博碩士論文 111524009 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:61 、訪客IP:18.189.194.168
姓名 洪丞威(Cheng-Wei Hung)  查詢紙本館藏   畢業系所 網路學習科技研究所
論文名稱 應用生成式模型輔助問題生成學習系統於國小社會 課程之研究
(Applying Generative Modeling to Assist Problem Generation Learning System in National Elementary School Social Studies Curriculum)
相關論文
★ 基於間隔效應與知識追蹤之適性化學習演算法系統設計與應用:以多益英語學習為例★ 結合社會調節學習平台與教中學課程設計以增進大學生視覺化資料分析能力與調節學習
★ 以深度知識追蹤模型應用於程式學習系統★ 結合聊天機器人與推薦系統之閱讀學伴應用於國小閱讀
★ 視覺化閱讀歷程系統於國小身教式持續安靜閱讀之應用★ 基於文本型程式編寫紀錄之自我調節儀表板於程式設計學習成效探究
★ 結合重新設計之翻轉教室模型與視覺化分析系統對於程式設計學習之影響★ 結合視覺化儀表板與合作腳本輔助VR共創活動以探討國小學童之學習行為、情感與認知參與
★ 結合視覺化儀表板之專案管理平台於在職學生專案能力與資料分析學習之影響★ 專題導向學習與調節學習儀表板應用於資料視覺化在職課程
★ 整合預測分析與學習儀表板以提升準時畢業率: 以印尼高等教育為例★ 結合生成式人工智慧之探究式學習同伴系統以增進研究生資料視覺化素養能力
★ 結合生成式人工智慧與4F動態回顧循環理論於國小閱讀學習同伴系統的應用與成效評估★ 應用指數平滑法實現短期學習成效預測與學習歷程儀表板系統建置
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   至系統瀏覽論文 (2029-8-1以後開放)
摘要(中) 社會課程在基礎教育中至關重要。然而,現今的社會課程主要還是藉由紙本教材搭配影片等多媒體的形式進行授課,無法有效提升學生學習動機。因此,本研究探討生成式輔助問題生成學習系統來開發一個虛擬同伴系統,旨在增強社會教育中的學習成效與學習動機。透過自行開發的考卷怪獸線上學習平台,本研究引入學習同伴的機制,學生可以領養一個小怪獸作為學習的夥伴,並且在學習中照顧與升級怪獸。系統的主要學習模式透過讓學生自由使用平板電腦拍攝學習主題相關的文字內容,系統從圖像中的重點文字進行影像辨識的擷取,並透過生成式AI產生問題,並結合遊戲化元素進行與同儕創造之問題進行練習挑戰。在此種科技輔助之下本研究結合問題創造的學習模式,學生可以從教課書尋找重點,藉由生成式模型的創造力,建構一個問題的範本,最後讓學生修改創造出屬於自己的問題。本研究也讓教師參與了整個問題創造的學習情境,教師可以透過本研究開發的學生學習歷程總覽給予學生問題修改的建議與回饋,幫助學生提高問題的品質與學習策略。
本研究實驗對象為三十七名四至六年級學生,他們使用平板電腦參加了為期 10 週的社會學習課程。研究採用量化和質化資料收集方法,以確保全面瞭解學生的觀點,研究工具包括社會科能力測驗、學習動機量表、批判性思考量表、自主學習量表。採用問卷調查評估學生對系統功能的看法以及學習方法對學習動機的潛在影響。
結果表明,學生的學習成就、學習動機、批判性思考以及自主學習都有顯著提高。透過分群演算法也發現越常使用本系統進行練習挑戰的學生,他們的學習成就會高於不常使用系統進行練習的學生。根據年級的分組檢定中也發現年級越高的學生在進行挑戰系統時也有著更高的答對率。本研究設計的問題創造學習模式與學習平臺提升了學生學習的效果,並找出與學習表現幅度較大的學生在學習行為上的差異。未來可以嘗試在其他領域使用此種學習模式進行學習,也可擴大實驗規模,進一步確認實驗的有效性。
摘要(英) The social studies curriculum plays a critical role in foundational education. However, the current social studies curriculum, delivered via traditional media like paper textbooks and videos, often fails to significantly boost students′ motivation to learn. Therefore, this study investigates the development of a virtual peer system by using a Generative AI question generating learning system, which aims to enhance the learning effectiveness and motivation in social education. Through the self-developed Exam Monster online learning platform, this study introduces the mechanism of learning peers, where students can adopt a small monster as a learning partner, and take care of and upgrade the monster during the learning process. The main learning mode of the system allows students to capture textbook content on their tablets, generate questions from the key words in the images, and combine them with gamification elements to practice challenges with peer-created questions. Leveraging this technology, the study integrates a problem generation learning model that enables students to identify central ideas in the textbook, craft a template for the problem using generative modeling creativity, and then alter it to formulate their unique problems. The study also allowed teachers to participate in the whole problem creation learning situation, and teachers could give students suggestions and feedback on problem modification through the overview of students′ learning history developed in this study, helping students to improve the quality of their problems and learning strategies.
The research involved 37 students from fourth to sixth grade who engaged in a 10-week social studies curriculum utilizing tablet computers. Quantitative and qualitative data collection methods were used to ensure a comprehensive understanding of students′ perspectives. Instruments used in the study included the Social Studies Competency Test, Motivation to Learn Scale, Critical Thinking Scale, and Self-Directed Learning Scale. A questionnaire was used to assess the students′ perceptions of the system′s functioning and the potential impact of learning methods on learning motivation.
The findings indicated that there was a significant improvement in students′ academic success, motivation, critical thinking abilities, and capacity for self-directed learning. The clustering analysis indicated that high-performing students tackled questions with greater diligence within the Paper Monster challenge platform, achieving a higher accuracy rate and frequently revisiting the challenges. Furthermore, assessments segmented by grade level showed that students at more advanced grade levels exhibited increased engagement rates in response to utilizing the challenge system. In this study, the developed question-creation learning model and platform improved student learning results and pinpointed behavioral differences among students with higher performance levels. Moving forward, we might consider applying this educational model to different fields of study. Additionally, enlarging the scope of the experiment could help us to more conclusively verify its effectiveness.
關鍵字(中) ★ 生成式 AI
★ 批判性思考
★ 問題生成
★ 社會科教育
★ 學習動機
關鍵字(英) ★ Generative AI
★ Critical Thinking
★ Question Generation
★ Social Studies Education
★ Learning Motivation
論文目次 中文摘要 i
Abstract iii
誌謝 v
目錄 vi
圖目錄 ix
表目錄 x
一、緒論 1
1-1 研究背景與動機 1
1-2 研究目的 3
1-3 研究問題 4
1-4 名詞解釋 4
二、文獻探討 6
2-1問題生成 6
2-1-1自動問題生成 6
2-1-2 ChatGPT生成式模型 7
2-1-3學生生成問題 9
2-2批判性思考 11
2-2-1批判性思考 11
2-2-2歷史批判性思考 12
2-3遊戲化學習與虛擬寵物 13
2-3-1遊戲化學習 13
2-3-2虛擬寵物 14
2-3-3學習同伴 15
2-4自主學習 16
2-4-1自主學習 16
2-4-2社會教育中的自主學習 18
2-4-3科技輔助自主學習 19
三、研究方法 21
3-1 研究設計 21
3.2 研究對象 21
3.3 實驗設計 22
3.4 研究工具 24
3-4-1 社會科能力測驗 25
3-4-2 學習動機問卷 25
3-4-3 自主學習問卷 25
3-4-4 批判性思考問卷 26
3-4-5 系統日誌與其他 26
3-5 分析工具與方法 27
3-5-1 問卷工具信度 28
3-5-2 常態檢定 28
3-6 學習表現分群 29
四、系統設計 31
4-1 系統總覽 31
4-2 問題創造:生成式輔助社會課程學生創造問題上傳平臺 33
4-3 怪獸養成:科技輔助社會課程之學習激勵與進步追蹤平臺 39
4-4 題目總覽:社會課程之學生創造題目查看 42
4-5 挑戰問答:社會課程之學習激勵與互動平臺 42
4-6 創作題目即時評估和教師輔助:提升學生生成創作題目的活動 45
4-7 學習歷程總覽: 47
五、研究結果 50
5-1社會科能力測驗: 50
5-1-1 學習表現之差異: 50
5-1-2 不同年級之學生對於客家博覽會理解能力差異: 51
5-2 學習動機變化: 52
5-2-1 課程設計與系統對高低學習表現學生的學習動機影響: 52
5-3 批判性思考變化: 53
5-4 自主學習變化: 53
5-4-1 課程設計與系統對高低學習表現學生的自主學習影響: 54
5-5 問卷量表間之關係: 55
5-6 學習日誌分析: 56
5-6-1 系統日誌統計: 56
5-6-2 學習動作日誌統計: 56
5-6-3 學習成效與學習行為之關聯性: 57
5-6-4 學習日誌與問卷量表之關聯性: 58
5-7 問卷調查結果: 59
5-7-1 開放式問卷編碼規則: 59
5-7-2 學生使用上無遭遇困難 59
5-7-3 學生根據需求使用問題生成 60
5-7-4 學生喜好本系統開發功能 62
六、討論 65
6-1 不同年級學生之差異 65
6-1-1 不同年級之學生對於問題創造系統上的使用差異 65
6-1-2 不同年級之學生對於學習動機之差異 67
6-1-3不同年級之學生對於批判性思考之差異 68
6-1-4不同年級之學生對於自主學習之差異 70
6-2 自動出題模式與手動出題模式之比較 71
6-2-1 出題數量統計 71
6-2-2 自動出題與手動出題的影響 72
6-3 相關研究之比較 74
6-3-1相關自動出題研究比較 74
6-3-2相關學習同伴研究比較 75
七、結論 77
7-1 研究結論 77
7-1-1 學生的學習能力、學習動機、批判性思考以及自主學習能力顯著提升 77
7-1-2 兩種出題模式皆受學生喜好 77
7-1-3 學生喜好挑戰同儕之題目 78
7-1-4 高學習成就之學生更常使用系統練習 79
7-1-5 練習次數與學習成就正相關 79
7-1-5 高年級學生在挑戰系統時會更謹慎的答題 80
7-1-6 高學習成就之學生透過有效使用系統學習 80
7-2 研究限制 80
7-3 未來展望 82
參考文獻 84
附錄一、知情同意書(學生) 94
附錄二、知情同意書(教師) 97
附錄三、客家博覽會能力測驗(前測) 100
附錄三、客家博覽會能力測驗(後測) 103
附錄四、第二次社會科能力測驗(四年級) 106
附錄五、第二次社會科能力測驗(五年級) 108
附錄六、第二次社會科能力測驗(六年級) 110
附錄七、第三次社會科能力測驗(四年級) 112
附錄八、第三次社會科能力測驗(五年級) 114
附錄九、第三次社會科能力測驗(六年級) 115
附錄十、學習動機問卷 117
附錄十一、批判性思考問卷 118
附錄十二、自主學習問卷 119
附錄十三、問題生成任務反思問卷 120
參考文獻 中文文獻
王金國. (2023). [推動中小學數位學習精進方案]的認識, 認同與實踐. 臺灣教育評論月刊, 12(1), 139-144.
https://doi.org/10.6791/TER.201210.0077
陳麗華, & 林淑華. (2008). 社會學習領域第二, 三, 四學習階段教科書中社會行動取向教材之比較分析. 課程與教學.
https://doi.org/10.6384/CIQ.200807.0093
英文文獻
Abd-El-Fattah, S. M. (2010). Garrison′s Model of Self-Directed Learning: Preliminary Validation and Relationship to Academic Achievement. Spanish Journal of Psychology, 13(2), 586-596. https://doi.org/Doi 10.1017/S1138741600002262
Abdullah, J., Mohd-Isa, W. N., & Samsudin, M. A. (2019). Virtual reality to improve group work skill and self-directed learning in problem-based learning narratives. Virtual Reality, 23(4), 461-471. https://doi.org/10.1007/s10055-019-00381-1
Abramovich, S., & Cho, E. (2006). Technology as a medium for elementary preteachers′ problem-posing experience in mathematics. Journal of Computers in Mathematics and Science Teaching, 25(4), 309-323. https://doi.org/10.1111/j.1949-8594.1977.tb09200.x
Acun, C., & Acun, R. (2024). GAI-Enhanced Assignment Framework: A Case Study on Generative AI Powered History Education. In: NeurIPS.
Aidinopoulou, V., & Sampson, D. G. (2017). An Action Research Study from Implementing the Flipped Classroom Model in Primary School History Teaching and Learning. Educational Technology & Society, 20(1), 237-247. https://doi.org/10.2991/sschd-17.2017.63
Akkari, A., & Maleq, K. (2020). Global citizenship education: Recognizing diversity in a global world. In Global citizenship education: Critical and international perspectives (pp. 3-13). Springer International Publishing Cham. https://doi.org/10.1007/978-3-030-44617-8_1
Alcivar, N. I. S., Gallego, D. C., Quijije, L. S., & Quelal, M. M. (2019). Developing a dashboard for monitoring usability of educational games apps for children. Proceedings of the 2019 2nd International Conference on Computers in Management and Business,
Arruabarrena, R., Sánchez, A., Blanco, J. M., Vadillo, J. A., & Usandizaga, I. (2019). Integration of good practices of active methodologies with the reuse of student-generated content. International Journal of Educational Technology in Higher Education, 16(1), 1-20. https://doi.org/ARTN 10
10.1186/s41239-019-0140-7
Atlas, S. (2023). ChatGPT for higher education and professional development: A guide to conversational AI. https://doi.org/10.4018/978-1-7998-9247-2.ch004
Bai, S., Hew, K. F., & Huang, B. (2020). Does gamification improve student learning outcome? Evidence from a meta-analysis and synthesis of qualitative data in educational contexts. Educational Research Review, 30, 100322. https://doi.org/10.1016/j.edurev.2020.100322
Barlow, A. T., & Cates, J. M. (2006). The impact of problem posing on elementary teachers′ beliefs about mathematics and mathematics teaching. School Science and Mathematics, 106(2), 64-73. https://doi.org/10.1111/j.1949-8594.2006.tb18136.x
Bonk, C. J., & Lee, M. M. (2017). Motivations, achievements, and challenges of self-directed informal learners in open educational environments and MOOCs. Journal of Learning for Development, 4(1). https://doi.org/10.56059/jl4d.v4i1.195
Brown, S. I., & Walter, M. I. (2005). The art of problem posing. Psychology Press. https://doi.org/10.4324/9780203052266-6
Chan, T.-W., & Chou, C.-Y. (1995). Simulating a learning companion in reciprocal tutoring systems. https://doi.org/10.3115/222020.222053
Chen, Z. H., Liao, C. V., Chien, T. C., & Chan, T. W. (2011). Animal companions: Fostering children′s effort-making by nurturing virtual pets. British Journal of Educational Technology, 42(1), 166-180. https://doi.org/10.1111/j.1467-8535.2009.01003.x
Costa, A. L., & Kallick, B. (2003). Assessment strategies for self-directed learning. Corwin Press. https://doi.org/10.4135/9781483328782.n6
Cox, C., & Tzoc, E. (2023). ChatGPT: Implications for academic libraries. College & Research Libraries News, 84(3), 99. https://doi.org/10.26443/el.v34i2.307
Dai, H. M., Teo, T., & Rappa, N. A. (2020). Understanding continuance intention among MOOC participants: The role of habit and MOOC performance. Computers in Human Behavior, 112, 106455. https://doi.org/ARTN 106455
10.1016/j.chb.2020.106455
Dehouche, N. (2021). Plagiarism in the age of massive Generative Pre-trained Transformers (GPT-3). Ethics in Science and Environmental Politics, 21, 17-23. https://doi.org/10.3354/esep00195
Deterding, S., Dixon, D., Khaled, R., & Nacke, L. (2011). From game design elements to gamefulness: defining" gamification". Proceedings of the 15th international academic MindTrek conference: Envisioning future media environments,
Deterding, S., Sicart, M., Nacke, L., O′Hara, K., & Dixon, D. (2011). Gamification. using game-design elements in non-gaming contexts. In CHI′11 extended abstracts on human factors in computing systems (pp. 2425-2428). https://doi.org/10.1145/1979742.1979575
Devlin-Scherer, R., & Sardone, N. B. (2010). Digital simulation games for social studies classrooms. The Clearing House, 83(4), 138-144. https://doi.org/10.1080/00098651003774836
Dijkstra, R., Genç, Z., Kayal, S., & Kamps, J. (2022). Reading Comprehension Quiz Generation using Generative Pre-trained Transformers. In: AachenCEUR-WS.
Divate, M., & Salgaonkar, A. (2017). Automatic question generation approaches and evaluation techniques. Current Science, 113(9), 1683-1691. https://doi.org/10.18520/cs/v113/i09/1683-1691
Doyle, E., Buckley, P., & McCarthy, B. (2021). The impact of content co-creation on academic achievement. Assessment & Evaluation in Higher Education, 46(3), 494-507. https://doi.org/10.1080/02602938.2020.1782832
Draper, B., Yee, W. L., Pedrana, A., Kyi, K. P., Qureshi, H., Htay, H., Naing, W., Thompson, A. J., Hellard, M., & Howell, J. (2022). Reducing liver disease-related deaths in the Asia-Pacific: the important role of decentralised and non-specialist led hepatitis C treatment for cirrhotic patients. Lancet Reg Health West Pac, 20, 100359. https://doi.org/10.1016/j.lanwpc.2021.100359
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., & Ahuja, M. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.24247/ijcmsjun20198
Elder, L., Gorzycki, M., & Paul, R. (2019). The Student Guide to Historical Thinking: Going Beyond Dates, Places, and Names to the Core of History. Rowman & Littlefield. https://doi.org/10.18574/nyu/9781479860524.003.0004
Elias, M. J., Zins, J., & Weissberg, R. P. (1997). Promoting social and emotional learning: Guidelines for educators. Ascd. https://earlylearningfocus.org/wp-content/uploads/2019/12/promoting-social-and-emotional-learning-1.pdf
English, L. D. (1997). Promoting a problem-posing classroom. Teaching children mathematics, 4(3), 172-179. https://doi.org/https://doi.org/10.5951/TCM.4.3.0172
Ennis, R. H. (1985). A logical basis for measuring critical thinking skills. Educational leadership, 43(2), 44-48. https://api.semanticscholar.org/CorpusID:17938065
Eysenbach, G. (2023). The Role of ChatGPT, Generative Language Models, and Artificial Intelligence in Medical Education: A Conversation With ChatGPT and a Call for Papers. JMIR Med Educ, 9(1), e46885. https://doi.org/10.2196/46885
Facione, P. (1990). Critical thinking: A statement of expert consensus for purposes of educational assessment and instruction (The Delphi Report). https://philpapers.org/archive/FACCTA.pdf
Feuerriegel, S., Hartmann, J., Janiesch, C., & Zschech, P. (2024). Generative ai. Business & Information Systems Engineering, 66(1), 111-126. https://doi.org/10.1007/s12599-020-00650-3
Garrison, D. R. (1997). Self-directed learning: Toward a comprehensive model. Adult education quarterly, 48(1), 18-33. https://doi.org/Doi 10.1177/074171369704800103
George, D., & Mallery, P. (2019). IBM SPSS statistics 26 step by step: A simple guide and reference. Routledge.
Gokcearslan, S. (2017). Perspectives of students on acceptance of tablets and self-directed learning with technology. Contemporary educational technology, 8(1), 40-55. https://doi.org/10.30935/cedtech/6186
González, C., & Mora, A. (2015). Técnicas de gamificación aplicadas en la docencia de Ingeniería Informática. ReVisión, 8(1), 29-40. https://doi.org/10.35362/rie5921387
Grévisse, C. (2023). Comparative Quality Analysis of GPT-Based Multiple Choice Question Generation. International Conference on Applied Informatics,
Green, T., Ponder, J., & Donovan, L. (2014). Educational technology in social studies education. Handbook of research on educational communications and technology, 573-582. https://doi.org/10.1007/978-1-4614-3185-5_45
Groh, F. (2012). Gamification: State of the art definition and utilization. Institute of Media Informatics Ulm University, 39, 31. https://doi.org/10.1007/BF02696290
Gupta, R., Park, J. B., Bisht, C., Herzog, I., Weisberger, J., Chao, J., Chaiyasate, K., & Lee, E. S. (2023). Expanding Cosmetic Plastic Surgery Research With ChatGPT. Aesthet Surg J, 43(8), 930-937. https://doi.org/10.1093/asj/sjad069
Han, Z. (2016). Historical geography and environmental history in China. Journal of Chinese Studies, 1, 1-8. https://doi.org/10.1186/s40853-016-0002-z
Hennis, T. (2017). Engaging at-risk youth through self-directed learning. Italian Journal of Educational Technology, 25(1), 18-30. https://doi.org/10.18356/15645304-2018-2-15
Heron, G., & Lerpiniere, J. (2013). Re-engineering the multiple choice question exam for social work. European Journal of Social Work, 16(4), 521-535. https://doi.org/10.1080/13691457.2012.691873
Horbach, A., Aldabe, I., Bexte, M., Lopez de Lacalle, O., & Maritxalar, M. (2020, May). Linguistic Appropriateness and Pedagogic Usefulness of Reading Comprehension Questions.Proceedings of the Twelfth Language Resources and Evaluation Conference Marseille, France.
Hughes, J., Morrison, L., Mamolo, A., Laffier, J., & de Castell, S. (2019). Addressing bullying through critical making. British Journal of Educational Technology, 50(1), 309-325. https://doi.org/10.1111/bjet.12714
Hwang, G.-J. (2014). Definition, framework and research issues of smart learning environments-a context-aware ubiquitous learning perspective. Smart Learning Environments, 1(1), 1-14. https://doi.org/10.1186/s40561-014-0004-5
Hwang, G. J., & Chen, N. S. (2023). Editorial Position Paper: Exploring the Potential of Generative Artificial Intelligence in Education: Applications, Challenges, and Future Research Directions. Educational Technology & Society, 26(2). https://doi.org/10.30191/Ets.202304_26(2).0014
Hwang, G. J., Chiu, L. Y., & Chen, C. H. (2015). A contextual game-based learning approach to improving students′ inquiry-based learning performance in social studies courses. Computers & Education, 81, 13-25. https://doi.org/10.1016/j.compedu.2014.09.006
Hwang, G. J., Yang, L. H., & Wang, S. Y. (2013). A concept map-embedded educational computer game for improving students′ learning performance in natural science courses. Computers & Education, 69, 121-130. https://doi.org/10.1016/j.compedu.2013.07.008
Ikwumelu, S., & Oyibe, O. A. (2014). Effects of Self-Directed Instructional Method on Secondary School Students’ Achievement in Social Studies. International Journal of Learning and development, 5(1), 1-9. https://doi.org/10.5296/ijld.v5i1.6891
Jones, J. A. (2019). Scaffolding self-regulated learning through student-generated quizzes. Active Learning in Higher Education, 20(2), 115-126. https://doi.org/10.1177/1469787417735610
Kalinauskas, M. (2014). Gamification in fostering creativity. Socialinės Technologijos, 4(01), 62-75. https://doi.org/10.13165/ST-14-4-1-05
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., & Hüllermeier, E. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and individual differences, 103, 102274. https://doi.org/10.18653/v1/2022.bigscience-1.6
Ke, F. F. (2008). Computer games application within alternative classroom goal structures: cognitive, metacognitive, and affective evaluation. Etr&D-Educational Technology Research and Development, 56(5-6), 539-556. https://doi.org/10.1007/s11423-008-9086-5
Khan, R. A., Jawaid, M., Khan, A. R., & Sajjad, M. (2023). ChatGPT- Reshaping medical education and clinical management. Pakistan Journal of Medical Sciences, 39(2), 605-607. https://doi.org/10.12669/pjms.39.2.7653
Khiat, H. (2015). Measuring self-directed learning: A diagnostic tool for adult learners. Journal of university teaching & learning practice, 12(2), 2. https://doi.org/10.53761/1.12.2.2
Kloos, C. D., Alario-Hoyos, C., Estévez-Ayres, I., Callejo-Pinardo, P., Hombrados-Herrera, M. A., Muñoz-Merino, P. J., Moreno-Marcos, P. M., Muñoz-Organero, M., & Ibáñez, M. B. (2024). How can Generative AI Support Education? 2024 IEEE Global Engineering Education Conference (EDUCON),
Knowles, M. S. (1975). Self-directed learning: A guide for learners and teachers. https://doi.org/10.1177/105960117700200220
Kobylarek, A., Błaszczyński, K., Ślósarz, L., & Madej, M. (2022). Critical Thinking Questionnaire (CThQ)–construction and application of critical thinking test tool. Andragogy Adult Education and Social Marketing, 2(2), 1-1. https://doi.org/10.15503/andr2022.1
Kumar, A. P., Nayak, A., K, M. S., Chaitanya, & Ghosh, K. (2023). A Novel Framework for the Generation of Multiple Choice Question Stems Using Semantic and Machine-Learning Techniques. International Journal of Artificial Intelligence in Education, 1-44. https://doi.org/10.1080/08850607.2021.1966589
Kurdi, G., Leo, J., Parsia, B., Sattler, U., & Al-Emari, S. (2020). A systematic review of automatic question generation for educational purposes. International Journal of Artificial Intelligence in Education, 30, 121-204. https://doi.org/10.1007/s40593-019-00186-y
Kusuma, S. F., Siahaan, D. O., & Fatichah, C. (2022). Automatic question generation with various difficulty levels based on knowledge ontology using a query template. Knowledge-Based Systems, 249, 108906. https://doi.org/ARTN 108906
10.1016/j.knosys.2022.108906
Lai, E. R. (2011). Critical thinking: A literature review. Pearson′s Research Reports, 6(1), 40-41. https://doi.org/10.1145/1979742.1979575
Lai, H., Gierl, M. J., Touchie, C., Pugh, D., Boulais, A. P., & De Champlain, A. (2016). Using Automatic Item Generation to Improve the Quality of MCQ Distractors. Teach Learn Med, 28(2), 166-173. https://doi.org/10.1080/10401334.2016.1146608
Last, M., & Danon, G. (2020). Automatic question generation. Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery, 10(6), e1382. https://doi.org/ARTN e1382
10.1002/widm.1382
Law, L. (2024). Application of generative artificial intelligence (GenAI) in language teaching and learning: A scoping literature review. Computers and Education Open, 100174. https://doi.org/10.1109/ICAIE50891.2020.00017
Lee, U. G., Jung, H. W., Jeon, Y., Sohn, Y., Hwang, W., Moon, J., & Kim, H. (2023). Few-shot is enough: exploring ChatGPT prompt engineering method for automatic question generation in english education. Education and Information Technologies, 1-33. https://doi.org/10.1007/s10639-023-12249-8
Li, X., Ma, Z., Tu, Y., & Du, Y. (2021). Study on the Application of Artificial Intelligence Technology in Empowering Education: Taking" Intelligent Learning Partner" as an Example. 2021 2nd International Conference on Information Science and Education (ICISE-IE),
Liu, M., Rus, V., & Liu, L. (2017). Automatic chinese multiple choice question generation using mixed similarity strategy. IEEE Transactions on Learning Technologies, 11(2), 193-202. https://doi.org/10.1109/TLT.2017.2679009
Maguth, B. M., List, J. S., & Wunderle, M. (2015). Teaching social studies with video games. The Social Studies, 106(1), 32-36. https://doi.org/10.1080/00377996.2014.961996
Majors, K. (2013). Children′s perceptions of their imaginary companions and the purposes they serve: An exploratory study in the United Kingdom. Childhood-a Global Journal of Child Research, 20(4), 550-565. https://doi.org/10.1177/0907568213476899
Malone, T. W., & Lepper, M. R. (2021). Making learning fun: A taxonomy of intrinsic motivations for learning. In Aptitude, learning, and instruction (pp. 223-254). Routledge. https://doi.org/10.32473/edis-4h340-2014
Maslow, A. H. (1958). A Dynamic Theory of Human Motivation. https://doi.org/https://doi.org/10.1037/11305-004
McConnell, A. R., Brown, C. M., Shoda, T. M., Stayton, L. E., & Martin, C. E. (2011). Friends with benefits: on the positive consequences of pet ownership. J Pers Soc Psychol, 101(6), 1239-1252. https://doi.org/10.1037/a0024506
McPeck, J. E. (1990). Critical thinking and subject specificity: A reply to Ennis. Educational researcher, 19(4), 10-12. https://doi.org/https://doi.org/10.2307/1176382
Morales-Urrutia, E. K., Ocaña, J. M., Pérez-Marín, D., & Pizarro, C. (2021). Can mindfulness help Primary Education students to learn how to program with an emotional learning companion? IEEE Access, 9, 6642-6660. https://doi.org/10.1109/ACCESS.2021.3049187
Morris, T. H. (2019). An analysis of Rolf Arnold′s systemic-constructivist perspective on self-directed learning. https://doi.org/10.4102/aosis.2021.BK279.01
Morris, T. H., & Rohs, M. (2023). The potential for digital technology to support self-directed learning in formal education of children: A scoping review. Interactive learning environments, 31(4), 1974-1987. https://doi.org/10.1080/10494820.2020.1870501
Myers, C. B., Adler, S., Brandhorst, A., Dougan, A. M., Dumas, W., Huffman, L., Rossman, P., Schneider, D. O., Stahl, R. J., & Baber, C. R. (2002). National standards for social studies teachers. Silver Spring, Md: National Council For The Social Studies. https://doi.org/10.1080/00377999809599827
National Center for History in the Schools, L. A., Ca. (1996). National Standards for History. Basic Edition. Center for History in the Schools.
Oak, J., & Bae, J. (2013). Smart Multiplatform-Based CPR Game App Design. Advanced Science and Technology Letters (Games and Graphics 2013), 39, 20-23. https://doi.org/10.14257/astl.2013.39.04
Ocaña, J., Morales-Urrutia, E., Pérez-Marín, D., & Pizarro, C. (2023). About Gamifying an Emotional Learning Companion to Teach Programming to Primary Education Students. Simulation & Gaming, 10468781231175013. https://doi.org/10.1109/SIIE53363.2021.9583626
Oliver, J., & Huxley, P. (1988). The development of computer assisted learning (CAL) materials for teaching and testing mental health social work in Great Britain: A review of four years progress. Journal of Teaching in Social Work, 2(2), 21-34. https://doi.org/https://doi.org/10.1300/J067v02n02_03
Ong, A. C., & Borich, G. D. (2006). Teaching strategies that promote thinking: Models and curriculum approaches. McGraw-Hill. https://doi.org/10.7459/ct/16.1.04
Oyibe, O. A., Edinyang, S. D., & Effiong, V. N. (2015). Self-directed learning strategy: A tool for promoting critical thinking and problem solving skills among social studies students. IOSR Journal of VLSI and Signal Processing, 5(3), 52-58. https://doi.org/10.21831/jptk.v25i1.22574
Park, Y., & Jo, I. H. (2015). Development of the Learning Analytics Dashboard to Support Students′ Learning Performance. Journal of Universal Computer Science, 21(1), 110-133. https://doi.org/10.1007/978-3-030-81222-5_22
Pintrich, P. R. (2000). Multiple goals, multiple pathways: The role of goal orientation in learning and achievement. Journal of educational psychology, 92(3), 544-555. https://doi.org/Doi 10.1037/0022-0663.92.3.544
Roa-Seïler, N., Craig, P., Arias, J. A., Saucedo, A. B., Díaz, M. M., & Rosano, F. L. (2014). Defining a child’s conceptualization of a virtual learning companion. INTED2014 Proceedings,
Rohs, M., & Ganz, M. (2015). MOOCs and the Claim of Education for All: A Disillusion by Empirical Data. International review of research in open and distributed learning, 16(6), 1-19. https://doi.org/10.19173/irrodl.v16i6.2033
Rudolph, J., Tan, S., & Tan, S. (2023). ChatGPT: Bullshit spewer or the end of traditional assessments in higher education? Journal of Applied Learning and Teaching, 6(1). https://doi.org/10.5040/9781472552891.ch-002
Salmon, A. K., & Barrera, M. X. (2021). Intentional questioning to promote thinking and learning. Thinking Skills and Creativity, 40, 100822. https://doi.org/10.1016/j.tsc.2021.100822
Sedrakyan, G., Malmberg, J., Verbert, K., Järvelä, S., & Kirschner, P. A. (2020). Linking learning behavior analytics and learning science concepts: Designing a learning analytics dashboard for feedback to support learning regulation. Computers in Human Behavior, 107, 105512. https://doi.org/10.1016/j.chb.2018.05.004
Seixas, P., & Peck, C. (2004). Teaching historical thinking. Challenges and prospects for Canadian social studies, 109-117. https://doi.org/10.4324/9781315717111-9
Seïler, N. R. (2016). Designing interaction strategies for companions interacting with children. In Emotions, Technology, and Design (pp. 129-168). Elsevier. https://doi.org/10.1016/B978-0-12-801872-9.00007-7
Shakurnia, A., Aslami, M., & Bijanzadeh, M. (2018). The effect of question generation activity on students′ learning and perception. J Adv Med Educ Prof, 6(2), 70-77. https://doi.org/ 10.1177/0301006618773081
Silver, E. A. (1994). On mathematical problem posing. For the learning of mathematics, 14(1), 19-28. https://api.semanticscholar.org/CorpusID:38326924
Snow, S., Wilde, A., Denny, P., & Schraefel, M. C. (2019). A discursive question: Supporting student-authored multiple choice questions through peer-learning software in non-STEMM disciplines. British Journal of Educational Technology, 50(4), 1815-1830. https://doi.org/10.1111/bjet.12686
Snowball, J. D., & McKenna, S. (2017). Student-generated content: an approach to harnessing the power of diversity in higher education. Teaching in Higher Education, 22(5), 604-618. https://doi.org/10.1080/13562517.2016.1273205
Song, D. (2016). Student-generated questioning and quality questions: A. Research Journal of Educational Studies and Review, 2(5), 58-70. https://doi.org/10.1515/9783110864205.98
Steuer, T., Filighera, A., Tregel, T., & Miede, A. (2022). Educational Automatic Question Generation Improves Reading Comprehension in Non-native Speakers: A Learner-Centric Case Study. Frontiers in artificial intelligence, 5, 900304. Retrieved 2022, from https://doi.org/10.3389/frai.2022.900304

Studies, N. C. f. t. S. (1994). Expectations of excellence: Curriculum standards for social studies. National Council for the Social Studies.
Suh, A., Wagner, C., & Liu, L. L. (2018). Enhancing User Engagement through Gamification. Journal of Computer Information Systems, 58(3), 204-213. https://doi.org/10.1080/08874417.2016.1229143
Sutiani, A., Situmorang, M., & Silalahi, A. (2021). Implementation of an inquiry learning model with science literacy to improve student critical thinking skills. International Journal of Instruction, 14(2), 117-138. https://doi.org/10.29333/iji.2021.1428a
Taecharungroj, V. (2023). “What Can ChatGPT Do?” Analyzing Early Reactions to the Innovative AI Chatbot on Twitter. Big Data and Cognitive Computing, 7(1), 35. https://doi.org/10.7238/a.v0i26.3368
Ten Dam, G., & Volman, M. (2007). Educating for Adulthood or for Citizenship: social competence as an educational goal. European journal of education, 42(2), 281-298. https://doi.org/10.1111/j.1465-3435.2007.00295.x
Thalheimer, W. (2003). The learning benefits of questions. Work Learning Research. https://doi.org/10.7146/peri.v8i16.8273
Van Blerkom, D. L., Van Blerkom, M. L., & Bertsch, S. (2006). Study strategies and generative learning: What works? Journal of College Reading and Learning, 37(1), 7-18. https://doi.org/10.1080/10790195.2006.10850190
Vie, J.-J., Popineau, F., Bruillard, É., & Bourda, Y. (2017). A review of recent advances in adaptive assessment. Learning analytics: Fundaments, applications, and trends: A view of the current state of the art to enhance e-learning, 113-142. https://doi.org/10.1007/978-3-319-52977-6_4
Vincent, S. (1999). The Multigrade Classroom: A Resource Handbook for Small, Rural Schools. Book 4: Instructional Organization, Curriculum, and Evaluation. https://doi.org/10.2307/1179676
Vishkaie, R. (2019). Hey emotion companion, can you be my friend? Proceedings of the 18th ACM International Conference on Interaction Design and Children,
Vogel, J. J., Vogel, D. S., Cannon-Bowers, J., Bowers, C. A., Muse, K., & Wright, M. (2006). Computer gaming and interactive simulations for learning: A meta-analysis. Journal of Educational Computing Research, 34(3), 229-243. https://doi.org/10.4337/9781839102431.00006
Wang, Y., Li, H., Feng, Y., Jiang, Y., & Liu, Y. (2020). AI-supported online collaborative learning: an exploratory study on group problem-solving processes and outcomes. Comput. Educ, 145, 103717. https://doi.org/10.24059/olj.v10i2.1764
Woolfolk, A., & Margetts, K. (2012). Educational psychology Australian edition. Pearson Higher Education AU. https://doi.org/10.1207/S15326985EP3504_04
Wu, M., Liao, C. C., Chen, Z.-H., & Chan, T.-W. (2010). Designing a competitive game for promoting students′ effort-making behavior by virtual pets. 2010 Third IEEE International Conference on Digital Game and Intelligent Toy Enhanced Learning,
Yaneva, V. (2018). Automatic distractor suggestion for multiple-choice tests using concept embeddings and information retrieval. Proceedings of the thirteenth workshop on innovative use of NLP for building educational applications,
Yilmaz, R., & Yilmaz, F. G. K. (2023). The effect of generative artificial intelligence (AI)-based tool use on students′ computational thinking skills, programming self-efficacy and motivation. Computers and Education: Artificial Intelligence, 4, 100147. https://doi.org/10.1016/0004-3702(76)90011-4
Yu, F. Y., Liu, Y. H., & Chan, T. W. (2005). A web-based learning system for question-posing and peer assessment. Innovations in education and teaching international, 42(4), 337-348. https://doi.org/10.1080/14703290500062557
Zhao, K., Zhou, J., & Zou, B. (2022). Developing subject knowledge co-construction and specific language use in a technology-enhanced CLIL programme: effectiveness and productive patterns. International Journal of Bilingual Education and Bilingualism, 25(6), 2172-2185. https://doi.org/https://doi.org/10.1080/13670050.2021.1890688
指導教授 洪暉鈞(Hui-Chun Hung) 審核日期 2024-7-29
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明