本研究旨在評估問題解決導向運算思維模式之效益。基於模式設計師資培育課程，以瞭解其對師資生以運算思維解決問題的能力和態度之影響。研究對象為13位修習中等學校教育學程之師資生，參與6天短期密集Python課程後，採行質、量化方法並用，分析其問題解決能力測驗、問題解決態度量表結果，及課室觀察、課後回饋、專題作品和訪談記錄結果。
研究結果顯示，師資生以運算思維解決問題的能力雖無顯著的前、後測成長差異，仍有正向影響，部分師資生開始能思考處理問題的優先順序，將複雜問題拆解成較容易解決的形式，主動應用所學解決生活上的問題。態度上也呈現正向改變，較肯定自己可以成功克服困難，願意多給自己嘗試的機會，不強求在解題過程時要達到完美，且意識到與他人合作的重要性。此外，針對課程的觀感，師資生認為，此教學模式利於有組織、有目的性地學習，亦可用於精進自我教學能力，未來若能採用類似的模式化教學，可促進學生更有結構的吸收新知。
本研究提出之模式尚有待未來研究進一步改進調整之，使模式越臻完整，並建議嘗試將模式融入一般學期性的師資培育課程或是其他領域的課程，繼續驗證模式之效益；評量方面則可針對模式中每一階段的運算思維內涵，發展評量指標，清楚劃分各運算思維內涵策略應有的行為表現；研究對象方面則可針對各類專業背景的師資生深入討論，探討其在能力、態度、著重觀點上的差異。

The study aims to evaluate the effectiveness of the Problem-solving-based Framework of Computational Thinking (CT) Components in improving the problem-solving skill and attitude of preservice teachers. The CT Framework was used to design a six-day Python workshop for 13 preservice teachers of secondary education program who volunteered to participate in the course. The design of the study is mixed of quantitative and qualitative methods to investigate how participation in the workshop influences preservice teachers’ problem-solving skill and attitude as well as their reflection and opinions.
The results of the study showed that this CT Framework of course did positively influence preservice teachers’ problem-solving skill and attitude in that they are now able to think procedural steps and priorities in dealing with problems and to break down complex problems into smaller parts that can be more easily tackled, especially in facing their daily encounters. Their dispositions become more confident, persistent, tolerant, purposive, and collaborative after engaging in the workshop. Positive reflections also include that this CT Framework of course design can facilitate their own learning as well as pedagogy so that in their future teaching they have ways to help students learn more structurally.
To further refine this CT Framework of course design, future studies can be geared toward implementing it in regular courses of various disciplines to assess its effectiveness, and developing valid measurements or rubrics to assess student achievement of the CT Components in each stage of the Framework.

中文部分
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。
孫維琳（2018）。以德菲法評析國際運算思維挑戰賽題型之研究（碩士論文）。取自https://hdl.handle.net/11296/3p92hw
國家教育研究院（2016）。十二年國教科技領域「資訊科技」科目課程綱要草案。取自https://www.naer.edu.tw/ezfiles/0/1000/attach/92/pta_10229_131308_9
4274.pdf
資訊及科技教育司（2016）。教育部資訊教育向前行「運算思維領航會」暨「資訊科技融入教學創新應用團隊選拔」頒獎典禮。取自 https://www.edu.tw/News_Content.aspx?n=9E7AC85F1954DDA8&s=FB3C38877790095C#

英文部分
Angeli, C., & Jaipal-Jamani, K. (2018). Preparing Pre-service Teachers to Promote Computational Thinking in School Classrooms. Proceedings of Computational thinking in the STEM disciplines, 127-150. https://doi.org/10.1007/978-3-319-93566-9_7
Araujo, A. L. S. O., Andrade, W. L., Guerrero, D. D. S., & Melo, M. R. A. (2019). How Many Abilities Can We Measure in Computational Thinking?: A Study on Bebras Challenge. In the Conference Proceedings of the 50th ACM Technical Symposium on Computer Science Education, 545-551. Minneapolis, USA. https://doi.org/10.1145/3287324.3287405
Araujo, A. L. S. O., Santos, J. S., Andrade, W. L., Guerrero, D. D. S., & Dagienė, V. (2017). Exploring computational thinking assessment in introductory programming courses. In the Conference Proceedings of the 2017 IEEE Frontiers in Education (FIE), 1-9. Indianapolis, USA. doi:10.1109/FIE.2017.8190652
Atmatzidou, S., Demetriadis, S., & Nika, P. (2018). How Does the Degree of Guidance Support Students’ Metacognitive and Problem Solving Skills in Educational Robotics? Journal of Science Education and Technology, 27(1), 70-85.
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? Inroads, 2(1), 48-54.
Bers, M. U., Flannery, L., Kazakoff, E. R., & Sullivan, A. (2014). Computational thinking and tinkering: Exploration of an early childhood robotics curriculum. Computers & Education, 72, 145-157.
Bocconi, S., Chioccariello, A., Dettori, G., Ferrari, A., Engelhardt, K., Kampylis, P., & Punie, Y. (2016). Developing computational thinking in compulsory education. European Commission, JRC Science for Policy Report. Rerieved from https://ec.europa.eu/jrc/en/publication/eur-scientific-and-technical-research-reports/developing-computational-thinking-compulsory-education-implications-policy-and-practice
Boom, K.-D., Bower, M., Arguel, A., Siemon, J., & Scholkmann, A. (2018). Relationship between computational thinking and a measure of intelligence as a general problem-solving ability. In the Conference Proceedings of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education, 206-211. Larnaca, Cyprus. https://doi.org/10.1145/3197091.3197104
Bower, M., & Falkner, K. (2015). Computational thinking, the notional machine, pre-service teachers, and research opportunities. In the Conference Proceedings of the 17th Australasian Computing Education (ACE 2015), 37-46. Sydney, Australia.
Brown, A. L. (1992). Design experiments: Theoretical and methodological challenges in creating complex interventions in classroom settings. The journal of the learning sciences, 2(2), 141-178.
Corradini, I., Lodi, M., & Nardelli, E. (2017). Conceptions and misconceptions about computational thinking among Italian primary school teachers. In the Conference Proceedings of the 2017 ACM Conference on International Computing Education Research, 136-144. Washington, USA. https://doi.org/10.1145/3105726.3106194
Csapó, B., & Funke, J. (2017). The development and assessment of problem solving in 21st-century schools. Retrieved from https://www.psychologie.uni-heidelberg.de/ae/allg/mitarb/jf/Csapo%20Funke%202017%20problem%20solving%2021st%20century.pdf
Denner, J., Werner, L., Campe, S., & Ortiz, E. (2014). Pair Programming: Under What Conditions Is It Advantageous for Middle School Students? Journal of Research on Technology in Education, 46(3), 277-296.
Denning, P. J. (2009). Beyond computational thinking. Communications of the ACM, 52(6), 28-30.
Department for Education in England [DOEE]. (2013). National curriculum in England: Computing programmes of study. Retrieved from https://www.gov.uk/government/publications/national-curriculum-in-england-computing-programmes-of-study/national-curriculum-in-england-computing-programmes-of-study
Djambong, T., & Freiman, V. (2016, October). Task-Based Assessment of Students' Computational Thinking Skills Developed through Visual Programming or Tangible Coding Environments. In the Conference Proceedings of the 13th International Conference on Cognition and Exploratory Learning in Digital Age (CELDA 2016), 41-51. Mannheim, Germany.
Dolgopolovas, V., Jevsikova, T., Savulionienė, L., & Dagienė, V. (2015). On Evaluation of computational thinking of software engineering novice students. In the Conference Proceedings of the IFIP TC3 Working Conference “A New Culture of Learning: Computing and next Generations, 90-99. Vilnius University, Lithuania.
Eickelmann, B., Labusch, A., & Vennemann, M. (2018). Computational Thinking and Problem-Solving in the Context of IEA-ICILS 2018. In the Conference Proceedings of the Open Conference on Computers in Education, 14-23. Linz, Austria. https://doi.org/10.1007/978-3-030-23513-0_2
Fernández, J., Zúñiga, M. E., Rosas, M. V., & Guerrero, R. A. (2018). Experiences in Learning Problem-Solving through Computational Thinking. Journal of Computer Science & Technology, 18(2), 136-142.
García-Peñalvo, F. J., & Mendes, A. J. (2018). Exploring the computational thinking effects in pre-university education. Computers in Human Behavior, 80, 407-411.
Google. (2010). Google for Education: Exploring Computational Thinking. Retrieved from https://edu.google.com/resources/programs/exploring-computational-thinking/?fbclid=IwAR3kdK1xB36HHtMbR3uis5ZZjRrluSttYdElg_FQrq6Um_mR0k6q9qBEl8w#!ct-overview
Grover, S., & Pea, R. (2013). Computational Thinking in K–12:A Review of the State of the Field. Educational Researcher, 42(1), 38-43.
Guzdial, M. (2008). Education Paving the way for computational thinking. Communications of the ACM, 51(8), 25-27.
Heintz, F., Mannila, L., & Färnqvist, T. (2016). A review of models for introducing computational thinking, computer science and computing in K-12 education. In the Conference Proceedings of the 2016 IEEE Frontiers in Education (FIE), 1-9. Erie, USA. doi: 10.1109/FIE.2016.7757410
Hemmendinger, D. (2010). A plea for modesty. ACM Inroads, 1(2), 4-7.
Hsiao, H. -S., & Lin, Y. -A. (2019). Constructing Expert Programming Thinking Process in the Field of Information Engineering, Promoting the Planning of Operational Thinking Teaching Activities. In the Proceedings of International Conference on Computational Thinking Education 2019, 24-29.
Hubwieser, P., & Mühling, A. (2014). Playing PISA with bebras. In the Conference Proceedings of the 9th Workshop in Primary and Secondary Computing Education, 128-129. Berlin, Germany.
International Society for Technology in Education[ISTE], & Computer Science Teachers Association[CSTA]. (2011). Operational Definition of Computational Thinking. Retrieved from https://id.iste.org/docs/ct-documents/computational-thinking-operational-definition-flyer.pdf
Jaipal - Jamani, K., & Angeli, C. (2016). Effect of Robotics on Elementary Preservice Teachers’ Self-Efficacy, Science Learning, and Computational Thinking. Journal of Science Education and Technology, 26(2), 175-192.
Jeng, H.-L., Liu, L.-W., & Chen, C.-N. (2019, July). Developing a Procedural Problem-based Framework of Computational Thinking Components. In the Conference Proceedings of 2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI), 272-277. Toyama, Japan.
Kalelioglu, F., Gulbahar, Y., & Kukul, V. (2016). A framework for computational thinking based on a systematic research review. Baltic Journal Modern Computing, 4(3), 583-596.
Kline, R. B. (1998). Principles and practice of structural equation modeling. New York: Guilford Press.
Kim, S., & Kim, H. Y. (2018). A computational thinking curriculum and teacher professional development in South Korea. In the Proceedings of Computational Thinking in the STEM Disciplines, 165-178.
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.
Krashen, S. D. (1983). The din in the head, input, and the language acquisition device. Foreign Language Annals, 16(1), 41-44.
Labusch, A., Eickelmann, B., & Vennemann, M. (2019). Computational Thinking Processes and Their Congruence with Problem-Solving and Information Processing. In the Proceedings of Computational Thinking Education, 65-78.
Lamprou, A., & Repenning, A. (2018). Teaching how to teach computational thinking. In the Conference Proceedings of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education, 69-74. Larnaca, Cyprus. https://doi.org/10.1145/3197091.3197120
Ling, U. L., Saibin, T. C., Labadin, J., & Aziz, N. A. (2017). Preliminary investigation: Teachers’ perception on computational thinking concepts. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(2), 23-29.
Lu, J. J., & Fletcher, G. H. (2009). Thinking about computational thinking. In the Proceedings of the 40th ACM technical symposium on Computer science education, 260-264.
Mouza, C., Yang, H., Pan, Y.-C., Ozden, S. Y., & Pollock, L. (2017). Resetting educational technology coursework for pre-service teachers: A computational thinking approach to the development of technological pedagogical content knowledge (TPACK). Australasian Journal of Educational Technology, 33(3), 1-16.
National Research Council. (2012). A framework for K-12 science education: Practices, crosscutting concepts, and core ideas. Washington, DC: National Academies Press.
Partnership for 21st Century Skills. (2019). Framework for 21st Century Learning Definitions. Retrieved from http://static.battelleforkids.org/documents/p21/P21_Framework_DefinitionsBFK.pdf
Pala, F. K., & Mıhçı Türker, P. (2019). The effects of different programming trainings on the computational thinking skills. Interactive Learning Environments, 27(8), 1-11.
Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas. New York, NY: Basic Books.
Pears, A., Dagiene, V., & Jasute, E. (2017). Baltic and Nordic K-12 Teacher Perspectives on Computational Thinking and Computing. In the Conference Proceedings of the Informatics in Schools: Focus on Learning Programming, 141-152. Helsinki, Finland. https://doi.org/10.1007/978-3-319-71483-7_12
Prieto-Rodriguez, E., & Berretta, R. (2014). Digital technology teachers' perceptions of computer science: It is not all about programming. In the Conference Proceedings of the 2014 IEEE Frontiers in Education Conference (FIE), 1-5. Madrid, Spain. doi: 10.1109/FIE.2014.7044134
Román-González, M. (2015). Computational thinking test: Design guidelines and content validation. In the Conference Proceedings of EDULEARN15, 2436-2444. Barcelona, Spain.
Román-González, M., Moreno-León, J., & Robles, G. (2019). Combining Assessment Tools for a Comprehensive Evaluation of Computational Thinking Interventions. In the Proceedings of Computational Thinking Education, 79-98.
Sadik, O., Leftwich, A.-O., & Nadiruzzaman, H. (2017). Computational thinking conceptions and misconceptions: Progression of preservice teacher thinking during computer science lesson planning. In the Proceedings of Emerging research, practice, and policy on computational thinking, 221-238.
Seehorn, D., Carey, S., Fuschetto, B., Lee, I., Moix, D., O'Grady-Cunniff, D., ...Verno, A. (2011). CSTA K--12 Computer Science Standards: Revised 2011. Retrieved from https://dl.acm.org/citation.cfm?id=2593249
Selby, C. C., & Woollard, J. (2013). Computational Thinking: The Developing Definition. Retrieved from https://eprints.soton.ac.uk/356481/
Selby, C. C., & Woollard, J. (2014). Refining an Understanding of Computational Thinking. Retrieved from https://eprints.soton.ac.uk/372410/
Sentance, S., & Csizmadia, A. (2017). Computing in the curriculum: Challenges and strategies from a teacher’s perspective. Education and Information Technologies, 22(2), 469-495.
Standl, B. (2017). Solving everyday challenges in a computational way of thinking. In the Conference Proceedings of the Informatics in Schools: Focus on Learning Programming, 180-191. Helsinki, Finland. https://doi.org/10.1007/978-3-319-71483-7_15
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard university press.
Webb, M., Davis, N., Bell, T., Katz, Y. J., Reynolds, N., Chambers, D. P., & Sysło, M. M. (2017). Computer science in K-12 school curricula of the 2lst century: Why, what and when? Education and Information Technologies, 22(2), 445-468.
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.
Wing, J. M. (2010). Research Notebook: Computational Thinking--What and Why? | Carnegie Mellon School of Computer Science. Retrieved from http://www.cs.cmu.edu/link/research-notebook-computational-thinking-what-and-why
Yadav, A., Good, J., Voogt, J., & Fisser, P. (2017). Computational thinking as an emerging competence domain. Proceedings of Competence-based vocational and professional education, 1051-1067.
Yadav, A., Mayfield, C., Zhou, N., Hambrusch, S., & Korb, J. T. (2014). Computational thinking in elementary and secondary teacher education. ACM Transactions on Computing Education (TOCE), 14(1), 1-16.
Yadav, A., Zhou, N., Mayfield, C., Hambrusch, S., & Korb, J. T. (2011). Introducing computational thinking in education courses. In the Conference Proceedings of the 42nd ACM technical symposium on Computer science education, 465-470. Dallas, USA. https://doi.org/10.1145/1953163.1953297
Yang, H., Mouza, C., & Pan, Y.-C. (2018). Examining pre-service teacher knowledge trajectories of computational thinking through a redesigned educational technology course. In the Conference Proceedings of the International Society of the Learning Sciences, 368-375.
Zha, S., Jin, Y., Moore, P., & Gaston, J. (2020a). A cross-institutional investigation of a flipped module on preservice teachers’ interest in teaching computational thinking. Journal of Digital Learning in Teacher Education, 36(1), 32-45.
Zha, S., Jin, Y., Moore, P., & Gaston, J. (2020b). Hopscotch into Coding: Introducing Pre-Service Teachers Computational Thinking. TechTrends, 64(1), 17-28.