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題名：建構博課師教學法強化適性化導引機制
作者：陳怡秀
作者(外文)：Yi-Hsiu Chen
校院名稱：國立東華大學
系所名稱：企業管理學系
指導教授：侯佳利
學位類別：博士
出版日期：2022
主題關鍵詞：創新教學法；博課師教學法；適性化導引；Adaptive guidance；BOOCs；Innovative teaching method
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現今教學普遍使用線上學習的情況下，再加上近幾年新冠肺炎(COVID-19)疫情的影響，為了不讓教學中斷，線上學習變成主要教學方式。但於實際教學現場發現，即便使用多種創新教學法，教學方式仍然以講授式教學為主，導致知識傳遞是單向的，即便是不同先備知識基礎的學生，其閱讀的教材內容難易度皆相同。目前線上學習的教學環境缺乏互動性，也缺乏班級經營，其平台沒有完整的學習數據能讓老師觀察學生的學習狀況，並且尚無適合的數位平台或工具能支援多種不同的創新教學法在教學上使用，而本研究認為完善的教學環境應是將平台、教材與創新教學法相互結合，才能提供最好的教學方法與策略。
本研究於2019年建構博課師教學法，並同時開發博課師平台與博課師教材以支援此教學法使做到整合式教學環境，讓老師可將教學平台、數位教材以及因課程特性使用的創新教學法一起整合使用。2019年至今已進行三年的教師社群，總共16位老師使用博課師教學法在42門課程，其分別所屬在25門學科的實務教學上，總共產出362本博課師教材，其中已提出7篇研討會論文、1篇SCI期刊論文、8個三創教學課程計畫。這些教學實務驗證博課師教學法除了解決現有教學問題外，也驗證博課師教學法能適用在不同學科領域的課程教學上，能符合課程特性、突顯課程特色，更能提供有效的自主學習的環境與方法，即便是不同先備知識基礎的學生，都能有適當的學習成效。
Online learning is used in most teaching nowadays, and due to the impact of the Coronavirus disease 2019 (COVID-19) in recent years, in order not to interrupt teaching, online learning has become the main teaching method. This study found in the actual teaching situation that even if a variety of innovative teaching methods are used, the teaching method still used didactic teaching, resulting in one-way knowledge. At present, the teaching environment of online learning lacks interactivity and classroom management. The online learning platform does not have complete learning data for teachers to observe students' learning status, and there is no suitable digital platform or tool to support a variety of innovative teaching methods in teaching. This study thinks a complete teaching environment should combine platforms, teaching materials and innovative teaching methods to provide the best teaching methods and strategies.
In 2019, this study built the teaching method, is called BOOCs, and developed the BOOCs platform and the BOOCs teaching material at the same time to support BOOCs to achieve an integrative teaching environment, so that teachers can integrated use the teaching platform, digital teaching materials and the innovative teaching methods used by the characteristics of the curriculum. From 2019 to now, the teacher professional learning community of BOOCs has been carried out for three years. A total of 16 teachers have used the BOOCs in 42 courses, and these courses belong to 25 disciplines. A total of 362 BOOCs teaching materials have been produced. Seven seminar papers, one SCI journal paper, and eight teaching curriculum planings have been proposed. These teaching practices verify BOOCs not only solves the existing teaching problems, but also verifies BOOCs can be applied to the course teaching of different disciplines, which can conform to the characteristics of the courses, highlight the characteristics of the courses, and can provide effective of self-regulated learning environment and method. Even students with different prior knowledge base can have appropriate learning performance.
2020台灣網路報告. Retrieved from https://report.twnic.tw/2020/
Alonso, A. A., & Arcos-Alonso, A. (2021). Problem-based learning and other active methodologies as support for distance teaching during the COVID-19 pandemic. Cypriot Journal of Educational Sciences, 16(1), 277-287.
Baker, R. S., & Inventado, P. S. (2014). Educational data mining and learning analytics. In Learning Analytics (pp. 61-75): Springer, New York, NY.
Bakhshinategh, B., Zaiane, O. R., ElAtia, S., & Ipperciel, D. (2018). Educational data mining applications and tasks: A survey of the last 10 years. Education and Information Technologies, 23(1), 537-553.
Bergmann, J., & Sams, A. (2015). Flipped learning: Gateway to student engagement: International Society for Technology in Education.
Bielawski, L., & Metcalf, D. (2003). Blended elearning: Integrating knowledge, performance, support, and online learning: Human Resource Development.
Bimba, A., Idris, N., Al-Hunaiyyan, A., Mahmud, R., & Shuib, L. (2017). Adaptive feedback in computer-based learning environments: a review. Adaptive Behavior, 25(5), 217-234.
Breslow, L., Pritchard, D. E., DeBoer, J., Stump, G. S., Ho, A. D., & Seaton, D. T. (2013). Studying learning in the worldwide classroom research into edX's first MOOC. Research & Practice in Assessment, 8, 13-25.
Burgess, J. R. D., & Russell, J. E. A. (2003). The effectiveness of distance learning initiatives in organizations. Journal of Vocational Behavior, 63(2), 289-303.
C.V.Ekwunife-Orakwue, K., & Teng, T.-L. (2014). The impact of transactional distance dialogic interactions on student learning outcomes in online and blended environments. Computers & Education, 78, 414-427.
Chandrasekar, P., Qian, K., Shahriar, H., & Bhattacharya, P. (2017). Improving the prediction accuracy of decision tree mining with data preprocessing. Paper presented at the 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC).
Chang, H.-P. (2018). An implementation of digital content model conversion system–From SCORM to EPUB. Journal of Applied Science and Engineering, 21(2), 271-278.
Chou, C., Peng, H., & Chang, C.-Y. (2010). The technical framework of interactive functions for course-management systems: Students’ perceptions, uses, and evaluations. Computers & Education, 55(3).
Collins, A. (1987). Cognitive apprenticeship: Teaching the craft of reading, writing, and mathematics. Technical report no. 403.
Cronje, J. C. (2020). Towards a new definition of blended learning. Electronic Journal of eLearning, 18(2), 114‑121.
Delisle, R. (1997). How to use problem-based learning in the classroom: ASCD.
Driscoll, M. (2002). Blended learning: Let’s get beyond the hype. E-Learning, 3(3).
EPUB3. (2018). Retrieved from https://www.edrlab.org/open-standards/epub/
EPUB 3.3. (2022). Retrieved from https://www.w3.org/TR/epub-33/
F.Agudo-Peregrina, Á., Iglesias-Pradas, S., Conde-González, M. Á., & Hernández-García, Á. (2014). Can we predict success from log data in VLEs? Classification of interactions for learning analytics and their relation with performance in VLE-supported F2F and online learning. Computers in human behavior, 31, 542-550.
Friedman, J. H., & Fisher, N. I. (1999). Bump hunting in high-dimensional data. Statistics and computing, 9(2), 123-143.
Garrison, D. R., & Vaughan, N. D. (2008). Blended learning in higher education: Framework, principles, and guidelines: John Wiley & Sons.
Gillani, N., & Eynon, R. (2014). Communication patterns in massively open online courses. The Internet and Higher Education, 23, 18-26.
Hannafin, M. J., Land, S. M., & Oliver, K. M. (1999). Open learning environments: Foundations, methods, and models. Instructional-design theories and models: A new paradigm of instructional theory, 2, 115-140.
Hew, K. F., & Cheung, W. S. (2014). Students’ and instructors’ use of massive open online courses (MOOCs): Motivations and challenges. Educational research review, 12, 45-58.
Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn? Educational psychology review, 16(3), 235-266.
Hoy, M. B. (2014). MOOCs 101: an introduction to massive open online courses. Medical reference services quarterly, 33(1), 85-91.
Kapıkıran, Ş., & Acun-Kapikiran, N. (2016). Optimism and psychological resilience in relation to depressive symptoms in university students: Examining the mediating role of self-esteem. Educational Sciences: Theory and Practice, 16(6), 2087-2110.
KEMP, S. (2022). Digital 2022: TAIWAN. Retrieved from https://datareportal.com/reports/digital-2022-taiwan
Knowles, M. S. (1975). Self-directed learning: A guide for learners and teachers. 2(2).
Koehler, M., & Mishra, P. (2009). What is technological pedagogical content knowledge (TPACK)? Contemporary issues in technology and teacher education, 9(1), 60-70.
Kuo, Y.-C., Eastmond, J. N., Bennett, L. J., & Schroder, K. E. E. (2009). Student perceptions of interactions and course satisfaction in a blended learning environment. Paper presented at the EdMedia+ Innovate Learning.
Lage, M. J., Platt, G. J., & Treglia, M. (2000). Inverting the classroom: A gateway to creating an inclusive learning environment. The journal of economic education, 31(1), 30-43.
Lambros, M. A. (2004). Problem-based learning in middle and high school classrooms: A teacher′ s guide to implementation: Corwin Press.
Lang, C., Siemens, G., Wise, A., & Gašević, D. (2017). Handbook of learning analytics: Society for Learning Analytics Research (SoLAR).
Liu, M. (2013). Blended learning in a university EFL writing course: Description and evaluation. Journal of Language Teaching and Research, 4(2).
Liu, M., McKelroy, E., Corliss, S. B., & Carrigan, J. (2017). Investigating the effect of an adaptive learning intervention on students’ learning. Educational technology research and development, 65(6), 1605-1625.
McAuley, A., Stewart, B., Siemens, G., & Cormier, D. (2010). The MOOC model for digital practice: Massive Open Online Courses : digital ways of knowing and learning: University of Prince Edward Island.
Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers college record, 108(6), 1017-1054.
Oliver, M., & Trigwell, K. (2005). Can 'blended learning' be redeemed? E-Learning, 2(1), 17-26.
Palincsar, A. S. (1986). The role of dialogue in providing scaffolded instruction. Educational psychologist, 21(1-2), 73-98.
Phyu, T. N. (2009). Survey of classification techniques in data mining. Paper presented at the International multiconference of engineers and computer scientists.
Reiser, B. J. (2004). Scaffolding complex learning: The mechanisms of structuring and problematizing student work. Journal of the Learning Sciences, 13(3), 273-304.
Rhode, J. (2009). Interaction equivalency in self-paced online learning environments: An exploration of learner preferences. The international review of research in open and distributed learning, 10(1).
Romero, C., Romero, J. R., & Ventura, S. (2014). A survey on pre-processing educational data. In Educational Data Mining: Applications and Trends (pp. 29-64): Springer.
Romero, C., & Ventura, S. (2007). Educational data mining: A survey from 1995 to 2005. Expert systems with applications, 33(1), 135-146.
Romero, C., & Ventura, S. (2013). Data mining in education. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 3(1), 12-27.
Romero, C., & Ventura, S. (2020). Educational data mining and learning analytics: An updated survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 10(3), e1355.
Sadiq, S., Tao, Y., Yan, Y., & Shyu, M.-L. (2017). Mining anomalies in medicare big data using patient rule induction method. Paper presented at the 2017 IEEE Third International Conference on Multimedia Big Data (BigMM).
Sanders, D., & Welk, D. S. (2005). Strategies to scaffold student learning: Applying Vygotsky's zone of proximal development. Nurse educator, 30(5), 203-207.
Sarawagi, N. (2013). Flipping an introductory programming course: yes you can! Journal of Computing Sciences in Colleges, 28(6), 186-188.
Scheuer, O., & McLaren, B. M. (2012). Educational data mining. Encyclopedia of the Sciences of Learning, 1075-1079.
Shulman, L. (1987). Knowledge and teaching: Foundations of the new reform. Harvard educational review, 57(1), 1-23.
Siadaty, M., Gašević, D., Jovanović, J., Pata, K., Milikić, N., Holocher-Ertl, T., . . . Hatala, M. (2012). Self-regulated workplace learning: A pedagogical framework and semantic web-based environment. Educational Technology & Society, 15(4), 75-88.
Siemens, G. (2013). Learning analytics: The emergence of a discipline. American Behavioral Scientist, 57(10), 1380-1400.
Silander, P. (2015). Phenomenon Based Learning. Retrieved from http://www.phenomenaleducation.info/phenomenon-based-learning.html
Slater, S., Joksimovic, S. k., Kovanovic, V., Baker, R. S., & Gasevic, D. (2017). Tools for educational data mining: A review. Journal of Educational and Behavioral Statistics, 42(1), 85-106.
Tamblyn, H. S. B. R. M. (1980). Problem-based learning: An approach to medical education (Vol. 1): Springer.
Truong, H. M. (2016). Integrating learning styles and adaptive e-learning system: Current developments, problems and opportunities. Computers in human behavior, 55, 1185-1193.
Tsai, T. P., Lin, J., Hou, J., Chen, Y., & Hsu, C. (2019). Preview analytics of EPUB3 ebook-based flipped classes using a big data approach. Journal of Internet Technology, 20(7), 2129-2140.
Tsai, T. P., Lin, J., & Lin, L. C. (2017). A flip blended learning approach for EPUB3 ebook-based course design and implementation. Eurasia Journal of Mathematics, Science and Technology Education, 14(1), 123-144.
Tsai, T. P., Lin, J., Lin, L. C., Chen, Y., & Liu, J. (2018). An effectiveness study on the class lecture in an EPUB3 ebook-based flip blended learning model. Paper presented at the 2018 Eurasian Conference on Educational Innovation (ECEI 2018).
Verma, D., & Mishra, N. (2017). Analysis and prediction of breast cancer and diabetes disease datasets using data mining classification techniques. Paper presented at the 2017 International Conference on Intelligent Sustainable Systems (ICISS).
Vygotsky, L. S. (1978). Mind in society: Development of higher psychological processes (M. Cole, V. Jolm-Steiner, S. Scribner, & E. Souberman Eds.): Harvard University Press.
Ward, J., & LaBranche, G. A. (2003). Blended learning: The convergence of e-learning and meetings. Franchising World, 35(4), 22-23.
Weka 3: Machine Learning Software in Java. (2021). Retrieved from https://www.cs.waikato.ac.nz/ml/weka/
Whitelock, D., & Jelfs, A. (2003). Editorial: Journal of educational media special issue on blended learning. Journal of Educational Media, 28(2), 99-100.
Wood, D., Bruner, J. S., & Ross, G. (1976). The role of tutoring in problem solving. Journal of Child Psychology and Psychiatry, 17, 89-100.
Zimmerman, B. J. (2008). Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects. American educational research journal, 45(1), 166-183.
Zimmerman, M. A. (1995). Psychological empowerment: Issues and illustrations. American journal of community psychology, 23(5), 581-599.
Zimmerman, T. D. (2012). Exploring learner to content interaction as a success factor in online courses. International Review of Research in Open and Distributed Learning, 13(4), 152-165.
大學入學考試中心. (2021). 110學年度學科能力測驗-各科成績標準一覽表(pdf). Retrieved from https://www.ceec.edu.tw/xmdoc/cont?xsmsid=0J018604485538810196&sid=0L055368691889545285
王佩瑜. (2018). 磨課師課程影片形式對學習之影響. 教育資料與圖書館學, 55(3), 319-348.
朱繼農. (2004). 網路科技 & 數位學習. 師友月刊(446), 40-42.
何宏發, & 陳清煌. (2021). 我國小學學生的大數據學習資料分析研究：以英文字彙自主學習為例. 數位學習科技期刊, 13(3), 81-108.
吳清山. (2013). 教育名詞 磨課師. 教育資料與研究(111), 267-268.
李招瑩. (2021). 族群藝術教育的跨域與創新. Paper presented at the 2021美感跨域與創新教學學術研討會, 國立臺灣藝術大學.
汪耀華, & 張基成. (2019). 大規模線上開放課程授課教師經驗、經驗本質及反思. 科學教育學刊, 27(1), 25-47.
林含諭. (2017). 資訊科技應用於適性化學習的教學策略之探討研究. 臺灣教育評論月刊, 6(6), 142-145.
邱郁文, 林益民, & 施東河. (2007). 系統特性、任務特性與電腦自我效能對個人線上學習行為傾向影響. 電子商務學報, 9(2), 235-266.
邱華慧. (2020). 大班教學環境中即時反饋及適性化學習系統的應用對大學生學習成效和投入的影響. 師資培育與教師專業發展期刊, 13(1), 101-128.
侯佳利, & 江采霖. (2020). 應用博課師BOOCs於實踐PBL式翻轉教學之研究 ──以Data Modeling為例. Paper presented at the ICIM 2020-第31屆國際資訊管理學術研討會.
侯佳利, & 陳怡秀. (2022). 運用博課師教學法探討預習與複習學習活動對於學生學習的幫助-以物件導向設計課程為例. Paper presented at the 2022後疫情時代教學創新示範國際研討會.
侯佳利, & 劉為駿. (2021). 鷹架理論結合博課師平台的自主學習器應用在程式設計教學對學習成效的影響(以Python為例). Paper presented at the 2021IMP第26屆資訊管理暨實務研討會論文集.
侯雅雯. (2017). MOOCs對高等教育教學之挑戰與問題. 課程研究, 12(1), 69-88.
柯志恩. (2021). 疫情下後設認知理論對線上自主學習的啟示. 臺灣教育評論月刊, 10(11), 62-67.
洪詠善. (2020). 停課不停學: 當自主學習成為日常. 課程研究, 15(1), 15-33.
胡詠翔. (2019). 大規模開放線上課程學習分析促進科技學科教學知識之研究. 教學實踐與創新, 2(1), 77-114.
徐新逸, & 賴婷鈴. (2013). 國際經驗對臺灣電子教科書發展之啟示. 教科書研究, 6(2), 1-31.
袁梅宇. (2014). 數據挖掘與機器學習：WEKA應用技術與實踐: 清華大學出版社.
張玄菩. (2017). 從SCORM數位學習教材標準看EPUB做為電子教科書檔案格式之特性與挑戰. 圖書資訊學研究, 12(1).
張淑萍, & 張瀞文. (2018). 磨課師課程與教材–設計、發展與實施策略. 科學發展, 549, 19-26.
張媛甯. (2021). 運用問題導向學習於跨領域學習課程之教學實踐研究. 教育理論與實踐學刊(44), 1-28.
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.
教育部資訊及科技教育司. (2019). 全國各級學校因應疫情停課居家線上學習. Retrieved from https://cpd.moe.gov.tw/page_two.php?id=34832
連育仁. (2021). 疫情與後疫情時代的複合教學準備與實踐. 評鑑雙月刊(92), 35-40.
郭彥谷, 陳俊魁, & 黃能堂. (2020). 科學教育的翻轉學習研究趨勢：2012～2019年學術期刊文獻回顧. 數位學習科技期刊, 12(4), 85-111.
郭勝煌. (2021). [後疫情時代] 停課不停學之 PBL 遠距教學實踐研究. 台北海洋科技大學學報, 12(2), 95-120.
郭靜姿, & 何榮桂. (2014). 翻轉吧教學! 台灣教育(686), 9-15.
陳秀靜, & 楊秋燕. (2020). 以鷹架學習策略於培養高齡服務者的文化能力之教學運用. 台灣健康照顧研究學刊(21), 36-71.
陳怡文. (2019). 淺談自主學習途徑-磨課師. 臺灣教育評論月刊, 8(1), 257-260.
陳怡秀, 林兆宇, 侯佳利, & 林至中. (2019). 以EPUB3電子書教材為基礎之適性化翻轉學習研究. 2019數位學習的創新與應用論文集.
陳怡秀, 林兆宇, 侯佳利, 林至中, & 嚴兆威. (2019). 運用博課師教學平台於適性化翻轉學習之研究. Paper presented at the NCS 2019 全國計算機會議.
陳偉泓. (2020). 後疫情時代，如何有效學習？. 點教育, 2(2), 1-3.
陳琦媛. (2017). 問題本位學習法(PBL)於師資職前教育課程運用之初探. 臺灣教育評論月刊, 6(10), 70-77.
陳雅玲. (2021). 於混合學習中基於學習分析儀表板系統應用之自我調節學習方法. 數位學習科技期刊, 13(3), 27-42.
曾榮梅. (2021). 當設計遇上PBL？在基本設計的教學實踐研究. 教育研究與實踐學刊, 68(2), 33-74.
曾釋嫻, & 蔡秉燁. (2015). 翻轉課堂教學與傳統教學對大學生學習策略之差異研究. 雙溪教育論壇(3), 1-19.
黃武元, & 王錦裕. (2002). 線上閱讀的學習時間型態與其學習行為及學習成就相關性之研究. 科學教育學刊, 10(4), 389-405.
黃政傑, & 張嘉育. (2010). 讓學生成功學習:適性課程與教學之理念與策略. 課程與教學, 13(3), 1-22.
楊坤原, & 張賴妙理. (2005). 問題本位學習的理論基礎與教學歷程. 中原學報, 33(2), 215-235.
楊彩鳳. (2021). 拉近生活與文化的距離：PBL問題導向學習設計. 師友雙月刊, 625, 139-144.
楊淳皓. (2012). 大學PBL課程教學實務：宜蘭大學的經驗與省思: 國立宜蘭大學.
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), 41-44.
劉聰仁, & 李彥瑋. (2019). 探討餐旅SPOC數位課程的學習風格, 持續使用意圖, 學習滿意度, 學習成效之關聯性. Paper presented at the NCS 2019 全國計算機會議.
鄭金昌, & 李建平. (2006). 鷹架理論應用在排球教學之研究. 雲科大體育(9), 151-160.
賴俊雄. (2017). 高教雲端化？：全球大學「推牆」與「護牆」現象的探討. Journal of Education Research(283), 72-85.
謝州恩. (2013). 鷹架理論的發展, 類型, 模式與對科學教學的啟示. 科學教育月刊(364), 2-16.
羅方吟, & 陳政煥. (2021). COVID-19疫情下同步與非同步資訊科技輔助的大學遠距英語文教學. 當代教育研究季刊, 29(1), 69-114.
羅珮瑄. (2019). EPUB3互動式電子書教學平台應用於英語溝通課程之成效. Paper presented at the 2019教學實踐研究暨校務研究學術研討會論文集, 國立宜蘭大學.
關超然, & 李孟智. (2013). PBL問題導向學習之理念、方法、實務與經驗: 台灣愛思唯爾有限公司.
 
 
 
 
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