研究生: |
詹瓊華 Chan, Chiung-Hua |
---|---|
論文名稱: |
遊戲之共變推理(思維)表現與遊戲焦慮、遊戲興趣、遊戲自我效能與後設認知之相關研究 The Study of Gameplay Anxiety, Gameplay Interest, Gameplay Self-Efficacy and Metacognition Related to the Performance of Covariation Reasoning |
指導教授: |
洪榮昭
Hong, Jon-Chao |
學位類別: |
博士 Doctor |
系所名稱: |
工業教育學系 Department of Industrial Education |
論文出版年: | 2018 |
畢業學年度: | 106 |
語文別: | 中文 |
論文頁數: | 161 |
中文關鍵詞: | 共變推理表現 、遊戲焦慮 、遊戲興趣 、遊戲自我效能 、後設認知 |
英文關鍵詞: | Covariation reasoning, Gameplay anxiety, Gameplay interest, Gameplay self-Efficacy, Metacognition |
DOI URL: | http://doi.org/10.6345/DIS.NTNU.DIE.030.2018.E01 |
論文種類: | 學術論文 |
相關次數: | 點閱:374 下載:0 |
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 |
共變推理能力在日常生活中是非常重要的思考技能。學生的共變推理表現與遊戲焦慮、遊戲興趣、後設認知與遊戲自我效能的相關性是本研究所要探討的。為了瞭解數位遊戲的成效,本研究應用了一款名為「NG麵包」的共變推理遊戲,這是專門為具有六個月烘焙學習經驗的高中學生所設計的數位遊戲,讓學生能運用所學到的知識來解決NG麵包遊戲中的問題。本研究選取138位16.5歲的高中生參與每週二十分鐘,連續實施六週的NG麵包遊戲。學生必須在每次遊戲實驗前、後填寫電腦問卷(包含遊戲實驗前實施的後設認知、遊戲自我效能問卷及實驗後實施的遊戲焦慮、遊戲興趣問卷)。最後,回收119份有效問卷。本研究根據問卷資料,採用SPSS 22及 AMOS 21進行信、效度的檢驗以及運用時間序列分析來驗證情感因素的相關變化。研究的結果發現:第一、提高參與者的後設認知和遊戲自我效能,可以提升遊戲興趣和共變推理表現。第二、遊戲自我效能和後設認知在共變推理能力上,具有非常重要的作用。第三、除相關性研究外,從時間序列分析發現,隨著NG麵包遊戲的練習時間增加,遊戲焦慮會逐漸降低。研究結果還顯示,遊戲自我效能和後設認知在共變推理中有著非常重要的作用。 然而,共變推理是一種重要的推理能力,需要實踐以應對日常生活所面臨的問題,因此,NG麵包遊戲可以作為提高學生共變推理能力的一個例子。此外,更可為不同背景的各種專業學科開發共變推理遊戲。
Covariation reasoning is very important thinking skills in daily life. How students performed their covariation reasoning in relation to their gameplay self-efficacy and in gameplay interest that associated with their gameplay anxiety and metacognition were studied. In order to understanding the effect of gameplay, this study used a game, named “No Good (NG) Bread” which was designed for senior high school students who have taken a half year of baking courses to apply their knowledge to solve baking problems. Participants aged 16.5 years old and 138 students were invited to practice that game 20 minutes for 6 times. The questionnaire related to metacognition and gameplay self-efficacy were delivered before this experiment, questionnaires related to gameplay anxiety and gameplay interest were given after each trial of game playing. Finally, 119 were usefully returned. After collecting of the questionnaires, the reliability and validity of measurement were done by SPSS 22. AMOS 21 and time series analysis was used to verify the change of affective factors. The results of this study showed that increasing participants’ metacognition and gameplay self-efficacy would increase gameplay interest and performance (i.e., covariation reasoning performance). In addition to correlation study, this study also used time serious analysis and found that decrease gameplay anxiety as practice times increased in practicing NG Bread. The results also suggested that gameplay self-efficacy and metacognition play very important roles in a covariation reasoning. However, covariation reasoning is an important reasoning skill and need to be practiced to cope daily life, therefore, the NG-Bread can be taken as an example for those students to enhance their covariation skills. Moreover, the different context of covariational reasoning can be developed for various disciplines.
一、中文部分
張景媛(1990)。後設認知能力與資優教育。資優教育季刊。
邱皓政(2011)。結構方程模式:LISREL/SIMPLIS原理與應用(二版)。臺北市:雙葉書廊。
蔡志敏(2014)。資訊科技教育政策接受模式之建立-以教師 e 化教學自
我效能及教師使用新科技之態度為例(未出版之博士論文)。國立臺灣
師範大學,臺北市。
二、英文部分
Ackerman, R., Parush, A., Nassar, F., & Shtub, A. (2016). Metacognition and system usability: Incorporating metacognitive research paradigm into usability testing. Computers in Human Behavior, 54, 101-113.
Adkins, S. S. (2013). The worldwide market for self-paced eLearning products and services: 2011–2016 forecast and analysis. Monroe, WA: Ambient Insight. Retrieved from http://www.ambientinsight.com/Resources/Documents/AmbientInsight-2011-2016-Worldwide-Self-paced-eLearning-Market-Premium-Overview.pdf
Agaoglu, O. & Metin, N. (2015). A survey study on the 4th-8th graders in the science and arts centers who play violent PC games comparing to their school only peer group. Journal of Gifted Education Research, 3(2), 11-25.
Ainley, M., & Ainley, J. (2011). A cultural perspective on the structure of student interest in science. International Journal of Science Education, 33(1), 51-71. doi:10.1080/09500693.2010.518640
Ainley, M., Hidi, S., & Berndorff, D. (2002). Interest, learning and the psychological processes that mediate their relationship. Journal of Educational Psychology, 94(3), 545–561. doi:10.1037/00220663.94.3.545
Akca, F. (2011). The relationship between test anxiety and learned helplessness. Social Behavior and Personality, 39(1), 101-112. doi:10.2224/sbp.2011.39.1.101
Akpinar, Y. (1999). Bilgisayar destekli ogretim ve uygulamalar. Ani Yayinevi. Ankara.
Al-Harthy, I. S., Was, C. A., & Isaacson, R. M. (2010). Goals, efficacy and metacognitive self-regulation a path analysis. International Journal of Education, 2(1), 1. doi:10.5296/ije.v2i1.357
Alivernini, F., & Lucidi, F. (2011). Relationship between social context, self-efficacy, motivation, academic achievement, and intention to drop out of high school: A longitudinal study. The Journal of Educational Research, 104(4), 241-252. doi:10.1080/00220671003728062
Alsawaier, R. S. (2018). The effect of gamification on motivation and engagement. The International Journal of Information and Learning Technology, 35(1), 56-79.
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin. 103(3), 411-423. doi:10.1037//0033-2909.103.3.411
Ansari, T. L., & Derakshan, N. (2011). The neural correlates of cognitive effort in anxiety: Effects on processing efficiency. Biological Psychology, 86(3), 337 -348. doi:10.1016/j.biopsycho.2010.12.013
Apriliyanti, R., Warsono, W., & Mujiyanto, J. (2018). The correlation between interest, motivation, English self-concept and English speaking performance in nursing students. English Education Journal, 8(3), 11-20.
Arbuckle, J. L. (2003). AMOS 5.0 update to the AMOS user's guide. Chicago, IL: SPSS.
Ardies, J., De Maeyer, S., Gijbels, D., & van Keulen, H. (2015). Students attitudes towards technology. International Journal of Technology and Design Education, 25(1), 43-65. doi:10.1007/s10798-014-9268-x
Aufenanger, S. J. (2005). Relationships between mental skills and competitive anxiety interpretation in open skill and close skill athletes (Doctoral dissertation, Miami University). Retrieved from https://etd.ohiolink.edu/pg_10?0::NO:10:P10_ACCESSION_NUM:miami1117130981
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation for structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94.
Baker, L., & Brown, A. L. (1984). Metacognitive skills and reading. In P. D. Pearson (Ed.). Handbook of reading research, 1, pp. 353-394. New Jersey: Lawrence Erlbaum Associates.
Balakrishnan, V., & Gan, C. L. (2016). Students’ learning styles and their effects on the use of social media technology for learning. Telematics and Informatics, 33(3), 808-821. doi:10.1016/j.tele.2015.12.004
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. (1986). The explanatory and predictive scope of self-efficacy theory. Journal of Social and Clinical Psychology, 4(3), 359-373. doi:10.1521/jscp.1986.4.3.359
Bandura, A. (1997). Self -efficacy: The exercise of control. New York: Freeman.
Bandura, A. (2001). Social cognitive theory: An argentic perspective. Annual Review of Psychology, 52, 1-26. doi:10.1146/annurev.psych.52.1.1
Bayer, U. C., Gollwitzer, P. M., & Achtziger, A. (2010). Staying on track: Planned goal striving is protected from disruptive internal states. Journal of Experimental Social Psychology, 46(3), 505-514.
Bayirtepe, E., & Tuzun, H. (2007). The effects of game-based learning environments on students’ achievement and self-efficacy in a computer course. Hacettepe University Journal of Education, 33, 41-54.
Bechara, A., Damasio, H., Tranel, D., & Damasio, A. R. (1997). Deciding advantageously before knowing the advantageous strategy. Science, 275, 1293-1295. doi:10.1126/science.275.5304.1293
Beilock, S. L., Gunderson, E. A., Ramirez, G., & Levine, S. C. (2010). Female teachers’ math anxiety affects girls’ math achievement. Proceedings of the National Academy of Sciences, 107(5), 1860-1863.
Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological bulletin, 88(3), 588.
Bentler, P. M., & Wu, E. J. C. (1995). EQS for Macintosh user's guide. Encino, CA: Multivariate Software.
Berger, J. L., & Karabenick, S. A. (2011). Motivation and students’ use of learning strategies: Evidence of unidirectional effects in mathematics classrooms. Learning and Instruction, 21(3), 416-428.
Bergin, D. A. (2016). Social influences on interest. Educational Psychologist, 51(1), 7-22. doi:10.1080/00461520.2015.1133306
Blackwell, L. S., Trzesniewski, K. H., & Dweck, C. S. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. Child development, 78(1), 246-263. doi:10.1111/j.1467-8624.2007.00995.x
Bloom, B. (1956). Taxonomy of educational objectives. Handbook I: Cognitive domain. New York, NY: Longman.
Bishop, S. J. (2007). Neurocognitive mechanisms of anxiety: An integrative account. Trends in Cognitive Sciences, 11(7), 307 – 316. doi:10.1016/j.tics.2007.05.008
Bjork, R. A., Dunlosky, J., & Kornell, N. (2013). Self-regulated learning: Beliefs, techniques, and illusions. Annual Review of Psychology, 64, 417–444. doi:10.1146/annurev-psych-113011-143823.
Boddez, Y., De Houwer, J., & Beckers, T. (2017). The inferential reasoning theory of causal learning: Towards a multi-process propositional account. In M. R. Waldmann (Ed.), The Oxford handbook of causal reasoning (pp. 53). Oxford: Oxford University Press. doi:10.1093/oxfordhb/9780199399550.013.7
Boekaerts, M. (2006). Self‐regulation and effort investment. In E. Sigel & K. A. Renninger (Eds.), Handbook of child psychology: Child psychology in practice (Vol. 4, pp. 345-377). Hoboken, NJ: John Wiley & Sons.
Bollen, K. A., & Paxton, P. (2017). Two-Stage least squares. In R. E. Schumacker & G. A. Marcoulides (Eds.), Interaction and nonlinear effects in structural equation modeling (pp. 125-152). New Jersey: Lawrence Erlbaum Associates.
Bommer, C., Sullivan, S., Campbell, K., Ahola, Z., Agarwal, S., O'Rourke, A., ... & Liepert, A. E. (2018). Pre-simulation orientation for medical trainees: An approach to decrease anxiety and improve confidence and performance. The American Journal of Surgery, 215(2), 266-271. doi: 10.1016/j.amjsurg.2017.09.038
Borkowski, J. G. (1992). Metacognitive theory: A framework for teaching literacy, writing, and math skills. Journal of Learning Disabilities, 25(4), 253-257. doi:10.1177/002221949202500406
Borkowski, J. G., Carr, M., Rellinger, E., & Pressley, M. (1990). Self-regulated cognition: Interdependence of metacognition, attributions, and self-esteem. Dimensions of Thinking and Cognitive Instruction, 1, 53-92.
Borkowski, J. G., & Kurtz, B. E. (1987). Metacognition and executive control. Westport, CT: Ablex Publishing.
Borkowski, J. G., Milstead, M., & Hale, C. (1988). Components of children’s metamemory: Implications for strategy generalization. In F. E. Weiner & M. Perlmutter (Eds.), Memory development: Universal changes and individual differences (pp. 73-100). New Jersey: Lawrence Erlbaum Associates.
Borkowski, J. G., Weyhing, R. S., & Turner, L. A. (1986). Attributional retraining and the teaching of strategies. Exceptional Children, 53(2), 130-137. doi:10.1177/001440298605300205
Bottino, R. M, Ferlino, L., Ott, M. & Travella, M. (2006). Developing strategic and reasoning abilities with computer games at primary school level. Computers & Education, 49(4), 1272-1286.
Bradley, B. P., Mogg, K., Falla, S. J., & Hamilton, L. R. (1998). Attentional bias for threatening facial expressions in anxiety: Manipulation of stimulus duration. Cognition & Emotion, 12(6), 737–753. doi:10.1080/026999398379411
Bradley, B. P., Mogg, K., & Millar, N. H. (2000). Covert and overt orienting of attention to emotional faces in anxiety. Cognition & Emotion, 14(6), 789–808. doi:10.1080/02699930050156636
Brick, N., MacIntyre, T., & Campbell, M. (2015). Metacognitive processes in the self-regulation of performance in elite endurance runners. Psychology of Sport and Exercise, 19, 1-9.
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. doi:10.1016/j.psychsport.2015.02.003
Brown, A. L. (1978). Knowing when, where, and how to remember: A Problem of Metacognition. In R. Glaser (Ed.), Advances in instructional psychology (Vol. 1, pp.77-165). New Jersey: Lawrence Erlbaum Associates.
Brown, E. (2016). Obama outlines $4 billion “Computer Science for All” education plan. Washington Post. Retrieved from https://www.washingtonpost.com/local/ education/obama-outlines-4-billion-computer-sciencefor-all-education-plan/2016/01/29/3ad40da2-c6d9-11e5-9693-933a4d31bcc8_story. html.
Busoniu, L., Babuska, R., De Schutter, B., & Ernst, D. (2010). Reinforcement learning and dynamic programming using function approximators (Vol. 39). Boca Raton: CRC press. doi:10.1201/9781439821091
Byrne, B. M. (2016). Structural equation modeling with AMOS: Basic concepts, applications, and programming. New York, NY: Routledge.
Cassell, V. E., Beattie, S. J., & Lawrence, G. P. (2018). Changing performance pressure between training and competition influences action planning because of a reduction in the efficiency of action execution. Anxiety, Stress, & Coping, 31(1), 107-120. doi:10.1080/10615806.2017.1373389
Catena, A., Maldonado, A., Perales, J. C., & Cándido, A. (2008). Interaction between previous beliefs and cue predictive value in covariation-based causal induction. Acta Psychologica, 128(2), 339-349.
Caprara, G. V., Di Giunta, L., Eisenberg, N., Gerbino, M., Pastorelli, C., & Tramontano, C. (2008). Assessing regulatory emotional self-efficacy in three countries. Psychological Assessment, 20(3), 227-237. doi:10.1037/1040-3590.20.3.227
Cervelló, E., Santos-Rosa, F. J., Jiménez, R., Nerea, A., & García, T. (2010). Motivation and anxiety in tennis players. European Journal of Human Movement, 9, 141-161.
Chang, C. C., & Yang, F. Y. (2010). Exploring the cognitive loads of high-school students as they learn concepts in web-based environments. Computers & Education, 55(2), 673-680. doi:10.1016/j.compedu.2010.03.001
Chen, R. S., & Tsai, C. C. (2007). Gender differences in Taiwan university students' attitudes toward web-based learning. Cyberpsychology & Behavior, 10(5), 645-654. doi:10.1089/cpb.2007.9974
Cheng, W. N. K., Hardy, L. & Markland, D. (2009). Toward a three-dimensional conceptualization of performance anxiety: Rationale and initial measurement development. Psychology of Sport and Exercise, 10(2), 271-278. doi:10.1016/j.psychsport.2008.08.001
Chien, T. C. (2012). Computer self-efficacy and factors influencing e-learning effectiveness. European Journal of Training and Development, 36(7), 670-686. doi:10.1108/03090591211255539
Chou, C., Wu, H. C., & Chen, C. H. (2011). Re-visiting college students’ attitudes toward the Internet-based on a 6-T model: Gender and grade level difference. Computers & Education, 56(4), 939–947. doi:10.1016/j.compedu.2010.11.004
Choi, J. H., Ju, S., Kim, K. S., Kim, M., Kim, H. J., & Yu, M. (2015). A study on Korean university students' depression and anxiety. Indian Journal of Science and Technology, 8(S8), 1-9. doi:10.17485/ijst/2015/v8iS8/64705
Christofi, M., Kyrlitsias, C., Michael-Grigoriou, D., Anastasiadou, Z., Michaelidou, M., Papamichael, I., & Pieri, K. (2018). A tour in the archaeological site of choirokoitia using virtual reality: A learning performance and interest generation assessment. In M. Ioannides, J. Martins, R. Žarnić, & V. Lim (Eds.), Advances in digital cultural heritage (pp. 208-217). Switzerland: Springer, Cham.
Christy, K. R., & Fox, J. (2014). Leaderboards in a virtual classroom: A test of stereotype threat and social comparison explanations for women's math performamce. Computers & Education, 78, 66-77. doi:10.1016/j.compedu.2014.05.005
Clark, D. B., Tanner-Smith, E. E., & Killingsworth, S. S. (2016). Digital games, design, and learning: A systematic review and meta-analysis. Review of Educational Research, 86(1), 79-122. doi:10.3102/0034654315582065
Colley, A., & Comber, C. (2003). Age and gender differences in computer use and attitudes among secondary school students: what has changed? Educational Research, 45(2), 155-165. doi:10.1080/0013188032000103235
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 9(2), 189-211. doi:10.2307/249688
Connolly, T. M., Boyle, E. A., MacArthur, E., Hainey, T., & Boyle, J. M. (2012). A systematic literature review of empirical evidence on computer games and serious games. Computers & Education, 59(2), 661–686. doi:10.1016/j.compedu.2012.03.004
Craft, L. L., Magyar, T. M., Becker, B. J., & Feltz, D. L. (2003). The relationship between the Competitive State Anxiety Inventory-2 and sport performance: A meta-analysis. Journal of Sport and Exercise Psychology, 25(1), 44-65. doi:10.1123/jsep.25.1.44
Critcher, C. R., & Ferguson, M. J. (2011). Affect in the abstract: Abstract mindsets promote sensitivity to affect. Journal of Experimental Social Psychology, 47(6), 1185–1191. doi: 10.1016/j.jesp.2011.04.014
Cross, D. R., & Paris, S. G. (1988). Developmental and instructional analyses of children’s metacognition and reading comprehension. Journal of Educational Psychology, 80(2), 131-142. doi: 10.1037/00220663.80.2.131
Crouch, C. H., Wisittanawat, P., Cai, M., & Renninger, K. A. (2018). Life science students’ attitudes, interest, and performance in introductory physics for life sciences: An exploratory study. Physical Review Physics Education Research, 14(1), 010111. doi:10.1103/PhysRevPhysEducRes.14.010111
Csikszentmihalyi, M. (1975). Beyond boredom and anxiety. San Franciso: Jossey-Bass.
Csikszentmihalyi, M. (2014). Toward a psychology of optimal experience. In M. Csikszentmihalyi (Ed.), Flow and the foundations of positive psychology (pp. 209-226). Dordrecht: Springer. doi:10.1007/978-94-017-9088-8_14
Csikszentmihalyi, M., & Schneider, B. (2000). Becoming adult: How teenagers prepare for the world of work. New York, NY: Basic Books.
Davis, M. H., & McPartland, J. M. (2012). High school reform and student engagement. In S. Christenson, A. Reschly, & C. Wylie (Eds.), Handbook of research on student engagement (pp. 515-539). Boston, MA: Springer. doi:10.1007/978-1-4614-2018-7_25
Dindar, M., & Akbulut, Y. (2015). Role of self-efficacy and social appearance anxiety on gaming motivations of MMOFPS players. Computers & Education, 81, 26-34. doi:10.1016/j.compedu.2014.09.007
D’Mello, S. (2013). A selective meta-analysis on the relative incidence of discrete affective states during learning with technology. Journal of Educational Psychology, 105(4), 1082-1099. doi:10.1037/a0032674
Drigas, A., Ioannidou, R. E., Kokkalia, G., & Lytras, M. D. (2014). ICTs, mobile learning and social media to enhance learning for attention difficulties. Journal of Universal Computer Science, 20(10), 1499-1510.
Durndell, A., & Haag, Z. (2002). Computer self efficacy, computer anxiety, attitudes towards the Internet and reported experience with the Internet, by gender, in an East European sample. Computers in Human Behavior, 18(5), 521-535. doi:10.1016/S0747-5632(02)00006-7
Efklides, Α. (2011). Interactions of metacognition with motivation and affect in self-regulated learning: The MASRL model. Educational Psychologist, 46, 6–25. doi:10.1080/00461520.2011.538645.
Ehrman, M. (1996). An exploration of adult language learners’ motivation, self-efficacy, and anxiety. In R. Oxford (Ed.), Language learning motivation: The new century, pp. 81-103. Honolulu: University of Hawai’i, Second Language Teaching and Curriculum Center.
Elliot, A. J., & McGregor, H. A. (1999). Test anxiety and the hierarchical model of approach and avoidance achievement motivation. Journal of Educational Psychology, 76(4), 628-644. doi:10.1037//00223514.76.4.628
Elliot, A. J., McGregor, H. A., & Gable, S. (1999). Achievement goals, study strategies, and exam performance: A mediational analysis. Journal of Educational Psychology, 91(3), 549-563. doi:10.1037//00220663.91.3.549
Eseryel, D., Law, V., Ifenthaler, D., Ge, X., & Miller, R. (2014). An investigation of the interrelationships between motivation, engagement, and complex problem solving in game-based learning. Journal of Educational Technology & Society, 17(1).
Everson, H. T., Smodlaka, I., & Tobias, S. (1994). Exploring the relationship of test anxiety and metacognition on reading test performance: A cognitive analysis. Anxiety, Stress and Coping, 7(1), 85-96. doi:10.1080/10615809408248395
Eysenck, M. W., Derakshan, N., Santos, R., & Calvo, M. G. (2007). Anxiety and cognitive performance: Attentional control theory. Emotion, 7(2), 336 – 353. doi:10.1037/1528-3542.7.2.336
Fan, X., Thompson, B., & Wang, L. (1999). Effects of sample size, estimation methods, and model specification on structural equation modeling fit indexes. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 56-83. doi:10.1080/10705519909540119
Farber, M. (2015). Gamify your classroom: A field guide to game-based learning. NY: Peter Lang Publishers. doi:10.3726/978-1-4539-1459-5
Fields, J. A., Nichols, L. O., Martindale-Adams, J., Zuber, J., & Graney, M. (2012). Anxiety, social support, and physical health in a sample of spouses of OEF/OIF service members. Military Medicine, 177(12), 1492-1497. doi:10.7205/MILMED-D-12-00036
Flavell, J. C. (1976). Metacognitive aspects of problem solving. In L. B. Resnick (Ed.), The nature of intelligence. Hillsdale, NJ: Erlbaum.
Flavell, J. C. (1979). Metacognition and cognitive monitoring: a new area of cognitive developmental inquiry. American Psychologist, 34(10), 906-911. doi:10.1037//0003-066X.34.10.906
Flowerday, T., & Shell, D. F. (2015). Disentangling the effects of interest and choice on learning, engagement, and attitude. Learning and Individual Differences, 40, 134–140. doi:10.1016/j.lindif.2015.05.003
Fokides, E. (2018). Digital educational games and mathematics. Results of a case study in primary school settings. Education and Information Technologies, 23(2), 851-867. doi:10.1007/s10639-017-9639-5
Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of marketing research, 18(3), 382-388. doi:10.2307/3150980
Garrison, D. R., & Akyol, Z. (2013). The community of inquiry theoretical framework. In M. G. Moore (Ed.), Handbook of distance education (3rd ed., pp. 104–120). NY: Routledge. doi:10.4324/9780203803738.ch7
Gee, J. P. (2016). Foreword. In C. L. Selfe, G. E. Hawisher, & D. Van Ittersum (Eds.), Gaming lives in the twenty-first century: Literate connections (pp. ix-xiii). NY: Palgrave Macmillan. doi:10.1057/9780230601765
Ghanbari, S., & Soltanzadeh, V. (2016). The mediating role of emotional intelligence in the relationship between self-efficacy of research and academic achievement motivation. Journal of Educational Measurement and Evaluation Studies Summer, 6(14), 41- 67.
Giannakos, M. N. (2013). Enjoy and learn with educational games: Examining factors affecting learning performance. Computers & Education, 68, 429–439. doi:0.1016/j.compedu.2013.06.005
Glynn, M. A., & Webster, J. (1993). Refining the nomological net of the Adult Playfulness Scale: Personality, motivational, and attitudinal correlates for highly intelligent adults. Psychological Reports, 72(3), 1023-1026. doi:10.2466/pr0.1993.72.3.1023
Goldstein, J. (2012). Play in children's development, health and well-being. Brussels: Toy Industries of Europe.
Gomila, T., & Calvo, P. (2008). Directions for an embodied cognitive science: Toward an integrated approach. In T. Gomila & P. Calvo (Eds.), Handbook of cognitive science: An embodied approach (pp. 1-25). Singapore: Elsevier. doi:10.1016/B978-0-08-046616-3.00001-3
Gottfried, A. E. (1985). Academic intrinsic motivation in elementary and junior high school students. Journal of Educational Psychology, 77(6), 631–645
doi:10.1037/0022-0663.77.6.631
Grigg, S., Perera, H. N., McIlveen, P., & Svetleff, Z. (2018). Relations among math self efficacy, interest, intentions, and achievement: A social cognitive perspective. Contemporary Educational Psychology, 53, 73-86. doi:10.1016/j.cedpsych.2018.01.007
Groff, J., McCall, J., Darvasi, P., & Gilbert, Z. (2016). In K. Schrier (Ed.), Learning, education and games: Bringing games into educational Contexts, 2, pp.19-40. Pittsburgh, PA: Carnegie Mellon.
Gui, R., Huang, W., Wu, N., & Huang, L. (2017). E-purchase intention of sustainable innovation in management srategies. International Journal of Engineering Innovation & Research, 6(2).
Gunes, F. (2015). Game-based learning approach. Turkish Studies, 10(11), 773-786.
Gunderson, E. A., Park, D., Maloney, E. A., Beilock, S. L., & Levine, S. C. (2018). Reciprocal relations among motivational frameworks, math anxiety, and math achievement in early elementary school. Journal of Cognition and Development, 19(1), 21-46.
Guthrie, J. T., Wigfield, A., & You, W. (2012). Instructional contexts for engagement and achievement in reading. In S. Christenson, A. Reschly, & C. Wylie (Eds.), Handbook of research on student engagement, pp. 601-634. Boston, MA: Springer.
Hacker, D. J. (2017). The role of metacognition in learning via serious games. In R. Zheng, & M. K. Gardner (Eds.), Handbook of research on serious games for educational applications, pp. 19-40. USA: IGI Global.
Hacker, D. J., Bol, L., & Bahbahani, K. (2008). Explaining calibration accuracy in classroom contexts: The effects of incentives, reflection, and explanatory style. Metacognition and Learning, 3, 101–121. doi: 10.1007/s11409-008- 9021-5.
Hacker, D. J., Dunlosky, J., & Graesser, A. C. (Eds.). (2009). Handbook of metacognition in education. New York, NY: Routledge.
Hackbarth, G., Grover, V., & Yi, M. Y. (2003). Computer playfulness and anxiety: Positive and negative mediators of the system experience effect on perceived ease of use. Information and Management, 40, 221-232.
Hahn, S. (2018). Researching the gender divide of digital games. Acta Ludica-International Journal of Game Studies, 2(1), 7-25.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2013). Multivariate data analysis (7th ed.). New Jersey: Prentice Hall.
Hair, J.F., Hult, G.T.M., Ringle, C.M., Sarstedt, M. (2017). A Primer on partial least squares structural equation modeling (2nd ed.). Thousand Oaks, CA: Sage.
Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414-433. doi:10.1007/s11747-011-0261-6
Hair, J. F., William, C. B., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis. Upper Saddle River, NJ: Pearson University Press.
Hamari, J., Sjöklint, M., & Ukkonen, A. (2016). The sharing economy: Why people participate in collaborative consumption. Journal of the Association for Information Science and Technology, 67(9), 2047–2059. doi:10.1002/asi.23552
Hanus, M. D., & Fox, J. (2015). Assessing the effects of gamification in the classroom: A longitudinal study on intrinsic motivation, social comparison, satisfaction, effort, and academic performance. Computers & Education, 80, 152-161. doi: 10.1016/j. compedu.2014.08.019
Harackiewicz, J. M., Durik, A. M., Barron, K. E., Linnenbrink-Garcia, L., & Tauer, J. M. (2008). The role of achievement goals in the development of interest: Reciprocal relations between achievement goals, interest, and performance. Journal of Educational Psychology, 100(1), 105-122. doi:10.1037/0022-0663.100.1.105
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
Hauser, R., Paul, R., & Bradley, J. (2012). Computer self-efficacy, anxiety, and learning in online versus face to face medium. Journal of Information Technology Education: Research, 11, 141-154. doi:10.28945/1633
Helle, L., Laakkonen, E., Tuijula, T., & Vermunt, J. D. (2013). The developmental trajectory of perceived self‐regulation, personal interest, and general achievement throughout high school: A longitudinal study. British Journal of Educational Psychology, 83(2), 252-266. doi:10.1111/bjep.12014
Hembree, R. (1988). Correlates, causes, effects, and treatment of test anxiety. Review of Educaional Reseach, 58, 47-77.
doi:10.3102/00346543058001047
Henderson, R., Deane, F., & Ward, M. (1995). Occupational differences in computer related anxiety: Implications for the implementation of a computer related patient management information system. Behavior and Information Technology, 14(1), 23-31. doi:10.1080/01449299508914622
Henschel, S., & Roick, T. (2017). Relationships of mathematics performance, control and value beliefs with cognitive and affective math anxiety. Learning and Individual Differences, 55, 97-107. doi:10.1016/j.lindif.2017.03.009
Ho, H. Z., Senturk, D., Lam, A. G., Zimmer, J. M., Hong, S., Okamoto, Y., ... & Wang, C. P. (2000). The affective and cognitive dimensions of math anxiety: A cross-national study. Journal for Research in Mathematics Education, 362-379.
Hidi, S. (2001). Interest, reading, and learning: Theoretical and practical considerations. Educational Psychology Review, 13(3), 191-209. doi:10.1023/A:1016667621114
Hidi, S., & Renninger, A. (2006). The four-phase model of interest development. Educational Psychologist, 41(2), 111–127. doi:10.1207/s15326985ep4102_4
Hong, J. C., Hwang, M. Y., Liu, M. C., Ho, H. Y., & Chen, Y. L. (2014). Using a “prediction–observation–explanation” inquiry model to enhance student interest and intention to continue science learning predicted by their Internet cognitive, failure. Computers & Education, 72, 110-120. doi:10.1016/j.compedu.2013.10.004
Hong, J. C., Hwang, M. Y., Tai, K. H., & Lin, P. C. (2015). Self-efficacy relevant to competitive anxiety and gameplay interest in the one-on-one competition setting. Educational Technology Research and Development, 63(5), 791-807. doi:10.1007/s11423-015-9389-2
Hong, J. C., Hwang, M. Y.*, Liu, Y. T., Lin, P. H., & Chen, Y. L. (2016a). The role of pre-game learning attitude in the prediction to competitive anxiety, perceived utility of pre-game learning of game and gameplay interest. Interactive Learning Environment, 24(1), 239-251. doi:10.1080/10494820.2013.841263
Hong, J. C., Hwang, M. Y., Szeto, E., Tsai, C. R., Kuo, Y. C., & Hsu, W. Y. (2016b). Internet cognitive failure relevant to self-efficacy, learning interest, and satisfaction with social media learning. Computers in Human Behavior, 55, 214-222. doi:10.1016/j.chb.2015.09.010
Hong, J. C., Lu, C. C. Wang, J. L., Liao, S., Wu, M. R., Hwang, M. Y., & Lin, P. S. (2013). Gender and prior science achievement affect categorization on a procedural learning task. Thinking Skills and Creativity, 8, 92 – 101. doi:10.1016/j.tsc.2012.07.005
Hong, J. C., Pei, Y. C., Hsiao, Feng, S., & Pei. S. L., (2012). Computer self-efficacy, competitive anxiety and flow state: Escaping from firing online Game. The Turkish Online Journal of Educational Technology, 11(3), 70-76. Retrieved from http://eric.ed.gov/?id=EJ989200
Hu, L., & P. M. Bentler (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1-55
Huang, Y. M., Huang, S. H., & Wu, T. T. (2014). Embedding diagnostic mechanisms in a digital game for learning mathematics. Educational Technology Research and Development, 62(2), 187-207. doi:10.1007/s11423-013-9315-4
Hui, E. C. M., & Bao, H. (2013). The logic behind conflicts in land acquisitions in contemporary China: A framework based upon game theory. Land Use Policy, 30(1), 373-380. doi:10.1016/j.landusepol.2012.04.001
Huizinga, J. (2017). Homo ludens: Oyunun toplumsal islevi uzerine bir deneme (6. basim, Cev. M. A. Kilicbay). İstanbul: Ayrinti.
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 & Education, 60(1), 254-263. doi:10.1016/j.compedu.2012.06.014
Hwang, M. Y., Hong, J. C., Hsu, T. F., & Chen, Y. J. (2011, November). The relation between students' anxiety and interest in playing an online game. In Games Innovation Conference (IGIC), 2011 IEEE International (pp. 37-39). IEEE. doi:10.1109/IGIC.2011.6114852
Ibrahim, S., & Almoslim, H. A. (2016). State anxiety and self-efficacy among track and field low and high performers. Indian Journal of Science and Technology, 9(7). doi:10.17485/ijst/2016/v9i7/81884
Isaacson, R. M., & Was, C. A. (2010). Believing you’re correct vs. knowing you’re correct: A Significant difference? The Researcher, 23, 1-12.
Jackson, L. A., Ervin, K. S., Gardner, P. D., & Schmitt, N. (2001). Gender and the Internet: Women communicating and men searching. Sex Roles, 44(5-6), 363-379. doi:10.1023/A:1010937901821
Jansen, M., Scherer, R., & Schroeders, U. (2015). Students' self-concept and self-efficacy in the sciences: Differential relations to antecedents and educational outcomes. Contemporary Educational Psychology, 41, 13-24. doi:10.1016/j.cedpsych.2014.11.002
Jerusalem, M. & Schwarzer, R. (1992). Self-efficacy as a resource factor in stress appraisal processes. Self-efficacy: Thought control of action, 195-213.
Jiang, Y., Song, J., Lee, M., & Bong, M. (2014). Self-efficacy and achievement goals as motivational links between perceived contexts and achievement. Educational Psychology, 34(1), 92-117. doi:10.1080/01443410.2013.863831
Jin, Y. X., & Dewaele, J. M. (2018). The effect of positive orientation and perceived social support on foreign language classroom anxiety. System, 74, 149-157.
Johnson, R. D. (2011). Gender differences in e-learning: Communication, social presence, and learning outcomes. Journal of Organizational and End User Computing (JOEUC), 23(1), 79-94.
Jöreskog, K. G., & Sörbom, D. (1996). LISREL 8 user’s reference guide. Uppsala, Sweden: Scientific Software International.
Jurik, V., Gröschner, A., & Seidel, T. (2013). How student characteristics affect girls' and boys' verbal engagement in physics instruction. Learning and Instruction, 23, 33-42. doi:10.1016/j.learninstruc.2012.09.002
Kapp, K.M. (2012). Games, gamification, and the quest for learner engagement. Training and Development, 66(6), 64-68.
Karamustafaoğlu, O., & Kaya, M. (2017). Eğitsel oyunlarla “yansıma ve aynalar” konusunun öğretimi: Yansımalı koşu örneği. Journal of Inquiry Based Activities, 3(2), 41-49.
Karsten, R., Mitra, A., & Schmidt, D. (2012). Computer self-efficacy: A meta-analysis. Journal of Organizational and End User Computing, 24(4), 54–80. doi:10.4018/joeuc.2012100104
Kashy, D.A., & Kenny, D.A. (2011). Dyadic data analysis using multilevel modeling. In J. Hox, & J. K. Roberts (Eds.), Handbook of advanced multilevel analysis (pp. 343-378). New York, NY: Routledge.
Kay, R. H. (2009). Examining gender differences in attitudes toward interactive classroom communications systems (ICCS). Computers & Education, 52(4), 730-740. doi:10.1016/j.compedu.2008.11.015
Kaye, L. K., & Pennington, C. R. (2016). “Girls can't play”: The effects of stereotype threat on females' gaming performance. Computers in Human Behavior, 59, 202-209. doi:10.1016/j.chb.2016.02.020
Kaye, L. K., Pennington, C. R., & McCann, J. J. (2018). Do casual gaming environments evoke stereotype threat? Examining the effects of explicit priming and avatar gender. Computers in Human Behavior, 78, 142-150. doi:10.1016/j.chb.2017.09.031
Ke, F. (2016). Designing and integrating purposeful learning in game play: A systematic review. Educational Technology Research and Development, 64(2), 219-244. doi:10.1007/s11423-015-9418-1
Ke F., Shute V. (2015) Design of game-based stealth assessment and learning support. In C.Loh, Y. Sheng, D. Ifenthaler (Eds.), Serious games analytics (pp.301-318). Advances in game-based learning. New York, NY: Springer, Cham
Kenny, D. A. (2006). Series editor’s note. In T. A. Brown (ED.), Confirmatory factor analysis for applied research (pp. ix-x). New York, NY: Guilford.
Kesici, S., Sahin, I., & Akturk, A. O. (2009). Analysis of cognitive learning strategies and computer attitudes, according to college students’ gender and locus of control. Computers in Human Behavior, 25(2), 529-534. doi:10.1016/j.chb.2008.11.004
Khalatbari, J., Ghorbanshirodi, S., Akhshabi, M., Hamzehpour, T., & Esmaeilpour, M. (2011). The effectiveness of the behavioral-cognitive therapy on the reduction of the rate of the depression and anxiety of the infertile women of the Rasht city. Indian Journal of Science and Technology, 4(11), 1578-1582.
Koklu, O. & Jakubowski, E. (2010). From interpretations to graphical representations: A Case study investigation of covariational reasoning. Eurasian Journal of Educational Research, 40, 151–170.
Koslowski, B. (1996). Theory and evidence. Cambridge. MA: The MIT Press.
Koslowski, B. (2012). Scientific reasoning: Explanation, confirmation bias, and scientific practice. In G. J. Feist & M. E. Gorman (Eds.), Handbook of the psychology of science (pp. 151-192). New York, NY: Springer.
Koivisto, J., & Hamari, J. (2014). Demographic differences in perceived benefits from gamification. Computers in Human Behavior, 35, 179-188. doi:10.1016/j.chb.2014.03.007
Kiili, K. (2005). Digital game-based learning: Towards an experiential gaming model. The Internet and Higher Education, 8(1), 13-24. doi:10.1016/j.iheduc.2004.12.001
Kim, H., Lee, E. K., & Park, S. Y. (2015). Critical thinking disposition, self-efficacy, and stress of Korean nursing students. Indian Journal of Science and Technology, 8(18), 1-5. doi:10.17485/ijst/2015/v8i18/76710
Kingsley, T. L., & Grabner‐Hagen, M. M. (2015). Gamification. Journal of Adolescent & Adult Literacy, 59(1), 51-61. doi:10.1002/jaal.426
Kitsantas, A., Cheema, J., & Ware, H. W. (2011). Mathematics achievement: The role of homework and self-efficacy beliefs. Journal of Advanced Academics, 22, 310–339. doi:10.1177/1932202X1102200206
Kizilcec, R. F., Pérez-Sanagustín, M., & Maldonado, J. J. (2017). Self-regulated learning strategies predict learner behavior and goal attainment in Massive Open Online Courses. Computers & Education, 104, 18-33. doi:10.1016/j.compedu.2016.10.001.
Kline, R. B. (2005). Principles and practice of structural equation modeling (2nd ed.). New York, NY: Guilford.
Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). New York, NY: The Guilford Press.
Krapp, A. (1999). Interest, motivation and learning: An educational-psychological perspective. European Journal of Psychology of Education, 14(1), 23-40. doi:10.1007/BF03173109
Kurtz, B. E., & Borkowski, J. G. (1987). Development of strategic skills in impulsive and reflective children: A longitudinal study of metacognition. Journal of Experimental Child Psychology, 43, 129-148.
doi:10.1016/0022-0965(87)90055-5
Labroo, A. A., & Pocheptsova, A. (2016). Metacognition and consumer judgment: Fluency is pleasant but disfluency ignites interest. Current Opinion in Psychology, 10, 154-159. doi:10.1016/j.copsyc.2016.01.008
Lagnado, D. A., & Sloman, S. (2004). The advantage of timely intervention. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30(4), 856-876. doi:10.1037/0278-7393.30.4.856
Lan, Y. J., Chen, N. S., Li, P., & Grant, S. (2015). Embodied cognition and language learning in virtual environments. Educational Technology Research and Development, 63(5), 639–644. doi:10.1007/s11423-015-9401-x
Law, E. L. C., & Sun, X. (2012). Evaluating user experience of adaptive digital educational games with Activity Theory. International Journal of Human-Computer Studies, 70(7), 478-497. doi:10.1016/j.ijhcs.2012.01.007
Lawrence, G. P., Khan, M. A., & Hardy, L. (2013). The effect of state anxiety on the online and offline control of fast target directed movements. Psychological Research, 77(4), 422-433. doi:10.1007/s00426-012-0440-1
Leaning, M. (2015). A study of the use of games and gamification to enhance student engagement, experience and achievement on a theory-based course of an undergraduate media degree. Journal of Media Practice, 16(2), 155-170. doi:10.1080/14682 753.2015.1041807
Lee, J. E. R., Nass, C. I., & Bailenson, J. N. (2014). Does the mask govern the mind?: Effects of arbitrary gender representation on quantitative task performance in avatar-represented virtual groups. Cyberpsychology, Behavior, and Social Networking, 17(4), 248-254. doi:10.1089/cyber.2013.0358
Lee, W., Lee, M. J., & Bong, M. (2014). Testing interest and self-efficacy as predictors of academic self-regulation and achievement. Contemporary Educational Psychology, 39(2), 86–99.
Lent, R. W., Brown, S. D., & Hackett, G. (1994). Toward a unifying social cognitive theory of career and academic interest, choice, and performance. Journal of Vocational Behavior, 45(1), 79–122. doi:10.1006/jvbe.1994.1027
Lent, R. W., Larkin, K. C., & Brown, S. D. (1989). Relation of self-efficacy to inventoried vocational interests. Journal of Vocational Behavior, 34(3), 279-288. doi:10.1016/0001-8791(89)90020-1
Liao, C. C., Chang, W. C., & Chan, T. W. (2018). The effects of participation, performance, and interest in a game‐based writing environment. Journal of Computer Assisted Learning, 34(3), 211-222.
Lieberman, J. N. (1965). Playfulness and divergent thinking: An investigation of their relationship at the kindergarten level. Journal of Genetic Psychology, 107(2), 219-224. doi:10.1080/00221325.1965.10533661
Liew, T. W., & Su-Mae, T. (2016). The effects of positive and negative mood on cognition and motivation in multimedia learning environment. Journal of Educational Technology & Society, 19(2), 104-115.
Lin, L., Atkinson, R. K., Savenye, W. C., & Nelson, B. C. (2016). Effects of visual cues and self-explanation prompts: Empirical evidence in a multimedia environment. Interactive Learning Environments, 24(4), 799-813. doi:10.1080/10494820.2014.924531
Loehlin, J. C. (2004). Latent variable models: An introduction to factor, path, and structural equation analysis (4th ed.). Mahwah, NJ: Lawrence Erlbaum.
Lomax, R. G., & Schumacker, R. E. (2004). A beginner's guide to structural equation modeling. Psychology Press.
Love, S., Kannis-Dymand, L., & Lovell, G. P. (2018). Metacognitions in Triathletes: Associations with attention, state anxiety, and relative performance. Journal of Applied Sport Psychology, 30(4), 421-436.
Lowrie, T., & Jorgensen, R. (2011). Gender differences in students’ mathematics game playing. Computers & Education, 57(4), 2244-2248. doi:10.1016/j.compedu.2011.06.010
Ludgate, H., Becker, S.A., & Johnson, L. (2015). Engaged learning. In
J. M. Spector (Ed.), The sage encyclopedia of educational technology (pp. 269-272). Thousand Oaks, CA: Sage. doi:10.4135/9781483346397.n118
MacCallum, R. C., Browne, M.W., and Sugawara, H.M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1(2), 130-149. doi:10.1037/1082-989X.1.2.130
MacCallum, R. C., & Hong, S. (1997). Power analysis in covariance structure modeling using GFI and AGFI. Multivariate Behavioral Research, 32(2), 193-210.
Madhavan, P., & Phillips, R. R. (2010). Effects of computer self-efficacy and system reliability on user interaction with decision support systems. Computers in Human Behavior, 26(2), 199–204. doi:10.1016/j.chb.2009.10.005
Madison, B. L., Carlson, M., Oehrtman, M., & Tallman, M. (2015). Conceptual pre-calculus: Strengthening students' quantitative and covariational
reasoning. Mathematics Teacher, 109(1), 54-59. doi:10.5951/mathteacher.109.1.0054
Magliano, J. P., McCrudden, M. T., Rouet, J. F., & Sabatini, J. (2018). The modern reader: Should changes to how we read affect research and theory? In M. F. Schober, D. N. Rapp, & M. A. Britt (Eds.), Handbook of discourse processes (2nd ed., pp. 343–361). New York, NY: Routledge.
Maloney, E. A., Ramirez, G., Gunderson, E. A., Levine, S. C., & Beilock, S. L. (2015). Intergenerational effects of parents' math anxiety on children's math achievement and anxiety. Psychological Science, 26, 1480-1488. doi:10.1177/0956797615592630.
Marsh, H. W., Balla, J. R., & Hau, K. T. (1996). An evaluation of incremental fit indices: A clarification of mathematical and empirical properties. In G. A. Marcoulides & R. E. Schumacker (Eds.). Advanced structural equation: Issues and techniques (pp. 315-353). Psychology Press.
Martens, R., Burton, D., Vealey, R. S., Bump, L. A., & Smith, D. E. (1990). Development and validation of the competitive state anxiety inventory-2. Competitive Anxiety in Sport, 117-190.
Masicampo, E. J., & Baumeister, R. F. (2011). Unfulfilled goals interfere with tasks that require executive functions. Journal of Experimental Social Psychology, 47(2), 300–311. doi:10.1016/j.jesp.2010.10.011
McInnes, K and Birdsey, N (2014). Understanding play: The perceptions of children, adolescents, parents and teachers. In: L. A. Barnett (Ed.), Play of individuals and societies. Inter-Disciplinary Press, Oxford.
McKenzie, C. R. M., & Mikkelsen, L. A. (2007). A Bayesian view of covariation assessment. Cognitive Psychology, 54(1), 33-61. doi:10.1016/j.cogpsych.2006.04.004
Mehrabian, A. (1996). Pleasure-arousal-dominance: A general framework for describing and measuring individual differences in temperament. Current Psychology, 14(4), 261-292. doi:10.1007/BF02686918
Meluso, A., Zheng, M., Spires, H. A., & Lester, J. (2012). Enhancing 5th graders’ science kcontent knowledge and self-efficacy through game-based learning. Computers & Education, 59(2), 497-504. doi:10.1016/j.compedu.2011.12.019
Mitchell, M. (1993). Situational interest: Its multifaceted structure in the secondary school mathematics classroom. Journal of Educational Psychology, 85(3), 424-436. doi:10.1037/0022-0663.85.3.424
Molina, J., Sandín, B. and Chorot, P. (2014). Sensibilidad a la ansiedad y presión psicológica: Efectos sobre el rendimiento deportivo en adolescentes. Cuadernos de Psicología del Deporte, 14(1), 45-54. doi:10.4321/S1578-84232014000100006
Moon, J.W., & Kim ,Y.G. (2001). Extending the TAM for a world-wide-web context. Information & Management, 38, 217-230. doi:10.1016/S0378-7206(00)00061-6
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
Morony, S., Kleitman, S., Lee, Y. P., & Stankov, L. (2013). Predicting achievement: Confidence vs. self-efficacy, anxiety, and self-concept in confucian and european countries. International Journal of Educational Research, 58, 79-96. doi:10.1016/j.ijer.2012.11.002
Morris, L. W., Davis, M. A., & Hutchings, C. H. (1981). Cognitive and emotional components of anxiety: Literature review and a revised worry-emotionality scale. Journal of Educational Psychology, 73(4), 541–555. doi:10.1037//0022-0663.73.4.541
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, 430-445.
Muris, P. (2002). Relationships between self-efficacy and symptoms of anxiety disorders and depression in a normal adolescent sample. Personality and Individual Differences, 32(2), 337-348.
Murphy, S. (Ed.). (2012). The Oxford handbook of sport and performance
psychology. Oxford University Press. doi:10.1093/oxfordhb/9780199731763.001.0001
Nedim Bal, P., & Metan, H. (2016). The effect of computer addiction management psycho-training program on 9th grade students. Abant Izzet Baysal University Journal of Faculty of Education, 16(1), 62-74.
Negretti, R., & Kuteeva, M. (2011). Fostering metacognitive genre awareness in L2 academic reading and writing: A case study of pre-service English teachers. Journal of Second Language Writing, 20(2), 95-110. doi:10.1016/j.jslw.2011.02.002
Nicaise, M. (1995). Treating test anxiety: A review of three approaches. Teacher Education and Practice, 11(1), 65-81.
Nie, Y., Lau, S., & Liau, A. K. (2011). Role of academic self-efficacy in moderating the relation between task importance and test anxiety. Learning and Individual Differences, 21(6), 736-741. doi:10.1016/j.lindif.2011.09.005
Ong, C. S., & Lai, J. Y. (2006). Gender differences in perceptions and relationship among dominants of e-learning acceptance. Computers in Human Behavior, 22(5), 816-829. doi:10.1016/j.chb.2004.03.006
Ortiz de Guinea, A., & Webster, J. (2011). Are we talking about the task or the computer? An examination of the associated domains of task-specific and computer self -efficacies. Computers in Human Behavior, 27(2), 978–987. doi:10.1016/j.chb.2010.12.002
Owens, M., Stevenson, J., Hadwin, J., & Norgate, R. (2012). Anxiety and depression in academic performance: An exploration of the mediating factors of worry and working memory. School Psychology International, 33(4), 433-449. doi:10.1177/0143034311427433
Pajares, F. (1996). Self-efficacy beliefs in academic settings. Review of Educational Research, 66(4), 543-578. doi:10.3102/00346543066004543
Papadakis, S. (2018). The use of computer games in classroom environment. International Journal of Teaching and Case Studies, 9(1), 1-25.
Park, B., Plass, J. L., & Brünken, R. (2014). Cognitive and affective processes in multimedia learning. Learning and Instruction, 29, 125 – 127. doi:10.1016/j.learninstruc.2013.05.005
Parker, P. D., Marsh, H. W., Ciarrochi, J., Marshall, S., & Abduljabbar, A. S. (2014). Juxtaposing math self-efficacy and self-concept as predictors of long-term achievement outcomes. Educational Psychology, 34(1), 29-48.
Pekrun, R., Cusack, A., Murayama, K., Elliot, A., & Thomas, K. (2014). The power of antici-pated feedback: Effects on students' achievement goals and achievement emotions. Learning and Instruction, 29, 115-124. doi:10.1016/j.learninstruc.2013.09.022.
Perales, J. C., Catena, A., Cándido, A., & Maldonado, A. (2017). Rules of causal judgment: Mapping statistical information onto causal beliefs. In M. R. Waldmann (Ed.), The Oxford handbook of causal reasoning (pp. 29-51). Oxford: Oxford University Press.
Phan, H. P. (2015). Maximizing academic success: Introducing the concept of optimized functioning. Education, 135(4), 439-456.
Phan, H. P., & Ngu, B. H. (2018). An examination of social and psychological influences on academic learning: a focus on self-esteem, social
relationships, and personal interest. Social Psychology of Education, 21(1), 51-73. doi:10.1007/s11218-017-9407-9
Potosky, D. (2002). A field study of computer efficacy beliefs as an outcome of training: The role of computer playfulness, computer knowledge, and performance during training. Computers in Human Behavior, 18(3), 241-255. doi:10.1016/S0747-5632(01)00050-4
Prensky, M. (2001). Digital game-based learning: Fun, play and games. What makes games engaging? New York, NY: McGraw-Hill.
Prensky, M. (2002). The motivation of gameplay: The real twenty‐first century learning revolution. On the Horizon, 10(1), 5-11. doi:10.1108/10748120210431349
Prensky, M. (2003). Digital game-based learning. Computers in Entertainment (CIE), 1(1), 21. doi:10.1145/950566.950596
Rachmann, S. J. (2013). Anxiety (3rd ed.). Psychology Press.
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
Ratan, R., & Sah, Y. J. (2015). Leveling up on stereotype threat: The role of avatar customization and avatar embodiment. Computers in Human Behavior, 50, 367-374. doi:10.1016/j.chb.2015.04.010
Raykov, T., and Marcoulides, G.A. (2006). A first course in structural equation modeling (2nd ed.). NJ: Lawrence Erlbaum Associates.
Renninger, K. A., & Hidi, S. (2015). The power of interest for motivation and engagement. New York, NY: Routledge. doi:10.4324/9781315771045
Renninger, K. A., Hidi, S., & Krapp, A. (Eds.). (2014). The role of interest in learning and development. Psychology Press.
Richardson, M., Abraham, C. & Bond, R. (2012). Psychological correlates of university students’ academic performance: A systematic review and meta-analysis. Psychological Bulletin, 138, 353–387. doi:10.1037/a0026838
Richter, G., Raban, D. R., & Rafaeli, S. (2015). Studying gamification: The effect of rewards and incentives on motivation. In T. Reiners, L. Wood (Eds.), Gamification in education and business (pp. 21-46). Switzerland: Springer, Cham.
Riggs, M. L., & Knight, P. A. (1994). The impact of perceived group success-failure on motivational beliefs and attitudes: a causal model. Journal of Applied Psychology, 79,755–766. doi:10.1037/0021-9010.79.5.755
Ritchie, L., & Williamon, A. (2013). Measuring musical self-regulation: Linking processes, skills, and beliefs. Journal of Education and Training Studies, 1(1), 106-117.
Rodríguez-Aflecht, G., Brezovszky, B., Pongsakdi, N., Jaakkola, T., Hannula-Sormunen, M. M., McMullen, J., & Lehtinen, E. (2015). Number Navigation Game (NNG): Experience and motivational effects. In J. Torbeyns, E. Lehtinen, & J. Elen (Eds.), Describing and studying domain-specific serious games (pp. 171-189). New York, NY: Springer, Cham. doi:10.1007/978-3-319-20276-1_11
Roeser, R. W., & Peck, S. C. (2009). An education in awareness: Self, motivation, and self-regulated learning in contemplative perspective. Educational Psychologist, 44(2), 119-136. doi:10.1080/00461520902832376
Rogaten, J., Moneta, G. B., & Spada, M. M. (2013). Academic performance as a function of approaches to studying and affect in studying. Journal of Happiness Studies, 14(6), 1751-1763. doi:10.1007/s10902-012-9408-5
Roick, T., Gölitz, D., & Hasselhorn, M. (2013). Affektive Komponenten der Mathematikkompetenz: Die Mathematikangst-Ratingskala für vierte bis sechste Klassen (MARS4–6). Diagnostik mathematischer Kompetenzen, 205-224.
Roick, J., & Ringeisen, T. (2017). Self-efficacy, test anxiety, and academic success: A longitudinal validation. International Journal of Educational Research, 83, 84-93.
Rottman, B. M., & Keil, F. C. (2012). Causal structure learning over time: Observations and interventions. Cognitive Psychology, 64(1-2), 93-125. doi:10.1016/j.cogpsych.2011.10.003
Ruiz-Ariza, A., Casuso, R. A., Suarez-Manzano, S., & Martínez-López, E. J. (2018). Effect of augmented reality game Pokémon GO on cognitive performance and emotional intelligence in adolescent young. Computers & Education, 116, 49-63. doi:10.1016/j.compedu.2017.09.002
Sansone, C., Smith, J. L., Thoman, D. B., & MacNamara, A. (2012). Regulating interest when learning online: Potential motivation and performance trade-offs. The Internet and Higher Education, 15(3), 141-149.doi:10.1016/j.iheduc.2011.10.004
Sáinz, M., & Eccles, J. (2012). Self-concept of computer and math ability: Gender implications across time and within ICT studies. Journal of Vocational Behavior, 80(2), 486-499. doi:10.1016/j.jvb.2011.08.005
Sáinz, M., & López-Sáez, M. (2010). Gender differences in computer attitudes and the choice of technology-related occupations in a sample of secondary students in Spain. Computers & Education, 54(2), 578-587. doi:10.1016/j.compedu.2009.09.007
Schaie, K. W., Dutta, R., & Willis, S. L. (1991). Relationship between rigidity-flexibility and cognitive abilities in adulthood. Psychology and Aging, 6(3), 371-383. doi:10.1037//0882-7974.6.3.371
Schönfeld, P., Brailovskaia, J., Bieda, A., Zhang, X. C., & Margraf, J. (2016). The effects of daily stress on positive and negative mental health: Mediation through self-efficacy. International Journal of Clinical and Health Psychology, 16(1), 1-10. doi:10.1016/j.ijchp.2015.08.005
Schottenbauer, M. A., Rodriguez, B. F., Glass, C. R., & Arnkoff, D. B. (2004). Computers, anxiety, and gender: an analysis of reactions to the Y2K computer problem. Computers in Human Behavior, 20(1), 67-83. doi:10.1016/S0747-5632(03)00044-X
Schraw, G. & Dennison, R. S. (1994). Assessing metacognitive awareness. Contemporary Educational Psychology, 19, 460-475. doi:10.1006/ceps.1994.1033
Schrier, K. (2014). (Ed.) Learning, education and games: Curricular and design considerations, 1. Pittsburgh, PA: ETC Press.
Schrier, K. (2016). (Ed.) Learning, education and games: Bringing games into educational contexts, 2. Pittsburgh, PA: ETC Press.
Schrier, K. (2017a). Designing learning with citizen science and games. Emerging Learning Design Journal, 4, 19-26. Retrieved from https://www.researchgate.net/profile/Karen_Schrier/publication/ 321609223_Designing_Learning_with_Citizen_Science_and_Games/links/5a28e833a6fdcc8e8671cb01/Designing-Learning-with-Citizen-Science-and-Games.pdf
Schrier, K. (2017b). Designing games for moral learning and knowledge building. Games and Culture, 1-38. Retrieved from http://journals.sagepub.com/doi/abs/10.1177/1555412017711514
Schunk, D. H. (1989). Self-efficacy and achievement behaviors. Educational Psychology Review, 1(3), 173-208. doi:10.1007/BF01320134
Schunk, D. H. (2007). Learning theories: An educational perspective. New York, NY: Prentice Hall.
Seaborn, K., & Fels, D. I. (2015). Gamification in theory and action: A survey. International Journal of Human-Computer studies, 74, 14-31. doi:10.1016/j.ijhcs.2014.09.006
Segars, A. H., & Grover, V. (1998). Strategic information systems planning success: An investigation of the construct and its measurement. MIS Quarterly, 22(2) 139-163.
Shi, Z., Gao, X., & Zhou, R. (2014). Emotional working memory capacity in test anxiety. Learning and Individual Differences, 32, 178-183. doi:10.1016/j.lindif.2014.03.011
Shu, Q., Tu, Q., & Wang, K. (2011). The impact of computer self-efficacy and technology dependence on computer-related technostress: A social cognitive theory perspective. International Journal of Human-Computer Interaction, 27(10), 923-939. doi:10.1080/10447318.2011.555313
Simmering, M. J., Posey, C., & Piccoli, G. (2009). Computer self‐efficacy and motivation to learn in a self‐directed online course. Decision Sciences Journal of Innovative Education, 7(1), 99-121. doi:10.1111/j.1540-4609.2008.00207.x
Simsek, A. (2011). The relationship between computer anxiety and computer self-efficacy. Online Submission, 2(3), 177-187.
Sloman, S. A., & Lagnado, D. (2015). Causality in thought. Annual Review of Psychology, 66, 223-247. doi:10.1146/annurev-psych-010814-015135
Snow, C. E., Burns, M. S., & Griffin, P. (1998). Preventing reading difficulties in young children: Committee on the prevention of reading difficulties in young children. Washington, DC: National Research Council.
Sobol-Shikler, T. (2011). Automatic inference of complex affective states. Computer Speech & Language, 25(1), 45-62. doi:10.1016/j.csl.2009.12.005
Spencer, S. J., Logel, C., & Davies, P. G. (2016). Stereotype threat. Annual Review of Psychology, 67, 415-437. doi:10.1146/annurev-psych-073115-103235
Spielberger, C. D. (1966). Theory and research on anxiety. Anxiety and Behavior, 1(3), 3-20. doi:10.1016/B978-1-4832-3131-0.50006-8
Spielberger, C. D. (Ed.). (2013). Anxiety: Current trends in theory and research. UK: Elsevier.
Squire, K. (2011). Video games and learning: Teaching and participatory culture in the digital age. New York, NY: Teachers College Press.
Stankov, L., Lee, J., Wenshu, L., & Hogan, D. J. (2012). Confidence: a better predictor of academic achievement than self-efficacy, self-concept and anxiety? Learning and Individual Differences, 22(6), 747-758. doi:10.1016/j.lindif.2012.05.013
Starbuck, W. H., & Webster, J. (1991). When is play productive? Accounting, Management and Information Technologies, 1(1), 71-90. doi:10.1016/0959-8022(91)90013-5
Steinkuehler, C., Squire, K., & Barab, S. (Eds.). (2012). Games, learning, and society: Learning and meaning in the digital age. Cambridge, UK: Cambridge University Press.
Stern, C., & West, T. V. (2014). Circumventing anxiety during interpersonal encounters to promote interest in contact: An implementation intention approach. Journal of Experimental Social Psychology, 50, 82-93. doi:10.1016/j.jesp.2013.09.008
Stewart, O., & Tei, E. (1983). Some implications of metacognition for reading instruction. Journal of Reading, 27(1), 36-43.
Stieler-Hunt, C., & Jones, C. M. (2015). A model for exploring the usefulness of games for classrooms. In DiGRA Conference.
Suliman, W. A., & Halabi, J. (2007). Critical thinking, self-esteem, and state anxiety of nursing students. Nurse Education Today, 27(2), 162-168. doi:10.1016/j.nedt.2006.04.008
Sun, J. C. Y., & Rueda, R. (2012). Situational interest, computer self-efficacy and self-regulation: Their impact on student engagement in distance education. British Journal of Educational Technology, 43(2), 191–204. doi:10.1111/j.1467-8535.2010.01157.x
Taraban, R., & Logue, E. (2012). Academic factors that affect undergraduate research experiences. Journal of Educational Psychology, 104(2), 499-514. doi:10.1037/a0026851
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(1), 381-396. doi:10.2307/4132314
Thompson, J. (2014). On writing notes in the field: Interrogating positionality, emotion, participation and ethics. McGill Journal of Education, 49(1), 247-254. doi:10.7202/1025781ar
Tiyuri, A., Saberi, B., Miri, M., Shahrestanaki, E., Bayat, B. B., & Salehiniya, H. (2018). Research self-efficacy and its relationship with academic performance in postgraduate students of Tehran University of Medical Sciences in 2016. Journal of Education and Health Promotion, 7.
Torkzadeh, G., Chang, J. C., Demirhan, D. (2006). A contingency model of computer and internet self-efficacy. Information & Management, 43(4), 541-550. doi:10.1016/j.im.2006.02.001
Trautwein, U., Lüdtke, O., Nagy, N., Lenski, A., Niggli, A., & Schnyder, I.(2015). Using individual interest and conscientiousness to predict academic effort: Additive, synergistic, or compensatory effects? Journal of Personality and Social Psychology, 109(1), 142–162. doi:10.1037/pspp0000034
Tsai, Y. H., Lin, C. H., Hong, J. C., & Tai, K. H. (2018). The effects of
metacognition on online learning interest and continuance to learn with MOOCs. Computers & Education, 121, 18-29.
Ullén, F., de Manzano, Ö., Almeida, R., Magnusson, P. K., Pedersen, N. L., Nakamura, J., ... & Madison, G. (2012). Proneness for psychological flow in everyday life: Associations with personality and intelligence. Personality and Individual Differences, 52(2), 167-172. doi:10.1016/j.paid.2011.10.003
Usher, E. (2016). Personal capability beliefs. In L. Corno & E. M. Anderman (Eds.), Handbook of educational psychology (3rd ed., pp. 146–159). New York, NY: Routledge.
Usher, E. L., & Pajares, F. (2009). Sources of self-efficacy in mathematics: A validation study. Contemporary Educational Psychology, 34(1), 89–101. doi:10.1016/j.cedpsych.2008.09.002
Van Damme, J., De Fraine, B., Van Landeghem, G., Opdenakker, M.-C., & Onghena, P. (2002). A new study on educational effectiveness in secondary schools in Flanders: An introduction. School Effectiveness and School Improvement, 13(4), 383–397. doi:10.1076/sesi.13.4.383.10285
Van Landeghem, H., & Vanmaele, H. (2002). Robust planning: a new paradigm for demand chain planning. Journal of Operations Management, 20(6), 769-783. doi:10.1016/S0272-6963(02)00039-6
Van Rheenen, D. (2012). A century of historical change in the game preferences of American children. Journal of American Folklore, 125(498), 411-443. doi:10.5406/jamerfolk.125.498.0411
Vermeulen, L., Castellar, E. N., Janssen, D., Calvi, L., & Van Looy, J. (2016). Playing under threat. Examining stereotype threat in femal game players. Computers in Human Behavior, 57, 377-387. doi:10.1016/j.chb.2015.12.042
Vogel, D. L., Wade, N., & Haake, S. (2006). Measuring the self-stigma associated with seeking psychological help. Journal of Counseling Psychology, 53, 325-337. doi:10.1037/0022-0167.53.3.325
Vos, N., Van Der Meijden, H., & Denessen, E. (2011). Effects of constructing versus playing an educational game on student motivation and deep learning strategy use. Computers & Edcuation, 56(1), 127-137.doi:10.1016/j.compedu.2010.08.013
Vukovic, R. K., Kieffer, M. J., Bailey, S. P., & Harari, R. R. (2013). Mathematics anxiety in young children: Concurrent and longitudinal associations with mathematical performance. Contemporary Educational Psychology, 38(1), 1-10. doi:10.1016/j.cedpsych.2012.09.001.
Walkington, C., Petrosino, A., & Sherman, M. (2013). Supporting algebraic reasoning through personalized story scenarios: How situational understanding mediates performance. Mathematical Thinking and Learning, 15(2), 89-120. doi:10.1080/10986065.2013.770717
Wayne, N. L., & Miller, G. A. (2018). Impact of gender, organized athletics, and video gaming on driving skills in novice drivers. PLOS ONE, 13(1). | Retrieved from https://doi.org/10.1371/journal.pone.0190885
Webster, J., & Martocchio, J. J. (1992). Microcomputer playfulness: Development of a measure with workplace implications. Management Information Systems Quarterly, 16(2), 201-226. doi:10.2307/249576
Webster, J., Trevino, L.K., & Ryan, L. (1993). The dimensionality and correlates of flow in human-computer interaction. Computers in Human Behavior, 9(4), 411–426. doi:10.1016/0747-5632(93)90032-N
Weinberg, R. S., & Gould, D. (2014). Foundations of sport and exercise psychology, 6E. Human Kinetics.
Weiner, B. (2013). Human motivation. Hove, UK: Psychology Press.
Wells, A. (2013a). Advances in metacognitive therapy. International Journal of Cognitive Therapy, 6(2), 186–201. doi:10.1521/ijct.2013.6.2.186.
Wells, A. (2013b). Cognitive therapy of anxiety disorders: A practice manual and conceptual guide. New York, NY: Wiley.
Wells, A., & Matthews, G. (1996). Modelling cognition in emotional disorder: The S-REF model. Behaviour Research and Therapy, 34(11-12), 881-888. doi:10.1016/S0005-7967(96)00050-2
Wigfield, A., & Cambria, J. (2010). Expectancy-value theory: Retrospective and prospective. In T. C. Urdan & S. A. Karabenick (Eds.), The decade ahead: Theoretical perspectives on motivation and achievement (pp. 35-70). Emerald Group Publishing Limited. doi:10.1108/S0749-7423(2010)000016A005
Wigfield, A., Cambria, J., & Eccles, J. S. (2012). Motivation in education. The Oxford handbook of human motivation, 463-478. doi:10.1093/oxfordhb/9780195399820.013.0026
Woszczynski, A. B., Roth, P. L., & Segars, A. H. (2002). Exploring the theoretical foundations of playfulness in computer interactions. Computers in Human Behavior, 18(4), 369-388. doi:10.1016/S0747-5632(01)00058-9
Wouters, P., van Nimwegen, C., van Oostendorp, H., & van der Spek, E. D. (2013). A meta-analysis of the cognitive and motivational effects of serious games. Journal of Educational Psychology, 105(2), 249-295. doi:10.1037/a0031311
Wouters, P., & van Oostendorp, H. (2017). Overview of instructional techniques to facilitate learning and motivation of serious games. In P. Wouters & H. van Oostendorp (Eds.), Instructional techniques to facilitate learning and motivation of serious games (pp. 1-16). New York, NY: Springer, Cham. doi:10.1007/978-3-319-39298-1_1
Yang, J. C., Lin, M. Y. D., & Chen, S. Y. (2018). Effects of anxiety levels on learning performance and gaming performance in digital game‐based learning. Journal of Computer Assisted Learning, 34(3), 324-334.
Yang, J. C., Quadir, B., & Chen, N. S. (2016). Effects of the Badge Mechanism on Self-Efficacy and Learning Performance in a Game-Based English Learning Environment. Journal of Educational Computing Research, 54(3), 371-394. doi:10.1177/0735633115620433
Yau, H. K., & Cheng, A. L. F. (2012). Gender difference of confidence in using technology for learning. Journal of Technology Studies, 38(2), 74-79. doi:10.21061/jots.v38i2.a.2
You, S., Dang, M., & Lim, S. A. (2016). Effects of student perceptions of teachers’motivational behavior on reading, english, and mathematics achievement: The mediating role of domain specific self-efficacy and intrinsic motivation. Child & Youth Care Forum, 45(2), 221-240. doi:10.1007/s10566-015-9326-x
Yu, R., & Singh, K. (2018). Teacher support, instructional practices, student motivation, and mathematics achievement in high school. The Journal of Educational Research, 111(1), 81-94. doi:10.1080/00220671.2016.1204260
Zimmerman, B. J. (2000). Attaining self-regulation: A social cognitive perspective. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 13-39). San Diego: Academic Press.
doi:10.1016/B978-012109890-2/50031-7