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Personalized Gamification in E-Learning with a Focus on Learners’ Motivation and Personality | ||
| Interdisciplinary Journal of Virtual Learning in Medical Sciences | ||
| مقاله 6، دوره 12، شماره 3، آذر 2021، صفحه 201-212 اصل مقاله (712.9 K) | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.30476/ijvlms.2021.89333.1070 | ||
| نویسندگان | ||
| MohammadHassan Abbasi1؛ Gholamali Montazer* 2؛ Fatemeh Ghrobani3؛ Zahra Alipour4 | ||
| 1Department of Information Technology Management, School of Management, Islamic Azad University, Tehran, Iran | ||
| 2Department of Information Technology Engineering, Tarbiat Modares University, Tehran, Iran | ||
| 3Department of Industrial Engineering, Islamic Azad University, Tehran, Iran | ||
| 4School of Management, Islamic Azad University, Tehran, Iran | ||
| چکیده | ||
| Background: This study sought to develop a personalized gamified e-learning system based on students' motivation and personality, and evaluate its efficacy with regard to their performance in mathematics. Methods: In this pretest-posttest experimental study, the participants included 117 students already familiar with e-learning systems. They took a mathematics course in January-February 2020, and were randomly assigned to five groups: Personalized Gamification (PG) based on motivation and personality (n=23), PG based on personality (n=23), PG based on motivation (n=23), non-personalized gamification (n=23), and control (n=25). Then the students’ scores and the time they spent on the learning management system (LMS) were compared before and after the personalization procedure. The collected data were analyzed using SPSS version 26. In this regard, independent-samples t-test was used to compare the mean scores at p 0.916 in both cases). Conclusion: PG has a significant positive effect on students’ scores compared to the non-gamified system, and it leads to a significant improvement in the learning time spent on LMS, compared to non-personalized gamified systems. | ||
| کلیدواژه‌ها | ||
| E-learning؛ Gamification؛ Motivation؛ Personality | ||
| مراجع | ||
|
Truong HM. Integrating learning styles and adaptive e-learning system: Current developments, problems and opportunities. Computers in human behavior. 2016 Feb 1;55:1185-93. doi:10.1016/j.chb.2015.02.014
Biletskiy Y, Baghi H, Keleberda I, Fleming M. An adjustable personalization of search and delivery of learning objects to learners. Expert Systems with Applications. 2009 Jul 1;36(5):9113-20. doi:10.1016/j.eswa.2008.12.038
Radwan NM. An Adaptive Learning Management System Based on Learner's Learning Style. Int. Arab. J. e Technol.. 2014 Jun;3(4):228-34.
Latham A, Crockett K, McLean D, Edmonds B. A conversational intelligent tutoring system to automatically predict learning styles. Computers & Education. 2012 Aug 1;59(1):95-109. doi:10.1016/j.compedu.2011.11.001
Kinley K, Tjondronegoro D, Partridge H, Edwards S. Modeling users' web search behavior and their cognitive styles. Journal of the Association for Information Science and Technology. 2014 Jun;65(6):1107-23. doi:10.1002/asi.23053
Ghorbani F, Montazer GA. E-learners’ personality identifying using their network behaviors. Computers in Human Behavior. 2015 Oct 1;51:42-52. doi:10.1016/j.chb.2015.04.043
Lestari W, Nurjanah D, Selviandro N. Adaptive Presentation based on Learning Style and Working Memory Capacity in Adaptive Learning System. InCSEDU (1) 2017 (pp. 363-370).
Plass JL, Homer BD, Pawar S, Brenner C, MacNamara AP. The effect of adaptive difficulty adjustment on the effectiveness of a game to develop executive function skills for learners of different ages. Cognitive Development. 2019 Jan 1;49:56-67. doi:10.1016/j.cogdev.2018.11.006
Noguti V, Singh S, Waller DS. Gender differences in motivations to use social networking sites. InGender economics: Breakthroughs in research and practice 2019 (pp. 676-691). IGI Global. doi:10.4018/978-1-5225-6912-1.ch081
Bauer M, Bräuer C, Schuldt J, Niemann M, Krömker H. Application of wearable technology for the acquisition of learning motivation in an adaptive e-Learning platform. In International Conference on Applied Human Factors and Ergonomics 2018 Jul 21 (pp. 29-40). Springer, Cham. doi:10.1007/978-3-319-94619-1_4
Zarrin F, Montazer G. Designing an intelligent tutoring system based on learners' self-efficacy and learning style features. In 7th International Conference on e-Learning and e-Teaching, Tehran, IRAN, 2019.
Zhou M, Winne PH. Modeling academic achievement by self-reported versus traced goal orientation. Learning and Instruction. 2012 Dec 1;22(6):413-9. doi:10.1016/j.learninstruc.2012.03.004
Shih HP. Using a cognition-motivation-control view to assess the adoption intention for Web-based learning. Computers & Education. 2008 Jan 1;50(1):327-37. doi:10.1016/j.compedu.2006.06.001
Lai CL, Hwang GJ, Liang JC, Tsai CC. Differences between mobile learning environmental preferences of high school teachers and students in Taiwan: A structural equation model analysis. Educational Technology Research and Development. 2016 Jun;64(3):533-54. doi:10.1007/s11423-016-9432-y
Law KM, Lee VC, Yu YT. Learning motivation in e-learning facilitated computer programming courses. Computers & Education. 2010 Aug 1;55(1):218-28. doi:10.1016/j.compedu.2010.01.007
Seif E. Human attributes and institutional learning. Tehran, University publication, 1995 in Persian.
Chyung SY, Moll AJ, Berg SA. The role of intrinsic goal orientation, self-efficacy, and e-learning practice in engineering education. Journal of Effective Teaching. 2010;10(1):22-37.
Allemand M, Steiger AE, Hill PL. Stability of personality traits in adulthood. GeroPsych. 2013 Feb 27. doi:10.1024/1662-9647/a000080
Tlili A, Essalmi F, Ayed LJ, Jemni M. A smart educational game to model personality using learning analytics. In2017 IEEE 17th International conference on advanced learning technologies (ICALT) 2017 Jul 3 (pp. 131-135). IEEE. doi:10.1109/ICALT.2017.65
Digman JM. Personality structure: Emergence of the five-factor model. Annual review of psychology. 1990 Feb;41(1):417-40. doi:10.1146/annurev.ps.41.020190.002221
Felder RM, Felder GN, Dietz EJ. The effects of personality type on engineering student performance and attitudes. Journal of engineering education. 2002 Jan;91(1):3-17. doi:10.1002/j.2168-9830.2002.tb00667.x
Fatahi S, Moradi H, Kashani-Vahid L. A survey of personality and learning styles models applied in virtual environments with emphasis on e-learning environments. Artificial Intelligence Review. 2016 Oct;46(3):413-29. doi:10.1007/s10462-016-9469-7
Hermans HJ. A questionnaire measure of achievement motivation. Journal of applied psychology. 1970 Aug;54(4):353. doi:10.1037/h0029675 PMid:5483811
Ryan RM, Connell JP. Perceived locus of causality and internalization: examining reasons for acting in two domains. Journal of personality and social psychology. 1989 Nov;57(5):749. doi:10.1037/0022-3514.57.5.749 PMid:2810024
Legault L, Green-Demers I, Pelletier L. Why do high school students lack motivation in the classroom? Toward an understanding of academic amotivation and the role of social support. Journal of educational psychology. 2006 Aug;98(3):567. doi:10.1037/0022-0663.98.3.567
Polácek K. QPA - Questionario Sui Processi di Apprendimento. Superiori e università. Firenze. Giunti O.S. Organizzazioni Speciali. 2005.
Vallerand RJ, Pelletier LG, Blais MR, Brière NM, Senécal CB, Vallières ÉF. Academic motivation scale (AMS-C 28), college (CEGEP) version. Educational and Psychological Measurement. 1993;52(53):1992-3. doi:10.1037/t25718-000
Ratelle CF, Guay F, Vallerand RJ, Larose S, Senécal C. Autonomous, controlled, and amotivated types of academic motivation: A person-oriented analysis. Journal of educational psychology. 2007 Nov;99(4):734. doi:10.1037/0022-0663.99.4.734
Utvær BK, Haugan G. The academic motivation scale: dimensionality, reliability, and construct validity among vocational students. Nordic Journal of Vocational Education and Training. 2016 Nov 8;6(2):17-45.
Costa Jr PT, McCrae RR. The Five-Factor Model and the NEO Inventories. 2009. doi: 10.1093/oxfordhb/9780195366877.013.0016
Nacke LE, Bateman C, Mandryk RL. BrainHex: A neurobiological gamer typology survey. Entertainment computing. 2014 Jan 1;5(1):55-62. doi:10.1016/j.entcom.2013.06.002
Thompson ER. Development and validation of an international English big-five mini-markers. Personality and individual differences. 2008 Oct 1;45(6):542-8. doi:10.1016/j.paid.2008.06.013. | ||
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