9.Garcia, M.B. Cooperative learning in computer programming: A quasi-experimental evaluation of Jigsaw teaching strategy with novice programmers. Education and Information Technologies, 26, 4839-4856. https://doi.org/10.1007/s10639-021-10502-6Grout, V., & Houlden, N. (2014). Taking computer science and programming into schools: The Glyndwˆ r/BCS Turing Project. Procedia - Social and Behavioral Sciences, 141(25), 680-685Grover, S., & Pea, R. (2013). Computational thinking in K-12 a review of the state of the field. Educational Researcher, 42(1), 38-43.Grover, S., Pea, R., & Cooper, S. (2015). Designing for deeper learning in a blended computer science course for middle school students. Computer Science Education, 25(2), 199-237.Gull, F., & Shehzad, S. (2015). Effects of cooperative learning on students’ academic achievement. Journal of Education and Learning, 9(3), 246-25.Hanks, B. (2008). Empirical evaluation of distributed pair programming. International Journal of Human-Computer Studies, 66(7), 530-544. https://doi.org/10.1016/j. ijhcs.2007.10.003Heintz, F., Mannila, L., & Färnqvist, T. (2016). A review of models for introducing computational thinking, computer science and computing in K-12 education. 2016 IEEE Frontiers in Education Conference (FIE), 1-9.Hergenhahn, B. R. (1982). An introduction to theories of learning (2nd ed.). Upper Saddle River, N.J.: Pearson/Prentice Hall.Howland, K, & Good,J. (2015). Learning to communicate computationally with flip: A bi-modal programming language for game creation. Computers & Education, 80, 224-240.Hsu, T.C., Chang, S.C. & Hung, Y.T. (2018). How to learn and how to teach computational thinking: Suggestions based on a review of the literature. Computers & Education, 126(1), 296-310.Hwang, W. Y., Wang, C. Y., Hwang, G. J., Huang, Y. M., & Huang, S. (2008). A web-based programming learning environment to support cognitive development. Interacting with Computers, 20, 524-534.Iskrenovic-Momcilovic, O. (2019). Pair programming with scratch. Education and Information Technologies, 24, 2943-2952. https://doi.org/10.1007/s10639-019-09905-3Sáez-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. doi:10.1016/j.compedu.2016.03.003Johnson, D. W., & Johnson, R. (1989). Cooperation and Competition: Theory and Research. Edina, MN: Interaction Book Company.Johnson, D. W., & Johnson, R. T. (1994). Learning together and alone: cooperative, competitive, and individualistic learning (4th ed.). Boston: Allyn and Bacon.Johnson, D. W., & Johnson, R. T. (2009). An educational psychology success story: Social interdependence theory and cooperative learning. Educational Researcher, 38, 365-379.Johnson, D., Johnson, R., & Stanne, M. (2000). Cooperative learning methods: A meta-analysis. University of Minnesota.Kaleliog˘lu, F. (2015). A new way of teaching programming skills to K-12 students: Code.org. Computers in Human Behavior, 52, 200-210.Kerr, N. L., & Bruun, S. E. (1983). Dispensability of member effort and group motivation losses: Free rider effects. Journal of Personality and Social Psychology, 44, 78-94.Kordaki, M. (2012). Diverse Categories of Programming Learning Activities could be Performed within Scratch. Procedia - Social and Behavioral Sciences, 46, 1162-1166.Lee, I., Martin, F., & Apone, K. (2014). Integrating computational thinking across the K-8 curriculum. ACM Inroad, 5(4), 64-71.Leiva, F. A. J., & Salas, C. A. C. (2013). Practices of advanced programming: Tradition versus innovation. Comput. Appl. Eng. Educ., 21, 237-244.https://doi.org/10.1002/cae.20465Lye, 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.Malan, D. J., & Leitner, H. H. (2007). Scratch for budding computer scientists. SIGCSE Bulletin, 39(1), 223-227.Maloney, J., Resnick, M., & Rusk, N. (2010). The Scratch programming language and environment. ACM Transactions on Computing Education, 10, 1-15.McDowell, C., Werner, L., Bullock, H., & Fernald, J. (2002). The effects of pair programming on performance in an introductory programming course. Proceedings of the 33rd SIGCSE technical symposium on computer science education. ACM SIGCSE Bulletin, 34(1), 38-42.National Research Council. (2010). Committee for the Workshops on Computational Thinking: Report of a workshop on the scope and nature of computational thinking. Washington, D.C: National Academies Press.Nijhot, W. & Kommers, P. (1985). An analysis of cooperation in relation to cognitive controversy. In R. Slavin et al. (Eds). Learning to cooperating to learn, 125-146.Nikou, S. A., & Economides, A. A. (2014). Transition in student motivation during a scratch and an app inventor course. 2014 IEEE Global Engineering Education Conference, 1042-1045.O’Reilly, D. (1998). School programming as literacy: The case for BOXER. Journal of Computer Assisted Learning, 14(1), 51-58.P´erez-Marín, D., Hijon-Neira, ´ R., Bacelo, A., & Pizarro, C. (2020). Can computational thinking be improved by using a methodology based on metaphors and scratch to teach computer programming to children? Computers in Human Behavior, 105, 105849.Papert, S. (1980). Mindstorms: Children, computer, and powerful ideas. New York: Basic Books.Papert, S. (1990). Epistemology and learning memo No. 2 . Cambridge MA: MIT.Artut, P. D., & Tarim, K. (2007). The effectiveness of jigsaw II on prospective elementary school teachers. Asia‐Pacific Journal of Teacher Education, 35(2), 129-141. doi : 10.1080/13598660701268551Perkins, D.V., & Saris, R.N. (2001). A “Jigsaw classroom” technique for undergraduate statistics courses. Teaching of Psychology, 28(2), 111-113.Levin, P. (2003). Running group projects: dealing with the free-rider problem. Planet, 9(1), 7-8. doi: 10.11120/plan.2003.00090007Piteira, M. & Costa, C. (2013). Learning computer programming: Study of difficulties in learning programming. 2013 International Conference on Information Systems and Design of Communication, 75-80. https://doi.org/10.1145/2503859.2503871Repenning, A. (2012). Programming goes back to school. Communications of the ACM, 55(5), 38-40.Resnick, M., Maloney, J., Monroy-Hernandez, A., Rusk, N., Eastmond, E., Brennan, K., et al. (2009). Scratch: Programming for all. Communications of the ACM, 52(11), 60-67.Rizvi, M., Humphries, T., Major, D., Jones, M., & Lauzun, H. (2011). A CSO course using scratch. Journal of Computing Sciences in Colleges, 26(3), 19-27.Robins, A., Rountree, J., & Rountree, N. (2003). Learning and teaching programming: A review and discussion. Computer Science Education, 13(2), 137-172.Rubinstein, A., & Chor, B. (2014). Computational thinking in life science education. PLoS Computational Biology, 10(11), e1003897.https://doi.org/10.1371/journal.pcbi.1003897Scherer, R. (2016). Learning from the past—The need for empirical evidence on the transfer effects of computer programming skills. Frontiers in Psychology, 7. https://doi.org/10.3389/fpsyg.2016.01390.Scherer, R., Siddiq, F., & Sánchez Viveros, B. (2019). The cognitive benefits of learning computer programming: A meta-analysis of transfer effects. Journal of Educational Psychology, 111, 764-792.Sharan, S. (1980). Cooperative learning in small groups: Recent methods and effects on achievement, attitudes, and ethnic relations. Review of Educational Research, 50(2), 241-271.Shen, H., Sun, C. (2000). RECIPE: a prototype for Internet-based real-time collaborative programming. 2nd International Workshop on Collaborative Editing Systems , 3-4.Slavin , R. E.( 1985 ) .Cooperative learning : Applying contact theory in desegregated schools. Joural of Social Issues, 43-62.Slavin, R. E. (1991). Synthesis of research on cooperative learning. Educational Leadership, 48, 71-82.Slavin, R. E. (1995). Cooperative learning: Theory, research, and practice. Boston: Allyn and Bacon.Snodgrass, M. R., Israel, M., & Reese, G. C. (2016). Instructional supports for students with disabilities in K-5 computing: Findings from a cross-case analysis. Computers & Education, 100, 1-17.Soloway, E. (1986). Learn to program = Learning to construct mechanisms and explanations. Comunications of the ACM, 28(9), 850-858.Nur Fitria, T. (2021). Creating sensation of learning in classroom: Using ’Gather Town’ platform video game-style for virtual classroom. Education and Human Development Journal, 6(2), 30-43. https://doi.org/10.33086/ehdj.v6i2.2106Tu, J. (2022). Meetings in the Metaverse: Exploring Online Meeting Spaces through Meaningful Interactions in Gather.Town [Unpublished master’s thesis]. University of Waterloo.Tucker, A., Deek, F., Jones, J., McCowan, D., Stephenson, C., & Verno, A. (2003). A Model Curriculum for K-12 Computer Science: Final Report of the ACM K-12 Task Force Curriculum Committee. The Association for Computing Machinery, New York.Voogt, J., Fisser, P., Good, J., Mishra, P., & Yadav, A. (2015). Computational thinking in compulsory education: Towards an agenda for research and practice. Education and Information Technologies, 20, 715-728.Walker, I., & Crogan, M. (1998). Academic performance, prejudice, and the jigsaw classroom: new pieces to the puzzle. Journal of Community & Applied Social Psychology, 8(6), 381-393.Webb, M., Davis, N., Bell, T., Katz, Y. J., Reynolds, N., Chambers, D. P., et al. (2017). Computer science in K-12 school curricula of the 2lst century: Why, what and when? Education and Information Technologies, 22(2), 445-468.Webb, N. M., Nemer, K. M., & Ing, M. (2006). Small-group reflections: parallels between teacher discourse and student behavior in peer-directed groups. The Journal of the Learning Sciences, 15(1), 63-119.Westcott, S. (2008). Effectiveness of using digital game playing in a first-level programming course [Unpublished doctoral dissertation]. USA: Pace University.Wijnstra, J. (2021). Making Great Onlin eSpaces: The influence of the online platform of GatherTown on the creativity of the students at the University of Groningen [Unpublished master’s thesis]. University of Groningen.Wing, J.M. (2006). Computational Thinking. Communications of the ACM, 49, 33-35.https://doi.org/10.1145/1118178.1118215Wing, J. M. (2008). Computational thinking and thinking about computing. Philosophical transactions of the royal society of London a: Mathematical, Physical and Engineering Sciences, 366, 3717-3725.Wolz, U., Leitner, H. H., Malan, D. J., & Maloney, J. (2009). Starting with scratch in CS1. SIGCSE Bulletin, 41, 2-3.Yu, A.T.W. (2017). Using jigsaw method to enhance the learning of research and consultancy techniques for postgraduate students. Engineering, Construction and Architectural Management, 24(6), 1081-1091. https://doi.org/10.1108/ECAM-03-2016-0080Zhong, B., Wang, Q., Chen, J., & Li, Y. (2016). An exploration of three-dimensional integrated assessment for computational thinking. Journal of Educational Computing Research, 53(4), 562-590. zh_TW dc.identifier.doi (DOI) 10.6814/NCCU202200997 en_US
