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題名:技術高中人工智慧深度學習特色課程之發展與成效評估研究
作者:蔡至誠
作者(外文):TSAI, CHIH-CHENG
校院名稱:國立高雄師範大學
系所名稱:工業科技教育學系
指導教授:朱耀明
羅希哲
學位類別:博士
出版日期:2021
主題關鍵詞:人工智慧深度學習人工智慧物聯網翻轉教學成效評估artificial intelligencedeep learningartificial intelligence of thingsflipped teachingeffectiveness evaluation
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本研究之目的在於透過4D雙菱形設計以建構適合於技術型高中實施「SPOC—AIoT模組課程」之模式,據此發展其教學模組並加以檢驗其成效。本研究採用混合研究法,歷經前導研究之實驗研究教學、量化與質性訪談得以建構「SPOC—AIoT模組課程」概略模型後,再導入第二階段之教學實驗加以修正以驗證本課程所發展「SPOC—AIoT模組課程」之可行性,並透過本研究據之研擬「SPOC—AIoT學習量表」,以自我效能、學習焦慮為自變項,基於科技接受模式之學習參與,探討學生接受本教學模組後對以學習成效與滿意度為依變項之影響。
本研究對象為高雄市某技術高中一年級電機電子群學生共72位(前導研究與導入研究各36位)歷時10個月之實驗教學,採模組化課程進行AIoT相關實作知能之翻轉教學。資料之收集與分析以量化為主(包含描述性統計、相依t檢定、SmartPLS之測量模型分析與結構模型分析)與質性訪談分析為輔之方式進行。依據研究結果與討論提出本研究之結究結論彙整如下:
1. 本研究建構「技術型高中人工智慧深度學習能力指標」適用於發展技術型高中學生學習AI之教學目標。
2. 本研究建構「SPOC—AIoT教學模組」有效提升學生學習AIoT知能。
3. 本研究建構「SPOC—AIoT學習量表」之研究架構有助於分析學生之學習成效與滿意度
4. 本研究建構「SPOC—AIoT教學模組」有效提升學生學習AIoT之學習成效
5. 本研究建構「SPOC—AIoT教學模式」,包含4D雙菱形設計模型四階段與PARDE行動研究四步驟。
The purpose of this study is to develop a model for theimplementation of the SPOC-AIoT modular curriculum in vocational high schoolsthrough a 4D double diamond design, and to develop and test the effectivenessof the teaching module. This study adopts a mixed research approach toconstruct a general model of the SPOC-AIoT modular curriculum through theexperimental research teaching, quantitative and qualitative interviews of thepilot study, and then to introduce the second stage teaching experiment toverify the feasibility of the SPOC-AIoT modular curriculum developed in thisprogram. The SPOC-AIoT learning scale was developed based on the self-efficacyand learning anxiety as the independent variables, and the learningparticipation based on the technology acceptance model, to investigate theeffect of students' acceptance of the teaching module on the learningeffectiveness and satisfaction as the dependent variables.
A total of 72 high school freshmen (36 in the pilot study and 36 inthe introductory study) from electrical subgroup of a vocational high school inKaohsiung City were taught in a 10-month experimental program, using amodularized curriculum to conduct flipped teaching of  their AIoT-related practical knowledge. Thedata collection and analysis were mainly quantitative (including descriptivestatistics, dependent t-checking, SmartPLS measurement model analysis andstructural model analysis) and qualitative interview analysis. Based on thefindings and discussions, the conclusions of this study are summarised asfollows.
1. Thisstudy constructs the "Vocational High School AI Deep Learning CompetencyIndicator" which is suitable for developing the teaching objectives of AIlearning for vocational  high schoolstudents.
2. Thisstudy constructs the "SPOC-AIoT Teaching Module" to effectivelyenhance students' knowledge of AIoT learning.
3. The studyconstructs the "SPOC-AIoT Learning Scale" as a research framework tohelp analyse students' learning effectiveness and satisfaction
4. Thisstudy constructs the "SPOC-AIoT Teaching Module" to effectivelyenhance students' learning effectiveness in learning AIoT
5. Thisstudy constructs the "SPOC-AIoT Teaching Model", which consists offour stages of the 4D double diamond design model and four steps of the PARDEaction research.
一、中文部分
中華人民共和國國務院(2017)。“十三五”國家科技創新規劃。取自http://big5.gov.cn/gate/big5/www.gov.cn/gongbao/content/2016/content_5103134.htm
中華人民共和國國務院(2017)。新一代人工智慧發展規劃。取自http://www.gov.cn/zhengce/content/2017-07/20/content_5211996.htm
中華人民共和國教育部(2017)。普通高中信息技術課程標準。取自http://www.zgjsks.com/uploadfile/2018/0118/2018118191745.pdf
中華民國行政院(2018) 。台灣人工智慧行動計畫。取自:https://www.ey.gov.tw/Page/448DE008087A1971/a28cd96b-bcc3-49ae-a09c-0381dbba69a7
日本人工知能技術戦略会議(2017),”人工知能の研究開発目標と産業化のロードマップ(案)”, http://www.nedo.go.jp/content/100862419.pdf。(日本人工知能技術戦略会議(第5回)會議資料2)
日本內閣府(2016)。第5期科学技術基本計画。取自:http://www8.cao.go.jp/cstp/kihonkeikaku/5honbun.pdf
王勝雄(2019)。Scratch 結合Arduino開放硬體對國中學生程式設計學習成效之研究。國立臺中教育大學數位內容科技學系碩士在職專班碩士論文,台中市。 取自https://hdl.handle.net/11296/2ys2c7曲建仲 (2018)。 機器是如何學習與進步? 人工智慧的核心技術與未來。科學月刊, 4,頁 282-291。
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[The Effects of Interactive Augmented RealityStrategies on Novice Programming]。中等教育, 68(3),頁 16-33。 doi: 10.6249/se.2017.68.3.02
李開復、王詠剛(2017)。人工智慧來了。:遠見天下文化出版股份有限公司。
周秉誼(2016)。淺談Deep Learning原理及應用。國立台灣大學計算機及資訊網路中心。取自http://www.cc.ntu.edu.tw/chinese/epaper/0038/20160920_3805.html。
林志成、田耐青、林仁煥、田育昆(2013)。特色課程的涵義與理論。載於林志成(主編)。特色學校理論、實務與案例(頁120-128)。臺北市:高等教育。
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),頁 5-20。
林庭安(2018)。為什麼你也要懂「程式設計」?培養「運算思維」,做事更精確、有效率。經理人。取自https://www.managertoday.com.tw/articles/view/55799。
林書弘、陳牧言 (2019)。 人工智慧技術於智慧醫療之理論探討與實務應用[Artificial Intelligence in Smart Health:Investigation of Theory and Practice]。護理雜誌, 66(2),頁 7-13。 doi: 10.6224/jn.201904_66(2).02
林珮萱 (2013)。21世紀人才必備的8大素養3大關鍵能力。遠見雜誌網站。資料取自:https://www.gvm.com.tw/article.html?id=17667
林業盈 (2015)。 應用樂高機器人發展資優教育方案之教學實例分析與探討[Analysis of Teaching Example by Applying LEGO Robotto Develop Program of Gifted Education]。資優教育季刊(137),頁 33-44。 doi: 10.6218/geq.2015.137.33-44
法國國民暨高等教育研究部(2017)。國家人工智慧戰略。取自http://www.enseignementsup-recherche.gouv.fr/cid116143/la-strategie-france-i.a.-soutenir-la-dynamique-francaise-autour-de-l-intelligence-artificielle.html
侯鈞元 (2017)。 人工智慧發展趨勢與台灣切入策略。電工通訊季刊,頁 11-15。
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),頁 1-8。
科技部科國司(2015)。跨領域工程教育人才培育與研究整合型計畫徵求書。取自https://www.most.gov.tw/folksonomy/detail?subSite=main&article_uid=0de281e6-1b96-4046-8fd1-d21746ba2399&menu_id=65bdde0c-029a-11e5-aa78-bcaec51ad21b&content_type=P&view_mode=listView。
胡惠君 (2018)。 4Ds 教學方法於農鄉服務設計之課程實踐。大學教學實務與研究學刊, 2(1),頁 79-106。
翁舒婷(2018)。AI教育向下扎根,台灣小學也要開始學AI了!。數位時代。取自https://www.bnext.com.tw/article/50339/ai-education-senoir-high-school。
國家教育研究院(2015)。十二年國教科技領域「資訊科技」科目課程綱要草案。未出版。
國家教育研究院(2018)。十二年國民基本教育課程綱要國民中小學暨普通型高級中等學校科技領域。取自https://www.naer.edu.tw/ezfiles/0/1000/attach/52/pta_18529_8438379_60115.pdf
國家教育研究院(2019)。十二年國民基本教育課程綱要國民中小學暨普通型高級中等學校科技領域。取自https://www.naer.edu.tw/ezfiles/0/1000/attach/52/pta_18529_8438379_60115.pdf。
張瀞文(2016)。程式設計入課綱,教育轉機或危機?。親子天下網站。取自https://www.parenting.com.tw/article/5070133-%E7%A8%8B%E5%BC%8F%E8%A8%AD%E8%A8%88%E5%85%A5%E8%AA%B2%E7%B6%B1%EF%BC%8C%E6%95%99%E8%82%B2%E8%BD%89%E6%A9%9F%E6%88%96%E5%8D%B1%E6%A9%9F%EF%BC%9F/。
教育部(2016)。2016-2020 資訊教育總藍圖。取自https://depart.moe.edu.tw/ED2100/News.aspx?n=1353704343B62511&sms=2ADD120E8E2615E3
教育部運算思維推動計畫  http://compthinking.csie.ntnu.edu.tw/
陳怡靜 (2015)。 機器人競賽的裁判與指導教師談機器人教育。中等教育。
谢榕 (2017)。 人工智能的国际化—多元化创新教学模式。计算机教育(6),頁 165-170。
谢榕、李霞 (2014)。 人工智能课程教学案例库建设及案例教学实践[Article]。计算机教育 / IT Education(19),頁 93。
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。
黃燕萍 (2017)。 運用理解設計品質成果導向學習理論探討程式語言課程教學成效。大學教學實務與研究學刊, 1(2),頁 125-144。
劉怡甫 (2013)。 與全球十萬人作同學: 談 MOOC 現況及其發展。評鑑雙月刊(42),頁 41-44。
劉怡甫 (2014)。 從 anti-MOOC 風潮談 MOOCs 轉型與 SPOCs 擅場。評鑑雙月刊(48),頁 36-41。
劉欣宜、洪詠善 (2016)。 高中職學校發展特色課程之課綱問題分析。高中職課程發展與設計: Development and Design in Senior and VocationalHigh Schools。
蔡玉卿、吳俊憲 (2017)。 學校參與特色招生特色課程的發展與實施困境: 以兩所個案高中為例。臺灣教育評論月刊, 6(12),頁 38-41。
鄭國明、吳宛臻(2017)。 機器人教學對高中生創造力之影響。 載於 Book 機器人教學對高中生創造力之影響,頁1579-1582。
鄭國明、林群峰、溫嘉榮 (2017)。 Kodu 遊戲設計教學對國小學童運算思維提昇成效之研究。TANET2017 臺灣網際網路研討會,頁 1566-1572。
賴和隆 (2016)。 應用運算思維於高中資訊教學設計之分享。教育脈動(6),頁 143-155。
謝雯伃(譯) (2018)。思考的演算:跟著電腦學思考,你也可以成為計算思考大師(Paul Curzon, Peter William McOwan著) 。臺北市:八旗文化。
蘇芳琪 (2018)。 人工智慧教學輔助系統應用。儀科中心簡訊(147),頁 9-10。
鐘森盈(2016)。職業學校特色課程實施成效之研究-以南區餐旅群科為例。國立高雄餐旅大學餐旅教育研究所在職專班碩士論文,高雄市。取自https://hdl.handle.net/11296/63h2y5。


二、外文部分
Abdullah, F., & Ward, R. (2016). Developing aGeneral Extended Technology Acceptance Model for E-Learning (GETAMEL) byanalysing commonly used external factors. Computers in Human Behavior, 56,238-256. doi:https://doi.org/10.1016/j.chb.2015.11.036
ACARA (2013). The Australian curriculum:Technologies information sheet. Retrieved 17 August, 2014, fromhttp://www.acara.edu.au/curriculum_1/learning_areas/ technologies.html
Ahmed, E., Yaqoob, I., Hashem, I. A. T., Khan, I.,Ahmed, A. I. A., Imran, M., & Vasilakos, A. V. (2017). The role of big dataanalytics in Internet of Things. Computer Networks, 129, 459-471.
Akçayır, G., & Akçayır, M. (2018). The flippedclassroom: A review of its advantages and challenges. Computers &Education, 126, 334-345. doi:https://doi.org/10.1016/j.compedu.2018.07.021
Alderson, P. (2001). Research by children.International Journal of Social Research Methodology, 4(2), 139-153.doi:10.1080/13645570120003
Almobaideen, W., Krayshan, R., Allan, M., &Saadeh, M. (2017). Internet of Things: Geographical Routing based on healthcarecenters vicinity for mobile smart tourism destination. TechnologicalForecasting Social Change, 123, 342-350.
Angeli, C., Voogt, J., Fluck, A., Webb, M., Cox, M.,Malyn-Smith, J., & Zagami, J. (2016). A K-6 computational thinkingcurriculum framework: Implications for teacher knowledge. Journal ofEducational Technology & Society, 19(3).
Argyris, C., & Schön, D. A. (1989).Participatory action research and action science compared: A commentary.American behavioral scientist, 32(5), 612-623.
Asghari, P., Rahmani, A. M., & Javadi, H. H. S.(2018). Service composition approaches in IoT: A systematic review. Journal ofNetwork Computer Applications, 120, 61-77.
Barr, V., & Stephenson, C. (2011). Bringingcomputational thinking to K-12: what is Involved and what is the role of thecomputer science education community? Inroads, 2(1), 48-54.
Baskerville, R. L. (1999). Investigating informationsystems with action research. Communications of the association for informationsystems, 2(1), 19.
Ben Arfi, W., Ben Nasr, I., Khvatova, T., & BenZaied, Y. (2020). Understanding acceptance of eHealthcare by IoT natives andIoT immigrants: An integrated model of UTAUT, perceived risk, and financialcost. Technological Forecasting and Social Change, 120437.doi:https://doi.org/10.1016/j.techfore.2020.120437
Bienkowski, M., Snow, E., Rutstein, D., &Grover, S. (2015). Assessment Design Patterns for Computational Thinking Practicesin Secondary Computer Science: A First Look.
Bond, M. (2020). Facilitating student engagementthrough the flipped learning approach in K-12: A systematic review. Computers& Education, 151, 103819. doi:https://doi.org/10.1016/j.compedu.2020.103819
Bower, M., & Falkner, K. (2015). Computationalthinking, the notional machine, pre-service teachers, and researchopportunities. Paper presented at the Proceedings of the 17th AustralasianComputing Education Conference (ACE 2015).
Bratarchuk, S. (2018). Python Programming Languageas a Tool for Integrated Learning of Robotics in Secondary School.International Journal of Smart Education Urban Society, 9(1), 76-86.
Brown, T. (2008). Design thinking. Harvard businessreview, 86(6), 84.
Brownlee, J. (2016). What is deep learning. Machinelearning mastery.
Camara, C., Peris-Lopez, P., & Tapiador, J. E.(2015). Security and privacy issues in implantable medical devices: Acomprehensive survey. Journal of biomedical informatics, 55, 272-289.
Carroll, M., Goldman, S., Britos, L., Koh, J.,Royalty, A., & Hornstein, M. (2010). Destination, Imagination and the FiresWithin: Design Thinking in a Middle School Classroom. International Journal ofArt & Design Education, 29(1), 37-53. doi:https://doi.org/10.1111/j.1476-8070.2010.01632.x
Chen, M., Challita, U., Saad, W., Yin, C., &Debbah, M. (2019). Artificial neural networks-based machine learning forwireless networks: A tutorial. IEEE Communications Surveys Tutorials, 21(4),3039-3071.
Chou, P. H. (2002). Algorithm education in Python.Proceedings of Python, 10, 2.
Chu, Q., Yu, X., Jiang, Y., & Wang, H. (2018).Data Analysis of Blended Learning in Python Programming, Cham.
Computing at School. (2016). Computational thinking:A guide for teachers. (LeCun et al.). Available: http://community.computingatschool.org.uk/files/6695/original.pdf
CSTA (2017). CSTA K-12 Computer Science Standards.Retrieved from https://www.csteachers.org/page/standards.
CSTA (Computational Thinking: Teacher Resources).(2011b). CSTA K–12 computer science standards. The ACM K-12 Education TaskForce. Retrieved fromhttps://cdn.ymaws.com/www.csteachers.org/resource/resmgr/472.11CTTeacherResources_2ed.pdf
CSTA (Computer Science Teachers Association).(2011a). CSTA K–12 computer science standards. The ACM K-12 Education TaskForce. Retrieved from http://www.csta.acm.org/Curriculum/sub/CurrFiles/CSTA_K-12_CSS.pdf
Czerkawski, B. C., & Lyman, E. W. (2015).Exploring issues about computational thinking in higher education. TechTrends,59(2), 57-65.
D’Ettole, G., Bjørner, T., & De Götzen, A.(2020). How to Design Potential Solutions for a Cross-country Platform thatLeverages Students’ Diversity: A User-Centered Design Approach – and ItsChallenges, Cham.
Day, J. A., & Foley, J. D. (2006). Evaluating aweb lecture intervention in a human–computer interaction course. IEEETransactions on education, 49(4), 420-431.
Deken, B., Koch, D., & Dudley, J. (2013).Establishing a Robotics Competition in an Underserved Region: Initial Impactson Interest in Technology and Engineering. Journal of Technology, Management& Applied Engineering, 29(3), 1.
Deng, R., Benckendorff, P., & Gannaway, D.(2019). Progress and new directions for teaching and learning in MOOCs.Computers & Education, 129, 48-60.doi:https://doi.org/10.1016/j.compedu.2018.10.019
Djambong, T., & Freiman, V. (2016). Task-BasedAssessment of Students' Computational Thinking Skills Developed through VisualProgramming or Tangible Coding Environments. International Association forDevelopment of the Information Society.
Department for Education in England (DOEE) (2013,September 11). National curriculum in England: Computing programmes of study.Retrieved from https://www.gov.uk/government/publications/national-curriculum-in-englandcomputing-programmes-of-study/national-curriculum-in-england-computingprogrammes-of-study
Domingos, P. (2015). The master algorithm: How thequest for the ultimate learning machine will remake our world: Basic Books.
Dong, B., Shi, Q., Yang, Y., Wen, F., Zhang, Z.,& Lee, C. (2021). Technology evolution from self-powered sensors to AIoTenabled smart homes. Nano Energy, 79, 105414.doi:https://doi.org/10.1016/j.nanoen.2020.105414
Dougherty, D. (2013). The maker mindset. In M. Honey& D. E. Kanter (Eds.), Design, make, play: Growing the next generation ofSTEM innovators (pp. 7–11). New York, NY: Routledge.
Dunn, T. (2019). Deep learning. In: Salem Press.
Ebner, M., Khalil, M., Schön, S., Gütl, C.,Aschemann, B., Frei, W., & Röthler, D. (2017). How inverse blended learningcan turn up learning with MOOCs. Paper presented at the Proceedings of theinternational conference MOOC-MAKER 2017.
Erbilgin, E. (2019). Two mathematics teacher educators’efforts to improve teaching and learning processes: An action research study.Teaching and Teacher Education, 78, 28-38.doi:https://doi.org/10.1016/j.tate.2018.11.005
Ertmer, P. A., Richardson, J. C., Belland, B.,Camin, D., Connolly, P., Coulthard, G., . . . Mong, C. (2007). Using PeerFeedback to Enhance the Quality of Student Online Postings: An ExploratoryStudy. Journal of Computer-Mediated Communication, 12(2), 412-433.doi:10.1111/j.1083-6101.2007.00331.x %J Journal of Computer-MediatedCommunication
European AI Alliance (2018). CommunicationArtificial Intelligence for Europe. Retrieved fromhttps://ec.europa.eu/digital-single-market/en/news/communication-artificial-intelligence-europe
Fadel, C. (2008). 21st Century Skills: How can youprepare students for the new Global Economy. Retrieved February, 20, 2018.
Federal Ministry for Economic Affairs andEnergy(2018). Key points for a Federal Government Strategy on ArtificialIntelligence. Retrieved from https://www.de.digital/DIGITAL/Redaktion/DE/Downloads/key-points-for-federal-government-strategy-on-artificial-intelligence.pdf?__blob=publicationFile&v=3
Filius, R. M., de Kleijn, R. A. M., Uijl, S. G.,Prins, F. J., van Rijen, H. V. M., & Grobbee, D. E. (2018). Strengtheningdialogic peer feedback aiming for deep learning in SPOCs. Computers &Education, 125, 86-100. doi:https://doi.org/10.1016/j.compedu.2018.06.004
Fox, A. (2013). From moocs to spocs. Communicationsof the ACM, 56(12), 38-40.
Fraanje, R., Koreneef, T., Mair, A. L., & Jong,S. d. (2016, 15-17 June 2016). Python in robotics and mechatronics education. Paperpresented at the 2016 11th France-Japan & 9th Europe-Asia Congress onMechatronics (MECATRONICS) /17th International Conference on Research andEducation in Mechatronics (REM).
Gardner, J., & Brooks, C. (2018). Studentsuccess prediction in MOOCs. User Modeling User-Adapted Interaction, 28(2),127-203.
Gartner (2016). Gartner’s Top 10 StrategicTechnology Trends for 2017. Retrievedfromhttps://www.gartner.com/smarterwithgartner/gartners-top-10-technologytrends-2017/.
Gartner (2017). Gartner Top 10 Strategic TechnologyTrends for 2018. Retrievedfromhttps://www.gartner.com/smarterwithgartner/gartner-top-10-strategic-technology-trends-for-2018/
Gartner (2018). Gartner Top 10 Strategic TechnologyTrends for 2019. Retrieved from https://www.gartner.com/smarterwithgartner/gartner-top-10-strategic-technology-trends-for-2019/
Google (2015). Exploring Computational Thinking.Retrieved from https://edu.google.com/resources/programs/exploring-computational-thinking/#!ct-overview
GOV.UK (2017). Growing the artificial intelligenceindustry in the UK. Retrieved fromhttps://www.gov.uk/government/uploads/system/uploads/attachment_data/file/652097/Growing_the_artificial_intelligence_industry_in_the_UK.pdf
GOV.UK (2018). Artificial Intelligence Sector Deal.Retrieved fromhttps://www.gov.uk/government/publications/artificial-intelligence-sector-deal
Grover, S., & Pea, R. (2013). ComputationalThinking in K–12 A Review of the State of the Field (Vol. 42).
Guanghui, Z., Yanjun, L., Yixiao, T., Zhaoxia, W.,& Chengming, Z. (2018). Case-Based Teaching Organization for PythonProgramming that Focuses on Skill Training. Paper presented at the 2018 13thInternational Conference on Computer Science & Education (ICCSE).
Hadad, R., & Lawless, K. A. (2015). Assessingcomputational thinking. In Encyclopedia of Information Science and Technology,Third Edition (pp. 1568-1578): IGI Global.
Haj-Bolouri, A., Bernhardsson, L., & Rossi, M.(2016). PADRE: A Method for Participatory Action Design Research, Cham.
Hansen, E. B., & Bøgh, S. (2020). Artificialintelligence and internet of things in small and medium-sized enterprises: Asurvey. Journal of Manufacturing Systems. doi:https://doi.org/10.1016/j.jmsy.2020.08.009
Hew, K. F., Hu, X., Qiao, C., & Tang, Y. (2020).What predicts student satisfaction with MOOCs: A gradient boosting treessupervised machine learning and sentiment analysis approach. Computers &Education, 145, 103724. doi:https://doi.org/10.1016/j.compedu.2019.103724
Hien, T. T. T. (2009). Why is action researchsuitable for education? VNU Journal of Foreign Studies, 25(2).
Hoffmann, R. (2013). MOOCs-Best practices and worstchallenges. Making Sense of the MOOCs.
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu,Y., . . . Cao, B. (2020). Clinical features of patients infected with 2019novel coronavirus in Wuhan, China. The Lancet, 395(10223), 497-506.doi:https://doi.org/10.1016/S0140-6736(20)30183-5
Jordan, K. (2014). Initial Trends in Enrolment andCompletion of Massive Open Online Courses. International Review of Research inOpen Distributed Learning, 15(1), 133-160.doi:https://doi.org/10.19173/irrodl.v15i1.1651
Kahn, K. (2017). A half-century perspective on ComputationalThinking. Tecnologias, Sociedade e Conhecimento, 4, 23-42.
Kahn, K., & Winters, N. (2017). Child-friendlyprogramming interfaces to AI cloud services. Paper presented at the EuropeanConference on Technology Enhanced Learning.
Kaplan, A. M., & Haenlein, M. (2016). Highereducation and the digital revolution: About MOOCs, SPOCs, social media, and theCookie Monster. Business Horizons, 59(4), 441-450.doi:https://doi.org/10.1016/j.bushor.2016.03.008
Kay, R., & Kletskin, I. (2012). Evaluating theuse of problem-based video podcasts to teach mathematics in higher education.Computers & Education, 59(2), 619-627.doi:https://doi.org/10.1016/j.compedu.2012.03.007
Kelly, R. (2012). Educating for creativity: A globalconversation: Brush Education.
Kensing, F. (2003). Methods and practices inparticipatory design (Vol. 27): ITU Press Copenhagen.
Koh, J. H. L., Chai, C. S., Benjamin, W., &Hong, H.-Y. (2015). Technological Pedagogical Content Knowledge (TPACK) andDesign Thinking: A Framework to Support ICT Lesson Design for 21st CenturyLearning. The Asia-Pacific Education Researcher, 24(3), 535-543.doi:10.1007/s40299-015-0237-2
Kolb, A. Y., & Kolb, D. A. (2005). LearningStyles and Learning Spaces: Enhancing Experiential Learning in HigherEducation. 4(2), 193-212. doi:10.5465/amle.2005.17268566
Kui, X., Liu, W., Xia, J., & Du, H. (2017).Research on the improvement of python language programming course teachingmethods based on visualization. Paper presented at the 2017 12th InternationalConference on Computer Science and Education (ICCSE).
LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deeplearning. Nature, 521, 436. doi:10.1038/nature14539
Lin, Q., Yin, Y., Tang, X., Hadad, R., & Zhai,X. (2020). Assessing learning in technology-rich maker activities: A systematicreview of empirical research. Computers & Education, 157, 103944.doi:https://doi.org/10.1016/j.compedu.2020.103944
Lo, C. K., Hew, K. F., & Chen, G. (2017). Towarda set of design principles for mathematics flipped classrooms: A synthesis of researchin mathematics education. Educational Research Review, 22, 50-73.doi:https://doi.org/10.1016/j.edurev.2017.08.002
Luka, I. (2014). Design thinking in pedagogy. TheJournal of Education, Culture, Society, 5(2), 63-74.
Manfra, M. M. (2019). Action Research andSystematic, Intentional Change in Teaching Practice. 43(1), 163-196.doi:10.3102/0091732x18821132
Masters, J. (1995). The history of action research.Action research electronic reader, 22, 2005.
McKernan, J. (1988). The countenance of curriculumaction research: Traditional, collaborative, and emancipatory-criticalconceptions. Journal of curriculum and supervision, 3(3), 173-200.
McKinsey&Compny (2018). AI to spur economic growth. Information Age,Retrieved fromhttps://www.information-age.com/mckinsey-global-institute-123474592/
McNiff, J., & Whitehead, J. (2010). You and youraction research project(3rd ed.): Routledge,London(2010).
Melles, G., Howard, Z., & Thompson-Whiteside, S.(2012). Teaching Design Thinking: Expanding Horizons in Design Education.Procedia - Social and Behavioral Sciences, 31, 162-166.doi:https://doi.org/10.1016/j.sbspro.2011.12.035
Min, S., Lee, B., & Yoon, S. (2017). Deeplearning in bioinformatics. Briefings in Bioinformatics, 18(5), 851-869.
MSIT (2018).The Innovation Growth Engine LeadingPreparation For The Fourth Industrial Revolution. Retrieved fromhttp://english.msip.go.kr/cms/english/pl/policies2/__icsFiles/afieldfile/2018/04/06/혁신성장영문-인쇄본.pdf
MSIT(2016). Korea Brain Initiative. Retrieved fromhttp://www.msip.go.kr/web/msipContents/contents.do?mId=ODQ
Mullarkey, M. T., & Hevner, A. R. (2015a).Entering Action Design Research, Cham.
Mullarkey, M. T., & Hevner, A. R. (2015b). EnteringAction Design Research. Paper presented at the New Horizons in Design Science:Broadening the Research Agenda, Cham.
Munir, M. T., Baroutian, S., Young, B. R., &Carter, S. (2018). Flipped classroom with cooperative learning as acornerstone. Education for Chemical Engineers, 23, 25-33.doi:https://doi.org/10.1016/j.ece.2018.05.001
Niemi, R. (2019). Five approaches to pedagogicalaction research. Educational Action Research, 27(5), 651-666.doi:10.1080/09650792.2018.1528876
NITI Aayog(2018). National Strategy for ArtificialIntelligence. Retrieved fromhttp://niti.gov.in/writereaddata/files/document_publication/NationalStrategy-for-AI-Discussion-Paper.pdf
NSTC(2016). THE NATIONAL ARTIFICIAL INTELLIGENCERESEARCH AND DEVELOPMENT STRATEGIC PLAN. Retrieved fromhttps://www.nitrd.gov/PUBS/national_ai_rd_strategic_plan.pdf
Organisation for Economic Co-operation andDevelopment (OECD) (2008). 21st Century Learning: Research, Innovation andPolicy Directions from recent OECD analyses. Retrieved from http://www.oecd.org/site/educeri21st/40554299.pdf
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel,V., Thirion, B., Grisel, O., . . . Dubourg, V. (2011). Scikit-learn: Machinelearning in Python. Journal of machine learning research, 12(Oct), 2825-2830.
Pendleton-Jullian, A. M., & Brown, J. S. (2015).Design unbound: Evolving design literacy pathways of efficacy: CreateSpace(distributor).
Perignat, E., & Katz-Buonincontro, J. (2019).STEAM in practice and research: An integrative literature review. Thinking Skillsand Creativity, 31, 31-43. doi:https://doi.org/10.1016/j.tsc.2018.10.002
Pham, L. L., Watford, S., Friedman, K. P., Wignall,J., & Shapiro, A. J. (2019). Python BMDS: A Python interface library andweb application for the canonical EPA dose-response modeling software.Reproductive Toxicology, 90, 102-108.doi:https://doi.org/10.1016/j.reprotox.2019.07.013
Pickard, L., Shah, D., & De Simone, J. (2018).Mapping microcredentials across MOOC platforms. Paper presented at the 2018Learning With MOOCS (LWMOOCS).
Pretty, J. N., Guijt, I., Thompson, J., &Scoones, I. (1995). Participatory learning and action–A trainers guide.
Rahman, M. A. (2008). Some trends in the praxis ofparticipatory action research. The SAGE handbook of action research:Participative inquiry, 49-62.
Ramírez, P. L. G., Lloret, J., Tomás, J., &Hurtado, M. (2020). IoT-Networks group-based model that uses AI for workgroupallocation. Computer Networks, 107745.doi:https://doi.org/10.1016/j.comnet.2020.107745
Ruddick, A. (2013). English Identity and PoliticalCulture in the Fourteenth Century: Cambridge University Press.
Russell, S. J., & Norvig, P. (2018). ArtificialIntelligence:A Modern Approach (3rd Edition).
Scheer, A., Noweski, C., & Meinel, C. J. D.(2012). Transforming constructivist learning into action: Design thinking ineducation. Design Technology Education: An International Journal, 17(3).
Schindlholzer, B. (2016). Artificial intelligence& the future of education systems. from D-Druck
Schuler, D., & Namioka, A. (1993). Participatorydesign: Principles and practices: CRC Press.
Sein, M. K., Henfridsson, O., Purao, S., Rossi, M.,& Lindgren, R. (2011). Action Design Research. MIS Quarterly, 35(1), 37-56.doi:10.2307/23043488
Selby, C., & Woollard, J. (2014). Refining anunderstanding of computational thinking.
Sethi, P., & Sarangi, S. R. (2017). Internet ofthings: architectures, protocols, and applications. Journal of ElectricalComputer Engineering, 2017.
Shi, Q., Zhang, Z., He, T., Sun, Z., Wang, B., Feng,Y., . . . Lee, C. (2020). Deep learning enabled smart mats as a scalable floormonitoring system. Nature communications, 11(1), 1-11.
Silapachote, P., & Srisuphab, A. (2017).Engineering Courses on Computational Thinking Through Solving Problems inArtificial Intelligence. International Journal of Engineering Pedagogy, 7(3),34-49.
Skinner, H. (2017). Action Research. In K. Kubacki& S. Rundle-Thiele (Eds.), Formative Research in Social Marketing:Innovative Methods to Gain Consumer Insights (pp. 11-31). Singapore: Springer Singapore.
Smith, P., Masterson, A., Basford, L., Boddy, G.,Costello, S., Marvell, G., . . . Wallis, B. (2000). Action research: a suitablemethod for promoting change in nurse education. Nurse Education Today, 20(7),563-570. doi:https://doi.org/10.1054/nedt.2000.0466
Sneider, C., Stephenson, C., Schafer, B., &Flick, L. (2014). Exploring the science framework and NGSS: Computationalthinking in the science classroom. Science Scope, 38(3), 10.
Solanki, V. K., Díaz, V. G., & Davim, J. P.(2019). Handbook of IoT and Big Data: CRC Press.
Srinath, K. (2017). Python–The Fastest GrowingProgramming Language. International Research Journal of EngineeringTechnology(IRJET), 4(12), 354-357.
Stewart, J. C., Davis, G. A., & Igoche, D. A.(2020). AI, IoT, AND AIoT: DEFINITIONS AND IMPACTS ON THE ARTIFICIALINTELLIGENCE CURRICULUM. Issues in Information Systems, 21(4).
Swantz, M. L. (2008). Participatory action researchas practice. The Sage handbook of action research: Participative inquiry andpractice, 31-48.
Tüzün, E., Tekinerdogan, B., Macit, Y., & İnce,K. (2019). Adopting integrated application lifecycle management within alarge-scale software company: An action research approach. Journal of Systemsand Software, 149, 63-82. doi:https://doi.org/10.1016/j.jss.2018.11.021
Tabaa, M., Monteiro, F., Bensag, H., & Dandache,A. (2020). Green Industrial Internet of Things from a smart industryperspectives. Energy Reports, 6, 430-446.doi:https://doi.org/10.1016/j.egyr.2020.09.022
Tahsien, S. M., Karimipour, H., & Spachos, P.(2020). Machine learning based solutions for security of Internet of Things(IoT): A survey. Journal of Network and Computer Applications, 161, 102630.doi:https://doi.org/10.1016/j.jnca.2020.102630
Titchen, A. (2015). Action research: genesis, evolutionand orientations. International Practice Development Journal, 5(1).
Tsai, C.-C., Cheng, T.-F., Shih, R.-C., & Lou,S.-J. (2019). The Construction of Artificial Intelligence Deep Learning AbilityIndicators for Vocational High School Students. Paper presented at the Int’lConference Proceedings.
Uijl, S., Filius, R., & Ten Cate, O. (2017).Student Interaction in Small Private Online Courses. Medical Science Educator,27(2), 237-242. doi:10.1007/s40670-017-0380-x
Ulibarri, N., E Cravens, A., Cornelius, M., Royalty,A., & Svetina Nabergoj, A. (2014). Research as design: Developing creativeconfidence in doctoral students through design thinking. International Journalof Doctoral Studies, 9, 249-270.
US Executive Office of the President (EOPOTUS)(2016). Preparing for the future of artificial intelligence. Retrieved from https://obamawhitehouse.archives.gov/sites/default/files/whitehouse_files/microsites/ostp/NSTC/preparing_for_the_future_of_ai.p
van Alten, D. C. D., Phielix, C., Janssen, J., &Kester, L. (2019). Effects of flipping the classroom on learning outcomes andsatisfaction: A meta-analysis. Educational Research Review, 28, 100281.doi:https://doi.org/10.1016/j.edurev.2019.05.003
Venable, J. (2006). A framework for design scienceresearch activities. Paper presented at the Emerging Trends and Challenges inInformation Technology Management: Proceedings of the 2006 Information ResourceManagement Association Conference
Wang, J., Jou, M., Lv, Y., & Huang, C.-C.(2018). An investigation on teaching performances of model-based flippingclassroom for physics supported by modern teaching technologies. Computers inHuman Behavior, 84, 36-48. doi:https://doi.org/10.1016/j.chb.2018.02.018
White House (2018). White House Hosts Summit onArtificial Intelligence for American Industry. Retrieved fromhttps://www.whitehouse.gov/articles/white-house-hosts-summit-artificial-intelligence-american-industry/
Whyte, W. H. (1980). The social life of small urbanspaces.
Wing, J. M. (2006). Computational thinking.Communications of the ACM, 49(3), 33-35.
Wing, J. (2017). Computational thinking\u2019sinfluence on research and education for all. Italian Journal of EducationalTechnology, 25(2), 7-14.
Wolfram, S. (2017). An Elementary Introduction tothe Wolfram Langauge: Wolfram Media, Incorporated.
Xu, J., Chao, C.-J., & Fu, Z. (2020). Researchon Intelligent Design Tools to Stimulate Creative Thinking. Paper presented atthe Cross-Cultural Design. User Experience of Products, Services, andIntelligent Environments, Cham.
Xingjian, S., Chen, Z., Wang, H., Yeung, D.-Y.,Wong, W.-K., & Woo, W.-c. (2015). Convolutional LSTM network: A machinelearning approach for precipitation nowcasting. Paper presented at the Advancesin neural information processing systems.
Yadav, A., Zhou, N., Mayfield, C., Hambrusch, S.,& Korb, J. T. (2011). Introducing computational thinking in education courses.Paper presented at the Proceedings of the 42nd ACM technical symposium onComputer science education.
Yáñez, C., Okada, A., & Palau, R. (2015). Newlearning scenarios for the 21st century related to Education, Culture andTechnology. International Journal of Educational Technology in HigherEducation, 12(2), 87-102. doi:10.7238/rusc.v12i2.2454
Zeng, D. (2013). From computational thinking to aithinking. IEEE Intelligent Systems(6), 2-4.
Zhu, M., Sari, A., & Lee, M. M. (2018). Asystematic review of research methods and topics of the empirical MOOCliterature (2014–2016). The Internet and Higher Education, 37, 31-39.doi:https://doi.org/10.1016/j.iheduc.2018.01.002
 
 
 
 
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