簡易檢索 / 詳目顯示

研究生: 張佳琪
Jhang, Jia-Ci
論文名稱: 成就情緒理論探討VR情境焦慮、VR情境興趣與學習遷移之相關研究
The Effect of Achievement Emotion on Interacting Anxiety and Learning Interest in Playing VR, and Learning Transfer
指導教授: 呂有豐
Lue, Yeou-Feng
洪榮昭
Hong, Jon-Chao
學位類別: 碩士
Master
系所名稱: 工業教育學系
Department of Industrial Education
論文出版年: 2020
畢業學年度: 108
語文別: 中文
論文頁數: 131
中文關鍵詞: 虛擬實境VR操作自我效能VR情境興趣VR情境焦慮心流經驗學習遷移
英文關鍵詞: Virtual reality, VR self-efficacy, Learning interest with playing VR, Interacting anxiety with VR, Flow experience, Learning transfer
DOI URL: http://doi.org/10.6345/NTNU202000729
論文種類: 學術論文
相關次數: 點閱:310下載:29
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 科技的進步引領了教育變革,使新科技運用於教育現場,期望創造出 倍數效果,當虛擬實境不再只出現在生活娛樂當中,而是融入了教育系統中,同時開拓現代學生的眼界,更貼近當前趨勢脈動。過往研究較少針對VR做混成式學習並探討其實際操作的遷移效果,本研究以成就情緒理論以及驅動力理論作為立論基礎,探究技術型高中不同群科學生的自我效能是否驅使其面對VR設備輔助技能學習的情意層面有所不同,並且從「VR情境興趣」、「VR情境焦慮」以及「心流經驗」等情意層面探討學生從虛擬到實體的學習遷移效果。
    本研究採用「備料達人廚房助手」VR軟體輔助技能學習,並以立意取樣法,以新北市技術型高中電子科及餐飲科學生作為研究對象,實驗過程共進行三次VR輔助學習課程,後進行一次的實際切肉測驗,回收之有效樣本數據共143份,後透過結構方程模式進行驗證性分析。根據資料分析結果如下: (1)虛擬實境的操作自我效能與VR情境興趣呈現顯著正相關。(2)VR操作自我效能與VR情境焦慮呈現顯著負相關。(3)VR情境興趣與心流經驗呈現顯著正相關。(4)VR情境焦慮與心流經驗呈現顯著負相關。(5)心流經驗與學習遷移呈現顯著正相關。此外,本研究試比較不同群科的學生對於使用VR輔助學習上情意態度之差異,實證結果發現電子科學生的VR操作自我效能及心流經驗皆高於餐飲科學生且達顯著差異。
    本研究結果提供未來新科技融入技能學習課程上的實務建議與未來研究方面之參考。

    More advanced technologies are introduced into classrooms, and this evolutionary change is expected to be of benefit to students. However, rare research has been done by blending VR with real practice to explore its transfer effect. To address this gap, the present research, based on achievement emotion theory and drive theory, aimed to examine whether vocational high school students' trait would affect their learning of meat cutting skills with the assistance of VR, in terms to investigate how self-efficacy driving emotional effects on learning transfer from their virtual experience to real-world tasks.
    The research adopted the purposive sampling. Students from vocational high school in New Taipei City were targeted to practice VR meat cutting for three times, and real meat cutting for once. These students were from two different majors: Electronic and restaurant management, to practice meat cutting via VR and blended real cutting afterward. 143 data were collected and subjected to confirmatory factor analysis with structural equation modeling. The research showed that: (1)VR self-efficacy is positively associated with learning interest with playing VR; (2)VR self-efficacy is negatively associated with interacting anxiety; (3)there is a significant positive association between learning interest with playing VR and flow experience; (4)interacting anxiety is negatively associated with flow experience; and (5)the flow experience is positively associated with learning transfer.
    Additionally, this research would also like to know whether the difference in students’ departments would also have resulted in students’ divergent learning attitudes toward VR assist learning. The score of VR self-efficacy and flow experience from students from the major of Electrical and Electronics are significantly higher than students from the major of Restaurant Management.
    According to the results, this study provided practical suggestions and also provided some new insights for future research.

    目次 謝誌i 摘要ii Abstract iii 目次iv 表次vi 圖次vii 第一章 緒論 1 第一節 研究背景與動機 1 第二節 研究目的與問題 4 第三節 研究流程 6 第四節 名詞釋義 8 第二章 文獻探討 11 第一節 教學媒體 11 第二節 虛擬實境 16 第三節 自我效能 21 第四節 VR 情境興趣 26 第五節 VR 情境焦慮 32 第六節 心流經驗 37 第七節 學習遷移 44 第三章 研究設計與實施 51 第一節 研究方法與架構 51 第二節 研究對象及範圍 55 第三節 研究工具 55 第四節 實驗流程64 第四章 研究結果與分析 73 第一節 樣本特徵分析 73 第二節 學習遷移之成效 74 第三節 工具分析 76 第四節 信校度分析 85 第五節 相關分析 87 第六節 差異分析 96 第五章 結論 101 第一節 研究結論 101 第二節 實務建議 103 第三節 研究限制及未來研究建議 105 參考文獻 107 附錄 129

    中文部分
    十二年國民基本教育技術型高級中等學校群科課程綱要(2018年12月)
    朱侃如(譯)(2004)。焦慮的意義(原作者:R. May)。新北市:立緒文化。
    吳芝儀(2011)。以人為主體之社會科學研究倫理議題。人文社會科學研究,5(4),19-39。
    吳政翰(2015)。高中生在實施啟發式科學寫作中生物探究能力及學習興趣之表現(未出版碩士論文)。國立彰化師範大學,彰化縣。
    吳聲毅(2008)。數位學習觀念與實作。臺北市:學貫行銷。
    吳麗珍、黃惠滿、李浩銑(2014)。方便取樣和立意取樣之比較。護理雜誌,61(3),105-111。
    李茂能(2019)。結構方程模式理論與實務:圖解AMOS取向。臺北市:五南。
    李銀蘭(2010)。餐飲垃圾回收管理的探討-以武漢市為例。武漢工業學院學報,29(4),100-102。
    周文忠(2005)。虛擬實境之意義與應用。資訊科學應用期刊,1(1),121-127。
    林靖凱(2008)。虛擬實境融入教學對國小智能障礙學童 校園尋路教學成效之研究(未出版碩士論文)。國立臺北教育大學,台北市。
    邱皓政(2004)。結構方程模式:LISREL的理論、技術與應用。臺北市:雙葉書廊。
    邱皓政(2011)。結構方程模式:LISREL的理論、技術與應用(二版)。臺北市:雙葉書廊。
    邱皓政(2019)。量化研究與統計分析:SPSS與R資料分析範例解析(六版)。臺北市:五南。
    侯宗旻(2018)。高職餐飲科中餐烹飪技能教學之反思。臺灣教育評論月刊,7(12),101-104。
    范信賢(2016)。核心素養與十二年國民基本教育課程綱要:導讀《國民核心素養:十二年國教課程改革的DNA》。教育脈動,5,1-7。
    區國良、曾郁庭、姚玉娟(2014)。體感式數位遊戲行動學習系統對學習成就及學習保留影響之研究。科學教育學刊,22(2),163-184。
    張玫芳(2019)。自我效能、學習興趣及學校學習風氣對科學學習投入之影響:跨層次的交互作用(未出版之碩士論文)。銘傳大學,桃園市。
    張春興(1995)。張氏心理辭典。臺北市:東華書局。
    張春興(2012)。教育心理學:三化取向的理論與實踐。臺北市:東華書局。
    張偉豪(2011)。SEM論文寫作不求人。臺北市:鼎茂圖書
    張基成、林冠佑(2016)。從傳統數位學習到遊戲式數位學習―學習成效、心流經驗與認知負荷。科學教育學刊,24(3),221-248。
    張霄亭(2009)。教育科技理論與實務。臺北市:學富文化。
    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。
    郭生玉(2012)。心理與教育研究法:量化、質性與混合研究方法。臺北市:精華。
    陳可涵(2010)。利用虛擬實境技術測驗空間定向能力(未出版之碩士論文)。國立臺東大學,臺東縣。
    陳寬裕、王正華(2013)。結構方程模型分析實務:AMOS的運用。臺北市:五南。
    陳寬裕、王正華(2018)。結構方程模型:運用AMOS分析。臺北市:五南。
    勞動部勞工保險局(2020)。勞工保險職業傷害傷病給付人次-按職業傷害類型、性別及行業別分【原始數據】。取自https://www.bli.gov.tw/0104093.html
    程剛,袁桂平(2005)。學習焦慮初探。瀋陽師範大學學報(社會科學版),29(6),21-23。
    黃芳銘(2009)。結構方程模式理論與應用(五版)。臺北市:五南。
    黃嘉文(2010)。以Cyber-Physical環境支援程式設計學習之探究(未出版碩士論文)。國立中央大學,桃園市。
    黃騏堯(2003)。國小高年級學童自然科實驗操作焦慮之研究-以存在主義的焦慮觀點為導向(未出版之碩士論文)。臺北市立師範學院,臺北市。
    楊博源(2006)。虛擬實境介面之逃生訓練系統對高齡者空間能力之影響(未出版碩士論文)。義守大學,高雄市。
    榮泰生(2008)。AMOS與研究方法。臺北市:五南。
    劉信吾(1999)。教學媒體。臺北市:心理。
    蔡福興(2008)。線上遊戲式學習在知識獲取與學習遷移成效之研究(未出版之博士論文)。國立臺灣師範大學,臺北市。
    鄭佩紋(2014)。國中九年級生校正式學習策略與學習英文單字成效之相關因素探討(未出版之碩士論文)。國立臺灣師範大學,臺北市。
    鄭昭明、陳億貞(譯)(2016)。普通心理學(原作者:R. J. Sternberg)。臺北市:雙葉書廊。
    盧姿麟(2011)。口譯學生的焦慮與心流經驗及其對口譯教學之意涵(未出版碩士論文)。國立臺灣師範大學,臺北市。
    蕭和典(2015)。Image-Story聯想多媒體教學法對高職生平假名學習成效影響之研究(未出版之碩士論文)。國立中正大學,嘉義縣。
    餐旅群科中心(2020)。餐旅群科中心服務學校一覽表【原始數據】。取自http://shcedu.tsvs.ntpc.edu.tw/schools.php
    戴凱欣(2018)。虛擬實境融入空間能力養成之研究(未出版之博士論文)。國立臺灣師範大學,臺北市。
    謝信正(2000)。網際網路建置虛擬環境之研究(未出版碩士論文)。國立中央大學,桃園市。
    魏子婷(2010)。比較論證取向教學與傳統教學對高一學生論證能力學習遷移的影響(未出版之碩士論文)。國立高雄師範大學,高雄市。
    譚華德、郝詠崴、黃明月(2019)。泰文學習拼字系統之創新教學:泰語學習自我效能、學習興趣、學習焦慮及學習成就之相關研究。教育科學研究期刊,64(3),1-29。

    英文部分
    Agogo, D., & Hess, T. J. (2018). “How does tech make you feel?” a review and examination of negative affective responses to technology use. European Journal of Information Systems, 27(5), 570-599. doi: 10.1080/0960085X.2018.1435230
    Agogo, D., & Hess, T.J. (2015, December). Technostress and technology induced state anxiety: Scale development and implications. In F. W. McFarlan & T. H. Davenport (Chair), Research in Progress Paper. Symposium conducted at the meeting of Association for Information Systems, Fort Worth, TX.
    Amorim, M. A., Isableu, B., & Jarraya, M. (2006). Embodied spatial transformations: “Body analogy” for the mental rotation of objects. Journal of Experimental Psychology General, 135(3), 327-347. doi:10.1037/0096-3445.135.3.327
    Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411.
    Arnold, J. & Brown, D. (1999). A map of the terrain. In J. Arnold, (Ed.), Affect in Language Learning (pp. 1-24). Cambridge, England: Cambridge University Press.
    Arslan, A. (2006). The attitude scale toward making computer supported education. Yüzüncü Yıl University Journal of the Faculty of Education, 2(2), 34-43.
    Arthur-Mensah, N., & Shuck B. (2014) Perspectives in HRD— e-Learning in developing countries: implications for workforce training and development in Africa. New Horizons in Adult Education and Human Resource Development, 26(4), 41-46.
    Artino, A. R., Holmboe, E. S., & Durning, S. J. (2012). Control‐value theory: Using achievement emotions to improve understanding of motivation, learning, and performance in medical education: AMEE Guide No. 64. Medical Teacher, 34(3), 148-160. doi: 10.3109/0142159X.2012.651515
    Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37(2), 122-147. doi: 10.1037/0003-066X.37.2.122
    Bandura, A. (1997). Self-efficacy: The exercise of control. New York, NY: Freeman.
    Bandura, A. (2012). On the functional properties of perceived self-efficacy revisited. Journal of Management, 38(1), 9-44. doi: 10.1177/0149206311410606.
    Bandura, A. (Ed.). (1995). Self-efficacy in changing societies. Cambridge, England: Cambridge University Press.
    Bentler, P. M. (1983). Comfirmatory factor analysis via noniterative estimation: A fast, inexpensive method. Journal of Marketing Research, 19(4), 417-424. doi: 10.2307/3151715
    Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588-606. doi: 10.1037/0033-2909.88.3.588
    Bhattacharjee, D., Paul, A., Kim, J. H., & Karthigaikumar, P. (2018). An immersive learning model using evolutionary learning. Computers & Electrical Engineering, 65, 236-249.
    Biggs, J., & Moore, P. (1993). The process of learning (3rd ed.). New York, NY: Prentice Hall.
    Bishop, S., Duncan, J., Brett, M., & Lawrence, A. D. (2004). Prefrontal cortical function and anxiety: Controlling attention to threat-related stimuli. Nature Neuroscience, 7(2), 184-188. doi:10.1038/nn1173
    Black, J. B., Segal, A., Vitale, J. M., & Fadjo, C. L. (2012). Embodied cognition and learning environment design. In D. Jonassen & S. Land (Eds.), Theoretical foundations of learning environments (pp. 198-223). New York, NY: Routledge.
    Bollen, K. A. (1989). Structural equations with latent variables. New York, NY: Wiley.
    Bollen, K. A. (1990). Overall fit in covariance structure models: Two types of sample size effects. Psychological Bulletin, 107(2), 256-259. doi:10.1037/0033-2909.107.2.256
    Bouchard, T. J. Jr. (2016). Experience producing drive theory: Personality “writ large”. Personality and Individual Differences, 90, 302-314. doi: 10.1016/j.paid.2015.11.007
    Bracq, M. S., Michinov, E., Arnaldi, B., Caillaud, B., Gibaud, B., Gouranton, V., & Jannin, P. (2019). Learning procedural skills with a virtual reality simulator: An acceptability study. Nurse Education Today, 79, 153-160. doi:10.1016/j.nedt.2019.05.026
    Bransford, J. D., Brown, A. L., & Cocking, R. R. (2000). How people learn: Brain, mind, experience and school. Washington D.C.: National Academy Press.
    Bricken, M. (1991). Virtual reality learning environments: potentials and challenges. Acm Siggraph Computer Graphics, 25(3), 178-184.
    Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Researcher, 18(1), 32-42. doi: 10.3102/0013189X018001032
    Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136-162). Newbury Park, CA: Sage.
    Burdea, G., & Coiffet P. (2003). Virtual reality technology (2nd ed.). New Jersey, NJ: John Wiley & Sons.
    Burner, J. S. (1960) The process of education. Cambridge, MA: Harvard Universityy press
    Butt, A. L., Kardong-Edgren, S., & Ellertson, A. (2018). Using game-based virtual reality with haptics for skill acquisition. Clinical Simulation in Nursing, 16, 25-32. doi:10.1016/j.ecns.2017.09.010
    Byrne, B.M. (2001). Structural equation modeling with AMOS: Basic concepts, applications, and programming. Mahwah, NJ: Erlbaum.
    Byrne, B.M. (2010). Structural equation modeling with AMOS: Basic concepts, applications, and programming (2nd ed.). New York, NY: Routledge, Taylor & Francis.
    Byrne, B.M. (2016). Structural equation modeling with AMOS: Basic concepts, applications, and programming (3th ed.). New York, NY: Routledge/Taylor & Francis.
    Carsrud, A. L., & Brännback, M. (Eds.). (2009). Understanding the entrepreneurial mind: Opening the black box (Vol. 24). Berlin, Germany: Springer Science & Business Media.
    Catalano, A. (2015). The effect of a situated learning environment in a distance education information literacy course. The Journal of Academic Librarianship, 41(5), 653-659. doi: 10.1016/j.acalib.2015.06.008.
    Cattell, R. B., & Scheier, I. H. (1958). The nature of anxiety: A review of thirteen multivariate analyses comprising 814 Variables. Psychological Reports, 4(3), 351-388. doi:10.2466/pr0.1958.4.3.351
    Chekaf, M., Gauvrit, N., Guida, A., & Mathy, F. (2018). Compression in working memory and its relationship with fluid intelligence. Cognitive science, 42(3), 904-922. doi: 10.1111/cogs.12601
    Chen, H. (2006). Flow on the net–detecting Web users’ positive affects and their flow states. Computers in Human Behavior, 22(2), 221-233. doi:10.1016/j.chb.2004.07.001
    Cheng, K. H., & Tsai, C. C. (2019). A case study of immersive virtual field trips in an elementary classroom: Students’ learning experience and teacher-student interaction behaviors, Computers & Education, 140, 1-15. doi: 10.1016/j.compedu.2019.103600.
    Cipresso, P., Giglioli, I. A. C., Raya, M. L. A., & Riva, G. (2018). The past, present, and future of virtual and augmented reality research: a network and cluster analysis of the literature. Frontiers in Psychology, 9, 1-20. doi:10.3389/fpsyg.2018.02086.
    Cohen, J (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.
    Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211.
    Csikszentmihalyi, M. (1975). Beyond boredom and anxiety. San Francisco, CA: Jossey-Bass.
    Csikszentmihalyi, M. (1982). Toward a psychology of optimal experience. In L. Wheeler (Ed.), Annual Review of Personality and Social Psychology, 3, 13-36. Beverly Hills, CA: Sage.
    Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York, NY: Harper& Row.
    Csikszentmihalyi, M. (1993). The evolving self: A psychology for the third millennium. New York, NY: Harper Collins.
    Csikszentmihalyi, M. (1996). Creativity: Flow and the psychology of discovery and invention. New York, NY: Harper Perennial.
    Csikszentmihalyi, M. (1997). Finding flow: The psychology of engagement with everyday life. New York, NY: Basic Books.
    Csikszentmihalyi, M. (2000). Beyond boredom and anxiety. San Francisco, CA: Jossey-Bass.
    Csikszentmihalyi, M.(1988).The flow experience and its significance for humanpsychology. In M. Csikszentmihalyi, & I. S. Csikszentmihalyi (Eds.), Optimalexperience:Psychological studies of flow in consciousness (pp.15-35). Cambridge, England: Cambridge University Press.
    Csikszentmihalyi, M., & Csikszentmihalyi, I. (Eds.). (1988). Optimal experience: Psychological studies of flow in consciousness. Cambridge, England: Cambridge University Press.
    Csikszentmihalyi, M., & Larson, R. (1984) Being Adolescent: Conflict and Growth in the Teenage Years, New York,.NY.
    Csikszentmihalyi, M., & Massimini, F. (1985). On the psychological selection of bio-cultural information. New Ideas in Psychology, 3(2), 115-138. doi: 10.1016/0732-118X(85)90002-9
    Da Rold, F. (2018). Defining embodied cognition: The problem of situatedness. New Ideas in Psychology, 51, 9-14. doi: 10.1016/j.newideapsych.2018.04.001.
    David, D., Edwin, Arman, E., Hikari, Chandra, N., & Nadia, N. (2019). Development of escape room game using VR technology. Procedia Computer Science, 157, 646-652. doi:10.1016/j.procs.2019.08.223
    Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. New York, NY: Plenurn.
    Diamond, A. (2002). Normal development of prefrontal cortex from birth to young adulthood: Cognitive functions, anatomy, and biochemistry. In D. T. Stuss & R. T. Knight (Eds.), Principles of frontal lobe function (p. 466-503). Oxford University Press. doi:10.1093/acprof:oso/9780195134971.003.0029
    Doll, W. J., Xia, W., & Torkzadeh, G. (1994). A confirmatory factor analysis of the end-user computing satisfaction instrument. MIS Quarterly, 18(4), 453-461. doi:10.2307/249524
    Dönmez-Turan, A., & Kır, M. (2019). User anxiety as an external variable of technology acceptance model: A meta-analytic study. Procedia Computer Science, 158, 715-724. doi:10.1016/j.procs.2019.09.107
    Dror, I. (2008). Technology enhanced learning: the good, the bad, and the ugly. Pragmatics Cognition, 16(2), 215-223. doi: 10.1075/p&c.16.2.02dro
    Eraut, M. (2012). Transfer of knowledge between education and workplace settings. In H. Daniels, L. Hugh, & P. Jill. (Eds.), Knowledge, values and educational policy (pp. 75-94). London, England: Routledge.
    Eysenck, M. W., & Calvo, M. G. (1992). Anxiety and performance: The processing efficiency theory. Cognition and Emotion, 6(6), 409-434. doi:10.1080/02699939208409696.
    Fabola, A., & Miller, A. (2016). Virtual Reality for early education: A study. In Allison, C., Morgado, L., Pirker, J., Beck, D., Richter, J., & Gütl, C. (Eds.), Immersive Learning Research Network (pp. 59-72). New York, NY: Springer.
    Falah, J., Khan, S., Alfalah, T., Alfalah, S. F., Chan, W., Harrison, D. K., & Charissis, V. (2014, August). Virtual Reality medical training system for anatomy education. In K. Arai & A. Mellouk(Chair), Science and Information Conference. Symposium conducted at IEEE. London, UK.
    Felnhofer, A., Kothgassner, O., Beutl, L., Hlavacs, H., Kryspin-Exner, I. (2012, October). Is virtual reality made for men only? exploring gender differences in the sense of presence. In S. L. Howard & D. David (Chair), International Society for Presence Research Annual Conference. Symposium conducted at The International Society for Presence Research, Philadelphia, PA.
    Ferguson, C., Davidson, P. M., Scott, P. J., Jackson, D., & Hickman, L. D. (2015). Augmented reality, virtual reality and gaming: an integral part of nursing. Contemp Nurse, 51(1), 1-4. doi:10.1080/10376178.2015.1130360
    Fornell, C. & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(3), 39-50. doi: 10.2307/3151312
    Freud, S. (1977). Inhibitions, symptoms and anxiety. New York, NY: WW Norton & Company.
    Fullagar, C. J., Knight, P. A., & Sovern, H. S. (2013). Challenge/skill balance, flow, and performance anxiety. Applied Psychology, 62(2), 236-259.
    Gagné, R. (1970). The conditions of learning (2nd ed.). New York, NY: Holt, Rinehart and Winston, Inc.
    Gao, J., Zhao, B., Xiong, Y., & Gan, I. (2019). Optimization design of the online learning environment for ethnic college students: the perspective of the emotional participation. Interactive Learning Environments, 27, 1-13. doi: 10.1080/10494820.2019.1636077
    Garn, A. C., Simonton, K., Dasingert, T., & Simonton, A. (2017). Predicting changes in student engagement in university physical education: Application of control-value theory of achievement emotions. Psychology of Sport and exercise, 29, 93-102.
    George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference. 11.0 update (4th ed.). Boston, MA: Allyn & Bacon.
    Gerbing, D. W., & Anderson, J. C.(1993). Monte carlo evaluations of goodness-of-fit indices for structural equation models. In K. Bollen & J. S. Long(Eds.), Testing structural equation modeling(pp. 40-65). Newbury Park, CA: Sage.
    Glanz, K., Rimer, B. K., & Viswanath, K. (2008). Health behavior and health education. San Francisco, CA: Jossey-Bass & John Wiley and Sons.
    Gray, R. (2017). Transfer of training from virtual to real baseball batting. Frontiers in psychology, 8, 1-11. doi: 10.3389/fpsyg.2017.02183
    Gray, R. (2019). Virtual environments and their role in developing perceptual-cognitive skills in sports. In A. M. Williams & R. C. Jackson (Eds.), Anticipation and decision making in sport (pp. 342-358). New York, NY: Routledge
    Gulliver, S. R., & Kent, S. (2013). Higher education: Understanding the impact of distance learning mode on user information assimilation and satisfaction. Proceedings of the International Conference on Information Technology Interfaces 2013, pp. 199-204). doi:10.2498/iti.2013.0538
    Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2019). Multivariate data analysis (8th ed.). Boston, MA: Cengage.
    Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Thousand Oaks, CA: Sage.
    Hancock, V. E. (1990). Promoting secondary school computer use? A coordinator is the key. Proceedings of the Paper presented at the meeting of international Conference on Technology and Education 1990.
    Hancock, V.E. (1990). Promoting secondary school computer use? A coordinator is the key. Comference on Technology and Education, Maryland.
    Harackiewicz, J. M., Smith, J. L., & Priniski, S. J. (2016). Interest matters: The importance of promoting interest in education. Policy insights from the behavioral and brain sciences, 3(2), 220-227. doi:10.1177/2372732216655542.
    Hargittai, E., & Shafer, S. (2006). Differences in actual and perceived online skills: The role of gender. Social Science Quarterly, 87(2), 432-448. doi:10. 1111/j.1540-6237.2006.00389.x.
    Harris, D. J., Buckingham, G., Wilson, M. R., Brookes, J., Mushtaq, F., Mon-Williams, M., & Vine, S. J. (2020). The effect of a virtual reality environment on gaze behaviour and motor skill learning. Psychology of Sport and Exercise, 101721, 1-28. doi: 10.1016/j.psychsport.2020.101721
    Hatlevik, O. E., Throndsen, I., Loi, M., & Gudmundsdottir, G. B. (2018). Students’ ICT self-efficacy and computer and information literacy: Determinants and relationships. Computers & Education, 118, 107-119. doi: 10.1016/j.compedu.2017.11.011.
    Henseler, J., Ringle, C.M. and Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. doi: 10.1007/s11747-014-0403-8
    Hidi, S., & Renninger, K. A. (2006). The four-phase model of interest development. Educational Psychologist, 4(2), 111-127. doi: 10.1207/s15326985ep4102_4
    Hong, J. C., Hwang, M. Y., Szeto, E., Tsai, C. R., Kuo, Y. C., & Hsu, W. Y. (2016). Internet cognitive failure relevant to self-efficacy, learning interest, and satisfaction with social media learning. Computers in Human Behavior, 55, 214-222.
    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.
    Hong, J. C., Hwang, M. Y., Tai, K. H., Lin, P. H., & Lin, P. C. (2020). Learning progress in a chinese order of stroke game: The effects of intrinsic cognitive load and gameplay interest mediated by flow experience. Journal of Educational Computing Research, 58(4), 842-862. doi: 10.1177/0735633119881471
    Hong, J. C., Tai, K. H., & Ye, J. H. (2019). Playing a Chinese remote‐associated game: The correlation among flow, self‐efficacy, collective self‐esteem and competitive anxiety. British Journal of Educational Technology, 50(5), 2720-2735.
    Hong, J. C., Tai, K. H., Hwang, M. Y., & Kuo, Y. C. (2016). Internet cognitive failure affects learning progress as mediated by cognitive anxiety and flow while playing a Chinese antonym synonym game with interacting verbal–analytical and motor-control. Computers & Education, 100, 32-44.
    Hong, J.C., Hwang, M.Y., Szeto E., Tsai, C.R., Kuo, Y.C., Hsu W.Y. (2016). Internet cognitive failure relevant to self-efficacy, learning interest, and satisfaction with social medial learning. Computers in Human Behavior, 55, 214-222. doi: 10.1016/j.chb.2015.09.010
    Hsu, Y. J., & Wen, Y. Y. (2017). A case study on how a user’s high altitude experience in a virtual reality game affects emotional experiences. International Journal on Digital Learning Technology, 9(2), 85-108.
    Hu, L., & Bentler, P. M. (1995). Evaluating model fit. In R. H. Hoyle (Ed.), Structural equation modeling: Concepts, issues and applications (pp. 76-99). Thousand Oaks, CA: Sage.
    Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1-55. doi: 10.1080/10705519909540118
    Huang, J., Su, S., Zhou, L., & Liu, X. (2013). Attitude toward the viral ad: expanding traditional advertising models to interactive advertising. Journal of Interactive Marketing, 27(1), 36-46. doi:10.1016/j.intmar.2012.06.001
    Huizinga, M., Dolan, C. V., & Molen, M. W. (2006). Age-related change in executive function: Developmental trends and a latent variable analysis. Neuropsychologia, 44(11), 2017-2036. doi: 10.1016/j.neuropsychologia.2006.01.010
    Hutchinson, K., Bodner, G. M., & Bryan, L. (2011). Middle-and high-school students’ interest in nanoscale science and engineering topics and phenomena. Journal of Pre-College Engineering Education Research, 1(1), 31-39. doi:10.7771/2157-9288.1028
    Igbaria, M., & Parasuraman, S. (1989). A path analytic study of individual characteristics, computer anxiety and attitudes toward microcomputers. Journal of Management, 15, 373–388. doi:10.1177/014920638901500302
    Johnson-Glenberg, M. C., Megowan-Romanowicz, C., Birchfield, D. A., & Savio-Ramos, C. (2016). Effects of embodied learning and digital platform on the retention of physics content: Centripetal force. Frontiers in Psychology, 7, 1819. doi:10.3389/fpsyg.2016.01819
    Jolles, D. D., Buchem, M. A., Rombouts, S. A. R. B., & Crone, E.A. (2012). Practice effects in the developing brain: A pilot study. Developmental Cognitive Neuroscience, 2(1), 180-191. doi: 10.1016/j.dcn.2011.09.001
    Judd, C. H. (1908). The relation of special training to general intelligence. Education Review, 36, 28-42.
    Kanellopoulou, C., Kermanidis, K.L., & Giannakoulopoulos A. (2019). The dual-coding and multimedia learning theories: film subtitles as a vocabulary teaching tool. Education Sciences, 9(3), 210. doi: 10.3390/educsci9030210
    Kavanagh, S., Luxton-Reilly, A., Wuensche, B., & Plimmer, B. (2017). A systematic review of virtual reality in education. Themes in Science and Technology Education, 10(2), 85-119.
    Kaye, L. K., Monk, R. L., Wall, H. J., Hamlin, I., & Qureshi, A. W. (2018). The effect of flow and context on in-vivo positive mood in digital gaming. International Journal of Human-Computer Studies, 110, 45–52.
    Kim, D., & Ko, Y. J. (2019). The impact of virtual reality (VR) technology on sport spectators' flow experience and satisfaction. Computers in Human Behavior, 93, 346-356. doi: 10.1016/j.chb.2018.12.040
    King, R. B., & Gaerlan, M. J. M. (2014). High self-control predicts more positive emotions, better engagement, and higher achievement in school. European Journal of Psychology and Education, 29, 81-100.
    Kiverstein, J. (2012). The meaning of embodiment. Topics in Cognitive Science, 4(4), 740-758. doi:10.1111/j.1756-8765.2012.01219.x
    Kline, R. B. (2004). Principles and practice of structural equation modeling (2nd ed.). New York, NY: Guilford.
    Krapp, A.(2005). Basic needs and the development of interest and intrinsic motivational orientations. Learning and Instruction, 15(5), 381-395. doi:10.1016/j.learninstruc.2005.07.007.
    Kristof, R., & Satran, A. (1995). Interactivity by design: Creating & communicating with new media. San Francisco, CA: Adobe Press.
    Kukulska-Hulme, A., & Viberg, O. (2018). Mobile collaborative language learning: State of the art. British Journal of Educational Technology, 49(2), 207-218.
    Lachlan, K. A., & Krcmar, M. (2011). Experiencing presence in video games: the role of presence tendencies, game experience, gender, and time spent in play. Communication Research Reports, 28(1), 27-31. doi: 10.1080/08824096.2010.518924
    Lago-Rodriguez, A., Lopez-Alonso, V., & Fernández-del-Olmo, M. (2013). Mirror neuron system and observational learning: Behavioral and neurophysiological evidence. Behavioural brain research, 248, 104-113. doi: 10.1016/j.bbr.2013.03.033
    Lamb, R. (2014). Examination of allostasis and online laboratory simulations in a middle school science classroom. Computers in Human Behavior, 39, 224-234. doi:10.1016/j.chb.2014.07.017
    Lamb, R., Antonenko, P., Etopio, E., & Seccia, A. (2018). Comparison of virtual reality and hands on activities in science education via functional near infrared spectroscopy. Computers & Education, 124, 14-26. doi: 10.1016/j.compedu.2018.05.014
    Lave, J., & E. Wenger. (1991). Situated learning: Legitimate peripheral participation. Cambridge, England: Cambridge University Press.
    Leberman, S., McDonald, L., & Doyle, S. (2006). The transfer of learning: Participants' perspectives of adult education and training. Aldershot, England: Gower Publishing, Ltd.
    Levinson, A. J., Weaver, B., Garside, S., McGinn, H., & Norman, G. R. (2007). Virtual reality and brain anatomy: A randomised trial of e-learning instructional designs. Medical Education, 41(5), 495-501. doi: 10.1111/j.1365-2929.2006.02694.x
    Lewis, T. M., Aggarwal, R., Rajaretnam, N., Grantcharov, T. P., & Darzi, A. (2011). Training in surgical oncology – The role of VR simulation. Surgical Oncology, 20(3), 134-139. doi:10.1016/j.suronc.2011.04.005
    Linnenbrink-Garcia, L., Patall, E. A., & Messersmith, E. E. (2013). Antecedents and consequences of situational interest. The British journal of educational psychology, 83(Pt 4), 591-614. doi:10.1111/j.2044-8279.2012.02080.x
    Lu, H., Hu, Y. P., & Gao, J. J. (2016). The effects of computer self-efficacy, training satisfaction and test anxiety on attitude and performance in computerized adaptive testing. Computers & Education, 100, 45-55.
    MacCallum, R. C., & Hong, S. (1997). Power analysis in covariance structure modeling using GFI and AGFI. Multivariate Behavioral Research, 32, 193-210.
    MacKinnon, D. P. (2008). Introduction to statistical mediation analysis. New York, NY: Lawrence Erlbaum Associates.
    Marcus, M., Haden, C. A., & Uttal, D. H. (2017). STEM Learning and Transfer in a Children's Museum and Beyond. Merrill-Palmer Quarterly, 63(2), 155-180.
    Massimini, F., & Carli, M. (1988). The systematic assessment of flow in daily experience. In M. Csikszentmihalyi, & I. S. Csikszentmihalyi (Eds.), Optimal experience: psychologicalstudies of flow in consciousness (pp. 266-287). Cambridge, England: Cambridge University Press.
    Mayer, R. E. (1998). Cognitive, metacognitive, and motivational aspects of problem solving. Instructional Science, 26, 49-63.
    Mayer, R. E. (2001). Multimedia learning. Cambridge, England: Cambridge University Press. doi:10.1017/CBO9781139164603
    Mayer, R. E. (2014). Multimedia Instruction. In J. Spector, M. Merrill, J. Elen, & M. Bishop (Eds.), Handbook of research on educational communications and technology (pp.385-399). New York, NY: Springer.
    Mbarek, R. (2011). Individual and perceptual characteristics influences on e-learning outcomes. Communications of the IBIMA, 2011, 1-14. doi: 10.5171/2011. 399939
    McLellan, H. (1994). Situated learning: continuing the conversation. Educational Technology, 34(10), 7-8.
    McMahan, R. P., Lai, C., & Pal, S.K. (2016). Interaction fidelity: The uncanny valley of virtual reality interaction. In Stephanie, L., & Randall S. (Eds.), Lecture Notes in Virtual, Augmented and Mixed Reality (pp. 59-70). Berlin, Germany: Springer.
    Moos, D. C. & Azevedo, R. (2009). Learning with computer-based learning environments: A literature review of computer self-efficacy. Review of Educational Research, 79(2), 576-600.
    Moreno R. (2006). Does the modality principle hold for different media? A test of the method-affects-learning hypothesis. Journal of Computer Assisted Learning, 22(3), 149-158. doi: 10.1111/j.1365-2729.2006.00170.x
    Moreno, R. & Mayer, R. E. (2002). Learning science in virtual reality multimedia environments: Role of media and methods. Journal of Educational Psychology, 94(3) , 598-610. doi: 10.1037/0022-0663.94.3.598
    Mulaik, S. A. James, L. R., Altine, J. V., Bennett, N., Lind, S., & Stilwell, C. D. (1989). Evaluation of goodness-of-fit indices for structural equation models. Psychological Bulletin, 105(3), 430-445.
    Mullins, J. K., & Sabherwal, R. (2020). Gamification: A cognitive-emotional view. Journal of Business Research, 106, 304-314.
    Nietfeld, J. L. (2020). Predicting transfer from a game-based learning environment. Computers & Education, 146, 103780.
    Novak, T. P., Hoffman, D. L., & Yung, Y. W. (2000). Measuring the customer experience in online environments: A structural modeling approach.  Marketing Science, 19(1), 22-42. doi: 10.1287/mksc.19.1.22.15184
    O’Farrell, S. L., & Morrison, G. M. (2003). A factor analysis exploring school bonding and related constructs among upper elementary students. The California School Psychologist, 8(1), 53-72.
    Omotayo, F. O., Haliru, A. (2020). Perception of task-technology fit of digital library among undergraduates in selected universities in Nigeria. The Journal of Academic Librarianship, 46(1), 1-10. doi: 10.1016/j.acalib.2019.102097
    Oxford, R. (1999). Anxiety and the language kearner: New insights. In J. Arnold (Ed.), Affect in Language Learning (pp. 58-67). Cambridge, England: Cambridge University Press.
    Parong, J. & Mayer, R. E. (2018). Learning science in immersive virtual reality. Journal of Educational Psychology, 110(6), 785-797. doi:10.1037/edu0000241
    Pearce, J. M., Ainley, M., & Howard, S. (2005). The ebb and flow of online learning. Computers in Human Behavior, 21(5), 745-771.
    Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review, 18, 315-341.
    Pekrun, R., Elliot, A. J., & Maier, M. A. (2009). Achievement goals and achievement emotions: Testing a model of their joint relations with academic performance. Journal of Educational Psychology, 101, 115-135.
    Perkins, D. N., & Salomon, G. (1992). Transfer of learning. International Encyclopedia of Education, 2, 6452-6457.
    Pinto, T., Pinto, A., Maia-Lima, C., and Barbot, A. (2016). Learning about volcanoes using virtual field trips: A study in a Portuguese elementary school, proceedings of 9th annual International Conference of Education, Research and Innovation, 2180-2188. doi: 10.21125/iceri.2016.1487
    Rizzolatti, G., & Craighero, L. (2004). The mirror-neuron system. Annual Review of Neuroscience, 27, 169-192.
    Ross-Stewart, L., Price, J., Jackson, D., & Hawkins, C. (2018). A preliminary investigation into the use of an imagery assisted virtual reality intervention in sport. Journal of Sports Science, 6(1), 20-30 . doi: 10.17265/2332-7839/2018.01.003.
    Schiefele, U. (1991). Interest, learning and motivation. Education Psychologist, 26, 299-323.
    Schiefele, U. (1991). Interest, learning, and motivation. Educational Psychologist, 26, 299–323. doi:10.1207/s15326985ep2603&4_5
    Schiefele, U. (2009). Situat ional and individual interest. In K. R. Wentzel & A. Wigfield (Eds.), Handbook of motivation at school (pp.197-222). New York, NY: Routledge.
    Schiefele, U., & Csikszentmihalyi, M. (1995). Motivation and ability as factors in mathematics experience and achievement. Journal for Research in Mathematics Education, 26(2), 163-181.
    Schumacker, R. E., & Lomax, R. G. (2004). A beginner’s guide to structural equation modeling (2nd ed.). Mahwah, NJ: Lawrence Erlbaum Associates.
    Schwartz, D., Bransford, J., & Sears, D. (2005). Efficiency and innovation in transfer. In J. Mestre (Ed.), Transfer of learning from a modern multidisciplinary perspective (pp. 1-51). Greenwich, CT: Information Age Publishing.
    Scovel, T. (1978). The effect of affect on foreign language learning: a review of the anxiety literature. Language Learning, 28(1), 129-142. doi: 10.1111/j.1467-1770.1978.tb00309.x
    Shaffer, D. W. (2006). How computer games help children learn. New York, NY: Palgrave Macmillan.
    Sherman, W. R., & Craig, A. B. (2018). Understanding Virtual Reality: Interface, Application, and Design. Burlington, MA: Morgan Kaufmann Publishers.
    Shim, K. C., Park, J. S., Kim, H. S., Kim, J. H., Park, Y. C., & Ryu, H. I. (2003). Application of virtual reality technology in biology education. Journal of Biological Education, 37(2), 71-74. doi:10.1080/00219266.2003.9655854
    Shin, D. (2017). How does immersion work in augmented reality games? A user-centric view of immersion and engagement. Information Communication & Society, 22(9), 1-18. doi:10.1080/1369118X.2017.1411519
    Shin, D. (2018). Empathy and embodied experience in virtual environment: To what extent can virtual reality stimulate empathy and embodied experience? Computers in Human Behavior, 78, 64-73. doi:10.1016/j.chb.2017.09.012
    Shin, D. H. (2017). The role of affordance in the experience of virtual reality learning: Technological and affective affordances in virtual reality. Telematics and Informatics, 32 (8), 1826-1836. doi: 10.1016/j.tele.2017.05.013
    Sigrist, R., Rauter, G., Marchal-Crespo, L., Riener, R., & Wolf, P. (2015). Sonification and haptic feedback in addition to visual feedback enhances complex motor task learning. Experimental brain research, 233(3), 909-925.
    Simonson, M. R., Maurer, M., Montag-Torardi, M., & Whitaker, M. (1987). Development of a standardized test of computer literacy and a computer anxiety index. Journal of Educational Computing Research, 3(2), 231–247. doi: 10.2190/7CHY-5CM0-4D00-6JCG
    Skinner, E., Furrer, C., Marchand, G., & Kindermann, T. (2008). Engagement and disaffection in the classroom: Part of a larger motivational dynamic? Journal of Educational Psychology, 100, 765-781.
    Skinner, E., Kindermann, T. A., & Furrer, C. J. (2008). A motivational perspective on engagement and disaffection. Educational and Psychological Measurement, 69, 493-525
    Škola, F., & Liarokapis, F. (2018). Embodied VR environment facilitates motor imagery brain–computer interface training. Computers & Graphics, 75, 59-71. doi: 10.1016/j.cag.2018.05.024
    Somrak, A., Humar, I., Hossain, M. S., Alhamid, M. F., Hossain, M. A., & Guna, J. (2019). Estimating VR Sickness and user experience using different HMD technologies: An evaluation study. Future Generation Computer Systems, 94, 302-316. doi: 10.1016/j.future.2018.11.041
    Spielberger, C. D. (1972). Anxiety: current trends in theory and research. New York, NY: Academic Press.
    Spielberger, C. D. (1996). Construct validity of the Beck Depression Inventory as a measure of state and trait depression in nonclinical populations. Depression and Stress, 2(2), 123-145.
    Steiner, G. (2001). Transfer of Learning, Cognitive Psychology of. International Encyclopedia of the Social & Behavioral Sciences 2001, 15845-15851. doi: 10.1016/B0-08-043076-7/01481-9
    Sutherland, I. E. (1968). A head-mounted three dimensional display. In Proceedings of the December 9-11, 1968, fall joint computer conference, part I (pp. 757-764). ACM.
    Swann, C. F., Keegan, R. J., Piggott, D., & Crust, L. (2012). A systematic review of the experience, occurrence, and controllability of flow states in elite sport. Psychology of Sport and Exercise, 13(6), 807-819. doi:10.1016/j.psychsport.2012.05.006
    Tarafdar, M., Tu, Q., Ragu-Nathan, B., & Ragu-Nathan, T. (2007). The impact of technostress on role stress and productivity. Journal of Management Information Systems, 24(1), 308-328. doi:10.2753/MIS0742-1222240109
    Thatcher, J. B., & Perrewe, P. L. (2002). An empirical examination of individual traits as antecedents to computer anxiety and computer self-efficacy. MIS Quarterly, 26(4), 381-396. doi: 10.2307/4132314
    Thoman, D. B., Smith, J. L., & Silvia, P. (2011). The resource replenishment function of interest. Social Psychological & Personality Science, 2, 592-599. doi:10.1177/1948550611402521
    Thomas, G. E. (1996). Teaching students with mental retardation: A life goal curriculum planning approach. Englewood Cliffs, NJ: Prentice-Hall, Inc.
    Thorndike, E. L. (1903). Educational Psychology. Montana, MT: Kessinger Publishing.
    Ullman, J. B. (2001). Structural equation modeling. In: B. G. Tabachnick, & L. S. Fidell (Eds.), Using multivariate statistics(4th) (pp. 653-771). Boston, MA: Pearson Education.
    Urbach, N., & Ahlemann, F. (2010). Structural equation modeling in information systems research using partial least squares. Journal of Information technology theory and application, 11(2), 5-40.
    Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342–365. doi: 10.1287/isre.11.4.342.11872
    Vergara, D., Rubio, M. P., & Lorenzo, M. (2017). New approach for the teaching of concrete compression tests in large groups of engineering students. Journal of Professional Issues in Engineering Education and Practice, 143 (2). doi:10.1061/(ASCE)EI.1943-5541.0000311
    Wang, C. Y., & Tsai, M. J. (2017). Students’ self-efficacy and attitudes toward web-based recipe learning in Taiwan culinary education. The Asia-Pacific Education Researcher, 26, 193-204.
    Wolf, E. J., Harrington, K. M., Clark, S. L., & Miller, M. W. (2013). Sample size requirements for structural equation models: An evaluation of power, bias, and solution propriety. Educational and psychological measurement, 73(6), 913-934.
    Yahaya, W. A. J. W., & Ahmad, A. (2017). The effectiveness of signaling principle in virtual reality courseware towards achievement of transfer learning among students with different spatial ability. AIP Conference Proceedings, 1891(1), 020144. doi:10.1063/1.5005476
    Yerkes, R. M., & Dodson, J. D. (1908). The relation of strength of stimulus to rapidity of habit‐formation. Journal of Comparative Neurology and Psychology, 18(5), 459-482. doi:10.1002/cne.920180503
    Yeşilyurt, E., Ulaş, A. H., & Akan, D. (2016). Teacher self-efficacy, academic self-efficacy, and computer self-efficacy as predictors of attitude toward applying computer-supported education. Computers in Human Behavior, 64, 591-601.
    Zacks, R. T., & Hasher, L. (1993). Capacity theory and the processing of inferences. In L. L. Light & D. M. Burke (Eds.), Language, memory, and aging (pp. 154-170). Cambridge, England: Cambridge University Press.

    下載圖示
    QR CODE