基於數位遊戲的語言學習 (Digital Game-Based Language Learning, DGBLL)的有效性已經被許多學者所認可。隨著計算機技術和多媒體學習環境的不斷發展，電腦代理人已經被廣泛應用於遊戲系統中提供學習引導或輔助。電腦代理人是指為了滿足教學目標而創建在數位學習系統中的虛擬化人物角色。然而在傳統教學系統中，電腦代理人是由單一角色的觀點進行設計，例如扮演教師或學生。具有單一的互動邏輯的電腦代理人往往無法因應學生的個人化需求進行調整，以發揮更佳的輔助學習效果。因此，本研究提出一種適性化角色調整策略，讓電腦代理人可以在數位遊戲中依據學生的需求，調整扮演的角色及功能，來促進學生的學習成就和高層次思維。為了驗證這個構想的成效，本研究開發了一個基於適性化電腦代理人機制的數位遊戲，並透過實驗來分析這個學習模式對於EFL (English as Foreign Language) 學生在英文詞彙學習成就、學習動機、自我效能及英文焦慮等方面的影響。本研究採取準實驗設計，受測者為同一所國中四個班共56名學生。兩個班級為實驗組 (N=30)，使用基於適性化電腦代理人機制的數位遊戲(Adaptive computer agent-based digital game, ACA-DG)進行學習；另外兩個班級為控制組 (N=26)，使用基於傳統電腦代理人的數位遊戲(Conventional computer agent-based digital game, CCA-DG)進行學習。研究結果顯示，實驗組學生的學習成就和自我效能感顯著高於控制組學生。同時，實驗組的學生英文學習焦慮感顯著低於控制組。而在學習動機方面，兩組學生並未存在顯著差異。

The effectiveness of digital game-based language learning (DGBLL) has been recognized by scholars. With the development of computer technology and multimedia learning environments, computer agents have been widely used in game systems to provide learning guidance or assistance. A computer agent is a virtual character that is created in a digital learning system to achieve instructional goals. However, in traditional teaching systems, computer agents are designed with a single role, such as a teacher or a student. Computer agents with a single interactive logic often lack the function to understand students' conditions and needs from various perspectives, and are unable to adapt for better learning support. Therefore, this study proposed an adaptive role-switching strategy that allows computer agents to adjust their roles and functions according to students' needs in digital games for promoting their learning achievement. To investigate the impact of this learning model on English vocabulary learning achievement, motivation, self-efficacy, and English anxiety among EFL (English as Foreign Language) students, an adaptive computer agent-based digital game was developed. A quasi-experiment was designed by recruiting 56 middle school students in four classes. Two classes (N=30) were arranged in the experimental group and used an adaptive computer agent-based digital game (Adaptive computer agent-based digital game, ACA-DG); two classes (N=26) were arranged in the control group and used the conventional computer agent-based digital game (Conventional computer agent-based digital game, CCA-DG). The results showed that students in the experimental group had significantly higher learning achievement and self-efficacy than those in the control group. On the other hand, students in the experimental group had significantly lower English learning anxiety than those in the control group. There was no significant difference between the two groups in terms of learning motivation.

Ahmadi, A., Sahragard, R., & Babaie Shalmani, H. (2017). Anthropomorphism–matters or not? On agent modality and its implications for teaching English idioms and design decisions. Computer Assisted Language Learning, 30(1-2), 149-172.
Arguedas, M., & Daradoumis, T. (2021). Analysing the role of a pedagogical agent in psychological and cognitive preparatory activities. Journal of Computer Assisted Learning.
Atkinson, R. K., Mayer, R. E., & Merrill, M. M. (2005). Fostering social agency in multimedia learning: Examining the impact of an animated agent’s voice. Contemporary Educational Psychology, 30(1), 117-139.
Bandura, A. (2012). On the functional properties of perceived self-efficacy revisited. Journal of management, 38(1), 9-44.
Belpaeme, T., Kennedy, J., Ramachandran, A., Scassellati, B., & Tanaka, F. (2018). Social robots for education: A review. Science robotics, 3(21).
Bevacqua, E., Eyben, F., Heylen, D., ter Maat, M., Pammi, S., Pelachaud, C., ... & Wöllmer, M. (2011, May). Interacting with emotional virtual agents. In International Conference on Intelligent Technologies for Interactive Entertainment (pp. 243-245). Springer, Berlin, Heidelberg.
Bilgin, C. U., Baek, Y., & Park, H. (2015). How debriefing strategies can improve student motivation and self-efficacy in game-based learning. Journal of Educational Computing Research, 53(2), 155-182.
Cai, Z., Feng, S., Baer, W., & Graesser, A. (2014). Instructional strategies in Trialogue-based intelligent tutoring systems. Design recommendations for intelligent tutoring systems, 2, 225-235.
Calvo‐Ferrer, J. R. (2017). Educational games as stand‐alone learning tools and their motivational effect on L 2 vocabulary acquisition and perceived learning gains. British Journal of Educational Technology, 48(2), 264-278.
Carlotto, T., & Jaques, P. A. (2016). The effects of animated pedagogical agents in an English-as-a-foreign-language learning environment. International Journal of Human-Computer Studies, 95, 15-26.
Chang, C. Y., Kao, C. H., Hwang, G. J., & Lin, F. H. (2020). From experiencing to critical thinking: A contextual game-based learning approach to improving nursing students’ performance in electrocardiogram training. Educational Technology Research and Development, 68(3), 1225-1245.
Castro-Alonso, J. C., Wong, R. M., Adesope, O. O., & Paas, F. (2021). Effectiveness of multimedia pedagogical agents predicted by diverse theories: A meta-analysis. Educational Psychology Review, 33(3), 989-1015.
Chen, H. J. H., & Hsu, H. L. (2020). The impact of a serious game on vocabulary and content learning. Computer Assisted Language Learning, 33(7), 811-832.
Chen, H. J. H., Hsu, H. L., & Chen, Z. H. (2020). A study on the effect of adding L1 glosses in the subtitle of an adventure game for vocabulary learning. Interactive Learning Environments, 1-17.
Chen, H., Park, H. W., & Breazeal, C. (2020). Teaching and learning with children: Impact of reciprocal peer learning with a social robot on children’s learning and emotive engagement. Computers & Education, 150, 103836.
Chen, S. L., & Liu, Y. T. (2021). Learning by designing or learning by playing? A comparative study of the effects of game-based learning on learning motivation and on short-term and long-term conversational gains. Interactive Learning Environments, 1-15.
Chen, Z. H., Chen, H. H. J., & Dai, W. J. (2018). Using narrative-based contextual games to enhance language learning: A case study. Journal of Educational Technology & Society, 21(3), 186-198.
Choi, S., & Clark, R. E. (2006). Cognitive and affective benefits of an animated pedagogical agent for learning English as a second language. Journal of educational computing research, 34(4), 441-466.
Davis, R. O., Vincent, J., & Wan, L. (2021). Does a pedagogical agent’s gesture frequency assist advanced foreign language users with learning declarative knowledge?. International Journal of Educational Technology in Higher Education, 18(1), 1-19.
Dinçer, S., & Doğanay, A. (2017). The effects of multiple-pedagogical agents on learners’ academic success, motivation, and cognitive load. Computers & Education, 111, 74-100.
El-Sabagh, H. A. (2021). Adaptive e-learning environment based on learning styles and its impact on development students' engagement. International Journal of Educational Technology in Higher Education, 18(1), 1-24.
Feine, J., Gnewuch, U., Morana, S., & Maedche, A. (2019). A taxonomy of social cues for conversational agents. International Journal of Human-Computer Studies, 132, 138-161.
Franciosi, S. J. (2017). The effect of computer game-based learning on FL vocabulary transferability. Journal of Educational Technology & Society, 20(1), 123-133.
Goldberg, B., & Cannon-Bowers, J. (2015). Feedback source modality effects on training outcomes in a serious game: Pedagogical agents make a difference. Computers in Human Behavior, 52, 1-11.
Gordon, G., & Breazeal, C. (2015). Bayesian Active Learning-Based Robot Tutor for Children’s Word-Reading Skills. Proceedings of the AAAI Conference on Artificial Intelligence, 29(1).
Graesser, A. C., Forsyth, C. M., & Lehman, B. A. (2017). Two Heads May Be Better than One: Learning from Computer Agents in Conversational Trialogues. Grantee Submission, 119, 1-20.
Gulz, A. (2004). Benefits of virtual characters in computer based learning environments: Claims and evidence. International Journal of Artificial Intelligence in Education, 14(3, 4), 313-334.
Guo, Y. R., & Goh, D. H. L. (2015). Affect in embodied pedagogical agents: Meta-analytic review. Journal of Educational Computing Research, 53(1), 124-149.
Hong, J. C., Hwang, M. Y., Tai, K. H., & Lin, P. H. (2019). Improving cognitive certitude with calibration mediated by cognitive anxiety, online learning self-efficacy and interest in learning Chinese pronunciation. Educational Technology Research and Development, 67(3), 597-615.
Horwitz, E. K., Horwitz, M. B., & Cope, J. (1986). Foreign language classroom anxiety. The Modern language journal, 70(2), 125-132.
Howard, C., Jordan, P., Di Eugenio, B., & Katz, S. (2017). Shifting the load: A peer dialogue agent that encourages its human collaborator to contribute more to problem solving. International Journal of Artificial Intelligence in Education, 27(1), 101-129.
Hung, H. T., Yang, J. C., Hwang, G. J., Chu, H. C., & Wang, C. C. (2018). A scoping review of research on digital game-based language learning. Computers & Education, 126, 89-104.
Hwang, G. J., Sung, H. Y., Chang, S. C., & Huang, X. C. (2020). A fuzzy expert system-based adaptive learning approach to improving students’ learning performances by considering affective and cognitive factors. Computers and Education: Artificial Intelligence, 1, 100003.
Israel‐Fishelson, R., & Hershkovitz, A. (2021). Micro‐persistence and difficulty in a game‐based learning environment for computational thinking acquisition. Journal of Computer Assisted Learning.
Johnson, A. M., Ozogul, G., & Reisslein, M. (2015). Supporting multimedia learning with visual signalling and animated pedagogical agent: Moderating effects of prior knowledge. Journal of Computer Assisted Learning, 31(2), 97-115.
Johnson, W. L., & Lester, J. C. (2018). Pedagogical agents: back to the future. AI Magazine, 39(2), 33-44.
Kao, G. Y. M., Chiang, C. H., & Sun, C. T. (2017). Customizing scaffolds for game-based learning in physics: Impacts on knowledge acquisition and game design creativity. Computers & Education, 113, 294-312.
Karampiperis, P., & Sampson, D. (2005). Adaptive learning resources sequencing in educational hypermedia systems. Journal of Educational Technology & Society, 8(4), 128-147.
Katsionis, G., & Virvou, M. (2004, October). A cognitive theory for affective user modelling in a virtual reality educational game. In 2004 IEEE international conference on systems, man and cybernetics (IEEE Cat. No. 04CH37583)(Vol. 2, pp. 1209-1213). IEEE.
Kim, B., Park, H., & Baek, Y. (2009). Not just fun, but serious strategies: Using meta-cognitive strategies in game-based learning. Computers & Education, 52(4), 800-810.
Li, H., & Graesser, A. C. (2021). The impact of conversational agents’ language on summary writing. Journal of Research on Technology in Education, 53(1), 44-66.
Li, R., Meng, Z., Tian, M., Zhang, Z., & Xiao, W. (2021). Modelling Chinese EFL learners’ flow experiences in digital game-based vocabulary learning: the roles of learner and contextual factors. Computer Assisted Language Learning, 34(4), 483-505.
Liew, T. W., Tan, S. M., & Ismail, H. (2017). Exploring the effects of a non-interactive talking avatar on social presence, credibility, trust, and patronage intention in an e-commerce website. Human-centric Computing and Information Sciences, 7(1), 1-21.
Liu, T. C., & Graf, S. (2009). Coping with mismatched courses: students’ behaviour and performance in courses mismatched to their learning styles. Educational Technology Research and Development, 57(6), 739.
Lu, Y. L., & Lien, C. J. (2020). Are they learning or playing? Students’ perception traits and their learning self-efficacy in a game-based learning environment. Journal of Educational Computing Research, 57(8), 1879-1909.
Ma, W., Adesope, O. O., Nesbit, J. C., & Liu, Q. (2014). Intelligent tutoring systems and learning outcomes: A meta-analysis. Journal of educational psychology, 106(4), 901.
Martha, A. S. D., & Santoso, H. B. (2019). The design and impact of the pedagogical agent: A systematic literature review. Journal of Educators Online, 16(1), n1.
Mayer, R. E., & Moreno, R. (1998). A split-attention effect in multimedia learning: Evidence for dual processing systems in working memory. Journal of educational psychology, 90(2), 312.
Moreno, R., & Mayer, R. (2007). Interactive multimodal learning environments. Educational psychology review, 19(3), 309-326.
Mostefai, B., Balla, A., & Trigano, P. (2019). A generic and efficient emotion-driven approach toward personalized assessment and adaptation in serious games. Cognitive Systems Research, 56, 82-106.
Müller, A., Son, J. B., Nozawa, K., & Dashtestani, R. (2018). Learning English idioms with a web-based educational game. Journal of Educational Computing Research, 56(6), 848-865.
Okita, S. Y., & Schwartz, D. L. (2013). Learning by teaching human pupils and teachable agents: The importance of recursive feedback. Journal of the Learning Sciences, 22(3), 375-412.
Pacella, D., & López-Pérez, B. (2018). Assessing children's interpersonal emotion regulation with virtual agents: The serious game Emodiscovery. Computers & Education, 123, 1-12.
Pai, K. C., Kuo, B. C., Liao, C. H., & Liu, Y. M. (2021). An application of Chinese dialogue-based intelligent tutoring system in remedial instruction for mathematics learning. Educational Psychology, 41(2), 137-152.
Pintrich, P.R., Smith, D.A.F., Garcia, T., & McKeachie, W.J. (1991). A manual for the use of the motivated strategies for learning questionnaire (MSLQ). MI: National Center for Research to Improve Postsecondary Teaching and Learning. (ERIC Document Reproduction Service No. ED 338122)
Plass, J. L., Homer, B. D., & Kinzer, C. K. (2015). Foundations of game-based learning. Educational Psychologist, 50(4), 258-283.
Ponticorvo, M., Dell’Aquila, E., Marocco, D., & Miglino, O. (2019). Situated psychological agents: A methodology for educational games. Applied Sciences, 9(22), 4887.
Qian, M., & Clark, K. R. (2016). Game-based Learning and 21st century skills: A review of recent research. Computers in human behavior, 63, 50-58.
Quinlan, J. R. (1983). Learning efficient classification procedures and their application to chess end games. In Machine learning (pp. 463-482). Springer, Berlin, Heidelberg.
Rahimi, S., Shute, V., Kuba, R., Dai, C. P., Yang, X., Smith, G., & Fernández, C. A. (2021). The use and effects of incentive systems on learning and performance in educational games. Computers & Education, 165, 104135
Reinders, H., & Wattana, S. (2015). Affect and willingness to communicate in digital game-based learning. ReCALL, 27(1), 38-57.
Reinhardt, J. (2017). Digital gaming in L2 teaching and learning. The handbook of technology and second language teaching and learning, 202-216.
Richards, D., & Dignum, V. (2019). Supporting and challenging learners through pedagogical agents: Addressing ethical issues through designing for values. British Journal of Educational Technology, 50(6), 2885-2901.
Rowe, J. P., Shores, L. R., Mott, B. W., & Lester, J. C. (2011). Integrating learning, problem solving, and engagement in narrative-centered learning environments. International Journal of Artificial Intelligence in Education, 21(1-2), 115-133.
Sabourin, J. L., Shores, L. R., Mott, B. W., & Lester, J. C. (2013). Understanding and predicting student self-regulated learning strategies in game-based learning environments. International Journal of Artificial Intelligence in Education, 23(1), 94-114.
Sawyer, R., Smith, A., Rowe, J., Azevedo, R., & Lester, J. (2017, June). Is more agency better? The impact of student agency on game-based learning. In International Conference on Artificial Intelligence in Education (pp. 335-346). Springer, Cham.
Schrader, C., & Grassinger, R. (2021). Tell me that I can do it better. The effect of attributional feedback from a learning technology on achievement emotions and performance and the moderating role of individual adaptive reactions to errors. Computers & Education, 161, 104028.
Schroeder, N. L., & Gotch, C. M. (2015). Persisting issues in pedagogical agent research. Journal of Educational Computing Research, 53(2), 183-204.
Schroeder, N. L., Romine, W. L., & Craig, S. D. (2017). Measuring pedagogical agent persona and the influence of agent persona on learning. Computers & Education, 109, 176-186.
Shute, V. J., Ke, F., Almond, R. G., Rahimi, S., Smith, G., & Lu, X. (2019). How to increase learning while not decreasing the fun in educational games. In R. Feldman (Ed.), Learning science: Theory, research, and practice (pp. 327–357). New York: McGraw Hill.
Shute, V., Rahimi, S., Smith, G., Ke, F., Almond, R., Dai, C. P., ... & Sun, C. (2021). Maximizing learning without sacrificing the fun: Stealth assessment, adaptivity and learning supports in educational games. Journal of Computer Assisted Learning, 37(1), 127-141.
Snow, E. L., Allen, L. K., Jacovina, M. E., & McNamara, D. S. (2015). Does agency matter?: Exploring the impact of controlled behaviors within a game-based environment. Computers & Education, 82, 378-392.
Standen, P. J., Brown, D. J., Taheri, M., Galvez Trigo, M. J., Boulton, H., Burton, A., ... & Hortal, E. (2020). An evaluation of an adaptive learning system based on multimodal affect recognition for learners with intellectual disabilities. British Journal of Educational Technology, 51(5), 1748-1765.
Sun, C. T., Chen, L. X., & Chu, H. M. (2018). Associations among scaffold presentation, reward mechanisms and problem-solving behaviors in game play. Computers & Education, 119, 95-111.
Sundqvist, P., & Wikström, P. (2015). Out-of-school digital gameplay and in-school L2 English vocabulary outcomes. System, 51, 65-76.
Tanaka, M. (2017). Factors affecting motivation for short in-class extensive reading. Journal of Asia TEFL, 14(1), 98.
Tang, J. T. (2020). Comparative study of game-based learning on preschoolers’ English vocabulary acquisition in Taiwan. Interactive Learning Environments, DOI: 10.1080/10494820.2020.1865406.
Taub, M., Sawyer, R., Smith, A., Rowe, J., Azevedo, R., & Lester, J. (2020). The agency effect: The impact of student agency on learning, emotions, and problem-solving behaviors in a game-based learning environment. Computers & Education, 147, 103781.
ter Vrugte, J., de Jong, T., Vandercruysse, S., Wouters, P., van Oostendorp, H., & Elen, J. (2017). Computer game-based mathematics education: Embedded faded worked examples facilitate knowledge acquisition. Learning and instruction, 50, 44-53.
Tsai, C. H., Cheng, C. H., Yeh, D. Y., & Lin, S. Y. (2017). Can learning motivation predict learning achievement? A case study of a mobile game-based English learning approach. Education and Information Technologies, 22(5), 2159-2173.
Veletsianos, G. (2010). Contextually relevant pedagogical agents: Visual appearance, stereotypes, and first impressions and their impact on learning. Computers & Education, 55(2), 576-585.
Veletsianos, G., & Russell, G. S. (2014). Pedagogical agents. In Handbook of research on educational communications and technology (pp. 759-769). Springer, New York, NY.
Wang, L. C., & Chen, M. P. (2010). The effects of game strategy and preference‐matching on flow experience and programming performance in game‐based learning. Innovations in Education and Teaching International, 47(1), 39-52.
Wang, M., & Zheng, X. (2021). Using game-based learning to support learning science: a study with middle school students. The Asia-Pacific Education Researcher, 30(2), 167-176.
Wang, V. H., & Osborne, T. F. (2017). Social robots and other relational agents to improve patient care. Using Technology to Improve Care of Older Adults, 166.
Wei, C. W., Kao, H. Y., Lu, H. H., & Liu, Y. C. (2018). The effects of competitive gaming scenarios and personalized assistance strategies on English vocabulary learning. Journal of Educational Technology & Society, 21(3), 146-158.
Yadav, A. K., & Oyelere, S. S. (2021). Contextualized mobile game-based learning application for computing education. Education and Information Technologies, 26(3), 2539-2562.
Yang, H. C., & Zapata-Rivera, D. (2010). Interlanguage pragmatics with a pedagogical agent: the request game. Computer Assisted Language Learning, 23(5), 395-412.
Yang, J. C., Lin, M. Y. D., & Chen, S. Y. (2018). Effects of anxiety levels on learning performance and gaming performance in digital game‐based learning. Journal of Computer Assisted Learning, 34(3), 324-334.
Yang, J. C., Quadir, B., & Chen, N. S. (2016). Effects of the badge mechanism on self-efficacy and learning performance in a game-based English learning environment. Journal of Educational Computing Research, 54(3), 371-394.
Yu, Z. G. (2018). Differences in serious game-aided and traditional English vocabulary acquisition. Computers & Education, 127, 214-232.
Zeng, H., Zhou, S. N., Hong, G. R., Li, Q. Y., & Xu, S. Q. (2020). Evaluation of Interactive Game-Based Learning in Physics Domain. Journal of Baltic Science Education, 19(3), 484-498.
Zheng, D., Bischoff, M., & Gilliland, B. (2015). Vocabulary learning in massively multiplayer online games: context and action before words. Educational Technology Research and Development, 63(5), 771-790.
Zou, D., Huang, Y., & Xie, H. (2021). Digital game-based vocabulary learning: where are we and where are we going?. Computer Assisted Language Learning, 34(5-6), 751-777.