研究生: |
張曉瑀 Chang, Hsiao-Yu |
---|---|
論文名稱: |
目標設定與引導策略對不同先備知識國中生以智慧眼鏡輔助機器人程式設計學習之成效及動機探討 Effects of Goal-Setting, Learning Guidance and Prior Knowledge on Junior High Students’ Learning of Robot Programming Supported by Smart Glass |
指導教授: |
陳明溥
Chen, Ming-Puu |
學位類別: |
碩士 Master |
系所名稱: |
資訊教育研究所 Graduate Institute of Information and Computer Education |
論文出版年: | 2018 |
畢業學年度: | 106 |
語文別: | 中文 |
論文頁數: | 110 |
中文關鍵詞: | 程式設計 、目標設定 、引導策略 、體驗式學習 、機器人教育 |
英文關鍵詞: | programming, goal-setting, guidance strategy, experiential learning, robotic instruction |
DOI URL: | http://doi.org/10.6345/THE.NTNU.GICE.001.2018.F02 |
論文種類: | 學術論文 |
相關次數: | 點閱:289 下載:22 |
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本研究旨在探討目標設定及引導策略對於國中學習者在機器人程式設計學習成效及學習動機。本研究之學習者依循學習單任務之目標設定及智慧眼鏡提供引導之範例影片進行機器人專題。本研究採因子設計之準實驗研究法,研究對象為八年級學習者,參與者為新北市某國中八年級159位學生,有效樣本141人。自變項包含目標設定、引導策略及先備知識;目標設定依任務目標屬性分為「整體目標」與「階段目標」;引導策略依引導方式分為「問題引導」與「程序引導」;先備知識依學習者前測成績分為「高先備知識」與「低先備知識」。依變項包含程式設計之學習成效(知識記憶、知識理解、知識應用)與學習動機(價值成分、期望成分)。
研究結果顯示:就學習成效而言,(1)在知識記憶方面,高先備知識學習者表現優於低先備知識學習者;整體目標組結合問題引導策略在知識記憶學習表現優於結合程序引導策略;(2)在知識理解方面,以整體目標為目標設定時,高先備知識學習者表現優於低先備知識學習者;(3)在知識應用方面,高先備知識學習者表現上優於低先備知識學習者;問題引導組學習表現優於程序引導組。在學習動機方面,(4)各實驗組學習者對機器人程式設計學習活動皆抱持著正向的學習動機,而問題引導組學習者有較高的學習動機表現。
The purpose of this study was to investigate the effects of types of goal-setting, learning guidance and prior knowledge on junior high school students’ learning performance and motivation toward robot programming. A quasi-experimental design was employed and a total of 141 eighth graders participated in the experimental activity. The independent variables included types of goal-setting (long-term goals vs. sub-term goals), learning guidance (question-guidance vs. procedure-guidance), and prior knowledge (high vs. low). The dependent variables were students’ learning performance and motivation.
The results revealed that: (a) for the comprehension performance, the high-prior knowledge group outperformed the low-prior knowledge group while receiving the long-term goal; the long-term goal combined with the question-guidance led to better comprehension performance; (b) as for the application performance, learners with high-prior knowledge had superior performance than the learners with low-prior knowledge did, and the question-guidance group outperformed the procedural-guidance group; and (c) all participants showed positive motiviation toward the robot programming learning, and particularly, the question-guidance group revealed higher degree of motiviation than the procedure-guidance group did.
中文部分
張春興(1996)。教育心理學-三化取向的理論與實務。臺北市:東華。
教育部(2017)。十二年國民基本教育課程總要總綱。臺北市:教育部。
豐佳燕、陳明溥(2017)。自我解釋與目標設定對國小學童學習遊戲程式設計之影響研究。第21屆全球華人電腦教育應用大會(GCCCE 2017)。北京:北京師範大學。
韓宜娣(2011)。鷹架支援與自我效能對國小學生程式設計學習表現與學習態度之影響。國立臺灣師範大學,台北市。
呂郁欣(2017)。引導策略與學習順序對國小機器人程式設計學習成效及態度之影響(未出版碩士論文)。國立臺灣師範大學,台北市。
盧健瑋(2017)。數位學習環境與引導策略對高低先備知識高中生數學遞迴學習成效與動機之影響(未出版碩士論文)。國立臺灣師範大學,台北市。
英文部分
Alcañiz, M., Contero, M., Pérez-López, D. & Ortega, M. (2010). Augmented reality technology for education. New Achievements in Technology Education and Development, 247–256.
Altin, H. (2013). Learning approaches to applying robotic in science education. Journal of Baltic Science Education, 12(3), 365–378.
Azuma, R. T. (1997). A survey of augmented reality. Presence: Teleoperators and Virtual Environments, 6(4), 3553–85.
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review.
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.
Billinghurst, M. (2002). Augmented reality and education. New Horizons for Learning, (figure 1), 21(3) 195-209.
Bower, B. T. (2016). Teaching introductory robotics programming. IEEE Robotics & Automation Magazine, (june), 67–73.
Brusso, R. C. & Orvis, K. A. (2013). The impeding role of initial unrealistic goal-setting on videogame-based training performance: Identifying underpinning processes and a solution. Computers in Human Behavior, 29(4), 1686–1694.
Brusso, R. C., Orvis, K. A., Bauer, K. N. & Tekleab, A. G. (2012). Interaction among self-efficacy, goal orientation, and unrealistic goal-setting on videogame-based training performance. Military Psychology, 24(1), 1–18.
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 and Education, 109, 162–175.
Chen, M. P. & Liao, B. C. (2015). Augmented reality laboratory for high school electrochemistry course. Proceedings - IEEE 15th International Conference on Advanced Learning Technologies: Advanced Technologies for Supporting Open Access to Formal and Informal Learning, ICALT 2015, 132–136.
Chen, M. P. & Tsai, C. C. (2016). Augmented-reality as a scaffolding tool for learning geometry. In In EdMedia: World Conference on Educational Media and Technology Association for the Advancement of Computing in Education (AACE). (pp. 1525–1529).
Clark, R. E. (2009). How much and what type of guidance is optimal for learning from instruction ? Constructivist Instruction: Success or Failure, 158–183.
CSTA. (2011). Computational thinking in K-12 education leadership toolkit. Computer Science Teachers Association (CSTA) and the International Society for Technology in Education (ISTE), 43.
Dean Jr, D. & Kuhn, D. (2007). Direct instruction vs. discovery: The long view. Science Education, 91(3), 384–397.
Del Bosque, L., Martinez, R. & Torres, J. L. (2015). Decreasing failure in programming subject with augmented reality tool. Procedia Computer Science, 75(Vare), 221–225.
Dewey, J. (1938). Experience and education. Kappa Delta Pi.
Erez, A. & Judge, T. A. (2001). Relationship of core self-evaluations to goal setting, motivation and performance. Journal of Applied Psychology, 86(6), 1270–1279.
Feng, C. Y. & Chen, M. P. (2014). The effects of goal specificity and scaffolding on programming performance and self-regulation in game design. British Journal of Educational Technology, 45(2), 285–302.
Gagne, R. (1985). The Conditions of Learning (4th.). New York: Holt, Rinehart & Winston.
Genc, Y., Riedel, S., Souvannavong, F., Akinlar, C. & Navab, N. (2002). Marker-less tracking for AR: A learning-based approach. Proceedings - International Symposium on Mixed and Augmented Reality, ISMAR 2002, 295–304.
Girvan, C., Conneely, C. & Tangney, B. (2016). Extending experiential learning in teacher professional development. Teaching and Teacher Education, 58, 129–139.
Grover, S. & Pea, R. (2013). Computational thinking in K-12: A review of the state of the field. Educational Researcher, 42(1), 38–43.
Hill, J. R. & Hannafin, M. J. (2001). Teaching and learning in digital environments: The resurgence of resource-based learning. Educational Technology Research and Development, 49(3), 37–52.
Hollenbeck, J. R. & Brief, A. P. (1987). The effects of individual differences and goal origin on goal setting and performance. Organizational Behavior and Human Decision Processes, 40(3), 392–414.
Issa, G., Hussain, S. M. & Al-Bahadili, H. (2014). Competition-based learning. International Journal of Information and Communication Technology Education, 10(1), 1–13.
Jarvis, P., Holford, J. & Griffin, C. (2003). The theory and practice of learning. Kogan Page.
Joshi, M. P. (2005). Experiential learning process: Exploring teaching and learning of strategic management framework through the winter survival exercise. Journal of Management Education, 29(5), 672–695.
Kaczmarczyk, L. C., Petrick, E. R., East, J. P. & Herman, G. L. (2010). Identifying student misconceptions of programming. Proceedings of the 41st ACM Technical Symposium on Computer Science Education - SIGCSE ’10, 107–111.
Kalelioğlu, F. (2015). A new way of teaching programming skills to K-12 students: Code.org. Computers in Human Behavior, 52, 200–210.
Katiyar, A., Kalra, K. & Garg, C. (2015). Marker based augmented reality. Advances in Computer Science and Information Technology, 2(5), 441–445.
Kesim, M. & Ozarslan, Y. (2012). Augmented reality in education: Current technologies and the potential for education. Procedia - Social and Behavioral Sciences, 47(222), 297–302.
Kipper, G. & Rampolla, J. (2012). Augmented reality: An emerging technologies guide to AR. Elsevier, 1–158.
Kobsiripat, W. (2015). Effects of the media to promote the scratch programming capabilities creativity of elementary school students. Procedia - Social and Behavioral Sciences, 174, 227–232.
Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Prentice Hall, Inc. New Jersey: Prentice-Hall: Englewood Cliffs.
Korkmaz, Ö. (2016). The effect of Scratch and Lego Mindstorms Ev3 based programming activities on academic achievement, problem solving skills and logical mathematical thinking skills of students. Malaysian Online Journal of Educational Sciences, 4(3), 73–88.
Latham, G. P., Mitchell, T. R. & Dossett, D. L. (1978). Importance of participative goal setting and anticipated rewards on goal difficulty and job performance. Journal of Applied Psychology, 63(2), 163–171.
Lazonder, A. W. & Harmsen, R. (2016). Meta-analysis of inquiry-based learning: Effects of guidance. Review of Educational Research, 86(3), 681–718.
Lewin, K. (1935). A dynamic theory of personality. Journal of Heredity.
Lin, M. H., Chen, M. P. & Chen, C. F. (2013). Exploring peer scaffolding opportunities on experiential problem solving learning. In C.B\vadic\va, N. T.Nguyen & M.Brezovan (Eds.), Computational Collective Intelligence. Technologies and Applications: 5th International Conference, ICCCI 2013, Craiova, Romania, September 11-13, 2013, Proceedings (pp. 572–581). Berlin, Heidelberg: Springer Berlin Heidelberg.
Liu, W., Cheok, A. D., Lim, C. M. L. & Theng, Y. L. (2007). Mixed reality classroom: learning from entertainment. DIMEA ’07 Proceedings of the 2nd International Conference on Digital Interactive Media in Entertainment and Arts P, ages 65-72.
Locke, E. A. (1996). Motivation through conscious goal setting. Applied and Preventive Psychology, 5(2), 117–124.
Locke, E. A. & Latham, G. P. (2006). New directions in goal-setting theory. Current Directions in Psychological Science, 15(5), 265–269.
Lunenburg, F. C. (2011). Goal-setting theory of motivation. International Journal of Management, Business, and Administration, 15(1), 1–6.
Lykke, M., Coto, M., Jantzen, C., Mora, S. & Vandel, N. (2015). Motivating students through positive learning experiences : A comparison of three learning designs for computer programming courses. Journal of Problem Based Learning in Higher Education, 3(2), 80–108.
Matlen, B. J. & Klahr, D. (2013). Sequential effects of high and low instructional guidance on children’s acquisition of experimentation skills: Is it all in the timing? Instructional Science, 41(3), 621–634.
Milgram, P., Takemura, H., Utsumi, A. & Kishino, F. (1994). Augmented reality: A class of displays on the reality-virtuality continuum. International Society for Optics and Photonics, 2351(Telemanipulator and Telepresence Technologies), 282–292.
Naharro-Berrocal, F., Pareja-Flores, C., Urquiza-Fuentes, J. & Velázquez-Iturbide, J. Á. (2002). Approaches to comprehension-preserving graphical reduction of program visualizations. Proceedings of the 2002 ACM Symposium on Applied Computing - SAC ’02, 771.
Ouahbi, I., Kaddari, F., Darhmaoui, H., Elachqar, A. & Lahmine, S. (2015). Learning basic programming concepts by creating games with Scratch programming environment. Procedia - Social and Behavioral Sciences, 191, 1479–1482.
Pea, R. & Kurland, D. M. (1984). On the cognitive effects of learning computer programming. New Ideas in Psychology, 2(2), 137–168.
Radu, I. & MacIntyre, B. (2009). Augmented-reality Scratch: A tangible programming environment for children. ACM CHI 09 Workshop on Tangibles for Children, 210–213.
Ruggiero, D. & Green, L. (2017). Problem solving through digital game design: A quantitative content analysis. Computers in Human Behavior, 73, 28–37.
Sáez-López, J.-M., Román-González, M. & Vázquez-Cano, E. (2016). Visual programming languages integrated across the curriculum in elementary school: A two year case study using Scratch in five schools. Computers & Education, 97, 129–141.
Seo, D. W. & Lee, J. Y. (2013). Direct hand touchable interactions in augmented reality environments for natural and intuitive user experiences. Expert Systems with Applications, 40(9), 3784–3793.
Sirkiä, T. & Sorva, J. (2012). Exploring programming misconceptions: An analysis of student mistakes in visual program simulation exercises. 12th Koli Calling International Conference on Computing Education Research, 19–28.
Soloway, E. (1986). Learning to program: Learning to construct mechanisms and explanations. Communications of the ACM, 29(9), 850–858.
Sommerauer, P. & Müller, O. (2014). Augmented reality in informal learning environments: A field experiment in a mathematics exhibition. Computers and Education, 79(2014), 59–68.
Spohrer, J. C. & Soloway, E. (1986). Novice mistakes: Are the folk wisdoms correct? Communications of the ACM, 29(7), 624–632.
Teo, Y. H. & Chai, C. S. (2009). Scaffolding online collaborative critiquing for educational video production. Knowledge Management and E-Learning, 1(1), 51–66.
Tosi, H. L., Locke, E. A. & Latham, G. P. (1991). A theory of goal setting and task performance. The Academy of Management Review, 16(2), 480.
Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35.
Wolz, U., Stone, M., Pearson, K., Pulimood, S. M. & Switzer, M. (2011). Computational thinking and expository writing in the middle school. ACM Transactions on Computing Education, 11(2), 1–22.