簡易檢索 / 詳目顯示

研究生: 陳怡靜
Chen, Yi-Ching
論文名稱: 任務導向式STEM帆船機器人主題統整課程的設計與評估之研究
指導教授: 張基成
學位類別: 博士
Doctor
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: 144
中文關鍵詞: 機器人機器人課程STEM教育STEM課程Arduino認知負荷任務導向教學
英文關鍵詞: robot, robotics curriculum, STEM curriculum, STEM education, Arduino, cognitive load, task-oriented instruction
DOI URL: http://doi.org/10.6345/DIS.NTNU.DTAHRD.001.2019.F06
論文種類: 學術論文
相關次數: 點閱:274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
  • 本研究以跨領域主題統整模式之網狀式方法建構出帆船機器人跨領域STEM主題統整課程,並結合線串式方法來呈現各相關知識之間的連結關係。另運用重理解的課程設計模式發展出帆船機器人跨領域STEM統整課程。機器人課程是目前用來激發學生對科學機器人課程是目前用來激發學生對科學、科技、工程及數學(簡稱STEM)較普遍且受歡迎的課程。本研究採用開放原始碼的軟硬體作為製作機器人的材料,以80位高中一年級學生實驗對象,分為兩班上課,實驗組採用任務導向機器人STEM統整課程,控制組則實施傳統無STEM統整機器人課程。實施一學期的課程後,研究結果顯示實驗組的學生對於STEM統整知識、技能表現及態度皆優於控制組之表現。實驗組的學生之認知負荷較控制組低,且對任務導向STEM主題統整課程滿意度較傳統機器人課程高。本研究發展的帆船機器人跨領域STEM統整課程及任務導向教學策略可供後續發展相關主題統整課程與教學之參考。

    This study has constructed a knowledge map of cross-disciplinary integrative STEM curriculum on robotic sailboat by using the webbed approach in the cross-disciplinary thematic integration model. The threaded method was used to display the linking relationships among relevant concepts on the map. Moreover, the Understanding by Design Model (UbD) was used to develop cross-disciplinary integrative STEM curriculum on robotic sailboat with Arduino. The study involved 82 Grade 10 students; divided into two groups, the experimental group experienced an integrated robotics STEM course, whereas the comparison group participated in a curriculum with commercial robotics. After a semester, the quantitative and qualitative data showed that the experimental group reported significantly more positive perceptions of integrated STEM, with strengthened knowledge, skills, and positive attitude towards related fields. The experimental group reported significantly lower cognitive load than control group. The cross-disciplinary integrative STEM curriculum on robotic sailboat and the task-oriented instructional strategy might be as references for future development in integrative course and instruction on relevant themes.

    摘 要 i Abstract ii 目 錄 iii 表 次 vi 圖 次 ix 第一章 緒論  第一節 研究緣起 1  第二節 研究目的與待答問題 5  第三節 名詞釋義 6  第四節 研究範圍與限制 7   第五節 研究重要性與貢獻 8 第二章 文獻探討  第一節 機器人STEM課程與教學 9  第二節 機器人STEM課程的教學成效 16  第三節 認知負荷與任務導向的教學策略 20  第四節 機器人STEM主題統整課程之評估 26 第三章 研究設計與實施  第一節 研究流程與方法 29  第二節 任務導向帆船機器人STEM主題統整課程設計 40  第三節 實驗設計 52  第四節 研究工具 65  第五節 資料處理與分析 77 第四章 研究結果與討論  第一節 兩組STEM知識成就之差異 79  第二節 兩組STEM實作技能之差異 84  第三節 兩組STEM態度之差異 87  第四節 兩組認知負荷之差異 89  第五節 學習成效與認知負荷之關係 91  第六節 機器人STEM課程之學習滿意度 114  第七節 綜合討論 116 第四章 結論與建議  第一節 結論 123  第二節 建議 128 參考文獻  一、中文部分 130  二、外文部分 131 附錄  附錄一、實作技能評量表 139  附錄二、態度量表 141  附錄三、認知負荷量表 142  附錄四、滿意度調查表 143

    一、中文文獻
    吳明隆、張毓仁(2011)。SPSS (PASW) 與統計應用分析 II。臺北市:五南。
    李坤崇、歐慧敏(2001)。統整課程理念與實務。臺北市:心理。
    林智中(2002)。課程統整真的比分科課程為好嗎?課程與教學,5(4),141-154。
    邱皓政(2008)。量化研究與統計分析: SPSS中文視窗版資料分析範例解析。臺北市:五南。
    高雄帆船學校(2013)。認識帆船課程。民108年6月20日,取自:http://140.115.236.72/demo-personal/xd703/web/C1300256/onlineV.html
    教育部(2014)。十二年國教課程綱要總綱。103年11月。http://www.rootlaw.com.tw/LawContent.aspx?LawID=A040080081012600-1031128
    單文經(2001)。解析Beane對課程統整理論與實際的主張。教育研究集刊,47,57-89。
    游家政(2000)。學校課程的統整及其教學。課程與教學,3(1),19-37。

    二、英文文獻
    Abaid, N., Kopman, V., & Porfiri, M. (2013). An attraction toward engineering careers: The story of a Brooklyn outreach program for KuFFFD12 Students. IEEE Robotics & Automation Magazine, 20(2), 31-39.
    Abdel-Salam, T., Sawaf, N. E., & Williamson, K. (2009). Robotics explorations to enhance information technology literacy in rural schools. Journal of Communication and Computer, 6(3), 55-63.
    Akkerman, S. F., Bronkhorst, L. H., & Zitter, I. (2013). The complexity of educational design research. Quality and Quantity, 47(1), 421-439.
    Alfieri, L., Higashi, R., Shoop, R., & Schunn, C. D. (2015). Case studies of a robot-based game to shape interests and hone proportional reasoning skills. International Journal of STEM Education, 2(1), 4.
    Alimisis, D. (2013). Educational robotics: Open questions and new challenges. Themes in Science & Technology Education, 6(1), 63-71.
    Altin, H., & Pedaste, M. (2013). Learning approaches to applying robotics in science education. Journal of Baltic Science Education, 12(3), 365-377.
    Araújo, A., Portugal, D., Couceiro, M. S., & Rocha, R. P. (2015). Integrating Arduino-based educational mobile robots in ROS. Journal of Intelligent & Robotic Systems, 77(2), 281-298.
    Arduino. (2018). Arduino official website. Retrieved 3 Oct, 2018, from http://www.arduino.cc/
    Avsec, S., Rihtaršič, D., & Kocijancic, S. (2014). A predictive study of learner attitudes toward open learning in a robotics class. Journal of Science Education and Technology, 23(5), 692-704.
    Barak, M., & Zadok, Y. (2007). Robotics projects and learning concepts in science, technology and problem solving. International Journal of Technology and Design Education, 19(3), 289-307.
    Barker, B. S., & Ansorge, J. (2007). Robotics as means to increase achievement scores in an informal learning environment. Journal of Research on Technology in Education, 39(3), 229-243.
    Barker, B. S., Nugent, G., & Grandgenett, N. F. (2014). Examining fidelity of program implementation in a STEM-oriented out-of-school setting. International Journal of Technology and Design Education, 24(1), 39-52.
    Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182.
    Beane, J. A. (1997). Curriculum integration. New York: Teachers College Press.
    Beane, J. A. (2011). Curriculum integration and the disciplines of knowledge. In J. Sefton-Green, P. Thomson, K. Jones, and L. B. Routledge (Eds.), The Routledge International Handbook of Creative Learning (pp. 193-199). New York, NY: Taylor and Francis.
    Becker, K., & Park, K. (2011). Effects of integrative approaches among science, technology, engineering, and mathematics (STEM) subjects on students' learning: A preliminary meta-analysis. Journal of STEM Education: Innovations and Research, 12(5/6), 23.
    Benitti, F. B. V. (2012). Exploring the educational potential of robotics in schools: A systematic review. Computers & Education, 58(3), 978-988.
    Bers, M. U. (2007). Project InterActions: A multigenerational robotic learning environment. Journal of Science Education & Technology, 16(6), 537-552.
    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.
    Bybee, R. W. (2010, 08/27). What is STEM education? Science, 329(5995), 996-996.
    Bybee, R. W. (2013). Case for STEM education : Challenges and opportunities. Arlington, VA: National Science Teachers Association.
    Campbell, D. M., & Harris, L. S. (2001). Collaborative theme building: How teachers write integrated curriculum. Needham Heights, MA: Allyn & Bacon.
    Carr, R. L., Bennett Iv, L. D., & Strobel, J. (2012). Engineering in the K-12 STEM standards of the 50 U.S. states: An analysis of presence and extent. Journal of Engineering Education, 101(3), 539-564.
    Chen, Y., & Chang, C. C. (2018). The impact of an integrated robotics STEM course with a sailboat topic on high school students’ perceptions of integrative STEM, interest, and career orientation. EURASIA Journal of Mathematics, Science and Technology Education, 14(12).
    Chism, N. V. N., & Szabó, B. S. (1997). How faculty development programs evaluate their services. Journal of Staff, Program, and Organization Development, 15(2), 55–62.
    Corbalan, G., Kester, L., & van Merrienboer, J. J. G. (2008). Selecting learning tasks: Effects of adaptation and shared control on learning efficiency and task involvement. Contemporary Educational Psychology, 33(4), 733-756.
    Cristoforis, P. D., Pedre, S., Nitsche, M., Fischer, T., Pessacg, F., & Pietro, C. D. (2013). A behavior-based approach for educational robotics activities. IEEE Transactions on Education, 56(1), 61-66.
    Doerschuk, P., Bahrim, C., Daniel, J., Kruger, J., Mann, J., & Martin, C. (2016). Closing the gaps and filling the STEM pipeline: A multidisciplinary approach. Journal of Science Education and Technology, 1-14.
    Eguchi, A. (2016). RoboCupJunior for promoting STEM education, 21st century skills, and technological advancement through robotics competition. Robotics and Autonomous Systems, 75, 692-699.
    English, L. D. (2016). STEM education K-12: Perspectives on integration. International Journal of STEM Education, 3(1), 1-8.
    Felder, R. M., Brent, R., & Prince, M. J. (2011). Engineering instructional development: Programs, best practices, and recommendations. Journal of Engineering Education, 100(1), 89-122.
    Feldon, D. F., Timmerman, B. C., Stowe, K. A., & Showman, R. (2010). Translating expertise into effective instruction: The impacts of cognitive task analysis (CTA) on lab report quality and student retention in the biological sciences. Journal of Research in Science Teaching, 47(10), 1165-1185.
    Fernandes, A., Couceiro, M. S., Portugal, D., Machado Santos, J., & Rocha, R. P. (2015). Ad hoc communication in teams of mobile robots using zigbee technology. Computer Applications in Engineering Education, 23(5), 733-745.
    Fogarty, R. (1991). Ten ways to integrate curriculum. Educational Leadership, 49(2), 61-65.
    Fogarty, R., Stoehr, J., & Gardner, H. (2008). Integrating curricula with multiple intelligences (2nd ed.). Thousand Oaks, CA: Corwin Press.
    Fortunati, L., Esposito, A., Ferrin, G., & Viel, M. (2014). Approaching social robots through playfulness and doing-it-yourself: Children in action. Cognitive Computation, 6(4), 789-801.
    Francom, G. M., & Gardner, J. L. (2013). How task-centered learning differs from problem-based learning: Epistemological influences, goals, and prescriptions. Educational Technology, 53(3), 33-38.
    Galeriu, C., Edwards, S., & Esper, G. (2014). An arduino investigation of simple harmonic motion. The Physics Teacher, 52(3), 157-159.
    Gonzalez-Gomez, J., Valero-Gomez, A., Prieto-Moreno, A., & Abderrahim, M. (2012). A new open source 3d-printable mobile robotic platform for education. In U. Rückert, S. Joaquin, and W. Felix (Eds.), Advances in autonomous mini robots (pp. 49-62). Berlin Heidelberg, Germany: Springer.
    Hagedorn, L. S., & Purnamasari, A. V. (2012). A realistic look at STEM and the role of community colleges. Community College Review, 40(2), 145-164.
    Hernandez, P., Bodin, R., Elliott, J., Ibrahim, B., Rambo-Hernandez, K., Chen, T., & Miranda, M. (2014). Connecting the STEM dots: Measuring the effect of an integrated engineering design intervention. International Journal of Technology & Design Education, 24(1), 107-120.
    Hussain, S., Lindh, J., & Shukur, G. (2006). The effect of LEGO training on pupils' school performance in mathematics, problem solving ability and attitude: Swedish data. Journal of Educational Technology & Society, 9(3), 182-194.
    Jacobs, H. H., Supervision, A. F., & Development, C. (1989). Interdisciplinary curriculum. Alexandria, VA : Association for Supervision and Curriculum Development.
    Jalani, N. H., & Sern, L. C. (2014). Effects of example-problem based learning on transfer performance in circuit theory. Journal of Technical Education and Training, 6(2), 28-37.
    Jaulin, L., & Le Bars, F. (2013). An interval approach for stability analysis: Application to sailboat robotics. IEEE Transactions on Robotics, 29(1), 282-287.
    Jojoa, E. M. J., Bravo, E. C., & Cortes, E. B. B. (2010). Tool for experimenting with concepts of mobile robotics as applied to children's education. IEEE Transactions on Education, 53(1), 88-95.
    Jungck, J. R., Gaff, H. D., Fagen, A. P., & Labov, J. B. (2010). Beyond BIO2010: Celebration and opportunities at the intersection of mathematics and biology. CBE-Life Sciences Education, 9(3), 143-147.
    Kalyuga, S., & Liu, T. C. (2015). Guest editorial: Managing cognitive load in technology-based learning environments. Educational Technology & Society, 18(4), 1-8.
    Kalyuga, S., & Singh, A. M. (2016). Rethinking the boundaries of cognitive load theory in complex learning. Educational Psychology Review, 28(4), 831-852.
    Kanter, D. E. (2010). Doing the project and learning the content: Designing project-based science curricula for meaningful understanding. Science Education, 94(3), 525-551.
    Katehi, L., Pearson, G., & Feder, M. (2009). Engineering in K-12 education: understanding the status and improving the prospects. Washington, DC: The National Academies Press.
    Kennedy, T. J., & Odell, M. R. L. (2014). Engaging students in STEM education. Science Education International, 25(3), 246-258.
    Kirschner, P., Sweller, J., & Clark, R. E. (2006). Why unguided learning does not work: An analysis of the failure of discovery learning, problem-based learning, experiential learning and inquiry-based learning. Educational Psychologist, 41(2), 75-86.
    Kolodner, J. L., Camp, P. J., Crismond, D., Fasse, B., Gray, J., Holbrook, J., Puntambekar, S., & Ryan, M. (2003). Problem-based learning meets case-based reasoning in the middle-school science classroom: Putting learning by design(tm) into practice. Journal of the Learning Sciences, 12(4), 495-547.
    Krajcik, J., McNeill, K. L., & Reiser, B. J. (2008). Learning‐goals‐driven design model: Developing curriculum materials that align with national standards and incorporate project‐based pedagogy. Science Education, 92(1), 1-32.
    Kubilinskiene, S., Zilinskiene, I., Dagiene, V., & Sinkevièius, V. (2017). Applying robotics in school education: A systematic review. Baltic Journal of Modern Computing, 5(1), 50-69.
    Leppink, J., Paas, F., van Gog, T., van der Vleuten, C. P. M., & van Merriënboer, J. J. G. (2014). Effects of pairs of problems and examples on task performance and different types of cognitive load. Learning and Instruction, 30, 32-42.
    Lindh, J., & Holgersson, T. (2007). Does lego training stimulate pupils’ ability to solve logical problems? Computers & Education, 49(4), 1097-1111.
    López-Rodríguez, F. M., & Cuesta, F. (2016). Andruino-A1: Low-cost educational mobile robot based on Android and Arduino. Journal of Intelligent & Robotic Systems, 81(1), 63-76.
    Mahoney, M. (2010). Students’ attitudes towards STEM: Development of an instrument for high school STEM-based programs. Journal of Technology Studies, 36(1), 53-64.
    Marvel, J. A., Falco, J., & Marstio, I. (2015). Characterizing task-based human–robot collaboration safety in manufacturing. IEEE Transactions on Systems, Man & Cybernetics. Systems, 45(2), 260-275.
    Mason, R., & Cooper, G. (2013). Mindstorms robots and the application of cognitive load theory in introductory programming. Computer Science Education, 23(4), 296-314.
    Meissner, B., & Bogner, F. X. (2013). Towards cognitive load theory as guideline for instructional design in science education. World Journal of Education, 3(2), 24-37.
    Merrill, M. D. (2002a). First principles of instruction. Educational Technology Research & Development, 50(3), 43-59.
    Merrill, M.D. (2002b). A pebble-in-the-pond model for instructional design. Performance Improvement, 41(7), 39–44.
    Merrill, M. D. (2007). A task-centered instructional strategy. Journal of Research on Technology in Education, 40(1), 5-22.
    Merrill, M. D. (2009). Finding e³ (effective, efficient, and engaging) instruction. Educational Technology, 49(3), 15-26.
    Merrill, M. D., & Gilbert, C. G. (2008). Effective peer interaction in a problem centered instructional strategy. Distance Education, 29(2), 199-207.
    Mitnik, R., Nussbaum, M., & Recabarren, M. (2009). Developing cognition with collaborative robotic activities. Educational Technology & Society, 12(4), 317-330.
    Mondada, F., Bonani, M., Riedo, F., Briod, M., Pereyre, L., Rétornaz, P., & Magnenat, S. (2017). Bringing robotics to formal education: The Thymio open-source hardware robot. IEEE Robotics & Automation Magazine, 24(1), 77-85.
    Nugent, G., Barker, B., & Grandgenett, N. (2012). The impact of educational robotics on student STEM learning, attitudes, and workplace skills. In B. Barker, G. Nugent, N. Grandgenett, & V. Adamchuk (Eds.), Robots in K-12 education: A new technology for learning (pp. 186–203). Hershey, PA: IGI Global.
    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.
    Nugent, G., Barker, B., Grandgenett, N., & Welch, G. (2016). Robotics camps, clubs, and competitions: Results from a US robotics project. Robotics and Autonomous Systems, 75, Part B, 686-691.
    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.
    Petre, M., & Price, B. (2004). Using robotics to motivate ‘back door’ learning. Education & Information Technologies, 9(2), 147-158.
    Pêtrès, C., Romero-Ramirez, M., & Plumet, F. (2012). A potential field approach for reactive navigation of autonomous sailboats. Robotics & Autonomous Systems, 60(12), 1520-1527.
    Plumet, F., Petres, C., Romero-Ramirez, M.-A., Gas, B., & Ieng, S.-H. (2015). Toward an autonomous sailing boat. IEEE Journal of Oceanic Engineering, 40(2), 397-407.
    Rihtaršič, D., Avsec, S., & Kocijancic, S. (2016). Experiential learning of electronics subject matter in middle school robotics courses. International Journal of Technology and Design Education, 26(2), 205-224.
    Rockland, R., Bloom, D.S., Carpinelli, J., Burr-Alezander, L., Hirsch, L.S., Kimmel, H. (2010). Advancing the “E” in K-12 STEM education. The Journal of Technology Studies, 36(1), 53-64.
    Rusk, N., Resnick, M., Berg, R., Pezalla-Granlund, M. (2008). New pathways into robotics: Strategies for broadening participation. Journal of Science Education and Technology,17, 59-69.
    Schnotz, W., & Kürschner, C. (2007). A reconsideration of cognitive load theory. Educational Psychology Review, 19(4), 469-508.
    Seul, J. (2013). Experiences in developing an experimental robotics course program for undergraduate education. IEEE Transactions on Education, 56(1), 129-136.
    Siiman, L. A., Pedaste, M., Tõnisson, E., Sell, R., Jaakkola, T., & Alimisis, D. (2014). A review of interventions to recruit and retain ICT students. International Journal of Modern Education and Computer Science, 6(3), 45-54.
    Silk, E. M., Higashi, R., Shoop, R., & Schunn, C. D. (2009). Designing technology activities that teach mathematics: Teaching mathematics in a technology classroom requires more than simply using mathematics with technology. The Technology Teacher, 69(4), 21-28.
    Slangen, L., van Keulen, H., & Gravemeijer, K. (2011). What pupils can learn from working with robotic direct manipulation environments. International Journal of Technology and Design Education, 21(4), 449-469.
    Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. Sociological methodology, 13, 290-312.
    Somyürek, S. (2015). An effective educational tool: Construction kits for fun and meaningful learning. International Journal of Technology and Design Education, 25(1), 25-41.
    Stohlmann, M., Moore, T. J., & Roehrig, G.H. (2012). Considerations for teaching integrated STEM education. Journal of Pre-College Engineering Education research, 2(1), 28-34.
    Sullivan, F. R., & Heffernan, J. (2016). Robotic construction kits as computational manipulatives for learning in the STEM disciplines. Journal of Research on Technology in Education, 48(2), 105-128.
    Sullivan, F. R., & Lin, X. (2012). The ideal science student: Exploring the relationship of Students' perceptions to their problem solving activity in a robotics context. Journal of Interactive Learning Research, 23(3), 1-36.
    Sullivan, F. R., & Moriarty, M. A. (2009). Robotics and discovery learning: Pedagogical beliefs, teacher practice, and technology integration. Journal of Technology and Teacher Education, 17(1), 109-142.
    Sweller, J. (2010). Element interactivity and intrinsic, extraneous, and germane cognitive load. Educational Psychology Review, 22(2), 123-138.
    Ucgul, M., & Cagiltay, K. (2014). Design and development issues for educational robotics training camps. International Journal of Technology and Design Education, 24(2), 203-222.
    van Gog, T., Paas, F., & Sweller, J. (2010). Cognitive load theory: Advances in research on worked examples, animations, and cognitive load measurement. Educational Psychology Review, 22(4), 375-378.
    Van Merriënboer, J. J., & Kirschner, P. A. (2012). Ten steps to complex learning: A systematic approach to four-component instructional design. Mahwah, NJ: Erlbaum.
    Van Merriënboer, J. J. G., Kester, L., & Paas, F. (2006). Teaching complex rather than simple tasks: Balancing intrinsic and germane load to enhance transfer of learning. Applied Cognitive Psychology, 20(3), 343-352.
    Van Merrienboer, J. J., & Sweller, J. (2005). Cognitive load theory and complex learning: Recent developments and future directions. Educational Psychology Review, 17(2), 147-177.
    Van Merriënboer, J. J. G., & Sweller, J. (2010). Cognitive load theory in health professional education: Design principles and strategies. Medical Education, 44(1), 85-93.
    Wiggins, G. P., & McTighe, J. (2011). The understanding by design guide to creating high-quality units. Alexandria, VA: Association for Supervision and Curriculum Development.
    Wiggins, G. T., & McTighe, J. (2005). Understanding by design. Alexandria, VA: Association for Supervision and Curriculum Development.
    Williams, D. C., Ma, Y., Prejean, L., Ford, M. J., & Lai, G. (2008). Acquisition of physics content knowledge and scientific inquiry skills in a robotics summer camp. Journal of Research on Technology in Education, 40(2), 201-216.
    Yilmaz, M., Ozcelik, S., Yilmazer, N., & Nekovei, R. (2013). Design-oriented enhanced robotics curriculum. IEEE Transactions on Education, 56(1), 137-144.
    Young-Corbett, D. E., Nussbaum, M. A., & Winchester Iii, W. W. (2010). Usability evaluation of drywall sanding tools. International Journal of Industrial Ergonomics, 40(1), 112-118.
    Yuen, T. T., Boecking, M., Stone, J., Tiger, E. P., Gomez, A., Guillen, A., & Arreguin, A. (2014). Group tasks, activities, dynamics, and interactions in collaborative robotics projects with elementary and middle school children. Journal of STEM Education: Innovations and Research, 15(1), 39-45.

    無法下載圖示 本全文未授權公開
    QR CODE