研究生: |
陳思穎 Chen, Szu-Ying |
---|---|
論文名稱: |
教師虛擬實境科技接受度與人格特質、認知彈性之研究 A Study on the Correlation between Teachers' Personality Traits and Cognitive Flexibility towards Teachers'Acceptance of Virtual Reality |
指導教授: |
郝永崴
Hao, Yung-Wei |
口試委員: |
張芳全
Chang, Fang-Chuan 趙貞怡 Chao, Jen-Yi 郝永崴 Hao, Yung-wei |
口試日期: | 2023/07/27 |
學位類別: |
碩士 Master |
系所名稱: |
課程與教學研究所 Graduate Institute of Curriculum and Instruction |
論文出版年: | 2023 |
畢業學年度: | 111 |
語文別: | 中文 |
論文頁數: | 186 |
中文關鍵詞: | 科技接受模式 、虛擬實境教學 、人格特質 、認知彈性 |
英文關鍵詞: | Technology Acceptance Model, Virtual Reality, Personality traits, Cognitive Flexibility |
研究方法: | 調查研究 |
DOI URL: | http://doi.org/10.6345/NTNU202301653 |
論文種類: | 學術論文 |
相關次數: | 點閱:179 下載:29 |
分享至: |
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
本研究旨在在於瞭解中學階段教師的人格特質、認知彈性及面對新興科技——虛擬實境的接受度之關係,試圖了解中學階段教師人格特質、認知彈性及虛擬實境科技接受度之現況,分析不同背景變項對於此三個變項的差異情形、探討三個變項之間的相關、預測及因果關係。
本研究採滾雪球抽樣,以自編之「中學教師人格特質、認知彈性及虛擬實境科技接受度之研究調查問卷」實施調查,共計回收171份,有效問卷為164份,有效問卷回收率為96%,其中又以曾參與虛擬實境相關研習的教師153份所得資料以描述性統計、單因子變異數、皮爾森績差相關、多元逐步回歸、結構方程等方法加以分析,獲得以下結論:
一、中等學校教師的「人格特質」組成較傾向「外向」、「直覺」、「情感」及「判斷」構面;中等學校教師在「虛擬實境科技接受度」及「認知彈性」之現況具有正面傾向。
二、中等學校教師在「虛擬實境科技接受度」中,以「知覺有用性」構面較高,「使用態度」次之,「知覺易用性」的科技接受度構面最低。
三、不同背景變項之對「教師人格特質」、「認知彈性」與「虛擬實境科技接受度」具有差異。
四、中學教師「人格特質」與教師「認知彈性」呈現正相關;中學教師「人格特質」之「直覺」、「情感」及「感知」與教師「虛擬實境科技接受度」呈現正相關;教師「認知彈性」與教師「虛擬實境科技接受度」呈現正相關。
五、教師「人格特質」、「認知彈性」對「虛擬實境科技接受度」具有顯著預測力。
六、教師「認知彈性」為教師「人格特質」與教師「虛擬實境科技接受度」呈現正相關的中介變項。
綜合以上,本研究提供了有關中學教師人格特質、認知彈性和虛擬實境科技接受度之間關聯的重要洞察,對於推進教育科技應用和教師專業發展具有實際價值。
The study aims to investigate the current status of personality traits, cognitive flexibility, and acceptance of virtual reality technology among middle school teachers, analyze the differences in these three variables based on different background variables, explore the correlations, predictions, and forecast among these variables.
The method adopted in this study was Snowball sampling, with 171 copies were collected. The valid questionnaire surveys were 164 copies, and valid return ratio was 96.0%. Among them, 153 teachers who had participated in virtual reality-related workshop were analyzed by descriptive statistics, one-way ANOVA, Pearson correlation coefficient, multiple regression, as well as structure equation modeling analysis. The conclusions are as follows:
1.Middle school teachers tend to exhibit "extraversion", "intuition", "feeling", and "judging" in their personality traits. They generally have a positive inclination towards acceptance of virtual reality technology and cognitive flexibility.
2.Among the dimensions of acceptance of virtual reality technology, middle school teachers ranked higher in "perceived usefulness", followed by "behavioral intention ", and "perceived ease of use" had the lowest level of acceptance.
3.Different background variables showed differences in the personality traits, cognitive flexibility, and acceptance of virtual reality technology among teachers.
4.There is a positive correlation between teachers' personality traits and cognitive flexibility. The dimensions of "intuition", "feeling", and "perceiving" in teachers' personality traits are positively correlated with their acceptance of virtual reality technology. Cognitive flexibility is also positively correlated with the acceptance of virtual reality technology among teachers.
5.Teachers' personality traits and cognitive flexibility have significant predictive power for the acceptance of virtual reality technology.
6.Teachers' cognitive flexibility acts as a mediator between teachers' personality traits and their acceptance of virtual reality technology.
In summary, this research provides valuable insights into the correlation between high school teachers' personality traits, cognitive flexibility, and the acceptance of virtual reality technology. These findings hold practical significance in advancing the application of educational technology and professional development for teachers.
任秋貴(2017)。以科技接受模式探討國中教師使用LINE即時通訊軟體為職場溝通媒介之研究-以高雄市為例。義守大學資訊管理學系碩士論文。取自 https://hdl.handle.net/11296/q3n3h9
周士雄(2010)。國中小教師應用互動式電子白板教學之創新接受度與科技接受度之相關研究—以屏東縣e化示範點學校為例。國立屏東教育大學教育科技研究所碩士論文。取自https://hdl.handle.net/11296/33dy4u
林杰(2022)。兼任學務行政職務教師人格特質、工作壓力與因應策略之研究-以臺北市及新北市立國民中學為例。國立臺灣師範大學公民教育與活動領導學系碩士論文。取自https://hdl.handle.net/11296/e3u29b。
林盈伶(2006)。人格特質、學習型態對學習成效之影響。朝陽科技大學企業管理系碩士班碩士論文。取自https://hdl.handle.net/11296/f9xs7q
林香君(2013)。情緒與認知彈性。國立成功大學行為醫學研究所碩士論文。取自https://hdl.handle.net/11296/2nhzre
金育文(2009)。兼任行政職務教師人格特質、工作壓力與因應策略之研究-以臺北市立國民中學為例。國立臺灣師範大學政治學研究所在職進修碩士班碩士論文。取自https://hdl.handle.net/11296/795s99。
高浩軒(2017)。虛擬實境對未來教育的影響。國立臺北教育大學數位科技設計學系碩士論文。取自 https://hdl.handle.net/11296/3hgxzg
張春興(2002)。教育心理學。東華書局。
梁朝雲、張弘毅(1999)。網路虛擬實境與情境學習的整合應用。教育資料與圖書館學,36(2),197-224。
陳俊諺(2020)。彰化縣國民小學教師人格特質與教學熱忱關係之研究。國立暨南國際大學教育政策與行政學系碩士論文。取自 https://hdl.handle.net/11296/fj6x49
陳鳳敏(2014)。教師認知彈性、正向思考、工作投入、工作壓力與生涯承諾之相關研究。國立臺灣師範大學創造力發展碩士班碩士論文。取自 https://hdl.handle.net/11296/zd8v6s
彭楊盛(2010)。國小教師人格特質、生涯發展與幸福感之研究。大葉大學教育專業發展研究所碩士在職專班碩士論文。取自 https://hdl.handle.net/11296/dmqeqq
曾婉如(2015)。桃園市國小教師人格特質、人際關係對幸福感之影響。大葉大學休閒事業管理學系碩士在職專班碩士論文。取自 https://hdl.handle.net/11296/yjfnxv
游家興(2010)。公立國民中學學務主任人格特質、工作壓力與情緒管理之研究。國立彰化師範大學教育研究所碩士論文。取自 https://hdl.handle.net/11296/j76dm3
馮美珠(2007)。國小教師人格特質、生活壓力、因應策略與憂鬱傾向之相關研究。國立屏東教育大學心理輔導教育研究所碩士論文。取自https://hdl.handle.net/11296/ag6yk2
黃惠玲(2008)。國小女教師人格特質工作壓力與主觀幸福感之相關研究。國立新竹教育大學人資處輔導教學碩士班碩士論文。取自 https://hdl.handle.net/11296/2q9f47
黃雅琪(2010)。桃園縣國中教師人格特質、社會支持與幸福感之相關研究。銘傳大學教育研究所碩士在職專班碩士論文。取自 https://hdl.handle.net/11296/576fdp
楊淑雅(2013)。桃園縣公立國民中學教師人格特質、工作壓力與復原力關係之研究。中原大學教育研究所碩士論文。取自 https://hdl.handle.net/11296/732556
劉玉玲(2014)。數位原生與數位移民的網路科技運用。臺灣教育評論月刊,3(7),4-8。
蔣家唐 (1994) 。資優生的認知發展特質暨成功資優教師之教學風格研究。特殊教育學報,9,223-256。
鄭進寶(2016)。高雄市國中兼行政職教師人格特質、行政倫理與工作投入關係之研究。國立高雄師範大學教育學系碩士論文。取自 https://hdl.handle.net/11296/wqprzn
蕭靜文(2014)。人格特質、專業成長認同對工作滿意度之探討-以新北市參與心評教師培訓之國中小特殊教育教師為例。國立臺北教育大學教育經營與管理學系臺碩士論文。取自 https://hdl.handle.net/11296/j3v64b
韓繼成(2002)。國民中學訓導人員角色壓力、人格特質與工作滿意度的關係之研究。國立彰化師範大學教育研究所碩士論文。取自 https://hdl.handle.net/11296/wek457
Abich, J., Parker, J., Murphy, J.S., et al. (2021). A review of the evidence for training effectiveness with virtual reality technology. Virtual Reality, 25, 919–933. https://doi.org/10.1007/s10055-020-00498-8
Adams Becker, S., Cummins, M., Davis, A., Freeman, A., Hall Giesinger, C., & Ananthanarayanan, V. (2017). NMC Horizon Report: 2017 Higher Education Edition. Austin, Texas: The New Media Consortium.
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Action control (p. 11-39). Springer, Berlin, Heidelberg.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
Ajzen, I., & Fishbein, M. (1975). A Bayesian analysis of attribution processes. Psychological bulletin, 82(2), 261.
Ajzen, I., & Madden, T. J. (1986). Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control. Journal of experimental social psychology, 22(5), 453-474.
Alalwan, N., Cheng, L., Al-Samarraie, H., Yousef, R., Ibrahim Alzahrani, A., & Sarsam, S. M. (2020). Challenges and Prospects of Virtual Reality and Augmented Reality Utilization among Primary School Teachers: A Developing Country Perspective. Studies in Educational Evaluation, 66, (In-Press). [100876]. https://doi.org/10.1016/j.stueduc.2020.100876
Al-Ani, Mayyadah & Kasto, Nadia. (2018). The Acceptance of using Augmented Reality Technology in Teaching Programming.
Alexopoulou, A., Batsou, A., & Drigas, A. (2020). Mobiles and Cognition: The Associations Between Mobile Technology and Cognitive Flexibility. International Journal of Interactive Mobile Technologies, 14(03),146–156. https://doi.org/10.3991/ijim.v14i03.11233
Barbey, A. K., Colom, R., & Grafman, J. (2013). Architecture of cognitive flexibility revealed by lesion mapping. Neuroimage, 82, 547-554.
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.
Buela, S., &Joseph, M.C. (2015). Relationship between Personality and Teacher Effectiveness of High School Teachers. The International Journal of Indian Psychology, 3, 57-70. https://doi.org/10.25215/0301.117.
Burdea, G.C., & Coiffet, P. (2003). Virtual Reality Technology. Presence: Teleoperators & Virtual Environments, 12, 663-664.
Campbell, Colin & Landry, Oriane & Russo, Natalie & Flores, Heidi & Jacques, Sophie. (2013). Cognitive Flexibility Among Individuals With Down Syndrome: Assessing the Influence of Verbal and Nonverbal Abilities. American journal on intellectual and developmental disabilities, 118, 193-200. https://doi.org/10.1352/1944-7558-118.3.193.
Carrington, P. J., Scott, J., & Wasserman, S.(2005). Models and methods in social network analysis (Vol. 28). Cambridge university press.
Casey, J.E., Pennington, L.K., & Mireles, S.V. (2020). Technology Acceptance Model: Assessing Preservice Teachers’ Acceptance of Floor-Robots as a Useful Pedagogical Tool. Technology, Knowledge and Learning, 1-16.
Cattell, H. B., & Wallbrown, F. H. (1989). The 16PF: Personality in depth.
Cattell, R. B. (1946). Description and measurement of personality.
Clark, R. E. (1985). Confounding in educational computing research. Journal of educational computing research, 1(2), 137-148.
Cuhadaroglu, A. (2013). Predictors of cognitive flexibility. Cumhuriyet UluslararasıEgitim Dergisi, 2(1), 86–101.
Dajani, D. R., & Uddin, L. Q. (2015). Demystifying cognitive flexibility: Implications for clinical and developmental neuroscience. Trends in neurosciences, 38(9), 571-578.
Davis, F. (1989) Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13, 319-340.https://doi.org/10.2307/249008
Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems. Cambridge, MA, 17.
Dawson, P., & Guare, R. (2004). Executive skils in children and adolescents: A practical guide to assessment and intervention, NY: The Guilford Press.
Day, D. V., & Silverman, S. B. (1989). Personality and job performance: Evidence of incremental validity. Personnel Psychology, 42(1), 25-36
Dennis, J. P., & Vander Wal, J. S. (2010). The cognitive flexibility inventory: Instrument development and estimates of reliability and validity. Cognitive therapy and research, 34(3), 241-253. https://doi.org/10.1007/s10608-009-9276-4
Devaraj, S.; Easley, R.F.; Crant, J.M. (2008). Research note-how does personality matter? Relating the five factor model to technologyacceptance and use. Information Systems Research, 19, 93-105. https://doi.org/10.1287/isre.1070.0153
Dheer, R. J., & Lenartowicz, T. (2019). Cognitive flexibility: Impact on entrepreneurial intentions. Journal of Vocational Behavior, 115, 103-339.
Diamond, A., Barnett, W. S., Thomas, J., & Munro, S. (2007). Preschool program improves cognitive control. Science, 318(5855), 1387-1388.
Dlamini, R. & Mbatha, K. (2018). The discourse on ICT teacher professional development needs: The case of a South African teachers’ union. International Journal of Education and Development using ICT, 14(2),. The University of the West Indies, West Indies. Retrieved August 15, 2022 from https://www.learntechlib.org/p/184684/.
Dweck, C. S. (2007). Is math a gift? Beliefs that put females at risk. In S. J. Ceci & W. M. Williams (Eds.), Why aren't more women in science?: Top researchers debate the evidence (pp. 47–55). American Psychological Association. https://doi.org/10.1037/11546-004
Dweck, Carol S. (2006). Mindset: The New Psychology of Success. New York: Random House.
Elmqaddem, N. (2019). Augmented reality and virtual reality in education. Myth or reality?. International journal of emerging technologies in learning, 14(3).
Esen–aygun, H. (2018). The Relationship between Pre–Service Teachers’ Cognitive Flexibility and Interpersonal Problem Solving Skills . Eurasian Journal of Educational Research , 18 (77) , 105-128 . Retrieved from https://dergipark.org.tr/en/pub/ejer/issue/42545/512704
Fransson, Göran & Holmberg, Jörgen & Westelius, Claes. (2020). The challenges of using head mounted virtual reality in K-12 schools from a teacher perspective. Education and Information Technologies. 25. 1-22. https://doi.org/10.1007/s10639-020-10119-1.
Greening, T. (1998). Building the constructivist toolbox: An exploration of cognitive technologies. Educational Technology, 23-35.
Guilford, J. P. (1975). Factors and factors of personality. Psychological Bulletin, 82(5), 802–814. https://doi.org/10.1037/h0077101
Guriting, P. and Oly Ndubisi, N. (2006), Borneo online banking: evaluating customer perceptions and behavioural intention, Management Research News, Vol. 29 No. 1/2, pp. 6-15. https://doi.org/10.1108/01409170610645402
Hernández-Serrano, Julián & Choi, Ikseon & Jonassen, David. (2002). Integrating Constructivism and Learning Technologies, Instruction and Technology, 103-128. https://doi.org/10.1007/0-306-47584-7_7.
Hilgard, E. R., & Atkinson, R. (1969). The Developmental Viewpoint. The Child. Jerome Seidman, ed. New York: Holt, Rinehart and Winston, 36.
Hoffmann, B. O. B., & Ritchie, D. (1997). Using multimedia to overcome the problems with problem based learning. Instructional science, 25(2), 97-115.
Hofmann, W., Schmeichel, B. J., & Baddeley, A. D. (2012). Executive functions and self-regulation. Trends in Cognitive Sciences, 16(3), 174–180. https://doi.org/10.1016/j.tics.2012.01.006
Holland, D. D., & Piper, R. T. (2014). A technology integration education (TIE) model: Millennial preservice teachers' motivations about technological, pedagogical, and content knowledge (TPACK) competencies. Journal of Educational Computing Research, 51(3), 257-294.
Hong, J. C., Hwang, M. Y., Szeto, E., Tai, K. H., & Tsai, C. R.(2020). Undergraduate science students’ scientist–practitioner gap: the role of epistemic curiosity and cognitive flexibility. International Journal of Science and Mathematics Education. Retrieved from https:// doi.org/10.1007/s10763-020-10096-4
Hu, P., Clark, T., & Ma, W. (2003). Examining technology acceptance by school teachers: A longitudinal study. Information & Management, 41, 227-241. https://doi.org/10.1016/S0378-7206(03)00050-8.
Jelińska, Magdalena & Paradowski, Michał B. (2021). Teachers' Engagement in and Coping with Emergency Remote Instruction During COVID-19-Induced School Closures: A Multinational Contextual Perspective. Online Learning, 25, 303–328. https://doi.org/10.24059/olj.v25i1.2492
Johnco, C., Wuthrich, V. M., & Rapee, R. M. (2015). The impact of late-life anxiety and depression on cognitive flexibility and cognitive restructuring skill acquisition. Depression and Anxiety, 32, 754-762.
Jung, C. G. (1971). Personality types. In The portable Jung (pp. 178-272).
Kashdan, T. B., & Rottenberg, J. (2010). Psychological flexibility as a fundamental aspect of health. Clinical Psychology Review, 30(7), 865-878.
Kent, H., & Fisher, D. (1997). Associations between Teacher Personality and Classroom Environment. Journal of Educational Psychology, 89(3), 571-579.
Kilic, F., & Demir, Ö. (2012). Views of prospective classroom teachers regarding creating instructional environment based on cognitive coaching and cognitive flexibility. 1.
Koehler, M. J., & Mishra, P. (2005). What happens when teachers design educational technology? The development of technological pedagogical content knowledge. Journal of Educational Computing Research, 32(2), 131–152. doi:10.2190/0EW7-01WB-BKHL-QDY
Lanier, J. (1988). A vintage virtual reality interview.
Lave, J. (1988). Cognition in practice: Mind, mathematics and culture in everyday life. Cambridge University Press.
Lawrence, G. (2009). People types and tiger stripes: A practical guide to learning styles. Gainseville, FL: Center for Application of Psychological Type.
Lederer, A. L., Maupin, D. J., Sena, M. P., & Zhuang, Y. (2000). The Technology Acceptance Model and the World Wide Web. Decision Support Systems, 29, 269-282. http://dx.doi.org/10.1016/S0167-9236(00)00076-2
Majid, F., & Shamsudin, N. (2019). Identifying Factors Affecting Acceptance of Virtual Reality in Classrooms Based on Technology Acceptance Model (TAM). Asian Journal of University Education, 15, 51. https://doi.org/10.24191/ajue.v15i2.7556
Mandela, N. B., Krug, G. H., Dahlberg, E., Mercy, L. L., Zwi, J. A., Anthony Lozano, R., & World Health Organization. (2003). World report on violence and health. Geneva: World Health Organization.
Martin, M. M., & Rubin, R. B. (1995). A new measure of cognitive flexibility. Psychological Reports, 76(2), 623-626.
Meiran, N. (2010). Task switching: Mechanisms underlying rigid vs. flexible self-control. In K. N. Ochsner, R. R. Hassin, & Y. Trope (Eds.), Self-control in society, mind, and brain (pp. 202-220). New York, NY: Oxford University Press.
Middleton, T., & Boman, D. (1994). Simon Says: Using speech to perform tasks in virtual environments. In The Second Annual Conference on Virtual Reality and Persons with Disabilities.
Miles, S., Gnatt, I., Phillipou, A., & Nedeljkovic, M. (2020). Cognitive flexibility in acute anorexia nervosa and after recovery: A systematic review. Clinical Psychology Review, 81, 101905.
Mills, C. J. (2003). Characteristics of Effective Teachers of Gifted Students: Teacher Background and Personality Styles of Students. Gifted Child Quarterly, 47, 272-281.
Mumtaz, S. (2000). Factors affecting teachers' use of information and communications technology: A review of the literature. Journal of Information Technology for Teacher Education, 9(3), 319-342.
Murdock, K. W., Oddi, K. B., & Bridgett, D. J. (2013). Cognitive correlates of personality: Links between executive functioning and the big five personality traits. Journal of Individual Differences, 34(2), 97–104. https://doi.org/10.1027/1614-0001/a000104
Myers, I. B., McCaulley, M. H., Quenk, N. L., & Hammer, A. L. (1998). The MBTI® Manual: A Guide to the Development and Use of the Myers-Briggs Type Indicator. Palo Alto: Consulting Psychologists Press.
Odacı, H., & Cikrikci, Ö. (2019). Cognitive flexibility mediates the relationship between big five personality traits and life satisfaction. Applied Research in Quality of Life, 14(5), 1229–1246. https://doi.org/10.1007/s11482-018-9651-y
Özbek, V., Alnıaçık, Ü., Koc, F., Akkılıç, M. E., & Kaş, E. (2014). The impact of personality on technology acceptance: A study on smart phone users. Procedia-Social and Behavioral Sciences, 150, 541–551. https://doi.org/10.1016/j.sbspro.2014.09.073
Özen, F., & Üçüncü, A. S. (2022). Developing the critical thinking skill test for high school students: A validity and reliability study. International Journal of Psychology and Educational Studies, 9(2), 492-508. https://dx.doi.org/10.52380/ijpes.2022.9.2.752
Porter, C., & Donthu, N. (2006). Using the technology acceptance model to explain how attitudes determine Internet usage: The role of perceived access barriers and demographics. Journal of Business Research, 59(9), 999-1007.
Reid, J. B. (1999). The relationship among personality type, coping strategies, and burnout in elementary teachers. Journal of Psychological Type, 51, 22-33.
Ritter, S. M., Damian, R. I., Simonton, D. K., van Baaren, R. B., Strick, M., Derks, J., & Dijksterhuis, A. (2012). Diversifying experiences enhance cognitive flexibility. Journal of Experimental Social Psychology, 48(4), 961-964.
Rosen, P. A., & Kluemper, D. H. (2008). The impact of the Big Five personality traits on the acceptance of social networking websites. AMCIS 2008 Proceedings, 274.
Rushton, S., Mariano, J., & Wallace, T. (2012). Program Selection among Pre-Service Teachers: MBTI Profiles within a College of Education. Creative Education, 3, 16-23. https://doi.org/10.4236/ce.2012.31003.
Rushton, S., Knopp, T. Y., & Smith, R. L. (2006). Teacher of the Year Award Recipients' Myers-Briggs Personality Profiles: Identifying Teacher Effectiveness Profiles Toward Improved Student Outcomes. Journal of Psychological Type, 66(4), 23–34.
Rushton, S., Morgan, J., & Richard, M. (2007). Teacher's Myers-Briggs personality profiles: Identifying effective teacher personality traits. Teaching and Teacher Education, 23(4), 432-441.
Schultheis, M. T., & Rizzo, A. A. (2001). The application of virtual reality technology in rehabilitation. Rehabilitation Psychology, 46(3), 296–311. https://doi.org/10.1037/0090-5550.46.3.296
Sears, S., Kennedy, J., Kaye, J., & Gail, L. (1997). Myers-Briggs personality profiles of prospective educators. The Journal of Educational Research, 90, 195-202.
Smith, C. A., & Konik, J. (2021). Who is satisfied with life? Personality, cognitive flexibility, and life satisfaction. Current Psychology: A Journal for Diverse Perspectives on Diverse Psychological Issues, 41(12), 9019–9026. https://doi.org/10.1007/s12144-021-01359-6
Spiro, R. J. & Jehng, J. (1990). Cognitive flexibility and hypertext: Theory and technology for the nonlinear and multidimensional traversal of complex subject matter. In D. Nix & R. J. Spiro (Eds.), Cognition, education and multimedia: Exploring ideas in high technology (pp. 163-205). New Jersey: Lawrence Erlbaum Associates.
Spiro, R. J., Collins, B. P., & Ramchandran, A. R. (2008). Modes of Openness and Flexibility in Cognitive Flexibility Hypertext Learning Environments. In L. Tomei (Ed.), Online and Distance Learning: Concepts, Methodologies, Tools, and Applications (pp. 1903-1908). IGI Global. https://doi.org/10.4018/978-1-59904-935-9.ch152
Spiro, R., Vispoel, W., & Schmitz, J. G. (1987). Knowledge acquisition for application: Cognitive flexibility and transfer in complex content domains. New Jersey: Lawrence Erlbaum Associates.
Svendsen, G. B., Johnsen, J. K., Sorensen, L. A., & Vitterso, J. (2013). Personality and technology acceptance: The influence of personality factors on the core constructs of the technology acceptance model. Behavior & Information Technology, 32(4), 323-334.
Syed-Abdul, S., Malwade, S., Nursetyo, A. A., et al. (2019). Virtual reality among the elderly: A usefulness and acceptance study from Taiwan. BMC Geriatrics, 19, 223. https://doi.org/10.1186/s12877-019-1218-8
Vygotsky, L. (1978). Interaction between learning and development. Readings on the development of children, 23(3), 34-41.
Wilson, C., Nusbaum, A., Whitney, P., & Hinson, J. (2017). Age-differences in cognitive flexibility when overcoming a preexisting bias through feedback. Journal of Clinical and Experimental Neuropsychology, 40, 10. https://doi.org/1080/13803395.2017.1398311.
Withall, A., Harris, L. M., & Cumming, S. R. (2010). A longitudinal study of cognitive function in melancholic and non-melancholic subtypes of major depressive disorder. Journal of Affective Disorders, 123(1-3), 150-157.
Wobrock, T., Ecker, U.K., Scherk, H., Schneider-Axmann, T., Falkai, P., & Gruber, O. (2008). Cognitive impairment of executive function as a core symptom of schizophrenia. World Journal of Biological Psychiatry, 29, 1–10.