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研究生: 梁心怡
Hsin-Yi Liang
論文名稱: 智慧聊天機器人輔助實境解謎遊戲式學習對博物館學習成效的影響
Effect of an artificial intelligence-based chatbot on students’ learning performance in alternate reality game-based museum learning
指導教授: 黃國禎
Gwo-Jen Hwang
口試委員: 楊接期
Jie-Chi Yang
王淑玲
Shu-Ling Wang
許庭嘉
Ting-Chia Hsu
楊凱翔
Kai-Hsiang Yang
黃國禎
Gwo-Jen Hwang
學位類別: 博士
Doctor
系所名稱: 應用科技學院 - 應用科技研究所
Graduate Institute of Applied Science and Technology
論文出版年: 2022
畢業學年度: 110
語文別: 中文
論文頁數: 108
中文關鍵詞: 實境解謎電腦輔助回饋聊天機器人博物館學習遊戲式學習人工智慧
外文關鍵詞: alternate reality game, computer-mediated feedback, chatbot, museum learning, game-based learning, artificial intelligence
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  • 博物館具有豐富多元的跨領域學習資源和開放性學習場域,可提供真實學習情境輔助素養導向學習。近年來,實境解謎遊戲逐漸被應用在博物館學習,透過有趣的問題解決活動吸引學習者主動參與,促進與博物館情境的互動。然而,大多學習者缺乏足夠的先備知識和後設認知能力可完成實境解謎遊戲的學習任務。為輔助學習者實境解謎遊戲學習,必須提供適當回饋幫助學習者自我調整學習,解決學習過程中所遇到的問題。因此,本研究嘗試開發一智慧聊天機器人於博物館實境解謎遊戲中,應用自然語言處理技術與決策樹提供一專家系統,針對學習者不同需求提供適性回饋。為探討智慧聊天機器人輔助實境解謎遊戲式學習的成效,本研究將此學習模式應用於某科學博物館的學習活動中。參與實驗的對象為國小六年級兩個班級,共39名學習者,實驗組使用智慧聊天機器人輔助實境解謎遊戲式學習,控制組學生使用一般實境解謎遊戲式學習。實驗結果顯示智慧聊天機器人輔助實境解謎遊戲式學習可有助於改善學習者的後設認知覺知、情感參與、行為參與及博物館學習印象。另外,學習成就和認知參與無顯著差異。


    Museum provides a free-choice learning environment with fruitful interdisciplinary learning resources to support competency-based learning in authentic learning contexts for diverse learners. Recently, alternate reality game has been applied in museum learning to encourage learners’ active engagement and their interactions with museum contexts through playful problem-solving activities. However, most learners have insufficient prior knowledge and metacognitive skills to complete the learning tasks in alternate reality games. To support learning with alternate reality games, there is a need to provide proper feedback so that the learners are capable of self-regulated learning and solve the encountered problems during the learning process. Therefore, this research intends to develop an artificial intelligence-based chatbot approach in alternate reality game-based learning to promote learning in museums. The aforesaid learning approach was implemented in a field-trip learning activity in a science museum to examine the effectiveness of this learning approach. The participants include 39 learners from two sixth-grade classes. The learners in the experimental group learned with the artificial intelligence-supported chatbot approach in alternate reality games-based learning, while those in the control group learned with a conventional alternate reality game-based learning approach to support their learning in the museum. The results showed the artificial intelligence-based chatbot approach can significantly improve metacognition awareness, affective engagement, and behavioral engagement. On the other hand, there were no significant differences between the two groups in terms of learning achievements and cognitive engagement.

    摘要 IV ABSTRACT V 致謝 VI 目錄 VII 圖目錄 X 表目錄 XI 第一章 緒論 1 1.1. 研究背景 1 1.2. 研究目的與問題 3 1.3. 名詞釋義 4 1.3.1. 博物館學習 4 1.3.2. 實境解謎遊戲式學習 5 1.3.3. 電腦輔助回饋 5 1.3.4. 智慧聊天機器人 5 第二章 文獻探討 7 2.1. 實境解謎遊戲輔助博物館學習 7 2.1.1. 博物館學習(Museum learning)定義與特性 7 2.1.2. 實境解謎遊戲(Alternate reality game; ARG)定義與特性 8 2.1.3. 實境解謎遊戲式學習(Alternate reality game-based learning)相關研究 10 2.2. 電腦輔助回饋(Computer-mediated feedback) 11 2.2.1. 電腦輔助回饋的定義與特性 11 2.2.2. 電腦輔助回饋相關研究 13 2.3. 智慧聊天機器人(Artificial intelligence-based chatbot; AI Chatbot) 15 2.3.1. 智慧聊天機器人定義與特色 15 2.3.2. 智慧聊天機器人相關研究與應用 16 第三章 系統開發 19 3.1. 系統架構 19 3.2. 實境解謎遊戲式學習情境 20 3.2.1. 學習活動及情境說明 20 3.2.2. 實境解謎遊戲式學習流程 21 3.3. 一般實境解謎遊戲式學習 23 3.4. 智慧聊天機器人輔助實境解謎遊戲式學習模式 25 3.4.1. 智慧聊天機器人回饋機制 25 3.4.2. 智慧聊天機器人回饋設計 28 3.4.3. 規則回饋模式與對話情境 29 第四章 研究設計 32 4.1. 研究架構 32 4.2. 實驗對象 33 4.3. 學習內容 34 4.4. 研究工具 34 4.4.1. 學習成就測驗 34 4.4.2. 後設認知覺知問卷 35 4.4.3. 參與度問卷 35 4.4.4. 行為參與 36 4.4.5. 繪圖心得回饋學習單 39 4.4.6. 開放性問題回饋 40 4.5. 實驗流程 40 4.6. 數據分析處理 42 第五章 研究結果與分析 44 5.1. 學習成就 44 5.2. 後設認知覺知 46 5.3. 參與度 (認知參與、情感參與、行為參與) 47 5.4. 實際行為參與 48 5.5. 博物館學習觀感 62 第六章 結論與建議 70 6.1. 結論 70 6.1.1. 學習成就 70 6.1.2. 後設認知覺知 71 6.1.3. 認知參與 72 6.1.4. 情感參與 73 6.1.5. 行為參與 74 6.1.6. 博物館學習觀感 76 6.2. 研究限制及建議 77 6.2.1. 研究限制 78 6.2.2. 對博物館從業人員的建議 78 6.2.3. 未來研究方向建議 79 參考文獻 - 80 - 附錄1—學習成就前測驗 - 89 - 附錄2—學習成就後測驗 - 91 - 附錄3—後設認知覺知問卷 - 94 - 附錄4—參與度問卷 - 95 -

    Artino Jr, A. R. (2009). Online learning: Are subjective perceptions of instructional context related to academic success? The Internet and Higher Education, 12(3-4), 117-125.
    Attali, Y., & van der Kleij, F. (2017). Effects of feedback elaboration and feedback timing during computer-based practice in mathematics problem solving. Computers & Education, 110, 154-169.
    Bell, R. L., Smetana, L., & Binns, I. (2005). Simplifying inquiry instruction. The science teacher, 72(7), 30-33.
    Berge, Z. L., & Muilenburg, L. Y. (2013). Handbook of mobile learning. Routledge.
    Bibauw, S., François, T., & Desmet, P. (2019). Discussing with a computer to practice a foreign language: research synthesis and conceptual framework of dialogue-based CALL. Computer Assisted Language Learning, 32(8), 827-877.
    Biduski, D., Bellei, E. A., Rodriguez, J. P. M., Zaina, L. A. M., & De Marchi, A. C. B. (2020). Assessing long-term user experience on a mobile health application through an in-app embedded conversation-based questionnaire. Computers in Human Behavior, 104, 106169.
    Bimba, A. T., Idris, N., Al-Hunaiyyan, A., Mahmud, R. B., & Shuib, N. L. B. M. (2017). Adaptive feedback in computer-based learning environments: a review. Adaptive Behavior, 25(5), 217-234.
    Cai, H., & Gu, X. (2019). Factors that influence the different levels of individuals’ understanding after collaborative problem solving: The effects of shared representational guidance and prior knowledge. Interactive learning environments, 30(4), 695-706.
    Candel, C., Máñez, I., Cerdán, R., & Vidal‐Abarca, E. (2021). Delaying elaborated feedback within computer‐based learning environments: The role of summative and question‐based feedback. Journal of computer assisted learning, 37(4), 1015-1029.
    Carless, D. (2019). Feedback loops and the longer-term: towards feedback spirals. Assessment & Evaluation in Higher Education, 44(5), 705-714.
    Chang, C.-Y., Kuo, S.-Y., & Hwang, G. H. (2022). Chatbot-facilitated Nursing Education: Incorporating a Knowledge-based Chatbot System into a Nursing Training Program. Educational Technology and Society, 25(1),15-27.
    Chang, C. Y., Hwang, G. J., & Gau, M. L. (2021). Promoting students' learning achievement and self‐efficacy: A mobile chatbot approach for nursing training. British Journal of Educational Technology, 53(1), 171-188.
    Charitonos, K., Blake, C., Scanlon, E., & Jones, A. (2012). Museum learning via social and mobile technologies:(How) can online interactions enhance the visitor experience? British Journal of Educational Technology, 43(5), 802-819.
    Chen, X., Breslow, L., & DeBoer, J. (2018). Analyzing productive learning behaviors for students using immediate corrective feedback in a blended learning environment. Computers & Education, 117, 59-74.
    Cáceres, M., Nussbaum, M., González, F., & Gardulski, V. (2021). Is more detailed feedback better for problem-solving? Interactive learning environments, 29(7), 1189-1210.
    Connolly, T. M., Stansfield, M., & Hainey, T. (2011). An alternate reality game for language learning: ARGuing for multilingual motivation. Computers & Education, 57(1), 1389-1415.
    Dean, D., & Suhartanto, D. (2019). The formation of visitor behavioral intention to creative tourism: the role of push–Pull motivation. Asia Pacific Journal of Tourism Research, 24(5), 393-403.
    De Beer, K., & Bothma, T. (2016). Alternate reality games (ARG) as innovative digital information sources. Library Hi Tech, 34(3), 433-453.
    Deeva, G., Bogdanova, D., Serral, E., Snoeck, M., & De Weerdt, J. (2021). A review of automated feedback systems for learners: Classification framework, challenges and opportunities. Computers & Education, 162, 104094.
    Dlab, M. H., Boticki, I., Hoic-Bozic, N., & Looi, C. K. (2020). Exploring group interactions in synchronous mobile computer-supported learning activities. Computers & Education, 146, 103735.
    Dockett, S., Main, S., & Kelly, L. (2011). Consulting young children: experiences from a Museum. Visitor Studies, 14(1), 13-33.
    Dondlinger, M. J., & McLeod, J. K. (2015). Solving real world problems with alternate reality gaming: Student experiences in the global village playground capstone course design. Interdisciplinary Journal of Problem-Based Learning, 9(2), 3.
    Drotner, K., & Schrøder, K. C. (2013). Museum communication and social media: The connected museum. Routledge.
    Elsom, S., Westacott, M., Stieler-Hunt, C., Glencross, S., & Rutter, K. (2021). Finding resources, finding friends: using an alternate reality game for orientation and socialisation in a university enabling program. Interactive learning environments, https://doi.org/10.1080/10494820.2021.1894181.
    Evangelia, M., & Konstantinos, M. (2019). From Literature to Alternate Reality Games: Prerequisites, Criteria, and Limitations of a Young Adult Novel’s Transformational Design for Educational Purposes. Advances in Literary Study, 7(04), 224.
    Falk, J. H., & Dierking, L. D. (2000). Learning from museums: Visitor experiences and the making of meaning. Altamira Press.
    Falk, J. H., & Dierking, L. D. (2013). Museum Experience Revisited. Left Coast Press.
    Falk, J. H., & Dierking, L. D. (2016). The museum experience revisited. Routledge.
    Falk, J. H., & Dierking, L. D. (2018). Learning from museums. Rowman & Littlefield.
    Falk, J. H., & Storksdieck, M. (2005). Using the contextual model of learning to understand visitor learning from a science center exhibition. Science education, 89(5), 744-778.
    Frank, B., Simper, N., & Kaupp, J. (2018). Formative feedback and scaffolding for developing complex problem solving and modelling outcomes. European Journal of Engineering Education, 43(4), 552-568.
    Fryer, L. K., Ainley, M., Thompson, A., Gibson, A., & Sherlock, Z. (2017). Stimulating and sustaining interest in a language course: An experimental comparison of Chatbot and Human task partners. Computers in Human Behavior, 75, 461-468.
    Fryer, L. K., Nakao, K., & Thompson, A. (2019). Chatbot learning partners: Connecting learning experiences, interest and competence. Computers in Human Behavior, 93, 279-289.
    Gaia, G., Boiano, S., & Borda, A. (2019). Engaging museum visitors with AI: The case of chatbots. In Museums and Digital Culture (pp. 309-329). Springer.
    Gilliam, M., Jagoda, P., Fabiyi, C., Lyman, P., Wilson, C., Hill, B., & Bouris, A. (2017). Alternate reality games as an informal learning tool for generating STEM engagement among underrepresented youth: A qualitative evaluation of the source. Journal of Science Education and Technology, 26(3), 295-308.
    Gutwill, J. P., & Allen, S. (2012). Deepening students' scientific inquiry skills during a science museum field trip. Journal of the Learning Sciences, 21(1), 130-181.
    Gutwill, J. P., & Allen, S. (2017). Group inquiry at science museum exhibits: Getting visitors to ask juicy questions. Routledge.
    Hassan, M. A., Habiba, U., Khalid, H., Shoaib, M., & Arshad, S. (2019). An adaptive feedback system to improve student performance based on collaborative behavior. Ieee Access, 7, 107171-107178.
    Hou, H.-T., Fang, Y.-S., & Tang, J. T. (2021). Designing an alternate reality board game with augmented reality and multi-dimensional scaffolding for promoting spatial and logical ability. Interactive learning environments, https://doi.org/10.1080/10494820.2021.1961810.
    Hou, H.-T., Wu, S.-Y., Lin, P.-C., Sung, Y.-T., Lin, J.-W., & Chang, K.-E. (2014). A Blended Mobile Learning Environment for Museum Learning. Journal of Educational Technology & Society, 17(2), 207-218.
    Hsiao, H.-S., Chang, C.-S., Lin, C.-Y., & Wang, Y.-Z. (2016). Weather observers: a manipulative augmented reality system for weather simulations at home, in the classroom, and at a museum. Interactive learning environments, 24(1), 205-223.
    Hsu, T.-Y., & Liang, H.-Y. (2017). A cyclical learning model to promote children’s online and on-site museum learning. The Electronic Library, 35(2), 333-347.
    Hsu, T.-Y., & Liang, H.-Y. (2021). Museum engagement visits with a universal game-based blended museum learning service for different age groups. Library Hi Tech. https://doi.org/10.1108/LHT-08-2020-0198
    Hsu, T.-Y., Liang, H., Chiou, C.-K., & Tseng, J. C. (2018). CoboChild: a blended mobile game-based learning service for children in museum contexts. Data Technologies and Applications, 52(3), 294-312.
    Hu, Y., Koren, Y., & Volinsky, C. (2008, December). Collaborative filtering for implicit feedback datasets. In 2008 Eighth IEEE international conference on data mining (pp. 263-272). Ieee.
    Huang, B., Hew, K. F., & Lo, C. K. (2019). Investigating the effects of gamification-enhanced flipped learning on undergraduate students’ behavioral and cognitive engagement. Interactive learning environments, 27(8), 1106-1126.
    Huang, W., Hew, K. F., & Fryer, L. K. (2021). Chatbots for language learning—Are they really useful? A systematic review of chatbot‐supported language learning. Journal of computer assisted learning, 38(1), 237-257.
    Hwang, G. J., & Chen, C. H. (2017). Influences of an inquiry‐based ubiquitous gaming design on students’ learning achievements, motivation, behavioral patterns, and tendency towards critical thinking and problem solving. British Journal of Educational Technology, 48(4), 950-971.
    Hwang, G. J., & Wang, S. Y. (2016). Single loop or double loop learning: English vocabulary learning performance and behavior of students in situated computer games with different guiding strategies. Computers & Education, 102, 188-201.
    Jerrett, A., Bothma, T. J., & de Beer, K. (2017). Exercising library and information literacies through alternate reality gaming. Aslib Journal of Information Management, 69(2), 230-254.
    Johnson, A., Huber, K. A., Cutler, N., Bingmann, M., & Grove, T. (2017). The museum educator's manual: educators share successful techniques. Rowman & Littlefield.
    Ke, F., Xie, K., & Xie, Y. (2016). Game‐based learning engagement: A theory‐and data‐driven exploration. British Journal of Educational Technology, 47(6), 1183-1201.
    Kiili, K. (2007). Foundation for problem-based gaming. British Journal of Educational Technology, 38(3), 394e404.
    Kiili, K., Lainema, T., de Freitas, S., & Arnab, S. (2014). Flow framework for analyzing the quality of educational games. Entertainment computing, 5(4), 367-377.
    Kim, J., Lee, E., Thomas, T., & Dombrowski, C. (2009). Storytelling in new media: The case of alternate reality games, 2001–2009. First Monday, 14(6). https://doi.org/10.5210/fm.v14i6.2484.
    Kim, J. Y., & Lim, K. Y. (2019). Promoting learning in online, ill-structured problem solving: The effects of scaffolding type and metacognition level. Computers & Education, 138, 116-129.
    Kim, S., Chang, M., Deater-Deckard, K., Evans, M. A., Norton, A., & Samur, Y. (2017). Educational games and students’ game engagement in elementary school classrooms. Journal of Computers in Education, 4(4), 395-418.
    King, B., & Lord, B. (2015). The manual of museum learning. Rowman & Littlefield.
    Klopfer, E., Perry, J., Squire, K., Jan, M. F., & Steinkuehler, C. (2017). Mystery at the Museum–A Collaborative Game for Museum Education. In Computer Supported Collaborative Learning 2005: The Next 10 Years! (pp. 316-320). Routledge.
    Koepfler, J. A., Sneeringer, K. T., & Goodlander, G. B. (2017). PHEON: Practicing Problem Solving and Gaining Museum Literacy from Transmedia and Alternate Reality Games in Museums. Journal of Interactive Humanities, 3(1), 1.
    Lai, C.-L. (2021). Exploring University Students’ Preferences for AI-Assisted Learning Environment. Educational Technology & Society, 24(4), 1-15.
    Law, V., & Chen, C.-H. (2016). Promoting science learning in game-based learning with question prompts and feedback. Computers & Education, 103, 134-143.
    Lee, J., Park, T., & Davis, R. O. (2022). What affects learner engagement in flipped learning and what predicts its outcomes? British Journal of Educational Technology, 53(2), 211-228.
    Liang, H. Y., Hsu, T. Y., & Hwang, G. J. (2021). Promoting children's inquiry performances in alternate reality games: A mobile concept mapping‐based questioning approach. British Journal of Educational Technology, 52(5), 2000-2019.
    Lin, C.-J., & Mubarok, H. (2021). Learning Analytics for Investigating the Mind Map-Guided AI Chatbot Approach in an EFL Flipped Speaking Classroom. Educational Technology & Society, 24(4), 16-35.
    Lord, B. (2007). The manual of museum learning. Rowman Altamira.
    Lord, B., & Piacente, M. (2014). Manual of Museum Exhibitions. Rowman & Littlefield
    Liu, S., Liu, S., Liu, Z., Peng, X., & Yang, Z. (2022). Automated detection of emotional and cognitive engagement in MOOC discussions to predict learning achievement. Computers & Education, 181, 104461
    Maier, U., Wolf, N., & Randler, C. (2016). Effects of a computer-assisted formative assessment intervention based on multiple-tier diagnostic items and different feedback types. Computers & Education, 95, 85-98.
    McGonigal, J. (2003). This is not a game: Immersive aesthetics and collective play. Digital arts & culture 2003 conference proceedings (pp. 110–119). Melbourne: DAC. https://janemcgonigal.com/learn-me/
    Milbourne, J., & Wiebe, E. (2018). The role of content knowledge in ill-structured problem solving for high school physics students. Research in Science Education, 48(1), 165-179.
    Molin, F., Haelermans, C., Cabus, S., & Groot, W. (2020). The effect of feedback on metacognition-a randomized experiment using polling technology. Computers & Education, 152, 103885.
    Narciss, S., Sosnovsky, S., Schnaubert, L., Andrès, E., Eichelmann, A., Goguadze, G., & Melis, E. (2014). Exploring feedback and student characteristics relevant for personalizing feedback strategies. Computers & Education, 71, 56-76.
    Ninaus, M., Greipl, S., Kiili, K., Lindstedt, A., Huber, S., Klein, E., Karnath, H.-O., & Moeller, K. (2019). Increased emotional engagement in game-based learning–A machine learning approach on facial emotion detection data. Computers & Education, 142, 103641.
    Noh, Y.-G., & Hong, J.-H. (2021). Designing Reenacted Chatbots to Enhance Museum Experience. Applied Sciences, 11(16), 7420.
    Pan, Y. T., Yang, K. K., Wilson, K., Hong, Z. R., & Lin, H. S. (2020). The impact of museum interpretation tour on visitors' engagement and post‐visit conservation intentions and behaviours. International Journal of Tourism Research, 22(5), 593-603.
    Pérez, J. Q., Daradoumis, T., & Puig, J. M. M. (2020). Rediscovering the use of chatbots in education: A systematic literature review. Computer Applications in Engineering Education, 28(6), 1549-1565.
    Ridley, D. S., Schutz, P. A., Glanz, R. S., & Weinstein, C. E. (1992). Self-regulated learning: The interactive influence of metacognitive awareness and goal-setting. The journal of experimental education, 60(4), 293-306.
    Ryan, R. M., Rigby, C. S., & Przybylski, A. (2006). The motivational pull of video games: A self-determination theory approach. Motivation and emotion, 30(4), 344-360.
    Saidi, S. S., & Siew, N. M. (2019). Reliability and Validity Analysis of Statistical Reasoning Test Survey Instrument Using the Rasch Measurement Model. International Electronic Journal of Mathematics Education, 14(3), 535-546.
    Sailer, M., Bauer, E., Hofmann, R., Kiesewetter, J., Glas, J., Gurevych, I., & Fischer, F. (2022). Adaptive feedback from artificial neural networks facilitates pre-service teachers’ diagnostic reasoning in simulation-based learning. Learning and Instruction, https://doi.org/10.1016/j.learninstruc.2022.101620.
    Sato, M., & Loewen, S. (2018). Metacognitive instruction enhances the effectiveness of corrective feedback: Variable effects of feedback types and linguistic targets. Language Learning, 68(2), 507-545.
    Schraw, G., & Dennison, R. S. (1994). Assessing metacognitive awareness. Contemporary educational psychology, 19(4), 460-475.
    Shute, V. J. (2008). Focus on formative feedback. Review of educational research, 78(1), 153-189.
    Sidana, S., Trofimov, M., Horodnytskyi, O., Laclau, C., Maximov, Y., & Amini, M. R. (2021). User preference and embedding learning with implicit feedback for recommender systems. Data Mining and Knowledge Discovery, 35(2), 568-592.
    Simon, N. (2010). The participatory museum. Museum 2.0.
    Sintoris, C., Stoica, A., Papadimitriou, I., Yiannoutsou, N., Komis, V., & Avouris, N. (2010). MuseumScrabble: Design of a mobile game for children’s interaction with a digitally augmented cultural space. International Journal of Mobile Human Computer Interaction (IJMHCI), 2(2), 53-71.
    Smits, M. H., Boon, J., Sluijsmans, D. M., & Van Gog, T. (2008). Content and timing of feedback in a web-based learning environment: Effects on learning as a function of prior knowledge. Interactive learning environments, 16(2), 183-193.
    Smutny, P., & Schreiberova, P. (2020). Chatbots for learning: A review of educational chatbots for the Facebook Messenger. Computers & Education, 151, 103862.
    Speight, M. C., Reynolds, M. R., & Cook, M. B. (2012). Museums and design education: looking to learn, learning to see. Ashgate Publishing, Ltd.
    Sperlí, G. (2021). A Cultural heritage framework using a Deep Learning based Chatbot for supporting tourist journey. Expert Systems with Applications, 115277.
    Srisawasdi, N., & Panjaburee, P. (2019). Implementation of game-transformed inquiry-based learning to promote the understanding of and motivation to learn chemistry. Journal of Science Education and Technology, 28(2), 152-164.
    Stylianidou, N., Sofianidis, A., Manoli, E., & Meletiou-Mavrotheris, M. (2020). “Helping Nemo!”—Using Augmented Reality and Alternate Reality Games in the Context of Universal Design for Learning. Education Sciences, 10(4), 95.
    Szulborski, D. (2005). This is not a game: A guide to alternate reality gaming. Incunabula.
    Tan, J. S., & Chen, W. (2022). Peer feedback to support collaborative knowledge improvement: What kind of feedback feed-forward? Computers & Education, 104467.
    Tang, K.-Y., Chang, C.-Y., & Hwang, G.-J. (2021). Trends in artificial intelligence-supported e-learning: a systematic review and co-citation network analysis (1998–2019). Interactive learning environments, https://doi.org/10.1080/10494820.2021.1875001.
    Tornqvist, D., & Tichon, J. (2021). Motivated to lose? Evaluating challenge and player motivations in games. Behaviour & Information Technology, 40(1), 63-84.
    Toumanidis, L., Karapetros, P., Giannousis, C., Kogias, D. G., Feidakis, M., & Patrikakis, C. Z. (2019). Developing the Museum-Monumental Experience from Linear to Interactive Using Chatbots. In Strategic Innovative Marketing and Tourism (pp. 1159-1167). Springer.
    Tsai, C. W. (2014). A quasi-experimental study of a blended course integrated with refined web-mediated pedagogy of collaborative learning and self-regulated learning. Interactive Learning Environments, 22(6), 737-751.
    Tsai, F.-H., Tsai, C.-C., & Lin, K.-Y. (2015). The evaluation of different gaming modes and feedback types on game-based formative assessment in an online learning environment. Computers & Education, 81, 259-269.
    Tulloch, R., Wolfenden, H., & Sercombe, H. (2021). Designing Alternate Reality Games for effective learning: a methodology for implementing multimodal persistent gaming in university education. Media Practice and Education, 22(2), 136-152.
    Valanne, E. A., Al Dhaheri, R. M., Kylmalahti, R., & Sandholm-Rangell, H. (2017). Phenomenon Based Learning Implemented in Abu Dhabi School Model. International Journal of Humanities and Social Sciences, 9(3), 1-17.
    Wang, D., & Han, H. (2021). Applying learning analytics dashboards based on process‐oriented feedback to improve students' learning effectiveness. Journal of computer assisted learning, 37(2), 487-499.
    Wang, J., Hwang, G.-H., & Chang, C.-Y. (2021). Directions of the 100 most cited chatbot-related human behavior research: A review of academic publications. Computers and Education: Artificial Intelligence, 100023.
    Wang, Y. F., Petrina, S., & Feng, F. (2017). VILLAGE—V irtual I mmersive L anguage L earning and G aming E nvironment: Immersion and presence. British Journal of Educational Technology, 48(2), 431-450.
    Wang, Z., Gong, S.-Y., Xu, S., & Hu, X.-E. (2019). Elaborated feedback and learning: Examining cognitive and motivational influences. Computers & Education, 136, 130-140.
    Whitton, N., Jones, R., Wilson, S., & Whitton, P. (2014). Alternate reality games as learning environments for student induction. Interactive learning environments, 22(3), 243-252.
    Winkler, R., Söllner, M., & Leimeister, J. M. (2021). Enhancing problem-solving skills with smart personal assistant technology. Computers & Education, 165, 10414
    Xun, G., & Land, S. M. (2004). A conceptual framework for scaffolding III-structured problem-solving processes using question prompts and peer interactions. Educational Technology Research and Development, 52(2), 5-22.
    Yang, K.-H. (2017). Learning behavior and achievement analysis of a digital game-based learning approach integrating mastery learning theory and different feedback models. Interactive learning environments, 25(2), 235-248.
    Yang, K.-H., & Lu, B.-C. (2021). Towards the successful game-based learning: Detection and feedback to misconceptions is the key. Computers & Education, 160, 104033.
    Yilmaz, F. G. K., & Yilmaz, R. (2019). Impact of pedagogic agent-mediated metacognitive support towards increasing task and group awareness in CSCL. Computers & Education, 134, 1-14.
    Yin, J., Goh, T.-T., Yang, B., & Xiaobin, Y. (2021). Conversation technology with micro-learning: The impact of chatbot-based learning on students’ learning motivation and performance. Journal of Educational Computing Research, 59(1), 154-177.
    Yuan, C. C., Li, C. H., & Peng, C. C. (2021). Development of mobile interactive courses based on an artificial intelligence chatbot on the communication software LINE. Interactive Learning Environments, https://doi.org/10.1080/10494820.2021.1937230.

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