研究生: |
陳冠鳳 Chen, Kuan-Fong |
---|---|
論文名稱: |
以VR爵士鼓遊戲探究中學生之節奏感增長信念與遊戲焦慮、心流經驗對學習價值及學習成效之相關研究 Using VR Drum to Explore the Learning Effectiveness of Senior High School Students: Incremental Belief of Rhythm Related to Gameplay Anxiety, Flow Experience, and Perceived Learning Value |
指導教授: |
洪榮昭
Hong, Jon-Chao |
口試委員: | 洪榮昭 陳曉雰 林展立 |
口試日期: | 2021/06/26 |
學位類別: |
碩士 Master |
系所名稱: |
創造力發展碩士在職專班 Continuing Education Master's Program of Creativity Development |
論文出版年: | 2021 |
畢業學年度: | 109 |
語文別: | 中文 |
論文頁數: | 136 |
中文關鍵詞: | 虛擬實境 、節奏感內隱信念 、遊戲焦慮 、心流經驗 、學習價值 、學習成效 、增長信念 |
英文關鍵詞: | virtual reality, rhythm implicit beliefs, gameplay anxiety, flow experience, learning value, learning effectiveness, incremental belief |
研究方法: | 準實驗研究單組時間序列分析法 |
DOI URL: | http://doi.org/10.6345/NTNU202100741 |
論文種類: | 學術論文 |
相關次數: | 點閱:411 下載:70 |
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 |
隨科技與網路的普及,相關的研究與日俱增,研究指出在教學中融合數位科技能使教學內容更豐碩,也為教學帶來更多的發揮空間。與教育現場相符應,近年來許多為音樂學習而設計的數位軟體出現,在音樂學習過程中,節奏練習是不可或缺的基本功,若結合數位科技媒材,能為節奏學習帶來新風貌。然而,目前在節奏練習中,尚未看到有合適的數位科技工具來幫助學生學習節奏,基於此,本研究採用了由國立臺灣師範大學數位遊戲學習實驗室所開發之虛擬實境遊戲「VR爵士鼓遊戲——打打爵士樂」來探討中學生於音樂課節奏學習上的成效。該遊戲內建了一項功能,可針對學習者演奏的內容進行分析,使學習者知道自己的錯誤處,根據系統反饋進行修正再練習,以得學習成效。
為瞭解此遊戲是否能有效提升學生節奏感,本研究以多媒體認知情意理論為基礎,以準實驗研究單組時間序列分析方式探討學生在遊戲進行時其認知、情緒狀態與學習成效間的關係。本研究邀請新北市某高中學生為研究參與對象,利用4週時間,進行5次實驗,並根據遊戲後臺數據及問卷調查來搜集資料,有效樣本共67份。問卷經參考相關文獻後進行編修,內容包括「節奏感增長信念」、「遊戲焦慮」、「心流經驗」與「學習價值」等向度。使用驗證性分析及結構方程模式分析得下列研究結果:
一、節奏感增長信念與遊戲焦慮具顯著負相關
二、節奏感增長信念與心流經驗具顯著正相關
三、遊戲焦慮與學習價值無相關
四、心流經驗與學習價值具顯著正相關
五、學習價值與學習成效具顯著正相關
六、遊戲焦慮經由學習價值中介與學習成效無相關
七、心流經驗經由學習價值中介與學習成效具正相關
八、節奏感增長信念經由遊戲焦慮、心流經驗、學習價值中介與學習成效無相關
而除了上述各構面之間的相關程度,本研究的結果表明從開始至最後階段,學生的節奏學習成效得到了顯著的提升。
With the booming of technology and the popularization, more and more researches indicate that the integration of digital technology in teaching can enrich the content and bring more possibilities for students to learn. In line with the application in education settings, there are many digital devices designed for teaching musical skills. Moreover, in the process of music learning, rhythm practice is an indispensable basic skill, and if it can be integrated with digital technology, it may bring a new style of rhythm learning. However, there is no suitable tool to help students in rhythm practice with embodied cognition. Thus, the present study adapted a virtual reality (VR) device, named “Drum VR”, which is developed by the Digital Game-based Learning Lab of National Taiwan Normal University. Drum VR, embedded a function to analyze the content of learners' performance, so that learners can know their mistakes and correct them based on the feedback spontaneously by the system to promote rhythm learning effectiveness.
In order to understand whether this game can effectively enhance students' sense of rhythm, this study, based on the multimedia cognitive-emotional theory, conducted an experimental study to explore the relationship between students' cognitive and emotional states and learning effectiveness when playing “Drum VR.” Students in a high school in New Taipei City were invited to take practice in these five sessions for four weeks. There 67 useful data were collected after Drum VR practices. The questionnaires were compiled by referring to relevant literature and included the dimensions of "rhythm incremental beliefs", "gameplay anxiety", "flow experiences", and "perceived learning value". The results of this study, using confirmatory factor analysis and structural equation model analysis, are as follows: 1. Rhythm incremental beliefs can negatively predict gameplay anxiety. 2. Rhythm incremental belief can positively predict flow experience. 3. Gameplay anxiety is not related to learning value. 4. Flow experience can positively predict learning value. 5. Learning value can positively predict learning effectiveness. 6. Game anxiety is not significantly related to learning effectiveness through learning value mediation. 7. Flow experience is positively correlated with learning effectiveness through learning value mediation. 8. Rhythm incremental belief is not significantly related to learning effectiveness through game anxiety, flow experience, and learning value mediation. Besides the relationship analysis, the result of this study also revealed that the learning progress is significantly promoted from beginning session to last session.
中文文獻
王曉晴、林啟超(2012)。國小學童數學課室目標結構、數學知識信念與學習行為組型關係之研究。東海教育評論,12,29-56。
王嬿惠、羅承浤、鮑惟豪、謝秉叡(2011)。數位動態與靜態影像之輔助學習成效比較-以英語學習為例。工程科技與教育學刊,8(3),343-350。
伍韋霖、蔡孟娟(2010)。運動新趨勢-Wii虛擬情境之運動效益研究。永續發展與管理策略,2(2),39-54。
江旻璇(2020)。桌遊融入英語教學對學習成效與英語口說焦慮之影響。國立高雄師範大學,高雄市。
何昱穎、張智凱、劉寶鈞(2010)程式設計課程之學習焦慮降低與學習動機維持─以 Scratch為補救教學工具。數位學習科技期刊,2(1),11-32。
何學庸、古蕙玲(2020)。增廣及虛擬(AR/VR)實境教學之應用-以觀光導覽解說課程為例。中華科技大學學報,79,113-133
吳明隆(2009)。結構方程模式:AMOS的操作與應用(第二版)。臺北市:五南。
吳珮如(2017)。學習焦慮與測驗焦慮對英語學習者在聽力成就表現與聽力能力自覺的影響。國立臺灣師範大學,臺北市。
吳萬益、林清河(2002)。行銷研究。臺北市:華泰文化事業股份有限公司。
阮姿綾(2014)。臺北市國小高年級學生自我效能、智力內隱信念、課室目標結構與學習投入之關係研究。國立臺北教育大學,臺北市。
林佩儒、柯志欣(2009)。線上音樂遊戲對音樂學習與節奏感提升成效之研究。屏東教育大學學報-教育類,33,37-67。
林昌臻(2020)。以認知—情感多媒體學習理論分析虛擬實境教學應用於技術型高中汽車美容之學習保留相關研究。國立臺灣師範大學,臺北市。
林欣怡(2015)。學習興趣、自我效能與學習價值對八年級學生科學學習成就之影響─以TIMSS2011臺灣為例。明道大學,彰化縣。
林欣慈、蔡明昌(2015)。自我實現、心流體驗與幸福展之研究:以參與鐵人三項中老年族群為例。運動休閒管理學報,12(2),15-28。
林彥廷(2019)。音樂素養與性別差異對生理訊號及心智負荷之影響探討 -以音樂節奏遊戲為例。中原大學,桃園市。
林家米、隋翠華(2017)。桌遊融入語詞學習之應用研究分析。臺灣教育評論月刊,6(4),196-202。
林惠玲、陳正倉(2011)。應用統計學(修訂四版)。臺北市:雙葉書廊。
林雅雯、曾志隆(2017)。「國中學生數學信念量表」之編製。測驗學刊,64(3),259-293 。
林瑜一(2013)。與腦相容的教學原則與策略初探。慈濟大學教育研究學刊,9,69-104。
林顯昌、林浪津、陳世杰(2017)AR/VR互動感知技術。電腦與通訊,170,1-4。
邱皓政(2013)。量化研究與統計分析:SPSS (PASW)資料分析範例解析。臺北市:五南。
邱皓政、林碧芳(2017)。統計學:原理與應用(3版)。臺北市:五南。
姚世澤(1988)。從「音樂實驗班教育」談音樂性向與成就測驗。師友月刊,257,46-48。
洪一平、李寅彰、 詹媛安、王碩仁(2020)。穿越記憶的聲景:〈風動四方-安平1634〉的虛擬實境。南藝學報,20,1–23。
洪榮昭、何雅娟、葉建宏、吳宇豐、戴凱欣(2020)。空間能力評量系統APP:圖學表現、遊戲興趣、遊戲焦慮及持續遊玩意願之相關研究。中等教育,71(1),29-51。
洪榮昭、詹瓊華(2018)。共變推理遊戲:遊戲自我效能與後設認知影響遊戲中的焦慮、興趣及表現之研究。教育科學研究期刊,63(3),131-162。doi: 10.6209/JORIES.201809_63(3).0005
高淑珍(2012)。以知識分享為中介變數探討學習動機、學習互動以及學習平台對協同學習滿 意度的影響。商管科技季刊,13(1),75-98。
高毓霠(2016)。虛擬實境VR、AR進入生活。禪天下,137,34–39。
張正杰、莊秀卿、羅綸新(2014)。多媒體呈現模式與認知風格對國小自然科學學習成效之影響。教育傳播與科技研究,108,31-48。doi:10.6137/RECT.2014.108.03
張春興(1998)。現代心理學。臺北市:東華。
張春興、林青山(1989)。教育心理學。臺北市:東華。
張訓(2018)。虛擬實境運用於教育場域可能面臨的問題。臺灣教育評論月刊,7(11),120-125。
張偉豪(2011)。論文寫作SEM不求人。臺北市:鼎茂。
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、心流體驗與認知負荷。科學教育學刊,24(3),221-248。doi:10.6173/CJSE.2016.2403.01
張聖淵、詹勳從(2019)。高中生持續參與遊戲意圖之研究:以3D摩托車數位遊戲為例。教育科學研究期刊,64(3),31-53。doi:10.6209/JORIES.201909_64(3).0002
張薇貞(2020)。《論語》學習態度對「孔子點點名互動遊戲」的認知負荷、遊戲興趣、遊戲學習價值之相關研究。國立臺灣師範大學,臺北市。
教育部(2018)。十二年國民基本教育課程綱要國民中小學暨普通型高級中等學校-藝術領域。臺北市:教育部。
莊敏仁、林佳穎、王美玲、張董淗(2010)。觸動心靈音樂欣賞教材教師指導系列手冊(一)。臺北市:東和音樂。
莊嵐雅(2011)。注意力偏誤訓練對射箭選手特質焦慮、運動特質焦慮與競賽狀態焦慮之影響。臺北市立體育學院運動科學研究所,臺北市。
莊懿妃、蔡義清、俞洪亮(2018)。商管研究資料分析:SPSS的應用(3版)。臺北市:華泰。
許一珍、范丙林、巫宗和、蕭文祥(2015)。心流經驗於遊戲使用者介面之研究。數位學習科技期刊,7(2),73-93。
許貴序(2001)。創造思考教學對高職邏輯設計課程學習成效之教學實驗研究。國立彰化師範大學,彰化市。
郭胤呈(2020)。沉浸式虛擬實境數位遊戲式教材對國中生學習動機之影響:以木尺實驗為例。淡江大學,新北市。
陳文慶(2000)。運動模擬與虛擬實境之整合研究。國立臺灣大學,臺北市。
陳弘哲、劉唯玉(2013)。音樂節奏電玩對國小學童節奏感影響之研究。臺北市立教育大學學報。44(1),85-118。
陳年麒(2015)。一套使用視覺通透式頭戴顯示器為輔助的擴增實境鋼琴學習系統。國立臺灣大學,臺北市。
陳和昌(2014)。音樂學習之心流經驗與學習成效之相關研究。國立屏東科技大學,屏東市。
陳怡婷(2010)。優秀桌球選手最佳運動表現的心理狀態及來源。國立臺灣師範大學,臺北市。
陳欣蓉、廖元甫(2018)。人工智慧整合的VR高中英語會話應用及輔導系統-研發整合腦波訊號偵測系統,視覺化發音過程模擬模組及對話機器人系統。科技部補助產學合作研究計畫。高雄市:國立高雄科技大學外語學院。
陳彙芳、范懿文(2000)。認知負荷對多媒體電腦輔助學習成效之影響研究。資訊管理研究,2(2),45-60。
陳詩涵(2015)。融合式節奏教學策略應用於國小四年級學童節奏學習之成效。國立臺中教育大學,臺中市。
程毓明、郭勝煌(2011)。遊戲式學習對學習成效影響之探討:以國中綜合活動童軍課程為例。工業科技教育學刊,4,25-32。
黃心健(2017)。影視跨界創作:VR虛擬實境應用。國土及公共治理季刊,5(4),98-103。
黃玟瑜(2003)。多感官音樂欣賞教學與知覺學習風格對學童學習成效之影響。國立臺北師範學院,臺北市。
黃淑賢、游子宜、施如齡(2018)。性別對於科技融入立體書的歷史學習成效與心流之研究。數位學習科技期刊,10(3),77-102。
葉建宏(2020)。內隱信念、虛擬實境中的專注力及空間能力、設計心流體驗與圖形創意表現:模式建構與驗證。國立臺灣師範大學,臺北市。
董維、張瑞觀、梁榮達(2009)。由周邊路徑效果探討特定網路廣告態度形成:人機互動、情緒及一般網路廣告態度。電子商務學報,11(1),143-172。
詹掌筆(2005)。探討多媒體教材導向教學法對國小四年級學生音樂學科之音感,節奏,演唱,記號及管樂學習成效影響之研究。國立交通大學,新竹市。
蔡福興、游光昭、蕭顯勝(2008)。從新學習遷移觀點發覺數位遊戲式學習之價值。課程與教學季刊,11(4),237-278。
鄭方靖(2012)。當代五大音樂教學法。高雄市:復文。
鄭宇君(2013)。從數位學習到新素養:電子書閱讀器對高中生社群的可能影響。新聞學研究,114,127-163。
鄭淑禎(2014)。博物館APP導覽系統之系統品質覺知及體驗價值與使用意圖相關研究。國立臺灣師範大學,臺北市。
鄭琇月(2003)。國小四到六年級節奏聽音能力及相關因素之研究。國立臺北師範學院,臺北市。
鄭雅尹(2019)。虛擬實境應用於教學之分析-以Google Cardboard(VR裝置)融入教學為例。臺灣教育評論月刊,8(3),256–258。
鄭慧鈴(2004)。主題式統整課程對國中學生音樂學習態度與成效之研究。國立臺灣師範大學,臺北市。
謝旻儕、林語瑄(2017)。虛擬實境與擴增實境在醫護實務與教育之應用。護理雜誌,64(6),12 -18。
鍾健剛(2002)。非同步遠距教學對高職汽車修護科汽油噴射引擎實習課程學習成效之影響。國立彰化師範大學,彰化市。
羅幼瓊、林曉芳、林清文(2013)。大學生課業任務價值量表編制之研究。高雄師大學報,34。1-20。
羅家駿、郭宛如(2020)。玩家人格特質與答題時間壓力對遊戲體驗、態度與表現之影響。教育傳播與科技研究,124,53-68。doi:10.6137/RECT.202012_(124).0004
譚華德、郝永崴、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。doi: 10.6209/JORIES.201909_64(3).0001
英文文獻
Abdous, M. (2019). Influence of satisfaction and preparedness on online students' feelings of anxiety. The Internet and Higher Education, 41, 34-44. doi: https://doi.org/10.1016/j.iheduc.2019.01.001
Abdullah, F., Kassim, M. H. B., & Sanusi, A. N. Z. (2017). Go virtual: Exploring augmented reality application in representation of steel architectural construction for the enhancement of architecture education. Advanced Science Letters, 23(2), 804–808.
Abuhamdeh, S., & Csikszentmihalyi, M. (2012). The importance of challenge for the enjoyment of intrinsically motivated, goal-directed activities. Personality & Social Psychology Bulletin, 38 (3), 317-330, doi:10.1177/0146167211427147
Abulrub A-H. G., Attridge A. N., & Williams M. A. (2010). Virtual reality in engineering education: The future of creative learning. International Journal of Emerging Technologies in Learning (iJET), 6(4), doi: 10.3991/ijet.v6i4.1766
Adage (2015). Nike puts you in Neymar's shoes on the soccer pitch with VR experience. Retrieved from: https://adage.com/creativity/work/hypervenom-vr-experience/42661.
Adams, E. (2014). Fundamentals of game design (3rd ed.). Berkeley, CA: New Riders.
Admiraal, W., J. Huizenga, J., Akkerman, S., & ten Dam, G. (2011). The concept of flow in collaborative game-based learning. Computers in Human Behavior, 27 (3), 1185-1194.
Ahmed, S. U. (2018). Interaction and interactivity: In the context of digital interactive art installation. In M. Kurosu (Ed.), Computer science human-computer interaction: Interaction in context (pp. 241–257). Berlin: Springer.
Akca, F. (2011). The relationship between test anxiety and learned helplessness. Social Behavior and Personality: An International Journal, 39(1), 101-112. doi:10.2224/sbp.2011.39.1.101
Aljughaiman, A., & Mowrer-Reynolds, E. (2005). Teachers’ conceptions of creativity and creative students. The Journal of Creative Behavior, 39(1), 17-34.
Amiri, M., & Ghonsooly, B. (2015). The relationship between English learning anxiety and the students’ achievement on examinations. Journal of Language Teaching and Research, 6(4), 855-865. doi:10.17507/jltr.0604.20
Amoura, C., Berjot, S., Gillet, N., & Altintas, E. (2013). Desire for control, perception of control: Their impact on autonomous motivation and psychological adjustment, Motivation and Emotion, 38, 323–335. doi: https://doi.org/10.1007/s11031-013-9379-9.
Andrews, J., & Smith, D. C. (1996). In search of the marketing imagination: Factors affecting the creativity of marketing programs for mature products. Journal of Marketing Research, 33, 174-187. doi:10.2307/3152145
Antonietti, A., & Cantoia, M. (2000). To see a painting versus to walk in a painting: An experiment on sense-making through virtual reality. Computers & Education, 34, 213-223.
Arens, K., Yeung, A. S., Craven, R. G., & Hasselhorn, M. (2011). The twofold multidimensionality of academic self-concept: Domain specificity and separation between competence and affect components. Journal of Educational Psychology, 103(4), 970–981. doi: https://doi.org/10.1037/a0025047.
Ashcraft, M. H. (2002). Math anxiety: Personal, educational, and cognitive consequences. Current Directions in Psychological Science, 11, 181-185. doi: 10.1111/1467-8721.00196
Ashcraft, M. H., & Kirk, E. P. (2001). The relationships among working memory, math anxiety and performance. Journal of Experimental Psychology: General, 130, 223-237. doi: 10.1037//0096-3445.130.2.224
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16, 74-94.
Bakadorova, O., Lazarides, R., & Raufelder, D. (2020). Effects of social and individual school self-concepts on school engagement during adolescence. European Journal of Psychology of Education, 35(1), 73-91. doi:10.1007/s10212-019-00423-x
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191-215. doi:10.1037/0033-295X.84.2.191
Bandura, A. (2001). Social Cognitive Theory: An Agentic Perspective. Annual Review of Psychology, 52, 1-26
Barlow, D. H. (2004). Anxiety and its disorders: The nature and treatment of anxiety and panic. New York: Guilford Press.
Boehme, K. L., Goetz, T., & Preckel, F. (2017). Is it good to value math? Investigating mothers’ impact on their children’s test anxiety based on control-value theory. Contemporary Educational Psychology, 51, 11-21. doi: https://doi.org/10.1016/j.cedpsych.2017.05.002
Bormann, K. (2005). Presence and the utility of audio spatialization. Presence, 14(3), 278–297.
Brom, C., Buchtová, M., Šisler, V., Děchtěrenko, F., Palme, R., & Glenk, L. M. (2014). Flow, social interaction anxiety and salivary cortisol responses in serious games: A quasi-experimental study. Computers & Education, 79, 69-100.
Brown, C. P., & Lan, Y. (2015). A qualitative metasynthesis comparing U.S. teachers' conceptions of school readiness prior to and after the implementation of NCBL. Teaching and Teacher Education, 45, 1-13.
Brown, E., & Cairns P. (2004). A grounded investigation of game immersion. Austria: Assocaiton for Computing Machinery
Byrne, K., Silasi-Mansat, C. D., & Worthy, D. A. (2015). Who chokes under pressure? The Big Five personality traits and decisionmaking under pressure. Personality and Individual Differences, 74, 22-28. doi:10.1016/j.paid.2014.10.009
Carleton, R. N. (2016). Into the unknown: a review and synthesis of contemporary models involving uncertainty. Journal of Anxiety Disorders, 39, 30-43.
Carr, P. B., & Dweck, C. S. (2011). Intelligence and motivation. In R. J. Sternberg, & S. B. Kaufman (Eds.), The Cambridge handbook of intelligence (pp.748-770), New York, NY: Cambridge University Press.
Cazan, A. M., Cocoradă, E., & Maican, C. I. (2016). Computer anxiety and attitudes towards the computer and the internet with Romanian high-school and university students. Computers in Human Behavior, 55, 258-267.
Çelik, B., & Gündoğdu, K. (2016). The effect of using humor and concept cartoons in high school ICT lesson on students’ achievement, retention, attitude and anxiety. Computers & Education, 103, 144-157.
Chen, H. (2006). Flow on the net–detecting web users’ positive affects and their flow states. Computer in Human Behavior, 22(2), 221-233.
Chen, H., Wigand, R. T., & Nilan, M. S. (1999). Optimal experience of Web activities. Computers in Human Behavior, 15(5), 585-608.
Chen, J. L., Penhune, V. B., & Zatorre, R. J. (2008). Listening to musical rhythms recruits motor regions of the brain. Cerebral Cortex, 18(12), 2844– 2854.
Chen, X., Chen, Z., Li, Y., He, T., Hou, J., Liu, S. & He, Y. (2019). ImmerTai: Immersive Motion Learning in VR Environments. Journal of Visual Communication and Image Representation, 58, 416-427. doi: https://doi.org/10.1016/j.jvcir.2018.11.039
Chen, Y. L., & Hsu, C. C. (2020). Self-regulated mobile game-based English learning in a virtual reality environment. Computers & Education, 154, 103910. doi:1 0.1016/j.compedu.2020.103910
Choi, B. & Baek, Y. (2011). Exploring factors of media characteristic influencing flow in learning through virtual worlds. Computers & Education, 57(4), 2382-2394
Clarke, G., Kehoe, J., & O'Broin, D. (2017). The effects of gamification on the formation of a habit of studying in tertiary level students. Reading: Academic Conferences International Limited. Retrieved from https://search.proquest.com/conference-papers-proceedings/effects-gamification-on-formation-habit-studying/docview/1967729644/se-2?accountid=14228
Cohen, J. (1988). Statistical power analysis for the behavioral science (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.
Conway, C. (2003). Good rhythm and intonation from day one in beginning instrumental music. Music Educators Journal, 89(5), 26-31
Cropley, D. H., Patston, T., Marrone, R. L., & Kaufman, J. C. (2019). Essential, unexceptional and universal: Teacher implicit beliefs of creativity. Thinking Skills and Creativity, 34, 100604. doi: https://doi.org/10.1016/j.tsc.2019.100604
Cruz, R. F. (2018). Marian Chace Foundation lecture: Rhythms of research and dance/movement therapy. American Journal of Dance Therapy, 40(1), 142-154. doi:10.1007/s10465-018-9267-7
Csikszentmihalyi, M. (1975). Beyond boredom and anxiety. San Francisco: Josey-Bass.
Csikszentmihalyi, M. (1988). Introduction. In M. Csikszentmihalyi & I. Csikszentmihalyi (Eds.), Optimal experience: Psychological studies of flow in consciousness (pp. 3-14). New York: Cambridge
Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York: Harrer and Row.
Csikszentmihalyi, M. (1993). The evolving self: A psychology for the third millennium. New York: HarperCollins.
Dai, T. & Cromley, J. G. (2014). Changes in implicit theories of ability in biology and dropout from STEM majors: A latent growth curve approach. Contemporary Educational Psychology, 39, 233-247. doi:10.1016/j.cedpsych.2014.06.003
Dai, T. & Cromley, J. G. (2014). Changes in implicit theories of ability in biology and dropout from STEM majors: A latent growth curve approach. Contemporary Educational Psychology, 39(3), 233-247.
Dalgarno, B., & Lee, M. J. W. (2010). What are the learning affordances of 3-D virtual environments? British Journal of Educational Technology, 41(1), 10–32.
de Moura, V. F., de Souza, C. A., & Viana, A. B. N. (2021). The use of massive open online courses (MOOCs) in blended learning courses and the functional value perceived by students. Computer & Education (161). 104077.
Dede, C. (2009). Immersive interfaces for engagement and learning. Science, 323(5910), 66–69.
Dell, C. (2010). Strings got rhythm: A guide to developing rhythmic skills in beginners. Music Educators Journal, 96(3), 31-34.
Demetriou, A., Larson, M. A., & Liem, C. (2016). Go with the flow: When listeners use music as technology. In Proceedings of seventeenth international society for music information retrieval conference. New York, USA, 7-11 August 2016 (pp. 292–298).
Dempsey, J. V., Lucassen, B., Haynes, L., & Casey, M. (1996). Instructional applications of computer games. Retrieved from ERIC database. (ED394500)
Dewaele, J. M., Witney, J., Saito, K., & Dewaele, L. (2018). Foreign language enjoyment and anxiety: The effect of teacher and learner variables. Language Teaching Research, 22, 676-697. doi: 10.1177/1362168817692161. doi: 10.1109/CVPR.2003.1211340
Dickey, M. D. (2005). Engaging by design: How engagement strategies in popular computer and video games can inform instructional design. Educational Technology Research and Development, 53, 67–83.
Dougherty, D. (2013). The maker mindset. In M. Honey, & D.E. Kanter (Eds.), Design, make, play: Growing the next generation of STEM innovators (pp.7-11). New York, NY: Routledge.
Dowling, W. J., & Tighe, T. J. (Eds.). (1993). Psychology and music: The understanding of melody and rhythm (1st ed.) (pp. 93-94). NY: Psychology Press. doi: https://doi.org/10.4324/9781315808116
Duchi, L., Lombardi, D., Paas, F., & Loyens, S. M. M. (2020). How a growth mindset can change the climate: The power of implicit beliefs in influencing people's view and action. Journal of Environmental Psychology, 70, 101461. doi: https://doi.org/10.1016/j.jenvp.2020.101461
Dweck, C. S. (1999). Self-theories: Their role in motivation, personality, and development. Philadelphia, PA: Psychology Press.
Dweck, C. S. (2000). Self-theories: Their role in motivation, personality, and development. New York, NY: Psychology Press.
Dweck, C. S., & Leggett, E. L. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95, 256-273. doi:10.1037/0033-295X.95.2.256
Dweck, C. S., & Master, A. (2008). Self-theories motivate self-regulated learning. In D.H. Schunk, & B.J. Zimmerman (Eds.), Motivation and self-regulated learning: Theory, research and applications (pp. 31-51). Mahwah, NJ: Lawrence Erlbaum Associates
Dweck, C. S., & Molden, D. C. (2005). Self-theories: Their impact on competence motivation and acquisition. In A. J. Elliot, & C. S. Dweck (Eds.), Handbook of competence and motivation (pp. 122-140). New York, NY: Guilford Press.
Dweck, C. S., Chiu, C., & Hong, Y. (1995). Implicit theories and their role in judgments and reactions: A world from two perspectives. Psychological Inquiry, 6, 267–285.
Dweck, C. S., Hong, Y., & Chiu, C. (1993). Implicit theories: Individual differences in the likelihood and meaning of dispositional inference. Personality and Social Psychology Bulletin, 19, 644–656.
Eccles, J. (1983). Expectancies, values, and academic behaviors. In J. T. Spence (Ed.), Achievement and achievement motives: Psychological and sociological approaches (pp. 75-146). San Francisco, CA: W. H. Freeman.
Eccles, J. S. (2005). Subjective task value and the Eccles et al. model of achievement related choices. In A. J. Elliot, & C. S. Dweck (Eds.), Handbook of competence and motivation (pp. 105–121). New York, NY: Guilford Press.
Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology (53),109-132.
Eccles, J. S., Adler, T. F., Futterman, R., Goff, S. B., Kaczala, C. M., Meece, J. L., & Midgley, C. (1983). Expectancies, values, and academic behaviors. In J. T. Spence (Ed.), Achievement and achievement motivation (pp. 75-146). San Francisco, CA: W. H. Freeman.
Emerson, R.W. (2019). Cronbach’s alpha explained, Journal of Visual Impairment & Blindness (Online), 113(3), 327-327. doi:10.1177/0145482X19858866
Erez, A., & Isen, A. M. (2002). The influence of positive affect on components of expectancy motivation. Journal of Applied Psychology, 87(6), 1055-1067. doi: https://doi.org/10.1037/0021-9010.87.6.1055
Erhel, A., & Jamet, E. (2018). Improving instructions in educational computer games: Exploring the relations between goal specificity, flow experience and learning outcomes. Computers in Human Behavior, 91, 106-114. doi: https://doi.org/10.1016/j.chb.2018.09.020
Eschrich, S., Mnte, T. F., & Altenmller, E. O. (2008). Unforgettable film music: The role of emotion in episodic long-term memory for music. BMC Neuroscience, 9, 48.
Ester, D. P., Scheib, J. W., & Inks, K. J. (2006). Takadimi: A rhythm system for all ages. Music Educators Journal, 93(2), 60-65.
Flanigan, A. E., Peteranetz, M.S., Shell, D. F., & Soh, L. K. (2017). Implicit intelligence beliefs of computer science students: Exploring change across the semester. Contemporary Educational Psychology, 48, 179-196.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39-50. doi: 10.2307/3151312
Frank, L. N., Stuart K. S., Skelton, Z., Drawbridge, M., Hyde, J. R., Lowery, M. S. & Wegner, N. C. (2021). Exercise duration and cohort affect variability and longevity of the response to exercise training in California Yellowtail (Seriola dorsalis). Aquaculture, 540, 736684. https://doi.org/10.1016/j.aquaculture.2021.736684
Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59-109. doi: 10.3102/00346543074001059
Fujioka, T., Trainor, L., Large, E., & Ross, B. (2009). Beta and gamma rhythms in human auditory cortex during musical beat processing. Annals of the New York Academy of Sciences, 1169, 89– 92.
Galy, E., Cariou, M., & Mélan, C. (2012). What is the relationship between mental workload factors and cognitive load types? International Journal of Psychophysiology, 83(3), 269-275. doi:10.1016/j.ijpsycho.2011.09.023
Gil, K., Jones, M., Mouw, T., Al-Kasspooles, M., Brahmbhatt, T., & DiPasco, P. J. (in press). Satisfaction or distraction: Exposure to non-preferred music may alter the learning curve for surgical trainees. Journal of Surgical Education. doi: https://doi.org/10.1016/j.jsurg.2020.04.019
Goetz, T., Pekrun, R., Hall, N., & Haag, L. (2006). Academic emotions from a social-cognitive perspective: Antecedents and domain specificity of students’ affect in the context of Latin instruction. British Journal of Educational Psychology, 76(2), 289-308. doi:10.1348/000709905X42860
Gorini, A., & Riva, G. (2008). Virtual reality in anxiety disorders: The past and the future. Expert Review of Neurotherapeutics, 8(2), 215–233.
Grahn, J. A. (2012). Neural mechanisms of rhythm perception: current findings and future perspectives. Topics in Cognitive Science 4 (4), 585–606
Gralewski, J., & Karwowski, M. (2018). Are teachers’ implicit theories of creativity related to the recognition of their students’ creativity? The Journal of Creative Behavior, 52(2). 156-167.
Greene, B. A., DeBacker, T. K., Ravindran, B., & Krows A. (1999). Goals, values, and beliefs as predictors of achievement and effort in high school mathematics classes. Sex Roles, 40(5), 421-458.
Grupe, D. W., & Nitschke, J. B. (2013). Uncertainty and anticipation in anxiety: an integrated neurobiological and psychological perspective. Nature Reviews Neuroscience volume 14, 488–501.
Guita, G. B. & Tan, D. A. (2018). Mathematics anxiety and students’ academic achievement in a reciprocal learning environment. International Journal of English and Education, 7(3),112-124.
Habok, A., Magyar, A., Nemeth, M. B., & Csapo, B. (2020). Motivation and self-related beliefs as predictors of academic achievement in reading and mathematics: Structural equation models of longitudinal data. International Journal of Educational Research, 103, 101634.
Haimovitz, K., Wormington, S. V., & Corpus, J. H. (2011). Dangerous mindsets: How beliefs about intelligence predict motivational change. Learning & Individual Differences, 21. 747-752.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLS-SEM). Thousand Oaks, CA: Sage.
Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., & Thiele, K. O. (2017). Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods. Journal of the Academy of Marketing Science, 45(5), 616–632.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 13(1), 2-24.
Hall-Phillips, A., Park, J., Chung, T. L., Anaza, N. A., & Rathod, S. R. (2016). I (heart) social ventures: Identification and social media engagement. Journal of Business Research, 69(2), 484-491.
Hancock, G. R., & Mueller, R. O. (Eds.) (2006). Structural equation modeling: A second course. Greenwich, CT: Information Age.
Harrison, J., & Lakin, J. (2018). Pre-service teachers' implicit and explicit beliefs about English language learners: An implicit association test study. Teaching and Teacher Education, 72, 54-63. doi: https://doi.org/10.1016/j.tate.2017.12.015
Hill, K., & Wigfield, A. (1984). Test anxiety: a major educational problem and what can be done about it. Elementary School Journal, 85, 105-126.
Hong, J. C., Hwang, M. Y., Tai, K. H. & Lin, P. H. (2017). Intrinsic motivation of Chinese learning in predicting online learning self-efficacy and flow experience relevant to students' learning progress. Computer Assisted Language Learning, 30(6), 552-574.
Hong, J. C., Hwang, M. Y., Tai, K. H., & Lin, P. H. (2021). The effects of intrinsic cognitive load and gameplay interest on flow experience reflecting performance progress in a Chinese remote association game. Computer Assisted Language Learning, 34(3), 358-378. DOI: 10.1080/09588221.2019.1614068 (SSCI)
Hong, J. C., Hwang, M. Y., Tai, K. H., & Tsai, C. R. (2017). An exploration of students’ science learning interest related to their cognitive anxiety, cognitive load, self-confidence and learning progress using inquiry-based learning with an iPad. Research in Science Education, 47(6), 1193-1212. doi:10.1007/s11165-016-9541-y
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: 10.1080/09588221.2019.1614068
Hong, J. C., Hwang, M. Y., Tsai, C. R., Tai, K. H., & Wu, Y. F. (2020). The effect of social dilemma on flow experience: Prosociality relevant to collective efficacy and goal achievement motivation. International Journal of Science and Mathematics Education, 18, 239-258.
Hong, J. C., Hwang, M. Y., Wu, N. C., Huang, Y. L., Lin, P. H., & Chen, Y. L. (2016). Integrating a moral reasoning game in a blended learning setting: Effects on students’interest and performance. Interactive Learning Environments, 24(3), 572-589. doi: 10.1080/10494820.2014.908926
Hong, J. C., Lin, M. P., Hwang, M. Y., Tai, K. H., & Kuo, Y. C. (2015). Comparing animated and static modes in educational gameplay on user interest, performance and gameplay anxiety. Computers & Education, 88, 109-118. doi: 10.1016/j.compedu.2015.04.018
Hong, J. C., Lin, P. H., & Hsieh, P. C. (2017). The effect of consumer innovativeness on perceived value and continuance intention to use smartwatch. Computers in Human Behavior, 67, 264-272
Hong, J. C., Lu, C. C., Hwang, M. Y., Kuo, Y. C., Wang, C. C., & Chou, C. Y. (2015). Larvae phobia relevant to anxiety and disgust reflected to the enhancement of learning interest and self-confidence. Learning and Individual Differences, 42, 147-152. doi:10.1016/j.lindif.2015.08.024
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., Tsai, C. R., Hsiao, H. S., Chen, P. H., Chu, K. C., Gu, J. J. & Sitthiworachart, J. (2019). The effect of the "Prediction-observation-quiz-explanation" inquiry-based e-learning model on flow experience in green energy learning. Computers & Education, 133, 127-138.
Hou, H. T. (2015). Integrating cluster and sequential analysis to explore learners’ flow and behavioral patterns in a simulation game with situated-learning context for science courses: A video-based process exploration. Computers in Human Behavior, 48, 424-435.
Hou, H. T., & Li, M. C. (2014). Evaluating multiple aspects of a digital educational problem-solving-based adventure game. Computers in Human Behavior, 29-38.
Hoy, A. W., & Spero, R. B. (2005). Changes in teacher efficacy during the early years of teaching: A comparison of four measures. Teaching and Teacher Education, 21(4), 343-356. doi:10.1016/j.tate.2005.01.007
Huang, N. T., Chiu, L.C., & Hong, J. C. (2016). Relationship amongst students’ problem-solving attitude, perceived value, behavioral attitude, and intention to participate in a science and technology contest. International Journal of Science and Mathematics Education. 14, 1419-1435
Hughes. J. S. (2015). Support for the domain specificity of implicit beliefs about persons’ intelligence, and morality. Personality and Individual Differences, 86, 195–203.
Hulleman, C. S., Kosovich, J. J., Barron, K. E., & Daniel, D. B. (2017). Making connections: Replicating and extending the utility value intervention in the classroom. Journal of Educational Psychology, 109(3), 387–404. doi: https://doi.org/10.1037/edu0000146
Hung, C. Y., Sun, J. C. Y., & Yu, P. T. (2015). The benefits of a challenge: Student motivation and flow experience in tablet-PC-game-based learning. Interactive Learning Environments, 23(2), 172-190.
Hwang, M. Y., Hong, J. C., Cheng, H. Y., Peng, Y. C., & Wu, N. C. (2013). Gender differences in cognitive load and competition anxiety affect 6th grade students’ attitude toward playing and intention to play at a sequential or synchronous game. Computers and Education, 60(1), 254-263. doi:10.1016/j.compedu.2012.06.014
Innocenti, E. D., Geronazzo, M. Vescovi, D. Nordahl, R., Serafin, S. Ludovico, L. A. & Avanzini, F. (2019). Mobile virtual reality for musical genre learning in primary education. Computers & Education, 139, 102-117
Inskip, C., Butterworth, R., & MacFarlane, A. (2008). A study of the information needs of the users of a folk music library and the implications for the design of a digital library system. Information Processing & Management, 44(2), 647–662.
Iversen, J. R., Patel, A. D., & Ohgushi, K. (2008). Perception of rhythmic grouping depends on auditory experience. The Journal of the Acoustical Society of America, 124(4), 2263– 2271.
Jacob, N., & McDermott, J. H. (2017). Integer ratio priors on musical rhythm revealed cross-culturally by iterated reproduction. Current Biology, 27(3), 359-370.
Jancke, L. (2008). Music, memory and emotion. Journal of Biology, 7(6), 21.
Jang, S., Vitale, J. M., Jyung, R. W., & Black, J. B. (2017). Direct manipulation is better than passive viewing for learning anatomy in a three-dimensional virtual reality environment. Computers & Education, 106, 150–165.
Jaques-Dalcroze, E. (1988). Rhythm, music, and education (2nd ed.). (L. F. Rubenstein, Trans.). New York: AYER. (Original work published 1921)
Jensen, J. F. (1998). Interactivity: Tracing a new concept in media and communication studies. Nordicom Review, 19, 185-204.
Jiménez, J. E., & O'Shanahanb, I. (2016). Effects of web-based training on Spanish pre-service and in-service teacher knowledge and implicit beliefs on learning to read. Teaching and Teacher Education, 55, 175-187. doi: https://doi.org/10.1016/j.tate.2016.01.006
Jones, T., Moore, T., & Choo, J. (2016). The impact of virtual reality on chronic pain. PLoS ONE 11 (12), e0167523. doi: https://doi.org/10.1371/journal.pone.0167523.
Kalawsky, R. S. (1993). The science of virtual reality and virtual environments. Cambridge, UK: Addison- Wesley.
Kang, S. J., Hong, C.M., & Lee, H. (2020). The impact of virtual simulation on critical thinking and self-directed learning ability of nursing students. Clinical Simulation in Nursing, 49, 66-72. doi: https://doi.org/10.1016/j.ecns.2020.05.008
Kang, Y. C., & Chen, C. Y. (2016). The study of evaluation the quality of the mobile experiential learning model. Creative Education, 7(16), 2490. doi:10.4236/ce.2016.716236
Killi, K., de Freitas, S., Arna, S., & Lainem, T. (2012). The design principles for flow experience in educational games. Procedia Computer Science, 15, 78-91.
Kim, D. & Perdue, R. R. (2013). The effects of cognitive, affective, and sensory attributes on hotel choice. International Journal of Hospitality Management, 35, 246-257.
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: https://doi.org/10.1016/j.chb.2018.12.040
Koelsch, S., Vuust, P., & Friston, K. (2019). Predictive processes and the peculiar case of music. Trends in Cognitive Sciences, 23(1), 63-77. https://doi.org/10.1016/j.tics.2018.10.006 63
Kolb, D. A., Boyatzis, R. E., & Mainemelis, C. (2001). Experiential learning theory: Previous research and new directions. Perspectives on Thinking, Learning, and Cognitive Styles, 1(8), 227-247.
Kuh, G. D., Kinzie, J., Schuh, J. H., & Whitt, E. J. (2005). Assessing conditions to enhance educational effectiveness: The inventory for student engagement and success. San Francisco, CA: Jossey-Bass.
Lamb, S., & Kwok, K. C. S. (2019). The effects of motion sickness and sopite syndrome on office workers in an 18-month field study of tall buildings. Journal of Wind Engineering and Industrial Aerodynamics, 186, 105-122. doi: https://doi.org/10.1016/j.jweia.2019.01.004
Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge, UK: Cambridge university press.
Law, K.M.Y., Lee, V.C.S., & Yu, Y.T. (2010). Learning motivation in e-learning facilitated computer programming courses. Computers & Education, 55 (1), 218-228. doi: 10.1016/j.compedu.2010.01.007
Leander, K. M., & Hollett, T. (2017). The embodied rhythms of learning: From learning across settings to learners crossing settings. International Journal of Educational Research, 84, 100-110. http://dx.doi.org/10.1016/j.ijer.2016.11.007
Lee, J. H., & Price, R. (2016). User experience with commercial music services: An empirical exploration. Journal of the Association for Information Science and Technology, 67(4), 800–811.
Leith, S. A., Ward, C. L. P., Giacomin, M., Landau, E. S., Ehrlinger, J., & Wilson, A. E. (2014). Changing theories of changes: Strategic shifting in implicit theory endorsement. Journal of Personality and Social Psychology, 107, 597–620. doi: http://dx.doi.org/10.1037/a0037699.
Li, Z., Kiiveri, M., Rantala, J., & Raisamo, R. (2021). Evaluation of haptic virtual reality user interfaces for medical marking on 3D models. International Journal of Human - Computer Studies, 147, 102561
Lim, D. H., Han, S. J., Oh, J., & Jang, C. S. (2019). Application of virtual and augmented reality for training and mentoring of higher education instructors. In J. Keengwe (Ed.), Handbook of research on virtual training and mentoring of online instructors (pp. 325–344). IGI Global.
Linnenbrink, E. A. (2006). Emotion research in education: Theoretical and methodological perspectives on the integration of affect, motivation, and cognition. Educational Psychology Review, 18, 307–314.
Lo, J. J., & Kuo, W. J., (2019). The impacts of time pressure on players’ gameplay attitudes of educational games. Paper presented at the 2019 International Conference on e-Commerce, e-Administration, e-Society, e-Education, and e-Technology, Fukuoka, Japan.
Luks, T. L., & Simpson, G. V. (2004). Preparatory deployment of attention to motion activates higher-order motion-processing brain regions. NeuroImage, 22, 1515 – 1522.
Makransky, G., & L. Lilleholt, L. (2018). A structural equation modeling investigation of the emotional value of immersive virtual reality in education. Educational Technology Research & Development, 66(5), 1141-1164.
Makransky, G., Bonde, M. T., Wulff, J. S. G., Wandall, J., Hood, M., Creed, P. A. (2016). Simulation based virtual learning environment in medical genetics counseling: An example of bridging the gap between theory and practice in medical education. BMC Medical Education, 16 (98), 1-9.
Maloney, E. A. & Beilock, S. L. (2012). Math anxiety: Who has it, why it develops, and how to guard against it. Trends in Cognitive Sciences, 16, 404-406. doi: 10.1016/j.tics.2012.06.008
Maples-Keller, J. L., Yasinski, C., Manjin, N., & Rothbaum, B.O. (2017). Virtual reality-enhanced extinction of phobias and post-traumatic stress. Neurotherapeutics 14(3), 554–563. doi: https://doi.org/10.1007/s13311-017-0534-y.
Marsh, H. W., & Hattie, J. (1996). Theoretical perspectives on the structure of self-concept. In B. A. Bracken (Ed.), Handbook of self-concept: Developmental, social, and clinical considerations (pp. 38–90). Oxford, England: John Wiley & Sons.
Marsh, H. W., & Yeung, A. S. (1998). Longitudinal structural equation models of academic self-concept and achievement: Gender differences in the development of math and English constructs. American Educational Research Journal, 35(4). 705-738.
Marsh, H. W., Ludtke, O., Nagengast, B., Trautwein, U., & Abduljabbar, A. S. (2015). Dimensional comparison theory: Paradoxical relations between self-beliefs and achievements in multiple domains. Learning and Instruction, 35, 16–32. doi: https://doi.org/10.1016/j.learninstruc.2014.08.005.
Marteau, T. M., & Bekker, H. (1992). The development of a six-item short-form of the state scale of the Spielberger State-Trait Anxiety Inventory (STAI). British Journal of Clinic Psychology, 31, 301-306.
Martin, D. P., & Rimm-Kaufman, S. E. (2015). Do student self-efficacy and teacher-student interaction quality contribute to emotional and social engagement in fifth grade math? Journal of School Psychology, 53(5), 359-373. doi:10.1016/j.jsp.2015.07.001
Mash, E. J., & Wolfe, D. A. (2002). Abnormal child psychology. Belmont, CA: Wadsworth.
Matthes, B. & Stoeger, H. (2018). Influence of parents’ implicit theories about ability on parents’ learning-related behaviors, children’s implicit theories, and children’s academic achievement. Contemporary Educational Psychology, 54, 271-280. doi: https://doi.org/10.1016/j.cedpsych.2018.07.001
Mayer, R. E. (2005). The Cambridge handbook of multimedia learning. Cambridge, CA: Cambridge University Press.
Mayne, R., & Green, H. (2020). Virtual reality for teaching and learning in crime scene investigation. Science & Justice, 60(5), 466-472. doi: https://doi.org/10.1016/j.scijus.2020.07.006
McLellan, H. (1996). Situated learning: multiple perspectives (Eds.), Situated learning perspectives (pp. 5-17). New Jersey: Educational Technology Publications Englewood Cliffs.
Merchant, Z., Goetz, E. T., Cifuentes, L., Keeney-Kennicutt, W., & Davis, T. J. (2014). Effectiveness of virtual reality-based instruction on students' learning outcomes in k-12 and higher education: A meta-analysis. Computers & Education, 70, 29–40.
Moneta, G. B. (2012). Advances in flow research. In S. Engeser (Ed.), On the measurement and conceptualization of flow (pp. 23-50). NY: Springer.
Moreno, R. & Valdez, R. (2005). Cognitive load and learning effects of having students organize pictures and words in multimedia environments: The role of student interactivity and feedback. Educational Technology Research and Development, 53, 35-45.
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.
Morris, P. O., Hope, E., Foulsham, T., & Mills, J. P. (2021). Dance, rhythm, and autism spectrum disorder: An explorative study. The Arts in Psychotherapy, 73, 101755. doi: https://doi.org/10.1016/j.aip.2020.101755
Mouratidis, A., Michou, A., & Vassiou, A. (2017). Adolescents’ autonomous functioning and implicit theories of ability as predictors of their school achievement and week-to-week study regulation and well-being. Contemporary Educational Psychology, 48, 56-66. doi:10.1016/j.cedpsych.2016.09.001
Nakamura, J., & Csikszentmihalyi, M. (2002). The concept of flow. In C.R. Snyder, & S.J. Lopez (Eds.), Handbook of positive psychology (pp. 89–105), New York, NY: Oxford University Press.
Newell, D. (2008). Teaching rhythm: New strategies and techniques for success. (pp.106-110). San Diego, CA: Neil A. Kjos Music Company
Ngoc, N., Hong, J. C., & Chen, M. L. (in press). Relationship between students’hands-on making self-efficacy, perceived value, cooperative attitude and competition preparedness in joining an iSTEAM Contest. Research in Science & Technological Education. Accepted on January 7, 2021. https://doi.org/10.1080/02635143.2021.1895100
Nicaise, M. (1995). Treating test anxiety: A review of three approaches. Teacher Education and Practice, 11(1), 65-81.
Novak, T. P., Hoffman, D. L. & Yung, Y. F. (1999). Measuring customer experience in online environments: A structural modeling approach. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.203.4000&rep=rep1&type=pdf
Nozaradan, S. (2014). Exploring how musical rhythm entrains brain activity with electroencephalogram frequency-tagging. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 369(1658)
Oliver, R. (2008). Engaging first year students using a web-supported inquiry-based learning setting. Higher Education, 55(3), 285-301.
Orehovački, T. & Babić, S. (2015). Inspecting quality of games designed for learning programming. In P. Zaphiris, & A. Ioannou (Eds.), Learning and collaboration technologies (pp. 620-631). Cham, CH: Springer.
Patston, T. J., Cropley, D. H., Marrone, R. L., & Kaufman, J. C. (2018). Teacher implicit beliefs of creativity: Is there an arts bias? Teaching and Teacher Education, 75, 366-374. doi: https://doi.org/10.1016/j.tate.2018.08.001
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. doi: 10.1007/s10648-006-9029-9
Pekrun, R., & Stephens, E. J. (2012). Academic emotions. In K. R. Harris, S. Graham, T. Urdan, J. M. Royer, & M. Zeidner (Eds.), Individual differences and cultural and contextual factors: Vol. 2. APA educational psychology handbook (pp. 3-31). Washington, DC: American Psychological Association.
Pekrun, R., Elliot, A. J., & Maier, M. A. (2006). Achievement goals and discrete achievement emotions: A theoretical model and prospective test. Journal of Educational Psychology, 98(3), 583–597. doi:https://doi.org/10.1037/0022-0663.98.3.583
Pekrun, R., Goetz, T., Titz, W., & Perry, R. P. (2002). Positive emotions in education. In E. Frydenberg (Ed.), Beyond coping: Meeting goals, visions, and challenges (pp. 149-173). Oxford, UK: Oxford University Press.
Pekrun, R., Perry, R. P. (2014). Control-value theory of achievement emotions. In R. Pekrun, L. Linnenbrink-Garcia (Eds.), International handbook of emotions in education (pp. 120-141), New York, NY: Taylor & Francis.
Pelargos, P. E., Nagasawa, D. T., Lagman, C., Tenn, S., Demos, J. V., Lee, S. J., et al. (2017). Utilizing virtual and augmented reality for educational and clinical enhancements in neurosurgery. Journal of Clinical Neuroscience, 35, 1–4.
Pesu, L., Aunola, K., Viljaranta, J., & Nurmi, J. E. (2016). The development of adolescents' self-concept of ability through grades 7-9 and the role of parental beliefs. Frontline Learning Research, 4, 92–109. doi: http://dx.doi.org/10.14786/flr.v4i3.249
Pesu, L., Aunola, K., Viljaranta, J., Hirvonen, R., & Kiuru, N. (2018). The role of mothers' beliefs in students' self-concept of ability development. Learning and Individual Differences, 65, 230–240.
Pivec, M., & Kearney, P. (2007). Games for learning and learning from games. Informatica (Ljubljana), 31(4), 419.
Prensky, M. (2001). Fun, play and games: What makes games engaging. Digital Game-based Learning, 5(1), 5–31
Prensky, M. (2003). Digital game-based learning. Computers in Entertainment. 1(1), 1-4.
Qian, J., Ma, Y., Pan, Z., & Yang, X. (2020). Effects of Virtual-real fusion on immersion, presence, and learning performance in laboratory education. Virtual Reality & Intelligent Hardware, 2(6), 569-584. doi: https://doi.org/10.1016/j.vrih.2020.07.010
Ramirez, G., Chang, H., Maloney, E. A., Levine, S. C., & Beilock, S. L. (2016). On the relationship between math anxiety and math achievement in early elementary school: The role of problem solving strategies. Journal of Experimental Child Psychology, 141, 83-100. doi:10.1016/j.jecp.2015.07.014
Reed, J. M. & Ferdig, R. E. (2021). Gaming and anxiety in the nursing simulation lab: A pilot study of an escape room. Journal of Professional Nursing, 37(2), 298-305. doi: https://doi.org/10.1016/j.profnurs.2021.01.006
Riva, G., Mantovani, F., Capideville, C. S., Preziosa, A., Morganti, F., Villani, D., Gaggioli, A., Botella, C. & Alcañiz M. (2007). Affective interactions using virtual reality: the link between presence and emotions. CyberPsychology & Behavior, 10(1), 45-56.
Rokeach, M. (1973). The nature of human values. Free Press.
Rozek, C. S., Hyde, J. S., Svoboda, R. C., Hulleman, C. S., & Harackiewicz, J. M. (2015). Gender differences in the effects of a utility-value intervention to help parents motivate adolescents in mathematics and science. Journal of Educational Psychology, 107(1), 195–206. doi: https://doi.org/10.1037/a0036981
Sauzon, H., Pala, P. A., Larrue, F., Wallet, G., Djos, M., Zheng, X., Guitton, P. & N’Kaoua, B. (2011). The use of virtual reality for episodic memory assessment: Effects of active navigation. Experimental Psychology, 59(2), 99–108.
Schank, R. C., Berman, T. R., & Macpherson, K. A. (1999). Learning by doing, Instructional-design theories and models. A New Paradigm of Instructional Theory, 2, 161–181.
Şener, S. (2015). Foreign language learning anxiety achievement: A case study of the students studying at çanakkale onsekiz mart university. Electronic Turkish Studies, 10(3), 875-890.
Serafin, S., Erkut, C., Kojs, J., Nilsson, N. C., & Nordahl, R. (2016). Virtual reality musical instruments: State of the art, design principles, and future directions. Computer Music Journal, 40(3), 22–40.
Sherwood, A., Carydias, E., Whelan, C., & Emerson, L. M. (2020). The explanatory role of facets of dispositional mindfulness and negative beliefs about worry in anxiety symptoms. Personality and Individual Differences, 190, 109933. doi: https://doi.org/10.1016/j.paid.2020.109933
Shively, R. L., & Ryan, C. S. (2013). Longitudinal changes in college math students’ implicit theories of intelligence. Social Psychology of Education, 16(2), 241-256.
Sholihin, M., Sari, R. C., Yuniarti, N., & Ilyana, S. (2020). A new way of teaching business ethics: The evaluation of virtual reality-based learning media. The International Journal of Management Education, 18(3), 100428. doi: https://doi.org/10.1016/j.ijme.2020.100428
Skadberg, Y. X., & Kimmel, J. R. (2004). Visitors' flow experience while browsing a web site: Its measurement, contributing factors and consequences. Computers in Human Behavior, 20 (3), 403-422.
Smith, S. M., & Vela, E. (2001). Environmental context-dependent memory: A review and meta-analysis. Psychonomic Bulletin & Review, 8(2), 203–220.
Spillers, F. (2004). Emotion as a cognitive artifact and the design implications for products that are perceived as pleasurable. Retrieved from https://www.semanticscholar.org/paper/Emotion-as-a-Cognitive-Artifact-and-the-Design-for-Spillers/d37de8bb4fac9518103bd764616b7c8028eb6984?p2df
Spinath, B., Spinath, F. M., Harlaar, N., & Plomin, R. (2004). Predicting school achievement from general cognitive ability, self-perceived ability, and intrinsic value. Intelligence, 34 (4). 363-374
Su, C. (2018). Exploring sustainability environment educational design and learning effect evaluation through migration Theory: An example of environment educational serious games. Sustainability, 10 (10), 33-63.
Su, C. H. (2016). The effects of students' motivation, cognitive load and learning anxiety in gamification software engineering education: A structural equation modeling study. Multimedia Tools and Applications, 75(16), 10013-10036.
Svanberg, J., Öhman, P., & Neidermeyer, P. E. (2019). Auditor objectivity as a function of auditor negotiation self-efficacy beliefs. Advances in Accounting, 44, 121-131. doi:10.1016/j.adiac.2018.10.001
Tang, M. C., & Jhang, P. S. (2019). Music discovery and revisiting behaviors of individuals with different preference characteristics: An experience sampling approach. Journal of the Association for Information Science and Technology. 71(5), 540-552. doi: https://doi.org/10.1002/asi.2425
Thorndike, E. (1927). The law of effect. The American Journal of Psychology, 39, 212-222. doi:10.2307/1415413
Tobert, S., Moneta, G. B. (2013). Flow as a function of affect and coping in the workplace. Individual Differences Research, 11, 102-113
Trevino, L. K., Webster, J. (1992). Flow in Computer-Mediated Communication: Electronic Mail and Voice mail evaluation and impacts, Communication Research, 19(5), 539-573.
Tung, W. (2000). An empirical study of ad-evoked mood formation on attitude toward the web advertising in the hypermedia computer-mediated environment. Dissertation, Mississippi State University.
Tung, W., Moore, R., & Engelland, B. (2006). Exploring attitudes and purchase intentions in a brand-oriented, highly interactive web site setting. Marketing Management Journal, 16(2), 94-106.
Vaill, A. L. (2014). Preparing online learners for success: Orientation methods and their impact on learner readiness (Doctoral dissertation). Retrieved from http://gradworks.umi.com/35/69/3569898.html
Vasuki, P. R. M., Sharma, M., Ibrahim, R., & Arciuli, J. (2017). Statistical learning and auditory processing in children with music training: An ERP study. Clinical Neurophysiology, 128, 1270–1281
Viola, P. & Jones, M. (2001). Rapid object detection using a boosted cascade of simple features. Proc. IEEE Conf. Computer Vision and Pattern Recognition, 1(1), 511-518.
Viola, P. & Jones, M. (2004). Robust real-time object detection. IEEE International Journal of Computer Vision, 57(2), 137-154.
Vorlander, M. (2007). Auralization: Fundamentals of acoustics, modelling, simulation, algorithms and acoustic virtual reality (1st ed.). Incorporated: Springer Publishing.
Vuorre, M. & Metcalfe, J. (2016). The relation between the sense of agency and the experience of flow. Consciousness & Cognition, 43, 133-142. doi: 10.1016/j.concog.2016.06.001
Wäschle, K., Allgaier, A., Lachner, A., Fink, S., Nückles, M. (2014). Procrastination and self-efficacy: Tracing vicious and virtuous circles in self-regulated learning. Learning and Instruction, 29, 103-114
Weinberg, R, S., & Gould, D. (1999), Personality and sport. In R. S. Weinberg & D. Gould (Eds.), Foundations of sport and exercise psychology (pp. 25-46). Champaign, IL: Human Kinetics.
White, M. J., & Bruning, R. (2005). Implicit writing beliefs and their relation to writing quality. Contemporary Educational Psychology, 30(2), 166-189.
Whitton, N. (2007). Motivation and computer game based learning. In ICT: Providing choices for learners and learning. Proceedings ascilite Singapore 2007. Retrieved from: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.85.7783&rep=rep1&type=pdf
Wigfield, A., & Eccles, J. (2000). Expectancy-value theory of achievement motivation. Contemporary Educational Psycholory, 25(1), 68-81.
Williams, E. H., Cristino, F., & Cross, E. S. (2019). Human body motion captures visual attention and elicits pupillary dilation. Cognition, 193, 104029. https://doi.org/10.1016/j.cognition.2019.104029
Wu, J., Li, P., & Rao, S. (2008). Why they enjoy virtual game worlds? An empirical investigation. Journal of Electronic Commerce Research, 9(3), 219-230.
Yang, J. C. & Quadir, B. (2018). Effects of prior knowledge on learning performance and anxiety in an English learning online role-playing game. Journal of Educational Technology & Society, 21(3), 174-185.
Yang, Q. F., Chang, S. C., Hwang, G. J., & Zou, D. (2020). Balancing cognitive complexity and gaming level: Effects of a cognitive complexity-based competition game on EFL students’ English vocabulary learning performance, anxiety and behaviors. Computers & Education, 148, 103808.
Yeager, D. S., & Dweck, C. S. (2012). Mindsets that promote resilience: When students believe that personal characteristics can be developed. Educational Psychologist, 47, 302-314. doi: 10.1080/00461520.2012.722805
Yin, J. H., Chng, C. B., Wong, P. M., Ho, N., Chua, M., & Chui, C. K. (2020). VR and AR in human performance research: An NUS experience. Virtual Reality & Intelligent Hardware, 2(5), 381-393. doi: 10.1016/j.vrih.2020.07.009.
Yin, M. S., Haddawy, P., Suebnukarn, S., Kulapichitr, F., Rhienmora, P., Jatuwat, V., & Uthaipattanacheep, N. (in press). Formative feedback generation in a VR-based dental Surgical skill training simulator. Journal of Biomedical Informatics, doi: https://doi.org/10.1016/j.jbi.2020.103659
Youngblut, C. (1998). Educational uses of virtual reality technology: Technical reports. Alexandria, VA: Institute for Defense Analyses.
Zembylas, M. (2008). Adult learners' emotions in online learning. Distance Education, 29(1), 71-87.
Zhang, X., Jiang, S., Ordóñez, P., Pablos, D., Lytras, M. D., & Sun. Y. (2017). How virtual reality affects perceived learning effectiveness: A task – technology fit perspective. Behaviour & Information Technology, 36(5), 548-556.