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Education and Information Technologies

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17-04-2020

Relationship between motivations, personality traits and intention to continue using MOOCs

Authors: Hend Abdullatif, J. Ángel Velázquez-Iturbide

Published in: Education and Information Technologies | Issue 5/2020

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Abstract

MOOCs represent an emerging model for delivering education services. Notwithstanding their potential, they suffer significant dropout rates, which have been attributed to the low motivation of the registered students. This research seeks to understand the variance in the levels of intention to continue using MOOCs (ICM) in relation to motivation (internal and external) and personality traits (agreeableness, extraversion, and conscientiousness). In this study, Structural Equation Modelling was applied to conduct an analysis of 212 professionals from Saudi Arabia who had used MOOCs in the previous three months. Internal motivations, but not the external ones, affect the ICM. Conscientiousness directly affects ICM and external motivation. Agreeableness affects the ICM with full mediation of internal motivations. Extraversion and agreeableness affect internal motivations. The main implication of this research is that, to use MOOCs in the future, different personalities need different motivations in their first use of them.

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Al-Qirim, N., Rouibah, K., Tarhini, A., Serhani, M. A., Yammahi, A. R., & Yammahi, M. A. (2018). Towards a personality understanding of information technology students and their IT learning in UAE university. Education and Information Technologies, 23(1), 29–40. https://doi.org/10.1007/s10639-017-9578-1.CrossRef

Alraimi, K. M., Zo, H., & Ciganek, A. P. (2015). Understanding the MOOCs continuance: The role of openness and reputation. Computers in Education, 80, 28–38. https://doi.org/10.1016/j.compedu.2014.08.006.CrossRef

Ashton, M. C., Lee, K., & Paunonen, S. V. (2002). What is the central feature of extraversion? Social attention versus reward sensitivity. Journal of Personality and Social Psychology, 83(1), 245–252. https://doi.org/10.1037/0022-3514.83.1.245.CrossRef

Blackwell, D., Leaman, C., Tramposch, R., Osborne, C., & Liss, M. (2017). Extraversion, neuroticism, attachment style and fear of missing out as predictors of social media use and addiction. Personality and Individual Differences, 116, 69–72.://doi.org/10.1016/J.PAID.2017.04.039.

Brahimi, T., & Sarirete, A. (2015). Learning outside the classroom through MOOCs. Computers in Human Behavior, 51, 604–609. https://doi.org/10.1016/j.chb.2015.03.013.CrossRef

Bratman, M. (1987). Intention, plans, and practical reason. Boston: Harvard Business School Press.

Bratt, C., Sidanius, J., Abrams, D., van der Toorn, J., Jost, J. T., & Chaikalis-Petritsis, V. (2011). Why men (and women) do and Don’t rebel. Personality and Social Psychology Bulletin, 38(2), 197–208. https://doi.org/10.1177/0146167211422544.CrossRef

Browne, M. W., & Cudeck, R. (1992). Alternative ways of assessing model fit. Sociological Methods & Research, 21(2), 230–258. https://doi.org/10.1177/0049124192021002005.CrossRef

Byrne, B. M. (1989). A primer of LISREL : Basic applications and programming for confirmatory factor analytic models (1st ed.). New York: Springer Verlag.CrossRef

Chamorro-Premuzic, T., & Furnham, A. (2003). Personality predicts academic performance: Evidence from two longitudinal university samples. Journal of Research in Personality, 37(4), 319–338. https://doi.org/10.1016/S0092-6566(02)00578-0.CrossRef

Chen, G., Davis, D., Hauff, C., & Houben, G.-J. (2016). On the impact of personality in massive open online learning. In Proceedings of the 2016 conference on user modeling adaptation and personalization - UMAP ‘16 (pp. 121–130). Halifax, NS, Canada: ACM Press. https://doi.org/10.1145/2930238.2930240.CrossRef

Deci, E. L., Koestner, R., & Ryan, R. M. (1999). A meta-analytic review of experiments examining the effects of extrinsic rewards on intrinsic motivation. Psychological Bulletin, 125(6), 627–668. https://doi.org/10.1037/0033-2909.125.6.627.CrossRef

Dečman, M. (2015). Modeling the acceptance of e-learning in mandatory environments of higher education: The influence of previous education and gender. Computers in Human Behavior, 49, 272–281. https://doi.org/10.1016/j.chb.2015.03.022.CrossRef

Deng, R., Benckendorff, P., & Gannaway, D. (2019). Progress and new directions for teaching and learning in MOOCs. Computers in Education, 129, 48–60. https://doi.org/10.1016/j.compedu.2018.10.019.CrossRef

DeYoung, C. G. (2010). Toward a theory of the big five. Psychological Inquiry, 21(1), 26–33. https://doi.org/10.1080/10478401003648674.CrossRef

DeYoung, C. G., Quilty, L. C., & Peterson, J. B. (2007). Between facets and domains: 10 aspects of the big five. Journal of Personality and Social Psychology, 93(5), 880–896. https://doi.org/10.1037/0022-3514.93.5.880.CrossRef

DeYoung, C. G., Carey, B. E., Krueger, R. F., & Ross, S. R. (2016). Ten aspects of the big five in the personality inventory for DSM-5. Personality Disorders, Theory, Research, and Treatment, 7(2), 113–123. https://doi.org/10.1037/per0000170.CrossRef

Feiler, D. C., & Kleinbaum, A. M. (2015). Popularity, similarity, and the network extraversion bias. Psychological Science, 26(5), 593–603. https://doi.org/10.1177/0956797615569580.CrossRef

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–55. https://doi.org/10.2307/3151312.CrossRef

Gomez-Zermeno, M., & Aleman, L. (2016). Research analysis on Mooc course dropout and R. Turkish Online Journal of Distance Education, 17(4), 3–14.

Hair, J. F., Tatham, R. L., Anderson, R. E., & William, B. (1998). Multivariate data analysis (5th ed.). New York: Prentice Hall.

Hew, K. F., & Cheung, W. S. (2014). Students’ and instructors’ use of massive open online courses (MOOCs): Motivations and challenges. Educational Research Review, 12, 45–58. https://doi.org/10.1016/J.EDUREV.2014.05.001.CrossRef

Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118.CrossRef

Hudiburg, R. A., Pashaj, I., & Wolfe, R. (1999). Preliminary investigation of computer stress and the big five personality factors. Psychological Reports, 85(2), 473–480. https://doi.org/10.2466/PR0.85.6.473-480.CrossRef

Joo, Y. J., So, H. J., & Kim, N. H. (2018). Examination of relationships among students’ self-determination, technology acceptance, satisfaction, and continuance intention to use K-MOOCs. Computers in Education, 122, 260–272. https://doi.org/10.1016/j.compedu.2018.01.003.CrossRef

Jost, J. T., & Burgess, D. (2000). Attitudinal ambivalence and the conflict between group and system justification motives in low status groups. Personality and Social Psychology Bulletin, 26(3), 293–305. https://doi.org/10.1177/0146167200265003.CrossRef

Jost, J. T., Banaji, M. R., & Nosek, B. A. (2004). A decade of system justification theory: Accumulated evidence of conscious and unconscious bolstering of the status quo. Political Psychology, 25(6), 881–919. https://doi.org/10.1111/j.1467-9221.2004.00402.x.CrossRef

Jost, J. T., Liviatan, I., Van Der Toorn, J., Alison Ledgerwood, A. M., & Nosek, B. A. (2011). The psychology of justice and legitimacy. In R. Bobocel, A. C. Kay, M. P. Zanna, & J. M. Olson (Eds.), The psychology of justice and legitimacy (1st ed., pp. 79–102). New York: Psychology Press. https://doi.org/10.4324/9780203837658.CrossRef

Kim, T. d., Yang, M.,. y., Bae, J., Min, B. a., Lee, I., & Kim, J. (2017). Escape from infinite freedom: Effects of constraining user freedom on the prevention of dropout in an online learning context. Computers in Human Behavior, 66, 217–231. https://doi.org/10.1016/j.chb.2016.09.019.

Kortum, P., & Oswald, F. L. (2018). The impact of personality on the subjective assessment of usability. International Journal of Human Computer Interaction, 34(2), 177–186. https://doi.org/10.1080/10447318.2017.1336317.CrossRef

Kosinski, M., Bachrach, Y., Kohli, P., Stillwell, D., & Graepel, T. (2014). Manifestations of user personality in website choice and behaviour on online social networks. Machine Learning, 95(3), 357–380. https://doi.org/10.1007/s10994-013-5415-y.MathSciNetCrossRef

Laurin, K., Kay, A. C., Proudfoot, D., & Fitzsimons, G. J. (2013). Response to restrictive policies: Reconciling system justification and psychological reactance. Organizational Behavior and Human Decision Processes, 122(2), 152–162. https://doi.org/10.1016/j.obhdp.2013.06.004.CrossRef

Littlejohn, A., Hood, N., Milligan, C., & Mustain, P. (2016). Learning in MOOCs: Motivations and self-regulated learning in MOOCs. The Internet and Higher Education, 29, 40–48. https://doi.org/10.1016/J.IHEDUC.2015.12.003.CrossRef

Liu, D., & Campbell, W. K. (2017). The big five personality traits, big two metatraits and social media: A meta-analysis. Journal of Research in Personality, 70, 229–240. https://doi.org/10.1016/j.jrp.2017.08.004.CrossRef

Longstaff, E. (2017). Ritual in online communities: A study of post-voting in MOOC discussion forums. International Journal of Human Computer Interaction, 33(8), 655–663. https://doi.org/10.1080/10447318.2016.1277639.CrossRef

Lung-Guang, N. (2019). Decision-making determinants of students participating in MOOCs: Merging the theory of planned behavior and self-regulated learning model. Computers in Education, 134, 50–62. https://doi.org/10.1016/j.compedu.2019.02.004.CrossRef

Marsh, H. W., & Hocevar, D. (1985). Application of confirmatory factor analysis to the study of self-concept: First- and higher order factor models and their invariance across groups. Psychological Bulletin, 97(3), 562–582. https://doi.org/10.1037/0033-2909.97.3.562.CrossRef

McCrae, R. R., & Costa, P. T. (1997). Personality trait structure as a human universal. American Psychologist, 52(5), 509–516. https://doi.org/10.1037/0003-066X.52.5.509.CrossRef

Mccrae, R. R., & Löckenhoff, C. E. (2010). Self-regulation and the five-factor model of personality traits. In Handbook of Personality and Self-Regulation (pp. 145–168). Wiley-Blackwell. https://doi.org/10.1002/9781444318111.ch7.

Milligan, C., & Littlejohn, A. (2017). Why study on a MOOC? The motives of students and professionals. International Review of Research in Open and Distance Learning, 18(2), 92–102. https://doi.org/10.19173/irrodl.v18i2.3033.CrossRef

Picazo-Vela, S., Chou, S. Y., Melcher, A. J., & Pearson, J. M. (2010). Why provide an online review? An extended theory of planned behavior and the role of big-five personality traits. Computers in Human Behavior, 26(4), 685–696. https://doi.org/10.1016/j.chb.2010.01.005.CrossRef

Podsakoff, P., MacKenzie, S., Lee, J., & Podsakoff, N. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879.CrossRef

Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54–67. https://doi.org/10.1006/ceps.1999.1020.CrossRef

Seemann, E. A., Buboltz, W. C., Thomas, A., Soper, B., & Wilkinson, L. (2005). Normal personality variables and their relationship to psychological reactance. Individual Differences Research, 3(2), 88–98.

Simmering, M. G., Arseneault, J. M., Ross, C., Sisic, M., Orr, E. S., & Orr, R. R. (2009). Personality and motivations associated with Facebook use. Computers in Human Behavior, 25(2), 578–586. https://doi.org/10.1016/j.chb.2008.12.024.CrossRef

Svendsen, G. B., Johnsen, J.-A. K., Almås-Sørensen, L., & Vittersø, J. (2013). Personality and technology acceptance: The influence of personality factors on the core constructs of the technology acceptance model. Behaviour & Information Technology, 32(4), 323–334. https://doi.org/10.1080/0144929X.2011.553740.CrossRef

Tabak, F., & Nguyen, N. T. (2013). Technology acceptance and performance in online learning environments: Impact of self-regulation. Journal of Online Learning and Teaching, 9(1), 116–130.

Torrance, E. P., & Brehm, J. W. (1968). A theory of psychological reactance. The American Journal of Psychology, 81(1), 133. https://doi.org/10.2307/1420824.CrossRef

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 in Education, 121, 18–29. https://doi.org/10.1016/j.compedu.2018.02.011.CrossRef

Wang, J.-L., Jackson, L. A., Zhang, D.-J., & Su, Z.-Q. (2012). The relationships among the big five personality factors, self-esteem, narcissism, and sensation-seeking to Chinese University students’ uses of social networking sites (SNSs). Computers in Human Behavior, 28(6), 2313–2319. https://doi.org/10.1016/j.chb.2012.07.001.CrossRef

Watted, A., & Barak, M. (2018). Motivating factors of MOOC completers: Comparing between university-affiliated students and general participants. The Internet and Higher Education, 37, 11–20. https://doi.org/10.1016/j.iheduc.2017.12.001.CrossRef

Wong, J., Baars, M., Davis, D., Van Der Zee, T., Houben, G. J., & Paas, F. (2019). Supporting self-regulated learning in online learning environments and MOOCs: A systematic review. International Journal of Human Computer Interaction, 35(4–5), 356–373. https://doi.org/10.1080/10447318.2018.1543084.CrossRef

Wu, B., & Chen, X. (2017). Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model. Computers in Human Behavior, 67, 221–232. https://doi.org/10.1016/j.chb.2016.10.028.CrossRef

Zheng, S., Rosson, M. B., Shih, P. C., & Carroll, J. M. (2015). Understanding Student Motivation, Behaviors and Perceptions in MOOCs. In Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing - CSCW ‘15 (pp. 1882–1895). New York, USA: ACM Press. https://doi.org/10.1145/2675133.2675217.

Zhou, M. (2016). Chinese university students’ acceptance of MOOCs: A self-determination perspective. Computers & Education, 92–93, 194–203. https://doi.org/10.1016/j.compedu.2015.10.012.CrossRef

Zimmerman, B. J. (1995). Self-regulation involves more than metacognition: A social cognitive perspective. Educational Psychologist, 30(4), 217–221. https://doi.org/10.1207/s15326985ep3004_8.CrossRef

Title: Relationship between motivations, personality traits and intention to continue using MOOCs
Authors: Hend Abdullatif
J. Ángel Velázquez-Iturbide
Publication date: 17-04-2020
Publisher: Springer US
Published in: Education and Information Technologies / Issue 5/2020
Print ISSN: 1360-2357
Electronic ISSN: 1573-7608
DOI: https://doi.org/10.1007/s10639-020-10161-z

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