On The Use of Gamification in Learning Style Questionnaires: An Experiment
Keywords:
E-learning, Education, Learning Style, Gamification, Data collectionAbstract
Online education provides students with a flexible educational option that helps them to complete their training at their own pace. Adaptive e-learning systems are one of the most exciting areas of research in online education. To adapt a system, understanding the learner is very important, through information such as his learning style. In our system, the "learning style index" is used to identify the learning style of a user, which is a questionnaire containing 44 questions based on the Felder–Silverman learning style model (FSLSM). The aim of our research is to gamify the learning style questionnaire, to motivate users and avoid their boredom and the abandonment of the long questionnaire. An empirical study is conducted to compare the gamified and classic questionnaires. The results show that the use of our method improve user's interactions, 98% of the participants are satisfied and only 7% of them drop the questionnaire.
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Y. Bai, H. Li, and Y. Liu, “Visualizing research trends and research theme evolution in E-learning field: 1999–2018,” Scientometrics, vol. 126, no. 2, pp. 1389–1414, 2021, doi: 10.1007/s11192-020-03760-7.
S. Ennouamani and Z. Mahani, “An overview of adaptive e-learning systems,” 2017 IEEE 8th Int. Conf. Intell. Comput. Inf. Syst. ICICIS 2017, vol. 2018-Janua, no. December, pp. 342–347, 2018, doi: 10.1109/INTELCIS.2017.8260060.
M. Vandewaetere, P. Desmet, and G. Clarebout, “The contribution of learner characteristics in the development of computer-based adaptive learning environments,” Comput. Human Behav., vol. 27, no. 1, pp. 118–130, 2011, doi: 10.1016/j.chb.2010.07.038.
W. Ali, “Online and Remote Learning in Higher Education Institutes: A Necessity in light of COVID-19 Pandemic,” High. Educ. Stud., vol. 10, no. 3, p. 16, 2020, doi: 10.5539/hes.v10n3p16.
M. del P. P. Ruiz, M. J. F. Díaz, F. O. Soler, and J. R. P. Pérez, “Adaptation in current e-learning systems,” Comput. Stand. Interfaces, vol. 30, no. 1–2, pp. 62–70, 2008, doi: 10.1016/j.csi.2007.07.006.
C. N. Pfeiffer and A. Jabbar, “Adaptive e-Learning: Emerging Digital Tools for Teaching Parasitology,” Trends Parasitol., vol. 35, no. 4, pp. 270–274, 2019, doi: 10.1016/j.pt.2019.01.008.
M. A. Hassan, U. Habiba, F. Majeed, and M. Shoaib, “Adaptive gamification in e-learning based on students’ learning styles,” Interact. Learn. Environ., vol. 29, no. 4, pp. 545–565, 2021, doi: 10.1080/10494820.2019.1588745.
S. McLeod, “Kolb ’ s learning styles and sxperiential learning cycle,” SimplyPsychology, pp. 1–8, 2017, [Online]. Available: https://www.simplypsychology.org/learning-kolb.html
D. A. Kolb, “Experiential Learning: Experience as The Source of Learning and Development,” Prentice Hall, Inc., no. 1984, pp. 20–38, 1984, doi: 10.1016/B978-0-7506-7223-8.50017-4.
N. C. S. U. Felder Richard M. and I. for the S. of A. D. Silverman Linda K., “Learning and Teaching Styles in Engineering Education,” Engr. Educ., vol. 78(7), pp. 674–681, 1988.
F. Rasheed and A. Wahid, “Learning style detection in E-learning systems using machine learning techniques,” Expert Syst. Appl., vol. 174, no. February, 2021, doi: 10.1016/j.eswa.2021.114774.
Z. Zainuddin, S. K. W. Chu, M. Shujahat, and C. J. Perera, “The impact of gamification on learning and instruction: A systematic review of empirical evidence,” Educ. Res. Rev., vol. 30, no. March 2019, 2020, doi: 10.1016/j.edurev.2020.100326.
C. Borrego, C. Fernández, I. Blanes, and S. Robles, “Room escape at class: Escape games activities to facilitate the motivation and learning in computer science,” J. Technol. Sci. Educ., vol. 7, no. 2, pp. 162–171, 2017, doi: 10.3926/jotse.247.
J. R. Chapman and P. J. Rich, “Does educational gamification improve students’ motivation? If so, which game elements work best?,” J. Educ. Bus., vol. 93, no. 7, pp. 314–321, 2018, doi: 10.1080/08832323.2018.1490687.
Supriyanto, J. Fahana, and S. Handoko, “Gamification to Improve Digital Data Collection in Ecotourism Management,” Proc. - 2nd East Indones. Conf. Comput. Inf. Technol. Internet Things Ind. EIConCIT 2018, pp. 139–142, 2018, doi: 10.1109/EIConCIT.2018.8878581.
M. Hoerger, “in Internet-Mediated University Studies : Implications in Psychological Research,” Cyberpsychology, Behav. Soc. Netw., vol. 13, no. 6, pp. 697–701, 2010.
A. P. Gilakjani, “A Match or Mismatch Between Learning Styles of the Learners and Teaching Styles of the Teachers,” Int. J. Mod. Educ. Comput. Sci., vol. 4, no. 11, pp. 51–60, 2012, doi: 10.5815/ijmecs.2012.11.05.
J. Feldman, A. Monteserin, and A. Amandi, “Automatic detection of learning styles: state of the art,” Artif. Intell. Rev., vol. 44, no. 2, pp. 157–186, 2015, doi: 10.1007/s10462-014-9422-6.
E. Mwamikazi, P. Fournier-Viger, C. Moghrabi, A. Barhoumi, and R. Baudouin, “An adaptive questionnaire for automatic identification of learning styles,” Lect. Notes Artif. Intell. (Subseries Lect. Notes Comput. Sci., vol. 8481, no. 2014, pp. 399–409, 2014, doi: 10.1007/978-3-319-07455-9_42.
Y. Ikawati, M. U. H. Al Rasyid, and I. Winarno, “Student Behavior Analysis to Detect Learning Styles in Moodle Learning Management System,” IES 2020 - Int. Electron. Symp. Role Auton. Intell. Syst. Hum. Life Comf., pp. 501–506, 2020, doi: 10.1109/IES50839.2020.9231567.
D. Q. Ahmadaliev, C. Xiaohui, and M. Abduvohidov, “A Web-based instrument to initialize learning style: An interactive questionnaire instrument,” Int. J. Emerg. Technol. Learn., vol. 13, no. 12, pp. 238–246, 2018, doi: 10.3991/ijet.v13i12.8725.
X. Tsortanidou, C. Karagiannidis, and A. Koumpis, “Adaptive educational hypermedia systems based on learning styles: The case of adaptation rules,” Int. J. Emerg. Technol. Learn., vol. 12, no. 5, pp. 150–168, 2017, doi: 10.3991/ijet.v12i05.6967.
R. M. Felder and J. Spurlin, “Applications, reliability and validity of the index of learning styles,” Int. J. Eng. Educ., vol. 21, no. 1 PART 1, pp. 103–112, 2005.
D. R. SHOCKLEY, “Learning Styles and Students’ Perceptions of Satisfaction in Community College Web-based Learning Environments,” 2005.
S. V. Kolekar, R. M. Pai, and M. M. Manohara Pai, “Adaptive User Interface for Moodle based E-learning System using Learning Styles,” Procedia Comput. Sci., vol. 135, pp. 606–615, 2018, doi: 10.1016/j.procs.2018.08.226.
B. a Soloman, N. Carolina, and R. M. Felder, “Index of Learning Styles Questionnaire,” Learning, no. January 1999, pp. 1–5, 2012, [Online]. Available: http://www.engr.ncsu.edu/learningstyles/ilsweb.html
M. S. Zywno, “A contribution to validation of score meaning for Felder-Soloman’s Index of Learning Styles,” ASEE Annu. Conf. Proc., pp. 2855–2870, 2003, doi: 10.18260/1-2--12424.
Sekaran et al., “THE EFFECT OF GAMIFICATION ON STUDENTS’ ENGAGEMENT AND MOTIVATION IN THREE WSU COURSES,” Pakistan Res. J. Manag. Sci., vol. 7, no. 5, pp. 1–2, 2018.
F. Teixes, “Actionable gamification: Beyond points, badges, and leaderboards,” Octalysis Media, pp. 1–151, 2017, [Online]. Available: https://leanpub.com/actionable-gamification-beyond-points-badges-leaderboards/read.
B. A. Myers, “Importance of Percent-Done Progress Indicators for Computer-Human Interfaces.,” no. April, pp. 11–17, 1985, doi: 10.1145/1165385.317459.
Z. Li, K. W. Huang, and H. Cavusoglu, “Quantifying the impact of badges on user engagement in online Q&A communities,” Int. Conf. Inf. Syst. ICIS 2012, vol. 5, pp. 3798–3807, 2012.
A. Bhattacherjee, “Understandinignformatiosnystems Continuancea: An Expectation-Confirmatiom Model,” MIS Quarterly, vol. 25, no. 3, pp. 351–370, 2001.
N. H. Anderson, “Integration theory and attitude change,” Psychol. Rev., vol. 78, no. 3, pp. 171–206, 1971, doi: 10.1037/h0030834.
J. Majuri, J. Koivisto, and J. Hamari, “Gamification of education and learning: A review of empirical literature,” CEUR Workshop Proc., vol. 2186, no. GamiFIN, pp. 11–19, 2018.
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