研究生: |
林育安 Lin, Yu-An |
---|---|
論文名稱: |
運用6E模式進行STEM機電整合活動中對高中生學習成效之研究 Study on the Learning Outcomes of High School Students in the STEM Electromechanical Integration Activities Using the 6E Model |
指導教授: |
蕭顯勝
Hsiao, Hsien-Sheng |
學位類別: |
碩士 Master |
系所名稱: |
科技應用與人力資源發展學系 Department of Technology Application and Human Resource Development |
論文出版年: | 2019 |
畢業學年度: | 107 |
語文別: | 中文 |
論文頁數: | 136 |
中文關鍵詞: | 機電整合 、6E模式 、STEM 、運算思維 |
英文關鍵詞: | mechatronics, 6E mode, STEM, computational thinking |
DOI URL: | http://doi.org/10.6345/NTNU201900805 |
論文種類: | 學術論文 |
相關次數: | 點閱:219 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 |
機電整合(Mechatronics)附屬於工程教育的其中,機電整合並非一門獨立的學科,而是機械、電機、電子、資訊、創意及設計的結合,機電整合課程包括科學知識、資訊科技、數學運算以及科技工具的整合應用,過程中會進行問題解決、分析與決策等活動,並且可以產生學生STEM(Science、Technology、Engineering、Mathematics)的興趣以及提升連結課堂教學與日常生活的學習效果。而6E(Engage、Explore、Explain、Engineer、Enrich、Evaluate)教學是以學習者為中心的教學模式,目的是提升學習者設計與探究的能力,搭配實作教學活動可以整合理論知識與實作經驗。而現今教學現場所使用的模式是專家程式設計思考程序來教學,著重於程式設計思考能力。
本研究旨在探討不同教學模式(6E模式、專家程式設計思考程序)對高中學生在機電整合課程。研究對象為高中三年級第一類組學生共162位學生,實驗採用準實驗研究法,自變項為教學模式,依照不同教學模式分為6E模式與專家程式設計思考程序教學模式兩種;依變項則包含實作能力、運算思維,並在實驗前後會以語意流程圖析法去探討學生認知結構。研究結果顯示:(1)採用6E模式在STEM機電整合課程能有效的提升實作能力;(2)兩組學生學習STEM機電整合課程後對於運算思維的能力皆有提升;(3)從認知結構訪談中了解到學生概念數量及迴歸連結數量皆有增加。研究建議為在課程設計時選用可操控玩具之主題,可引起學生注意力及提升課程趣味性並且未來可將6E模式用於其他需要專題實作的課程。
Mechatronics is related to engineering education. Mechatronics is not an independent discipline, but a combination of mechanics, motors, electronics, information, creativity and design. Mechatronics courses include scientific knowledge, information technology, mathematical operations and technology. The integration of tools, problem solving, analysis and decision-making activities can generate students' interest in STEM (science, technology, engineering, mathematics), improve the learning effect of connecting classroom teaching and daily life, and 6E ( Engage、Explore、Explain、Engineer、Enrich、Evaluate) Teaching is a learner-centered teaching model designed to enhance learners' design and exploration skills. Combining handson teaching activities can integrate theoretical knowledge and practical experience, but The model used in today's teaching scenes is an expert programming thinking program to focus on programming thinking.
This study aims to explore the different teaching modes of high school students in the mechatronics curriculum (6E model, expert programming thinking process). The research was like the first batch of 162 students from high school. The experiment uses a quasi-experimental research method, and independent variable is a teaching mode. According to different teaching modes, it is divided into 6E mode and expert programming thinking program teaching mode. Dependent variable include practical ability and computational thinking, and will discuss the semantic structure of students before and after the experiment. The results show that: (1) using the 6E mode in the STEM mechatronics process can effectively improve the practical ability; (2) the two groups of students learn STEM mechatronics after improving their thinking ability; (3) from the cognitive structure in the interview, It is understood that the number of student concepts and the number of regression links have increased. The study suggests that the theme of steerable toys should be used in the design of the course, which can attract students' attention and enhance the interest of the course. In the future, the 6E model can be used for other courses that require thematic implementation.
一、 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。
林坤誼(2016)。虛實STEM場域對培養國中生合作問題解決能力的效益。論文發表於第五屆工程與科技教育學術研討會,國立臺灣師範大學。
汪殿杰, 巫鍵志, 王意蘭, 與 吳致娟. (2014). 強調動手實作的科技教育-以臺北市立大同高中為例。中等教育。
國家教育研究院(2015)。十二年國民基本教育科技領域課程綱要草案研修說明。台北:國家教育研究院。
張永福(2008)。實作評量的特性及其理論基礎。研習資訊,25(3),79-86。
張玉山、楊雅茹(2014)。STEM教學設計之探討:以液壓手臂單元為例。科技與人力教育季刊,1(1),2-17。
教育部(2019)。十二年國民基本教育課程綱要總綱。台北:教育部。
黃一峯、朱耀明(2013)。知識來源對學生動手做活動學習影響探究分析。工業科技教育學刊,6,45-56。
聶健文、顏芳慧(2010)實作導向的護理研究訓練成效評值。南臺灣醫學雜誌,6(1), 30-37。
羅希哲、蔡慧音、曾國鴻(2011)。高中女生STEM網路專題式合作學習之研究。高雄師大學報,30,41-61。
二、 外文部分
Alimisis, D. (2013). Educational robotics: Open questions and new challenges. Themes in Science and Technology Education, 6(1), 63-71.
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.
Arangala, C. (2013). Developing curiosity in science with service. J. Civic Commit, 20, 1-10.
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.
Ball, T., Protzenko, J., Bishop, J., Moskal, M., de Halleux, J., & Braun, M. (2016). The BBC micro: bit coded by Microsoft Touch Develop. Microsoft Research.
Barr, D., Harrison, J., & Conery, L. (2011). Computational thinking: A digital age skill for everyone. Learning & Leading with Technology, 38(6), 20-23.
Beer, R. D., Chiel, H. J., & Drushel, R. F. (1999). Using autonomous robotics to teach science and engineering. Communications of the ACM, 42(6), 85-92.
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.
Besemer, S. P. (1998). Creative product analysis matrix: testing the model structure and a comparison among products--three novel chairs. Creativity Research Journal, 11(4), 333-346.
Besemer, S. P., & O'Quin, K. (1999). Confirming the three-factor creative product analysis matrix model in an American sample. Creativity Research Journal, 12(4), 287-296.
Besemer, S. P., & Treffinger, D. J. (1981). Analysis of creative products: Review and synthesis. The Journal of Creative Behavior, 15(3), 158-178.
Blank, D. (2006). Robots make computer science personal. Communications of the ACM, 49(12), 25-27.
Brennan, K., & Resnick, M. (2012). New frameworks for studying and assessing the development of computational thinking. In Proceedings of the 2012 annual meeting of the American Educational Research Association, Vancouver, Canada (Vol. 1, p. 25).
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.
Bull, G., & Berry, R. (2011). Classroom engineering and craft technologies. Learning and Leading with Technology, 38, 26–27.
Burke, B. N. (2014). The ITEEA 6E Learning ByDesign™ Model: maximizing informed design and inquiry in the integrative STEM classroom. Technology and Engineering Teacher, 73(6), 14-19.
Bybee, R. W., Taylor, J. A., Gardner, A., Van Scotter, P., Carlson Powell, J., Westbrook, A., & Landes, N. (2006). The BSCS 5E Instructional Model: Origins, effectiveness and applications. Retrieved from http://www.bscs.org/bscs-5e-instructional-model
Chang, Y. S., Chien, Y. H., Lin, H. C., Chen, M. Y., & Hsieh, H. H. (2016). Effects of 3D CAD applications on the design creativity of students with different representational abilities. Computers in Human Behavior, 65, 107-113.
Computer Science Teachers Association (CSTA) (2011). CSTA K-12 computer science standards. The ACM K-12 Education Task Force. Retrieved from https://goo.gl/aM7X3A.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates Inc.
Cohen, J. (1994). The earth is round (p < .05). American Psychologist, 49(12), 997-1003.
Cropley, D. H. (2016). Creativity in engineering. Multidisciplinary contributions to the science of creative thinking (pp. 155-173). Singapore : Springer.
Cuny, J., Snyder, L., & Wing, J. M. (2010). Demystifying computational thinking for non-computer scientists. Unpublished manuscript in progress. Retrieved from https://goo.gl/ucFwE9.
Gerstner, S., & Bogner, F. X. (2010). Cognitive achievement and motivation in hands‐on and teacher‐centred science classes: Does an additional hands‐on consolidation phase (concept mapping) optimise cognitive learning at work stations?. International Journal of Science Education, 32(7), 849-870.
Gonzalez-Gomez, J., Valero-Gomez, A., Prieto-Moreno, A., & Abderrahim, M. (2012). A new open source 3d-printable mobile robotic platform for education. Advances in Autonomous Mini Robots, 49-62.
Goodman, B. E., Freeburg, E. M., Rasmussen, K., & Meng, D. (2006). Elementary education majors experience hands-on learning in introductory biology. Advances in Physiology Education, 30(4), 195-203.
International Society for Technology in Education (ISTE) (2014). Operational definition of computational thinking. Retrieved from http://www.iste.org/docs/ct-documents/computational-thinking-operational-definition-flyer.pdf?sfvrsn=2
Kalelioğlu, F. (2015). A new way of teaching programming skills to K-12 students: Code. org. Computers in Human Behavior, 52, 200-210.
Kandlhofer, M., & Steinbauer, G. (2016). Evaluating the impact of educational robotics on pupils’ technical-and social-skills and science related attitudes. Robotics and Autonomous Systems, 75, 679-685.
Karp, T., 與 Maloney, P. (2013). Exciting young students in grades K-8 about STEM through an afterschool robotics challenge. American Journal of Engineering Education, 4(1), 39-54
Ke, F. (2014). An implementation of design-based learning through creating educational computer games: A case study on mathematics learning during design and computing. Computers & Education, 73, 26-39.
Nugent, G., Barker, B., Grandgenett, N., & Adamchuk, V. I. (2010). Impact of robotics and geospatial technology interventions on youth STEM learning and attitudes. Journal of Research on Technology in Education, 42(4), 391-408.
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.
Rother, K., Rother, M., Pleus, A., & Belzen, A. U. Z. (2010). Multi-stage learning aids applied to hands-on software training. Briefings in Bioinformatics, 11(6), 582-586. doi: Doi 10.1093/Bib/Bbq024
Stohlmann, M., Moore, T. J., & Roehrig, G. H. (2012). Considerations for teaching integrated STEM education. Journal of Pre-College Engineering Education Research (J-PEER), 2(1), 1-4.
Tsai, K. C. (2016). Fostering creativity in design education: Using the creative product analysis matrix with chinese undergraduates in Macau. Journal of Education and Training Studies, 4(4), 1-8.
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 of London A: mathematical, physical and engineering sciences, 366(1881), 3717-3725.
Wu, C. C., Tseng, I. C., & Huang, S. L. (2008). Visualization of program behaviors: Physical robots versus robot simulators. Informatics Education-Supporting Computational Thinking, 53-62.