| 研究生: |
陳芸亭 Chen, Yun-Ting |
|---|---|
| 論文名稱: |
結合學生出題策略與社會競爭於運算思維遊戲之開發與探討 Design and Exploration of the Computational Thinking Game with Student-Generated Questions and Social Competition |
| 指導教授: |
黃悅民
Huang, Yueh-Min |
| 學位類別: |
碩士 Master |
| 系所名稱: |
工學院 - 工程科學系 Department of Engineering Science |
| 論文出版年: | 2020 |
| 畢業學年度: | 108 |
| 語文別: | 中文 |
| 論文頁數: | 88 |
| 中文關鍵詞: | 運算思維 、遊戲式學習 、學生出題 、社會競爭 |
| 外文關鍵詞: | Computational Thinking, Game-Based Learning, Student-Generated Questions, Social Competition |
| 相關次數: | 點閱:107 下載:0 |
| 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 |
運算思維是一種解決問題的思考方式,也是電腦科學中一項重要的核心能力;它不僅是電腦科學家才需擁有的能力,而是每個人都應該具備的基本能力。早期運算思維普遍使用程式設計進行教學活動,如C語言、C++、Java等,這對於初學者或年幼學童造成相當程度的負擔;而隨著視覺化程式設計的出現,無疑解決了這項問題,它可以透過拖拉和組合的步驟完成程式製作,進而對運算思維的培育更加容易。此外,以遊戲式學習的運算思維學習課程也逐漸成熟,像是code.org與Blockly遊戲皆是成功的案例;然而,傳統的運算思維遊戲可以透過暴力法反覆操作來完成解題任務,這恐怕限制了運算思維的發展。除此之外,早期的遊戲式學習架構經常乎略了競爭的重要性,它除了能夠促使同儕之間進行比較外,亦能有效地增進學習者的學習動機。
有鑑於此,本研究開發了一套結合學生出題策略與社會競爭的運算思維遊戲平台,並以台南市國小五、六年級生為實驗對象,採用準實驗設計方法探討介入實驗策略的成效,以支持本研究之實驗設計。從實驗結果顯示,將學生出題策略及社會競爭對學習者的運算思維能力有正向的影響;同時,在觀察實驗組與控制組學習者之學習動機、學習信心,發現實驗結果存在顯著的差異,表示實驗組的學習體驗是優於控制組。整體而言,本研究設計之運算思維遊戲平台及學習活動以提升學習者運算思維能力為主要研究目的,從研究結果可以看出結合出題策略與社會競爭可以有效的提升運算思維能力,並且具有正面的學習體驗。
Computational thinking (CT) is a way of thinking to solve problems and an important main ability in Computer Science. Early computational thinking generally used coding for teaching. When visual programming language appears, the program can be completed by dragging and combining steps. In addition, the computational thinking learning courses based on game-based learning have gradually matured. However, traditional computational thinking games can complete the problem-solving tasks through violent method repeated operations, which may limit the development of computational thinking. In addition, the early game-based learning framework often overlooked the importance of competition. It can encourage a peer comparison and effectively enhance students' motivation.
In view of this, this study developed a computational thinking playing platform that combined student-generated questions and social competition. The experimental results show that the student-generated questions strategies and social competition have a positive impact on the students’ computational thinking ability. Simultaneously, after observing the learning motivation, learning confidence between students of the experimental group and the control group, the experiment is found there are significant differences in the results, indicating that the experimental group's learning experience is better than the control group. . Overall, the computational thinking playing platform and learning activities designed in this study aim to enhance the student's computational thinking ability. From the research results, combining student-generated questions and social competition can effectively improve computational thinking ability and have a positive learning experience.
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.
高雄市政府教育局. e-Game. Retrieved from https://www.kh.edu.tw/
教育部. (2016). 教育部運算思維推動計畫. Retrieved from http://compthinking.csie.ntnu.edu.tw
Abramovich, S., & Cho, E. (2006). Technology as a medium for elementary preteachers' problem-posing experience in mathematics. Journal of Computers in Mathematics and Science Teaching, 25(4), 309-323.
Aflalo, E. (2018). Students generating questions as a way of learning. Active Learning in Higher Education, 1469787418769120.
Akilli, G. K. (2007a). Games and simulations: A new approach in education. In Games and simulations in online learning: Research and development frameworks (pp. 1-20): IGI Global.
Akilli, G. K. (2007b). Games and simulations: A new approach in education.
Amorim, C. (2005). Beyond algorithmic thinking: An old new challenge for science education. Paper presented at the Eighth International History, Philosophy, Sociology & Science Teaching Conference, July 15 to July 18, 2005, University of Leeds, England.
Anastasiadis, T., Lampropoulos, G., & Siakas, K. (2018). Digital Game-based Learning and Serious Games in Education. International Journal of Advances in Scientific Research and Engineering, 4(12), 139-144.
Anderson, N. D. (2016). A call for computational thinking in undergraduate psychology. Psychology Learning & Teaching, 15(3), 226-234.
Balanskat, A., & Engelhardt, K. (2015). Computing our future. Computer programming and coding Priorities, school curricula and initiatives across Europe. European Schoolnet.
Barlow, A. T., & Cates, J. M. (2006). The impact of problem posing on elementary teachers' beliefs about mathematics and mathematics teaching. School Science and Mathematics, 106(2), 64-73.
Barr, D., Harrison, J., & Conery, L. (2011). Computational thinking: A digital age skill for everyone. Learning & Leading with Technology, 38(6), 20-23.
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(1), 48-54.
Barradas, R., Lencastre, J. A., Soares, S., & Valente, A. (2020). Developing computational thinking in early ages: a review of the code. org Platform.
Bebras International Challenge on Informatics and Computational Thinking. (2015). Retrieved from http://www.bebras.org
Blazauskas, T., Limanauskiene, V., & Kersiene, V. (2012). Competition Based Online Social Learning. Paper presented at the International Conference on Information and Software Technologies.
Bouras, C., Igglesis, V., Kapoulas, V., Misedakis, I., Dziabenko, O., Koubek, A., . . . Sfiri, A. (2004). Game based learning using web technologies. Int. J. Intell. Games & Simulation, 3(2), 70-87.
Brennan, K., & Resnick, M. (2012). New frameworks for studying and assessing the development of computational thinking. Paper presented at the Proceedings of the 2012 annual meeting of the American educational research association, Vancouver, Canada.
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.
Brown, S. I., & Walter, M. I. (2005). The art of problem posing: Psychology Press.
Buss, A., & Gamboa, R. (2017). Teacher transformations in developing computational thinking: Gaming and robotics use in after-school settings. In Emerging research, practice, and policy on computational thinking (pp. 189-203): Springer.
Chen, Z.-H. (2014). Learning preferences and motivation of different ability students for social-competition or self-competition. Journal of Educational Technology & Society, 17(1), 283-293.
Chen, Z.-H., & Chen, S. Y. (2014). When educational agents meet surrogate competition: Impacts of competitive educational agents on students' motivation and performance. Computers & Education, 75, 274-281.
Cheng, H., Wu, W., Liao, C., & Chan, T. (2009). Equal opportunity tactic: Lessening negative effect in competition games in classrooms. Computers and Education, 53(3), 866-876.
Chin, C. (2002). Student-generated questions: Encouraging inquisitive minds in learning science. Teaching and Learning, 23(1), 59-67.
Chodkiewicz, H., & Kiszczak, A. (2019). Investigating the use of student-generated questions in disciplinary reading practices in higher education environments. Paper presented at the SOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference.
Cicchino, M. I. (2015). Using game-based learning to foster critical thinking in student discourse. Interdisciplinary Journal of Problem-Based Learning, 9(2).
Code.org. (2014). Teach our K-8 intro to computer science. Retrieved from https://code.org
Correia, M., & Santos, R. (2017). Game-based learning: The use of Kahoot in teacher education. Paper presented at the 2017 International Symposium on Computers in Education (SIIE).
Crocco, F., Offenholley, K., & Hernandez, C. (2016). A proof-of-concept study of game-based learning in higher education. Simulation & gaming, 47(4), 403-422.
Cuny, J., Snyder, L., & Wing, J. M. (2010). Demystifying computational thinking for non-computer scientists. Unpublished manuscript in progress, referenced in http://www. cs. cmu. edu/~ CompThink/resources/TheLinkWing. pdf.
del Olmo-Muñoz, J., Cózar-Gutiérrez, R., & González-Calero, J. A. (2020). Computational thinking through unplugged activities in early years of Primary Education. Computers & Education, 150, 103832.
Di Stasio, M. R., Savage, R., & Burgos, G. (2016). Social comparison, competition and teacher–student relationships in junior high school classrooms predicts bullying and victimization. Journal of Adolescence, 53, 207-216.
Díaz-Lauzurica, B., & Moreno-Salinas, D. (2019). Computational thinking and robotics: A teaching experience in compulsory secondary education with students with high degree of apathy and demotivation. Sustainability, 11(18), 5109.
Dori, Y. J., & Herscovitz, O. (1999). Question‐posing capability as an alternative evaluation method: Analysis of an environmental case study. Journal of Research in Science Teaching: The Official Journal of the National Association for Research in Science Teaching, 36(4), 411-430.
Education, D. f. (2013). National curriculum in England: Computing programmes of study. Gov. uk.
Fraser, N. (2013). Blockly. In: Google.
Futschek, G. (2006). Algorithmic thinking: the key for understanding computer science. Paper presented at the International conference on informatics in secondary schools-evolution and perspectives.
Futschek, G., & Moschitz, J. (2011). Learning algorithmic thinking with tangible objects eases transition to computer programming. Paper presented at the International conference on informatics in schools: Situation, evolution, and perspectives.
Games, A., & Squire, K. D. (2011). Searching for the fun in learning: A historical perspective on the evolution of educational video games. Computer games and instruction, 17-46.
Garcia, G. E., & Pearson, P. D. (1990). Modifying reading instruction to maximize its effectiveness for all students. Center for the Study of Reading Technical Report; no. 489.
Gärling, T., Fang, D., Holmen, M., & Michaelsen, P. (2020). Financial risk-taking related to individual risk preference, social comparison and competition. Review of Behavioral Finance.
Garris, R., Ahlers, R., & Driskell, J. E. (2002). Games, motivation, and learning: A research and practice model. Simulation & gaming, 33(4), 441-467.
Gilbert, D. T., Giesler, R. B., & Morris, K. A. (1995). When comparisons arise. Journal of personality and social psychology, 69(2), 227.
Gomes, A., & Mendes, A. J. (2007). Learning to program-difficulties and solutions. Paper presented at the International Conference on Engineering Education–ICEE.
Google. (2004). Blockly Games. Retrieved from https://blockly-games.appspot.com/about?lang=e
Google. (2012). Introduction to Blockly. Retrieved from https://developers.google.com/blockly/guides/overview.
Grover, S., Cooper, S., & Pea, R. (2014). Assessing computational learning in K-12. Paper presented at the Proceedings of the 2014 conference on Innovation & technology in computer science education.
Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field. Educational researcher, 42(1), 38-43.
Harvey, B., & Mönig, J. (2010). Bringing “no ceiling” to Scratch: Can one language serve kids and computer scientists. Proc. Constructionism, 1-10.
Heintz, F., Mannila, L., Nordén, L.-Å., Parnes, P., & Regnell, B. (2017). Introducing programming and digital competence in Swedish K-9 education. Paper presented at the International Conference on Informatics in Schools: Situation, Evolution, and Perspectives.
Hertel, G., Nohe, C., Wessolowski, K., Meltz, O., Pape, J. C., Fink, J., & Hüffmeier, J. (2018). Effort gains in occupational teams–the effects of social competition and social indispensability. Frontiers in psychology, 9, 769.
Hsu, C.-C., & Wang, T.-I. (2018). Applying game mechanics and student-generated questions to an online puzzle-based game learning system to promote algorithmic thinking skills. Computers & Education, 121, 73-88.
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, 296-310.
Hu, M., Winikoff, M., & Cranefield, S. (2012). Teaching novice programming using goals and plans in a visual notation. Paper presented at the Proceedings of the Fourteenth Australasian Computing Education Conference-Volume 123.
Huschens, M., Rothlauf, F., & Rothe, R. (2019). On the Role of Social Comparison Processes in Gamified Work Situations. Paper presented at the Proceedings of the 52nd Hawaii International Conference on System Sciences.
ISTE&CSTA. (2011). Operational Definition of Computational Thinking for K–12 Education. Retrieved from https://cdn.iste.org/www-root/ct-documents/computational-thinking-operational-definition-flyer.pdf?sfvrsn=2
Janakiraman, S., Watson, S. L., Watson, W. R., & Newby, T. (2021). Effectiveness of digital games in producing environmentally friendly attitudes and behaviors: A mixed methods study. Computers & Education, 160, 104043.
Jin, G., Tu, M., Kim, T.-H., Heffron, J., & White, J. (2018). Evaluation of game-based learning in cybersecurity education for high school students. Journal of Education and Learning (EduLearn), 12(1), 150-158.
Jones, S. P., Bell, T., Cutts, Q., Iyer, S., Schulte, C., Vahrenhold, J., & Han, B. (2011). Computing at school. International comparisons. Retrieved May, 7, 2013.
Jong, M. S. (2015). Does online game-based learning work in formal education at school? A case study of VISOLE. Curriculum Journal, 26(2), 249-267.
Julian, J. W., & Perry, F. A. (1967). Cooperation contrasted with intra-group and inter-group competition. Sociometry, 79-90.
Kalelioglu, F., & Gülbahar, Y. (2014). The Effects of Teaching Programming via Scratch on Problem Solving Skills: A Discussion from Learners' Perspective. Informatics in Education, 13(1), 33-50.
Kátai, Z. (2015). The challenge of promoting algorithmic thinking of both sciences‐and humanities‐oriented learners. Journal of Computer Assisted Learning, 31(4), 287-299.
Kazimoglu, C., Kiernan, M., Bacon, L., & Mackinnon, L. (2012). A serious game for developing computational thinking and learning introductory computer programming. Procedia-Social and Behavioral Sciences, 47, 1991-1999.
Ke, F. (2008a). Alternative goal structures for computer game-based learning. International Journal of Computer-Supported Collaborative Learning, 3(4), 429.
Ke, F. (2008b). Computer games application within alternative classroom goal structures: cognitive, metacognitive, and affective evaluation. Educational Technology Research and Development, 56(5-6), 539-556.
Kebritchi, M. (2008). Examining the pedagogical foundations of modern educational computer games. Computers & Education, 51(4), 1729-1743.
Kelleher, C., & Pausch, R. (2005). Lowering the barriers to programming: A taxonomy of programming environments and languages for novice programmers. ACM Computing Surveys (CSUR), 37(2), 83-137.
Kim, B., Park, H., & Baek, Y. (2009). Not just fun, but serious strategies: Using meta-cognitive strategies in game-based learning. Computers & Education, 52(4), 800-810.
King, A. (1994). Guiding knowledge construction in the classroom: Effects of teaching children how to question and how to explain. American educational research journal, 31(2), 338-368.
Larsen, T. (2020). Using Student-Generated Questions to Promote Curiosity and Student Learning.
Levine, T., & Donitsa-Schmidt, S. (1998). Computer use, confidence, attitudes, and knowledge: A causal analysis. Computers in Human Behavior, 14(1), 125-146.
Liao, C.-W., Chen, C.-H., & Shih, S.-J. (2019). The interactivity of video and collaboration for learning achievement, intrinsic motivation, cognitive load, and behavior patterns in a digital game-based learning environment. Computers & Education, 133, 43-55.
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.
McCall, J. (2012). Navigating the problem space: The medium of simulation games in the teaching of history. The History Teacher, 46(1), 9-28.
Michael, D. R., & Chen, S. L. (2005). Serious games: Games that educate, train, and inform: Muska & Lipman/Premier-Trade.
Mussweiler, T. (2003). Comparison processes in social judgment: mechanisms and consequences. Psychological review, 110(3), 472.
Nebel, S., Schneider, S., & Rey, G. D. (2016). From duels to classroom competition: Social competition and learning in educational videogames within different group sizes. Computers in Human Behavior, 55, 384-398.
Orji, F. A., Greer, J., & Vassileva, J. (2019). Exploring the effectiveness of socially-oriented persuasive strategies in education. Paper presented at the International Conference on Persuasive Technology.
Palinscar, A. S., & Brown, A. L. (1984). Reciprocal teaching of comprehension-fostering and comprehension-monitoring activities. Cognition and instruction, 1(2), 117-175.
Papert, S. (1980). Mindstorms: children, computers, and powerful ideas Basic Books. Inc. New York, NY.
Partovi, T., & Razavi, M. R. (2019). The effect of game-based learning on academic achievement motivation of elementary school students. Learning and Motivation, 68, 101592.
Pho, A., & Dinscore, A. (2015). Game-based learning. Tips and Trends.
Pintrich, P. R. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ).
Plass, J. L., Homer, B. D., & Kinzer, C. K. (2015). Foundations of game-based learning. Educational Psychologist, 50(4), 258-283.
Prensky, M. (2001). Fun, play and games: What makes games engaging. Digital game-based learning, 5(1), 5-31.
Prensky, M. (2003). Digital game-based learning. Computers in Entertainment (CIE), 1(1), 21-21.
Prensky, M. (2007). Don’t Bother Me Mom: I’m learning. In: Minnesota.
Reeve, J., & Deci, E. L. (1996). Elements of the competitive situation that affect intrinsic motivation. Personality and Social Psychology Bulletin, 22(1), 24-33.
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.
Scardamalia, M., & Bereiter, C. (1985). Fostering the development of self-regulation in children's knowledge processing. Thinking and learning skills: Research and open questions, 2, 563-577.
Seehorn, D., Carey, S., Fuschetto, B., Lee, I., Moix, D., O’Grady-Cunniff, D., . . . Verno, A. (2011). CSTA K-12 computer science standards. Computer Science Teachers Association, Association for Computing Machinery, New York.
Selby, C., & Woollard, J. (2013). Computational thinking: the developing definition.
Septiyanti, N. D., Shih, J.-L., & Zakarijah, M. (2020). Fostering Computational Thinking Through Unplugged and Robotic Collaborative Game-Based Learning on Primary School Students. American Journal of Educational Research, 8(11), 866-872.
Shaffer, D. W., Squire, K. R., Halverson, R., & Gee, J. P. (2005). Video games and the future of learning. Phi delta kappan, 87(2), 105-111.
Shearer, J. D. (2011). Development of a digital game-based learning best practices checklist. Bowling Green State University,
Shute, V. J., Sun, C., & Asbell-Clarke, J. (2017). Demystifying computational thinking. Educational Research Review, 22, 142-158.
SMITH, M. (2016). Computer Science For All. Retrieved from https://obamawhitehouse.archives.gov/blog/2016/01/30/computer-science-all
Sosnovsky, S., Fang, Q., de Vries, B., Luehof, S., & Wiegant, F. (2020). Towards Adaptive Social Comparison for Education. Paper presented at the European Conference on Technology Enhanced Learning.
Stapel, D. A., & Koomen, W. (2005). Competition, cooperation, and the effects of others on me. Journal of personality and social psychology, 88(6), 1029.
Sung, H.-Y., Hwang, G.-J., Lin, C.-J., & Hong, T.-W. (2017). Experiencing the Analects of Confucius: An experiential game-based learning approach to promoting students' motivation and conception of learning. Computers & Education, 110, 143-153.
Sung, W., Ahn, J., & Black, J. B. (2017). Introducing computational thinking to young learners: Practicing computational perspectives through embodiment in mathematics education. Technology, Knowledge and Learning, 22(3), 443-463.
Sutaphan, S., & Yuenyong, C. (2019). STEM education teaching approach: Inquiry from the context based. Paper presented at the Journal of Physics: Conference Series.
Sysło, M. M., & Kwiatkowska, A. B. (2015). Introducing a new computer science curriculum for all school levels in Poland. Paper presented at the International conference on informatics in Schools: Situation, evolution, and perspectives.
Tauer, J. M., & Harackiewicz, J. M. (1999). Winning isn't everything: Competition, achievement orientation, and intrinsic motivation. Journal of Experimental Social Psychology, 35(3), 209-238.
Topalli, D., & Cagiltay, N. E. (2018). Improving programming skills in engineering education through problem-based game projects with Scratch. Computers & Education, 120, 64-74.
Troussas, C., Krouska, A., & Sgouropoulou, C. (2020). Collaboration and fuzzy-modeled personalization for mobile game-based learning in higher education. Computers & Education, 144, 103698.
Tsarava, K., Moeller, K., Pinkwart, N., Butz, M., Trautwein, U., & Ninaus, M. (2017). Training computational thinking: Game-based unplugged and plugged-in activities in primary school. Paper presented at the European Conference on Games Based Learning.
Turchi, T., Fogli, D., & Malizia, A. (2019). Fostering computational thinking through collaborative game-based learning. Multimedia Tools and Applications, 78(10), 13649-13673.
Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information systems research, 11(4), 342-365.
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(4), 715-728.
Vorderer, P., Hartmann, T., & Klimmt, C. (2003). Explaining the enjoyment of playing video games: the role of competition. Paper presented at the Proceedings of the second international conference on Entertainment computing.
Watts, M., Gould, G., & Alsop, S. (1997). Questions of Understanding: Categorising Pupils' Questions in Science. School Science Review, 79(286), 57-63.
White, R., & Gunstone, R. (2014). Probing understanding: Routledge.
Whitin, P. (2004). Promoting Problem-Posing Explorations. Teaching Children Mathematics, 11(4), 180.
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.
Wong, B. Y. (1985). Self-questioning instructional research: A review. Review of educational research, 55(2), 227-268.
Yang, Q.-F., Chang, S.-C., Hwang, G.-J., & Zou, D. (2020). Balancing cognitive complexity and gaming level: Effects of a cognitive complexity-based competition game on EFL students' English vocabulary learning performance, anxiety and behaviors. Computers & Education, 148, 103808.
Yang, S., Lee, J. W., Kim, H.-J., Kang, M., Chong, E., & Kim, E.-m. (2020). Can an online educational game contribute to developing information literate citizens? Computers & Education, 161, 104057.
Yin, Y., Hadad, R., Tang, X., & Lin, Q. (2019). Improving and Assessing Computational Thinking in Maker Activities: the Integration with Physics and Engineering Learning. Journal of Science Education and Technology, 1-26.
Yu, F.-Y. (2019). An online learning system supporting student-generated explanations for questions: design, development, and pedagogical potential. Interactive Learning Environments, 1-21.
Yu, F.-Y., Han, C., & Chan, T.-W. (2008). Experimental comparisons of face-to-face and anonymous real-time team competition in a networked gaming learning environment. CyberPsychology & Behavior, 11(4), 511-514.
Yu, F.-Y., & Liu, Y. (2008). The comparative effects of student question-posing and question-answering strategies on promoting college students’ academic achievement, cognitive and metacognitive strategies use. Journal of Education and Psychology, 31(3), 25-52.
Yu, F.-Y., & Wu, C.-P. (2016). The effects of an online student-constructed test strategy on knowledge construction. Computers & Education, 94, 89-101.
Yu, F.-Y., & Wu, W.-S. (2020). Effects of student-generated feedback corresponding to answers to online student-generated questions on learning: What, why, and how? Computers & Education, 145, 103723.
Yu, F. Y., & Chen, Y. J. (2014). Effects of student‐generated questions as the source of online drill‐and‐practice activities on learning. British Journal of Educational Technology, 45(2), 316-329.
Yu, F. Y., & Liu, Y. H. (2005). Potential values of incorporating a multiple‐choice question construction in physics experimentation instruction. International Journal of Science Education, 27(11), 1319-1335.
Yu, F. Y., & Liu, Y. H. (2009). Creating a psychologically safe online space for a student‐generated questions learning activity via different identity revelation modes. British Journal of Educational Technology, 40(6), 1109-1123.
Yukselturk, E., Altıok, S., & Başer, Z. (2018). Using game-based learning with kinect technology in foreign language education course. Journal of Educational Technology & Society, 21(3), 159-173.
Zapata-Ros, M. (2015). Pensamiento computacional: Una nueva alfabetización digital. Revista de Educación a Distancia (RED)(46).
Zhang, L., & Nouri, J. (2019). A systematic review of learning computational thinking through Scratch in K-9. Computers & Education, 141, 103607.
Zhao, W., & Shute, V. J. (2019). Can playing a video game foster computational thinking skills? Computers & Education, 141, 103633.
Zsakó, L., & Szlávi, P. (2012). ICT Competences: Algorithmic Thinking. Acta Didactica Napocensia, 5(2), 49-58.