問題導向的學習策略已被廣泛地運用在機器人程式設計等跨領域課程，但在此策略中加入範例的引導是否能更具學習成效，是常被關切的課題。本研究以準實驗法，探究「範例引導混合問題導向學習」以及「一般問題導向學習」兩種不同但常用之教學策略的成效，針對95名國民小學五年級學生，進行各14節的機器人程式設計課程。課程前後以自編關鍵能力量表評量學生的自主學習、合作學習、問題解決、批判思考及創造創新等能力。在評量實施後以國際運算思維測驗（Bebras test）評量學生運算思維，和以認知負荷量表評量學生在兩種學習策略下，學習機器人程式設計的認知負荷。研究結果顯示混合範例引導與問題導向學習策略，因為有適切的鷹架範例導入，可以：提升國小學生的自主學習、合作學習、問題解決以及批判思考等能力，並在學習機器人程式設計上有較好的學習成就，同時提升學生在機器人程式設計的運算思維、降低學生的知負荷。

Problem-based learning(PBL) strategy has been widely applied to interdisciplinary curricula, including robotics programming. However, whether incorporating the guidance of examples into this strategy can increase learning effectiveness is frequently discussed. This study explores the effectiveness of two different but commonly used learning strategies, that is, “problem-based learning combined with example guidance ” and “general problem-based learning”, through a quasi-experimental method. A 14-period robotics programming course was implemented for 95 elementary school fifth-graders. A self-designed key competency scale was used to assess the students’ competencies before and after the course, including autonomous learning, cooperative learning, problem solving, critical thinking, and creativity and innovation. Following the assessment, the Bebras test was administered to evaluate the computational thinking of the students, and a cognitive load assessment was implemented to evaluate the cognitive load of students when learning robotics programming through the two different learning strategies.Consequently, the example-guided and problem-based combined learning strategy can enhance elementary school students’ autonomous learning, cooperative learning, problem solving, and critical thinking skills, achieve better learning achievement effectiveness in robotics programming because of the incorporation of appropriate scaffolding examples. In addition, the mixed learning strategy can also improve the students’ computational thinking in robotics programming and reduce their cognitive load.

壹、中文部分
徐凡鈞（2018）。數位時代，取自https://www.bnext.com.tw/article/48885/school-42-is-located-in-paris
王秀鶯（2013）。導入Scratch程式教學對國中生自我效能與學習成就之探究～以程式設計課程為例。人文社會學報，9 (1)，1-15。
何品萱、王麗君、陳明溥（2017）。互動式擴增實境在國中生機器人程式設計學習之探討。中等教育，68（3），16-33。
吳正己（2010，7月）。臺灣中小學資訊科技教育的沿革與現況。中國教育技術協會資訊技術教育專業委員會第六屆學術年會暨海峽兩岸信息技術教育研討會，西安。
吳正己、林凱胤( 1997 ) 。問題解決導向的程式語言教學。資訊教育雜誌，創刊十年特刊， 75-83 。
吳正已、林凱胤（1997）。問題解決導向的程式語言教學。資訊教育雜誌創刊十年特刊，75-83。
吳志緯（2002）。國小學生以電腦樂高進行科學學習之個案研究（未出版之碩士論文）。臺北師範學院科學教育研究所，台北。
吳金聰、施木炎（2005）。國小數學教學的問題及其解決之道--從認知負荷的觀點談起。國教天地，162，23-28。
吳偉元（2018）。運用問題導向學習教學策略提升國小學童運算思維能力之研究-以程式設計課程為例（未出版之碩士論文）。國立臺北教育大學，臺北市。
吳清山（2011）。發展學生核心素養，提升學生未來適應力。研習資訊，28 (4)，1-3。
李隆盛、楊秀全（2019）。範例引導學習與問題導向學習之教學策略對國小學生機器人程式學習的影響。數位學習科技期刊，11（4），77-104。
何偉雲（2001）。初步探討影響學童自然科學習成就因素的排序。屏東師院學報，14，933-952。
林信良(2015)。視覺化程式語言的未來。取自http://www.ithome.com.tw/voice/93114
施又瑀（2018）。臺灣程式教育的困境與展望。臺灣教育評論月刊，7（9），1-8。
施能木（2008）。應用樂高教學方案在國小生活科技課程對學童創造力影響之研究（未出版之博士論文）。國立臺灣師範大學工教系科技教育組，台北。
胡凌嫣（2016年12月14日）。逆向課程設計法：課綱為經、評量為緯。選才電子報，268。2017年8月10日，取自：https://www.ceec.edu.tw/xcepaper/cont?xsmsid=0J066588036013658199&sid=0J184523333374769111
柴昌維、陳家驊（2013）。輔助機器人設計開發之經驗學習方法剖析。2013 福祉科技與服務管理國際研討會。南開科技大學。取自 http://ee.nkut.edu.tw/people/writing_seminar.php?Sn=149 。
桃園市教育局（2016）。桃園市國民小學資訊科技課程綱要。桃園市：教育局。
涂金堂（2011）。運用「範例(worked-out example)」在國小數學問題解決的教學實驗研究。教育心理學報，43(1)，25-50。
徐新逸、項志偉（2016）。翻轉教室融入國小六年級資訊課程對批判性思考能力之影響。課程與教學，19(4)，32-60。
翁楊絲茜、夏至賢、王湄雁 (2014)。樂高機器人輔助程式學習之探討。數位學習科技期刊，6(4)，1-12。
國家教育研究院（2015）。核心素養發展手冊。新北市：國家教育研究院。
張玉山（1994）。從杜威的教育思想看成人教育的特性。社教資料雜誌，191，10-15。
張玉山（2008）。以問題解決為基礎的科技教學活動設計以創意機器人研習為例。研習資訊，25(3)、61-69。
張基成、陳怡靜(2018)。機器人跨領域STEM主題式統整課程與任務導向式教學的設計及及評鑑。科學教育學刊，26(4)，305-331。
張基成、曾繁勛、嚴萬軒、陳怡靜（2019）。帆船機器人STEM跨領域統整課程的發展及學生認知成就與態度－網狀式主題統整與重理解的課程設計。第八屆工程、技術與科技教育學術研討會，57-73。
張曉瑀(2018)。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(未出版碩士論文)。國立臺灣師範大學，臺北市。
張德銳、林縵君（2016）。PBL在教學實習上的應用成效與困境之研究。師資培育與教師專業發展期刊，9（2），1-25。
教育部（2014）。十二年國民基本教育課程綱要總綱。臺北市：教育部。
教育部（2016）。2016-2020 資訊教育總藍圖。臺北市：教育部。
教育部（2016）。十二年國教科技領域「資訊科技」科目課程綱要草案。臺北市：教育部。
教育部（2020）。國民小學科技教育及資訊教育課程發展參考說明。臺北市：教育部。
梁耀東（2010）。樂高機器人在國小數學教學的應用―以Kolb的學習理論為基礎（未出版之碩士論文）。國立屏東大學，屏東縣。
莊謙本，黃議正，沈家伃（ 2011）。植基認知負荷取向在課程教材設計及其教學成效分析，屏東教育大學學報-教育類，36，169-206。
郭秀緞（2005）。以認知負荷的觀點探討數學問題設計的適切性。教育研究，13，169-182。
郭惠雯（2008）。背不動的「數學」書包--從認知負荷觀點談數學學習。師說，204，19-20。
陳怡靜、張基成（2015 ）。兩岸機器人教育的現況與發展，中等教育，66（3），37-59。
陳明溥（2003, 12月10日）。網際網路與問題解決學習。台大教與學期刊電子報，20。
陳密桃（2003）。 認知負荷理論及其對教學的啟示。國立高雄師範大學教育學系教育學刊，21，29-51。
陸希平、王本榮、陳家玉（2006）。問題導向學習。醫學教育，10(2)，89-97。
黃子瓔（2010）。從3R到4C：淺談21世紀能力的發展與趨勢。數位典藏與學習電子報，9（11）。取自http://newsletter.teldap.tw/news/InsightReportContent.php?nid=4112&lid=466
董松喬(2011)。運用互動式電子白板進行社會領域問題導向學習之研究（未出版之碩士論文）。國立臺北教育大學教育傳播與科技研究所。2011。1-92。
趙貞怡(2013)，原住民學童在電腦樂高機器人課程中的創造力與團隊合作能力 。教育實踐與研究，26(1)，33-62。
趙嘉浩、梁至中、蔡孟蓉(2017)。機器人課程教材鷹架對高中生未來關鍵學習能力的影響。數位學習科技期刊，9(3)，95-114。
劉明洲（2017）。創客教育、運算思維、程式設計～幾個從「想」到「做」的課程與教學設計觀念。臺灣教育評論月刊，6（1），138-140。
劉蔚之（2008, 6月27日）。歐盟「關鍵能力」建置之最新現況。教育評鑑與發展研究中心電子報。取自http://epaper.creed.ntnu.edu.tw/index.php?id=16
潘培鈞、賴阿福（2014），應用多元學習策略於Scratch程式設計課程對於五年級學童問題解決能力之影響。國教新知，61(4), 46-63。
蔡清田（2011）。課程改革中的素養與核心素養。教育研究月刊，206，119-130。
蔡清田（2014)。國民核心素養：十二年國教課程改革DNA。臺北市：高等教育。
蔡清田（2016）。核心素養研究與課程設計的新進展。教育與多元文化研究，13，233-246。
蕭佳明、黃瑛綺 (2012)。樂高機器人應用於科學與創意教育市場創業之研究，遠東學報，29(3)，375-386。
賴信豪（2018）。淺談程式設計實習課程對於學生培養問題解決能力之障礙與改善策略。臺灣教育評論月刊，7（6），104-108。
賴麗珍(譯)(2008)。重理解的課程設計－專業發展實用手冊(原作者：Jay McTighe & Grant Wiggins)。台北市：心理出版社。
謝建全、施能木、鄭承昌（2004）。機械人組合教學輔具在國小創意學習與問題解決歷程教學上之應用。資優教育學術研討會，臺南，2004年11月。

貳、外文部分
Allan, J. (2011). Responsibly competent: Teaching, ethics and diversity. Policy Futures in Education, 9(1), 130-137.
Altin, H., & Pedaste, M. (2013). Learning approaches to applying robotics in science education. Journal of Baltic Science Education, 12(3), 365-378.
Azevedo, R., Verona, M. E., & Cromley, J. G. (2001). Fostering students collaborative problem solving with RiverWeb. In J. D. Moore, C. L. Redfield, & W. L. Johnson (Eds.), Artificial intelligence in education:Al-ED in the wired and wireless future,167-175. Amsterdam: IOS Press.
Barnett, J., & Hodson, D. (2001). Pedagogical context knowledge: toward a fuller understanding of what good science teachers know. Science Education, 85(4), 426-453.
Belland, B. R. (2017). Instructional scaffolding in STEM education. Springer: Cham,Switzerland.
Benitti, F.（2012). Exploring the educational potential of robotics in schools：A sySTEMatic review. Computers & Education,58 (3)，978-988.
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.
Blanchard, S., Freiman, V., & Lirette-Pitre, N. (2010). Strategies used by elementary schoolchildren solving robotics-based complex tasks: Innovative potential of technology. Procedia Social & Behavioral Sciences, 2(2), 2851-2857.
Blanchard, S., Freiman, V., & Lirrete-Pitre, N. (2010). Strategies used by elementary schoolchildren solving robotics-based complex tasks: Innovative potential of technology. Procedia - Social and Behavioral Sciences, 2(2), 2851-2857.
Bredenfeld, A., Hofmann, A., & Steinbauer, G. (2010). Robotics in education initiatives in Europe-status, shortcomings and open questions. In Workshop Proceedings of Intl. Conf. on Simulation, Modeling and Programming for Autonomous Robots (SIMPAR 2010) .
Brennan, K., & Resnick, M. (2012, April). New frameworks for studying and assessing the development of computational thinking. Paper presented at the Annual American Educational Research Association Meeting, Vancouver, Canada.
Brunken, R., Plass, J. L., & Leutner, D. (2003). Direct measurement of cognitive load in multimedia learning. Educational Psychology, 38(1), 53-61.
Casad, B. J., & Jawaharlal, M. (2012). Learning through guided discovery: An engaging approach to K-12 STEM education. In American Society for Engineering Education. American Society for Engineering Education.
Chambers, J., Carbonaro, M., & Rex, M. (2007). Scaffolding knowledge construction through robotic technology: A middle school case study. Electronic Journal for the Integration of Technology in Education, 6, 55-70.
Chi, M. T. M., Bassok, M., Lewis, M. W., Reimann, P., & Glaser, R. (1989).Self-explanations: How students study and use examples in learning to solve problems. Cognitive Science, 13, 145-182.
Ching, Y., Yang, D., Wang, S. et al. (2019).Elementary School Student Development of STEM Attitudes and Perceived Learning in a STEM Integrated Robotics Curriculum. TechTrends,63,590-601.
Coelho, A. D.,Assis, W. O.,Silva, J. G.(2009).The Scientific Initiation as an Instrument of Training for Future Researchers.9th IFIP World Conference on Computers in Education-WCCE.
Collins, A., & Halverson, R. (2010). The second educational revolution: Rethinking education in the age of technology. Journal of Computer Assisted learning, 26(1), 18-27.
Commission of the European Communities (2005). Proposal for a recommendation on key competences for lifelong learning, COM 548 final. Brussels: Commission of European Communities.
Cooper, G., & Sweller, J. (1987). Effects of schema acquisition and rule automation on mathematical problem-solving transfer. Journal of Educational Psychology, 79(4), 347-362.
de Kereki, I. F. (2008). Scratch: Applications in computer science 1. 38th ASEE/IEEE Frontiers in Education Conference, Saratoga Springs, NY, October 22-25, 2008. Retrieved from http://icee.usm.edu/ICEE/conferences/FIEC2008/papers/1044.pdf
Dalbey, J. and Linn, M. C. (1986). Cognitive consequences of programming: Augmentations to basic instruction. Journal of Educational Computing Research,2, 75-93.
Dean Jr, D. & Kuhn, D. (2007). Direct instruction vs. discovery: The long view. Science Education, 91(3), 384-397.
Deek, F. P., Kimmel, H. & McHugh, J. A. (1998).Pedagogical changes in the delivery of the first-course in computer science: Problem solving, then programming. Journal of Engineering Education, 87, 313-320.
Deek, F. P. (1999). A framework for an automated problem solving and program development environment. Journal of Integrated Design and Process Science, 3(3), 1-13.
Eguchi, A., Educational Robotics for Promoting 21st Century Skills. Journal of Automation Mobile Robotics and Intelligent SySTEMs, 2014. 8,5-11.
Falloon, G. (2015). Building computational thinking through programming in K-6 education: A New Zealand experience.In L. Gomez Chova, A. Lopez Martinez, & I. Chandel Torres (Eds.), EDULearn Proceedings (882–892). Barcelona, Spain: IATED Academy.
Fernaeus, Y., Kindborg, M., & Scholz, R. (2006). Programming and tools: Rethinking children's programming with contextual signs. Conference on Interaction Design and Children IDC '06, June 7-9, Tampere, Finland. ACM Press.
Fisch, K. (2006). Did you know. Retrieved from http://thefischbowl.blogspot.tw/2006/08/did-you-know.html
Fund, Z. (2007). The effects of scaffolded computerized science problem-solving on achievement outcomes: A comparative study of support programs. Journal of Computer Assisted Learning, 23, 410-424.
Garner, S.(2003).Learning to program using part-complete solutions. In Computer Based Learning in Science, Nicosia, Cyprus.
Garner, S.(2009). A quantitative study of a software tool that supports a Part-Complete Solution Method on learning outcomes. Journal of Information Technology Education,8, 285-310.
Gerber, L. C., Calasanz-Kaiser, A., Hyman, L., Voitiuk, K., Patil, U., & Riedel-Kruse, I.H. (2017). Liquid-handling Lego robots and experiments for STEM education and research. PLOS Biology, 15(3), 1-9.
Grover, S., & Pea, R. (2013). Computational Thinking in K–12. Educational Researcher, 42(1), 38-43.
Hadjerrouit, S. (2008). Towards a blended learning model for teaching and learning computer programming: A case study. Informatics in Education, 7(2), 181-210.
Hannafin, M., Land, S., & Oliver, K. (1999). Open learning environments: Foundations, methods, and models. In C. M. Reigeluth (Ed.), Instructional-design theories and models: A new paradigm of instructional theory (115-140). Mahwah, NJ: Erlbaum.
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.
Hoffman, B. & Spatariu, A. (2008). The influence of self-efficacy and metacognitve prompting on math problem-solving efficiency. Contemporary Educational Psychology, 33(4), 875-893.
Hohn, R. L. & Moraes, I. (1998). Use of rule-based elaboration of worked examples to promote the acquisition of programming plans. The Journal of Computer Information SySTEMs, 38(2), 35-40.
Howland, J., Jonassen, D., & Marra, R. (2012). Meaningful learning with technology (4th ed.). Upper Saddle River, NJ: Pearson.
ISTE (2017). ISTE Standards for Students. Retrieved from https://www.iste.org/standards/for-students
Jonassen, D. H. (2000). Towards a design theory of problem solving. Educational Technology, Research and Development, 48(4), 63-85.
Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J.(2003). The expertise reversal effect.Educational Psychologist, 38, 23-32.
Kalyuga, S., & Sweller, J. (2004). Measuring knowledge to optimize cognitive load factors during instruction. Journal of Educational Psychology, 96, 558-568.
Kandlhofer, M., & Steinbauer, G. (2015). Evaluating the impact of educational robotics on pupils’ technical- and social-skills and science related attitudes. Robotics and Autonomous SySTEMs, 75, 679-685.
Kelly, T. L. (1939). The Selection of Upper and Lower Groups for the Validation of Test Items. Journal of Educational Psychology, 30,17-24.
Kobsiripat W. (2015). Effects of the media to promote the scratch programming capabilities creativity of elementary school students. Social and Behavioral Sciences, 174, 227-232.
Lathifah A., Budiyanto C., Yuana.,RA (2019).The contribution of robotics education in primary schools: Teaching and learning.AIP Conference Proceedings , 2194 , 020053.
Lazonder, A. W. & Harmsen, R. (2016). Meta-analysis of inquiry-based learning: Effects of guidance. Review of Educational Research, 86(3), 681-718.
Lim, B. R. (2001). Guidelines for designing inquiry-based learning on the Web: Online professionaldevelopment of educators. Unpublished dissertation, Indiana University, Bloomington, IN.
Lin, C. Y., & Reigeluth, C. M. (2016). Scaffolding wiki-supported collaborative learning for small-group projects and whole-class collaborative knowledge building. Journal of Computer Assisted Learning, 32(6), 529-547.
Linder, S. P. Nestrick, B. E.,Mulders, S.,Lavelle, C. L.(2001).Facilitating active learning With inexpensive mobile robots.Journal of Computing Sciences in Colleges, 16(4),21-33.
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.
Makino, K., Matsuo, Y., & Ohyama, Y. (2012). Management of a lecture of robot contest for many students. IFAC Proceedings Volumes, 45(11), 336-341.
Master, A., Cheryan, S., Moscatelli, A., & Meltzoff, A. N. (2017). Programmingexperience promotes higher STEM motivation among first-grade girls. Journal of Experimental Child Psychology, 160, 92-106.
Matson, T.E., Pauly, R. and DeLoach, S. (2003) Robotic simulators to develop logic and critical thinking skills in under served K-6 school children. In Proceedings of the 2003 ASEE Midwest Section Meeting.
McTighe, J., & Wiggins, G. (2012). Understanding by design framework. Retrieved from http://www.ascd.org/ASCD/pdf/siteASCD/ publications/UbD_WhitePaper0312. pdf
Mouratidis, A., Vansteenkiste, M., Lens, W., & Sideridis, G. (2008). The motivating role of positive feedback in sport and physical education: Evidence for a motivational model. Journal of Sport & Exercise Psychology, 30(2), 240-268.
Mwangi, W., & Sweller, J. (1998). Learning to solve compare word problems: The effect of example format and generating self-explanations. Cognition and Instruction, 16, 173-199.
National Science and Technology Council, (2018).Charting a course for Success: America’s Strategy for STEM Education, Retrieved from https://www.whitehouse.gov/wp-content/uploads/2018/12/STEM-Education-Strategic-Plan-2018.pdf
Nilssona, B., & Folkestad, G. (2005). Children's practice of computer-based composition. Music Education Research, 7(1), 21-37.
NMC/CoSN Horizon Report--2017 K-12 Edition. Retrieved from https://www.nmc.org/publication/nmccosn-horizon-report-2017-k-12-edition/
Ormrod, J. E. (2011). Educational psychology: Developing learners (7th ed.). Boston: Pearson Education.
Paas, F., van Gog, T., & Sweller, J. (2010). Cognitive load theory: New conceptualizations, specifications, and integrated research perspectives. Educational Psychology Review, 22(2), 115-121.
Papert, S., & Harel, I. (1993). Constructionism. Norwood, NJ：Ablex Publishing Corporation.
Paris, C., Colineau, N., Lu, S., & Vander Linden, K. (2005). Automatically generating effective online help. International Journal on E-learning, 4(1), 83-103.
Pérez-Marín, D., Hijón-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.
Petre, M., & Price, B. (2004). Using robotics to motivate‘back door’learning. Education and Information Technologies, 9(2), 147-158.
Renkl, A. (2011). Instruction based on examples. In R. E. Mayer & P. A. Alexander (Eds.), Handbook of research on learning and instruction , 272-295.
Renkl, A. (2014).Learning from worked examples: How to prepare students for meaningfulproblem solving. In V. A. Benassi, C. E. Overson,& C. M Hakala (Eds.), Applying the Science of Learning in Education: Infusing psychological science into curriculum. Re-trievable form http://teachpsych.org/ebooks/asle2014/index.php.
Rissanen, A. J. (2014). Active and peer learning in STEM education strategy. Science education international, 25(1), 1-7.
Rychen, D. S. (2004). Key competencies for all: an overarching conceptual frame of reference. Developing Key Competencies in Education: Some lessons from International and National Experience. Geneva: UNESCO/International Bureau of Education.
Sáez-López J. M. et al. (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.
Sargent, R., Resnick, M., Martin, F., & Silverman, B. (1996). Building and learning with programmable brick. Constructionism in Practice (161-173). Mahwah, NJ：Lawrence Erlbaum Associates.
Savage, E. & Sterry, L. (1990). A conceptural framework for technology education.
Sisman,B., Kucuk,S., Yaman Y.(2021) .The Effects of Robotics Training on Children’s Spatial Ability and Attitude Toward STEM.International Journal of Social Robotics, 13(2), 379-389.
Sklar,E., Parsons,S., Azhar,M.Q., & Andrewlevich,V.(2006). Educational robotics in Brooklyn (short version), in Proc. the AAAI Mobile Robot Workshop.
Silva, E. (2009). Measuring Skills for 21st Century Learning. The Phi Delta Kappan, 90(9), 630-634.
Smith, P. L., & Ragan, T. J. (1999). Instructional design (2nd ed.). New York, NY：John Wiley & Sons.
Stergiopoulou, M., Karatrantou, A., Panagiotakopoulos, C.(2016).Educational robotics and STEM education in primary education: a pilot study using the H&S electronic sySTEMs platform. In: International Conference EduRobotics, 88-103.
Swaid, S. I. (2015). Bringing Computational Thinking to STEM Education. Procedia Manufacturing, 3, 3657-3662.
Sweller, J. (2004). Instructional design consequences of an analogy between evolution by natural selection and human cognitive architecture. Instructional Science, 32(l), 9-3l.
Tam, M. (2001). Introducing problem-based learning: Learning matters at Lingnan . from http://www.ln.edu.hk/tlc/learning_matters/05-2001-242001.pdf
Taylor, K. (2016). Collaborative robotics, more than just working in groups: effects of student collaboration on learning motivation, collaborative problem solving, and science process skills in robotic activities. (Doctoral dissertation). Retrieved March 20, 2019 from https://scholarworks.boisestate.edu/cgi/viewcontent.cgi?article=2179&context=td.
United Nations Education, Scientific and Cultural Organization. (2003). Nurturing the treasure: vision and strategy 2002-2007. Retrieved from http://unesdoc.unesco.org/images/0013/001311/131145e.pdf
Valente, J. A. (1995). Logo as a Window into the Mind. Logo Update, 4(1). Retrieved November 30, 2007, from http://el.media.mit.edu/logo-foundationlpubs/logoupdate/
Van Merrienboer, J. J. G., & Sweller, J. (2005). Cognitive load theory and complex learning: recent developments and future directions. Educational Psychology Review, 17, 147-177.
Vygotsky, L. S. (1978). Mind in society:The development of higher psychological processes. Cambridge,MA: Harvard University Press.
Ward, M., & Sweller, J. (1990). Structuring effective worked examples.Cognition and Instruction, 7, 1-39.
Ward, T. B. Smith, S. M., & Finke, R. A.（2005）。創造性認知。載於R. J. Sternberg（主編），創造力（李乙明、李淑貞譯）（頁2-19）。臺北市：五南。
Williams, K., Igel, I., Poveda, R., Kapila, V., & Iskander, M. (2012). Enriching K-12 science and mathematics education using LEGOs. Advances in Engineering Education, 3(2), 1-27.
Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35.
Wiggins, G. P., McTighe, J., Kiernan, L. J., & Frost, F. (1998). Understanding by design. Alexandria, VA: Association for Supervision and Curriculum Development.
Winslow, L. E. (1996). Programming pedagogy: A psychological overview. SIGCSE Bulletin, 28, 17-22.
Wood, D. J., Bruner, J. S., & Ross, G.(1976). The role of tutoring in problem solving. Journal of Child Psychology and Psychiatry, 17(2),89-100.
Wouters, P., & van Oostendorp, H. (2013).A meta-analytic review of the role of instructional support in game-based learning.Computers & Education, 60, 412-425.
Yánez-Aldecoa, C., Okada, A., Palau, R. (2015). New learning scenarios for the 21st century related to Education, Culture and Techonology, Revista de universidady sociedad del conocimiento, 12(2), 87-102.
Zembal-Saul, C., Munford, D., Crawford, B., Friendrichsen, P., & Land, S. (2002). Scaffolding preservice science teachers’ evidence-based arguments during an investigation of natural selection. Research in Science Education, 32(4), 437-463.