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| Title: | 原則導向的知識翻新教案設計之成效—以永續發展教案為例
Evaluating the Effectiveness of Principles-Based Knowledge Building Lesson Design: Using Sustainable Development Lesson Plans as Example |
| Authors: | 林青欣
Lin, Cing-Sin |
| Contributors: | 洪煌堯
Hong, Huang-Yao
林青欣
Lin, Cing-Sin |
| Keywords: | 原則導向
知識翻新
教案設計
教案自動評量
認知層次
Principle-based approach
Knowledge Building
Lesson Design
Automated Lesson Plan Assessment
Cognitive Levels |
| Date: | 2025 |
| Issue Date: | 2025-07-01 14:14:25 (UTC+8) |
| Abstract: | 人工智慧的快速發展正重塑當代教育現場。儘管108課綱強調核心素養的培養，實務現場仍缺乏具體可操作的教學原則，導致教師在教案設計上面臨挑戰。行之有年的「知識翻新理論」強調學生能動性、想法改進與社群互動，能彌合理論與實務的落差，提供教師素養導向教案設計的重要依據。本研究旨在運用知識翻新理論，設計原則導向的知識翻新活動，協助教師將知識翻新原則轉化為具體的教學實踐。同時，本研究亦發展具信效度的教案評估工具，探索大型語言模型於教育評量中的應用，以發掘科技輔助教學與評量的創新模式。
本研究採個案研究法，以55位參與十週原則導向知識翻新活動的教師為研究對象。在知識翻新十二項原則的引導下，從教案設計品質、對原則的自我理解、教案檢核表中的自創原則內容與知識論壇貼文等面向，檢視教師表現，探究其對原則理解的成效與轉變歷程。資料蒐集採混合研究法，量化資料包含：（1）大型語言模型對基於原則導向的知識翻新教案、基於108課綱核心素養教案的評分；（2）知識翻新原則理解自我評估量表。上述量化資料分別以獨立樣本t檢定和成對樣本t檢定分析教師教案表現及其對原則理解的自評變化。質性資料則包含：（1）知識論壇貼文；（2）教師設計的原則導向知識翻新教案；（3）教案檢核表。上述質性資料依認知目標層次進行語料編碼，並以單因子相依變異數分析呈現教師對知識翻新原則的認知歷程。
研究結果如下：（1）經指令訓練的 ChatGPT 可作為教案自動評量工具，有效協助教師客觀檢視教案設計，且本研究開發的完整指令集大幅降低教師訓練ChatGPT的時間成本，促進教師自主精進教案設計；（2）原則導向的知識翻新教案不僅符合核心素養精神，更達到知識翻新的更高境界。研究發現知識翻新原則對當前課程改革具重要實用價值，為教師提供具體可行的教學方向；（3）為期十週的原則導向知識翻新活動顯著提升教師對知識翻新原則的理解，驗證原則為導向的知識翻新活動在增進教師原則理解的有效性；（4）教師對原則理解的自評分數與教案表現分數在 Idea 和 Agent 面向具顯著正相關；（5）原則導向的知識翻新活動在知識論壇與社群支持下，促進教師朝向高認知層次成長，尤其高分組教師的認知發展呈現明顯的階段性變化與進步。
The rapid advancement of artificial intelligence is reshaping contemporary education. Although the curriculum emphasizes the cultivation of core competencies, it lacks concrete and actionable teaching principles. This gap poses challenges for teachers in developing lesson plans. Knowledge Building（KB）theory emphasizes student agency, idea improvement, and community interaction, offering teachers valuable guidance for competency-based lesson planning. This study applies KB theory to design a principles-based program aimed at supporting teachers in transforming KB principles into teaching practices. Additionally, the study develops reliable and valid tools for automated lesson plan assessment. At the same time, the study explores innovative applications of large language models（LLMs）in educational assessment, pioneering new directions in technology-assisted teaching and evaluation.
The research adopts a case study approach involving 55 teachers participating in a ten-week program. Guided by the twelve KB principles, the study examined teacher performance through multiple data sources: the quality of lesson plans, self-assessment scores on KB principles, lesson plan checklists, and weekly posts on the Knowledge Forum （KF）. These dimensions collectively revealed how teachers understood and applied the principles over time. The research adopts a mixed-methods approach. Quantitative data included (1) automated LLM assessments of principles-based KB lesson plans and competency-based lesson plans, analyzed using independent t-tests to assess performance differences; and (2) a KB principles self-assessment, analyzed using paired t-tests to evaluate teachers’ perceptions. Qualitative data included: (1) teachers’ KF posts; (2) their principles-based lesson plans; and (3) lesson plan checklists. These were coded according to cognitive levels and analyzed using repeated-measures ANOVA to trace teachers’ conceptual development.
The findings are as follows:(1) Instruction-tuned ChatGPT effectively evaluates lesson plans, helping teachers objectively refine them. The prompt set developed significantly reduces the training burden for teachers, supporting autonomous improvement; (2) Principles-based KB lesson plans not only align with core competency requirements but also achieve higher KB standards; (3) The ten-week program significantly enhances teachers’ understanding of KB principles, confirming the effectiveness of principles-based implementation; (4) Teachers' self-assessment scores show significant positive correlations with lesson performance in Idea and Agent dimensions; and (5) With support from the KF and community interactions, the program facilitates higher-order cognitive growth, particularly among high-performing participants who demonstrate clear and progressive conceptual advancement. |
| Reference: | 王金國 (2021)。素養導向教學設計的問題分析與建議. 臺灣教育評論月刊，10(1)，186-192。
王逸棻（2020）。中小學新課綱之素養教育課程實踐。臺灣教育評論月刊，9(1)，61-64。
吳宛婷（2023）。108課綱國中國文科教學困境與因應策略。臺灣教育評論月刊，12(10)，94-98。
吳清山（2019）。教師執行新課綱之新挑戰、新思維與新作為。師友雙月刊，(613)， 7-12。
吳清山、王令宜、黃建翔（2014）。國民小學推動永續發展教育之調查研究。課程與教學，17(2)，93-117。
吳清山、林天祐（2012）。永續發展教育。教育研究月刊，219，129-130。
吳靖國（2022）。新課綱為高中教師帶來的教學負荷。臺灣教育評論月刊，11(3)。
吳壁純、鄭淑慧、陳春秀（2017）。以學生學習為主軸的生活課程素養導向教學。教育研究月刊，275，50-63。
吳璧純、詹志禹（2018）。從能力本位到素養導向教育的演進、發展及反思。教育研究與發展期刊，14(2)，35-64。
周淑卿、吳璧純、林永豐、張景媛、陳美如（2018）。素養導向教學設計參考手冊。臺北：教育部國民及學前教育署。
周淑卿、李駱遜、涂慶隆、楊俊鴻（2018）。國小試行十二年國教課程的狀況: 以國家教育研究院合作學校為例。教育研究月刊，289，55-73。
林永豐（2017）。論十二年國民基本教育課程總綱學習重點的規劃思維與意涵。課程與教學，20(1)，105-125。https://doi.org/10.6384/CIQ.201701_20(1).0005
林永豐（2017a）。核心素養的課程教學轉化與設計。教育研究月刊，275，4-17。
林奎宇、洪煌堯（2012）。知識創新學習環境量表之編製 〔未出版之碩士論文〕。國立政治大學教育研究所。
林政逸、吳珮瑩（2016）。學習共同體前導學校實施情形、困境與因應策略之研究。師資培育與教師專業發展期刊，9(2)，59-88。
林倍伊、林顯達、李佩蓉、詹雯靜、洪國財、洪煌堯（2016）。在不同模式的電腦支援協作學習環境下，師培生理解教學理論層次之差異－以Blackboard和Knowledge Forum為例。資訊社會研究，(31)，66-102。
洪詠善（2018）。素養導向教學的界定、轉化與質踐。課程協作與質踐（第二輯負58-74)。臺北市：教育部師資課程教學與評量協作中心。
洪詠善、范信賢（2015）。同行~走進十二年國民基本教育課程綱要總綱。新北市：國家教育研究院。
洪煌堯、蔡佩真、林倍伊（2014）。透過知識創新教學理念與學習平臺以培養國小學生自然課合作學習與翻新想法的習慣。科學教育學刊，22(4)，413-439。https://doi.org/10.6173/CJSE.2014.2204.04
國家教育研究院（2014）。十二年國民基本教育課程體系發展指引。
張珍悅、徐勝一（2010）。永續發展教育脈絡探討：「聯合國永續發展教育十年計畫」之回顧。地理研究，(52)，1-26。https://doi.org/10.6234/JGR.2010.52.01
張景媛、林佳慧(2017）。綜合活動領域素養導向教學設計發展與實例。教育研究月刊，275，34-49。
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（2021）。十二年國民基本教育課程綱要總綱。臺北市：教育部。
許籐繼（2022）。十二年國教課綱實施對高中生學習負荷的問題與因應。臺灣教育評論月刊，11(3)，7-13。
陳美如（2017）。朝向學生學習的學校教育與課程教學變革探究。課程改革 2016 回顧與展望，77-100。
黃光雄、蔡清田(2017)。課程發展與設計新論。臺北市: 五南。
歐用生（2018）。歐序：深度的核心素養觀。載於楊俊鴻：素養導向課程與教學：理論與實踐。臺北市:高等教育文化事業有限公司。
潘慧玲、黃曬莉、陳文彥、鄭淑惠（2020）。學校準備好了嗎？國高中教育人員實施108課綱的變革準備度。教育研究與發展期刊，16(1)，65-100。https://doi.org/10.6925/SCJ.202003_16(1).0003
潘慧玲、鄭淑惠(2018)。植基真實情境的共學效應:學習共同體促動之教師改變。 課程與教學季刊，21(4)，121-150。
蔡清田（2012）。課程發展與設計的關鍵 DNA ：核心素養。五南。
蔡清田（2014）。國民核心素養:十二年國教課程改革的DNA。臺北:高等教育。
蔡清田（2018）。核心素養的課程發展。臺北：五南。
蔡清田（2019）。核心素養的學校本位課程發展。臺北:五南。
蔡清田（2020）。十二年國民基本教育課程綱要研修的核心素養。臺灣教育評論月刊，9(1)，8-12。
蔡清田、洪若烈、陳延興、盧美貴、陳聖謨、方德隆、林永豐、李懿芳（2012）。K-12各教育階段核 心素養與各領域課程統整研究。國家教育研究院委託研究報告。嘉義縣:國立中正大學課程研究所。
蔡清田、陳伯璋、陳延興、林永豐、盧美貴、李文富、方德隆、陳聖謨、楊 俊鴻、高新建、李懿芳、范信賢 （2013）。十二年國民基本教育課程發展指引草案擬議研究（國家教育研究院委託研究報告）。
Bentham, H. （2013）. Clearing the path that has been laid: A conceptualization of education for sustainable development. Journal of Teacher Education for Sustainability, 15(2), 25-41.
Bereiter, C. （2002）. Education and mind in the knowledge age. Mahwah, NJ: Lawrence Erlbaum Associates.
Bereiter, C. （2013）. Principled Practical Knowledge: Not a Bridge but a Ladder. Journal of the Learning Sciences, 23(1), 4–17. https://doi.org/10.1080/10508406.2013.812533
Blank, I. A. （2023）. What are large language models supposed to model? Trends in Cognitive Sciences, 27(11), 987–989. https://doi.org/10.1016/j.tics.2023.08.006
Brown, A. & Green, T.（2018）. Beyond teaching instructional design models: exploring the design process to advance professional development and expertise. Journal of Computing in Higher Education. 30.
Brown, H. D. （2001）. Teaching by Principles: An Interactive Approach to Language Pedagogy 2nd Edition. New York: Addison Wesley Longman, Inc.
Bucol, J. L., & Sangkawong, N. (2024). Exploring ChatGPT as a writing assessment tool. Innovations in Education and Teaching International, 1–16.
Chan, C. K., & Colloton, T. (2024). Generative AI in higher education: The ChatGPT effect. Routledge.
Chan, C. K., & Song, Y. （2010）. Towards a principle-based approach for knowledge creation in teacher professional development. Summer Institute, University of Toronto, Canada.
Dann, R. （2014）. Assessment as learning: blurring the boundaries of assessment and learning for theory, policy and practice. Assessment in Education: Principles, Policy & Practice, 21(2), 149–166. https://doi.org/10.1080/0969594X.2014.898128
David, P. A., & Foray, D. （2003）. Economic fundamentals of the knowledge society. Policy Futures in Education, 1(1), 2049.
Dick, W. & Cary, L. （1990）, The Systematic Design of Instruction (3rd Ed.). New York: Harper Collins.
Farhang, Asst & Ghorianfar, Sakhi Murad. (2023). Lesson Plan and Its Importance in Teaching Process. International Journal of Current Science Research and Review. 06. 10.47191/ijcsrr/V6-i8-57.
Floridi, L., & Chiriatti, M. (2020). GPT-3: Its nature, scope, limits, and consequences. Minds & Machines, 30(4), 681–694. https://doi.org/10.1007/s11023-020-09548-1
Fütterer, T., Fischer, C., Alekseeva, A., et al. (2023). ChatGPT in education: Global reactions to AI innovations. Scientific Reports, 13.
Gagne, R. M., Briggs, L. J. & Wagner, W. W. （1992）.Fostering sustained idea improvement with principle-based knowledge building analytic tools Principles of Instructional Design (4th Ed.). New York:Holt, Reihhart, and Winston Inc.
Gardner, J., O'Leary, M., & Yuan, L. (2021). Artificial intelligence in educational assessment:‘Breakthrough? Or buncombe and ballyhoo?’. Journal of Computer Assisted Learning, 37(5), 1207-1216.
Gao, Z.（2023）. Practical Knowledge Level Characteristics and Innovative Practice Achievement Transformation Mechanism of Vocational College Students. International Journal of Emerging Technologies in Learning. 18. 232-249.
Gerry, Stahl. （2007）. Meaning making in CSCL: Conditions and preconditions for cognitive processes by groups. Computer-Supported Collaborative Learning Conference, CSCL. 8. 652-661.
Hänze, M., Müller, M., & Berger, R. （2018）. Cross-age tutoring: How to promote tutees' active knowledge-building. Educational Psychology, 1-12.
Hargreaves, D. H. （1999）. The knowledge-creating school. British Journal of Educational Studies,47(2),122–144.
Homer-Dixon, T. （2006）. The upside of down: Catastrophe, creativity, and the renewal of civilization.Washington, DC: Island Press.
Hong, H. Y., Scardamalia, M., Messina, R., & Teo, C. L. (2015). Fostering sustained idea improvement with principle-based knowledge building analytic tools. Computers & Education, 89, 91-102.
Hong, H.Y. & Sullivan, F.R. （2009）. Towards an Idea-Centered, Principle-Based Design Approach to Support Learning as Knowledge Creation. Educational Technology Research and Development, 57(5), 613-627.
Hong, H.-Y., & Chai, C. S. （2017）. Principle-based design: Development of adaptive mathematics teaching practices and beliefs in a knowledge building environment. Computers & Education, 115, 3855.https://doi.org/10.1016/j.compedu.2017.07.011
Hong, H.-Y., Scardamalia, M., Messina, R., & Teo, C. L. （2008）. Principle-based design to foster adaptive use of technology for building community knowledge. In G. Kanselaar, V. Jonker, P. A. Kirschner, & F. J.
Hong, H.Y., Scardamalia, M., Zhang, J. & Zhang, J. （2010）. Knowledge Society Network: Toward a Dynamic, Sustained Network for Building Knowledge. Canadian Journal of Learning and Technology / La revue canadienne de l’apprentissage et de la technologie, 36(1),. Canadian Network for Innovation in Education.
Hong, Huang-Yao & Chen, Fei-Ching & Chai, Ching & Chan, Wen-Ching. （2010）. Teacher-education students’ views about knowledge building theory and practice. Instructional Science
Hong, Huang-Yao & Sullivan, Florence. （2009）. An idea-centered, principle-based design approach to support learning as knowledge creation. Educational Technology Research and Development, 57, 613-627. Educational Technology Research and Development.
Hume, A., & Coll, R. K. （2009）. Assessment of learning, for learning, and as learning: New Zealand case studies. Assessment in Education: Principles, Policy & Practice, 16(3), 269–290. https://doi.org/10.1080/09695940903319661
Iqbal, Md & Siddiqie, Shamsun & Mazid, Abdul. （2021）. Rethinking theories of lesson plan for effective teaching and learning. Social Sciences & Humanities Open. 4. Journal of Philosophy of Education, 48(4), 621-636.
Jauhiainen, J. S., & Garagorry Guerra, A. (2024). Generative AI in education: ChatGPT-4 in evaluating students’ written responses. Innovations in Education and Teaching International, 1–18.
Jukiewicz, Marcin. (2023). The Future of Grading Programming Assignments in Education: The Role of ChatGPT in Automating the Assessment and Feedback Process.
Kalla, D., Smith, N., Samaah, F., & Kuraku, S. (2023). Study and analysis of ChatGPT and its impact on different fields of study. International Journal of Innovative Science and Research Technology, 8(3), 7.
Kanık, Mehmet. (2024). The use of ChatGPT in assessment. International Journal of Assessment and Evaluation. 11. 608-621.
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., Stadler, M., Weller, J., Kuhn, J., & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103.
Klyshbekova, Maira & Abbott, Pamela. (2024). ChatGPT and Assessment in Higher Education: A Magic Wand or a Disruptor? Electronic Journal of e-Learning.
Kolade, O., Owoseni, A., & Egbetokun, A. (2024). Is AI changing learning and assessment as we know it? Evidence from a ChatGPT experiment and a conceptual framework. Heliyon, 10(4).
Lambrechts, W., Ghijsen, P. W. Th., Jacques, A., Walravens, H., Van Liderkerke, L., & Van Petegem, P. （2018）. Sustainability segmentation of business students: Toward self-regulated development of critical and interpretational competences in a post-truth era. Journal of Cleaner Production, 202, 561-570. https://doi.org 10.1016/ j.jclepro.2018.07.303
Lee, E. Y.C., Chan, C.K.K., & van Aalst, J. （2006）. Students assessing their own collaborative knowledge building. International Journal of Computer-Supported Collaborative Learning. 1(1). 58-87.Lesson Plan and Its Importance in Teaching Process. International Journal of Current Science Research and Review.
Leggatt, J., Broverman, A., & Pratt, K. (2023). What is ChatGPT? A review of the AI program in its own words. Forbes.
Lin, Feng & Chan, Carol. （2018）. Promoting elementary students’ epistemology of science through computer-supported knowledge-building discourse and epistemic reflection. International Journal of Science Education.
Liu, J., Liu, Z., Wang, C., Xu, Y., Chen, J., & Cheng, Y. (2024). K-12 students' higher-order thinking skills: Conceptualization, components, and evaluation indicators. Thinking Skills and Creativity, 52, 101551.
Mager, R. （1975）. Preparing Instructional Objectives (2nd Ed.). Belmont, CA: Lake Publishing Co.
Makarenko, O., Borysenko, O., Horokhivska, T., Kozub, V., & Yaremenko, D. (2024). Embracing Artificial Intelligence in Education: Shaping the Learning Path for Future Professionals. Multidisciplinary Science Journal, 6
Mekterovic, I., & Brkic, L. (2017). Setting up automated programming assessment system for higher education database course. International Journal of Education and Learning Systems, 2.
Merrill, M.D. （1983）. Component Display Theory. In C. Reigeluth (ed.), Instructional Design Theories and Models, 143-174. Hillsdale, NJ: Erlbaum Associates.
Moon, J. （2000）. Children Learning English. Oxford: Macmillan Education.
Moore, S., Nguyen, H. A., Bier, N., Domadia, T., & Stamper, J. (2022). Assessing the quality of student-generated short answer questions using GPT-3. In I. Hilliger, P. J. Munoz- Merino, T. D. Laet, A. Ortega-Arranz & T. Farrell (Eds.), Educating for a new future: Making sense of technology-enhanced learning adoption. 243-257.
Moore, S., Nguyen, H.A., Chen, T., & Stamper, J. (2023). Assessing the Quality of Multiple- Choice Questions Using GPT-4 and Rule-Based Methods. In O. Viberg, I. Jivet, P. K. Munoz-Merino, M. Perifanou & T. Papathoma (Eds.), Responsive and Sustainable Educational Features. 229-245.
OECD,. （2019）. An OECD Learning Framework 2030. 10.1007/978-3-030-26068-2_3.
Paavola, S., Lipponen, L., & Hakkarainen, K. （2004）. Models of innovative knowledge communities and three metaphors of learning. Review of Educational Research, 74(4), 557-576.
Parkin, S., Johnston, A., Buckland, H., Brookes, F., & White, E. （2004）. Learning and skills for sustainable development: Developing a sustainability literate society—Guidance for higher education institutions. Forum for the Future.
Pikkarainen, Eetu. (2014). Competence as a Key Concept of Educational Theory: A Semiotic Point of View. Journal of Philosophy of Education. 48. 10.1111/1467-9752.12080.
Ratnawati, Ratnawati. （2017）Developing a Lesson Plan for Teaching English for Specific Purposes to Adult Learners, University.Journal of Applied Linguistics and Literacy
Ray, P. P. (2023). ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet of Things and Cyber-Physical Systems, 3, 121-154.
Scardamalia, M., & Bereiter, C. （2006）. Knowledge building: Theory, pedagogy, and technology. In K. Sawyer (Ed.), Cambridge handbook of the learning sciences 97-11. New York: Cambridge University Press.
Scardamalia, M. (2002). Collective cognitive responsibility for the advancement of knowledge. Liberal education in a knowledge society, 97, 67-98.
Scardamalia, M. (2004). CSILE/knowledge forum education and technology: An encyclopedia.183–192. Santa Barbara, CA: ABC-CLIO.
Sfard, A. （1998）. On two metaphors for learning and the dangers of choosing just one. EducationalResearcher, 27(2), 413.
Shah, M. M., & Kavathiya, H. R. (2024). Artificial Intelligence in Education: The Power and
Dangers of ChatGPT in the Classroom: Unveiling the Future: Exploring Conversational AI. Springer.
Skalka, J., Drlík, M., & Obonya, J. (2019). Automated assessment in learning and teaching programming languages using virtual learning environment. 2019 IEEE global engineering education conference (EDUCON). 689-697.
Soliman, Dina & Costa, Stacy & Scardamalia, Marlene. (2021). Knowledge Building in Online Mode: Insights and Reflections. Education Sciences. 11. 10.3390/educsci11080425.
Tan, S. C., Chan, C., Bielaczyc, K., Ma, L., Scardamalia, M., & Bereiter, C. (2021). Knowledge building: Aligning education with needs for knowledge creation in the digital age. Educational Technology Research and Development, 69(4), 2243–2266.
Team, O. (2022). ChatGPT: Optimizing language models for dialogue. 2022-09-20)[2023-09-27]. https://openai. com/blog/chatgpt.
United Nations Educational, Scientic and Cultural Organization (UNESCO). （2005）. Krogh, G., Ichijo, K., & Nonaka, I. （2000）Towards knowledge societies. Paris: UNESCO.von. Enabling knowledge creation. New York: Oxford University
United Nations Educational, Scientific and Cultural Organization. （2013b）.
United Nations Educational, Scientific and Cultural Organization. （2013c）. Education: Mission. Retrieved from http://www.unesco.org/new/en/ education/themes/leading-the-international-agenda/education-for-sustaina ble-development/mission/
Wang, H., Dang, A., Wu, Z., & Mac, S. (2024). Generative AI in higher education: Seeing ChatGPT through universities' policies, resources, and guidelines. Computers and Education: Artificial Intelligence, 7.
Yang, X., Wang, Q., & Lyu, J. (2024). Assessing ChatGPT’s educational capabilities and application potential. ECNU Review of Education, 7(3), 699-713.
Zhang, J., Hong, H.-Y., Scardamalia, M., Teo, C., & Morley, E. （2011）. Sustaining knowledge building as a principle-based innovation at an elementary school. Journal of the Learning Sciences, 20(2), 262-307. |
| Description: | 碩士
國立政治大學
教育學系
112152012 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0112152012 |
| Data Type: | thesis |
| Appears in Collections: | [教育學系] 學位論文
|
Files in This Item:
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| 201201.pdf | | 5081Kb | Adobe PDF | 1 | View/Open |
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