A study of e-learning motivation in Haryana, India: do gender and locality matter?
DOI:
https://doi.org/10.47408/jldhe.vi39.1529Keywords:
e-learning motivation, digital learning, online education, gender differences, digital education, digital divideAbstract
This study explores undergraduate students' motivation for e-learning in Haryana, India, considering gender (male and female) and locality (urban and rural) differences. Data was collected from a random sample of 400 students enrolled in colleges. The results indicate that female and rural students demonstrated higher levels of motivation than male and urban students, revealing significant differences. The study emphasises the importance of addressing digital infrastructure challenges and providing focused support to enhance e-learning participation among diverse student groups, ensuring fair access to educational opportunities.
The practical implications of this research suggest that by implementing tailored interventions, educational institutions and policymakers can enhance student engagement and outcomes. This can lead to a more effective educational environment that benefits a wide range of learners. To achieve this, they should focus on bridging the digital gap among diverse groups and adopting strategies that create supportive e-learning environments for all students.
References
Al-Fraihat, D., Joy, M., Masa’deh, R., & Sinclair, J. (2020). Evaluating e-learning systems success: an empirical study. Computers in Human Behavior, 102, 67–86. https://doi.org/10.1016/j.chb.2019.08.004
Aparicio, M., Bacao, F., & Oliveira, T. (2016). An e-learning theoretical framework. Educational Technology and Society, 19(1), 292–307. https://www.learntechlib.org/p/192717/
Artino, A. R. (2008). Motivational beliefs and perceptions of instructional quality: predicting satisfaction with online training. Journal of Computer Assisted Learning, 24(3), 260–270. https://doi.org/10.1111/j.1365-2729.2007.00258.x
BW Online Bureau. (2025, January 28). Experts call for higher education funding, digital infra, climate literacy. Business World. https://www.businessworld.in/article/pre-budget-expectations-2025-education-sector-546240
Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. Plenum Press. https://doi.org/10.1007/978-1-4899-2271-7
Dichev, C., & Dicheva, D. (2017). Gamifying education: what is known, what is believed, and what remains uncertain: a critical review. International Journal of Educational Technology in Higher Education, 14(1), 1–36. https://doi.org/10.1186/s41239-017-0042-5
Dixson, M. D. (2015). Measuring student engagement in the online course: the online student engagement scale (OSE). Online Learning, 19(4), 143–157. https://doi.org/10.24059/olj.v19i4.561
Ehsan, M. M., & Zaidan, E. (2024). Exploring internet inclusivity and effectiveness of e-learning initiatives during the pandemic — a comparative analysis. Frontiers in Education, 8, Article 1301135. https://doi.org/10.3389/feduc.2023.1301135
Fowler, K. S. (2007). The motivation to learn online questionnaire [Unpublished Master’s dissertation, University of Georgia]. UGA Open Scholar. https://openscholar.uga.edu/record/7673/files/fowler_kevin_s_200712_ma.pdf
Fowler, K. S. (2018). The motivation to learn online questionnaire [Doctoral dissertation, University of Georgia]. UGA Open Scholar. https://getd.libs.uga.edu/pdfs/fowler_kevin_s_201805_phd.pdf
Hung, M., Chou, C., Chen, C., & Own, Z. (2010). Learner readiness for online learning: scale development and student perceptions. Computers and Education, 55(3), 1080–1090. https://doi.org/10.1016/j.compedu.2010.05.004
Innab, A., & Alqahtani, N. (2023). The mediating role of e-learning motivation on the relationship between technology access and satisfaction with e-learning. Nursing Open, 10(4), 2552–2559. https://doi.org/10.1002/nop2.1513
Kew, S. N., Petsangsri, S., Ratanaolarn, T., & Tasir, Z. (2018). Examining the motivation level of students in e-learning in higher education institutions in Thailand: a case study. Education and Information Technologies, 23(6), 2947–2967. https://doi.org/10.1007/s10639-018-9753-z
Mariya, K., Shakeel, A., Shazli, T., Naqvi, H. R., Akhtar, N., & Siddiqui, M. A. (2022). Analysing the role of gender and place of residence in acceptability and satisfaction towards e-learning among university students’ during COVID-19 pandemic in India. SN Social Sciences, 2(233),1–28. https://doi.org/10.1007/s43545-022-00544-z
Mathrani, A., Umer, R., Sarvesh, T., & Adhikari, J. (2023). Rural–urban, gender, and digital divides during the COVID-19 lockdown: a multi-layered study. Societies, 13(5), 122. https://doi.org/10.3390/soc13050122
Mensah, C., Kugbonu, M. A., Appietu, M. E., Nti, G. A., & Forson, M. A. (2024). Social support, computer self-efficacy, online learning satisfaction and cognitive engagement of students. Cogent Education, 11(1), 1–16. https://doi.org/10.1080/2331186X.2024.2335803
Ministry of Education. (2020). All India survey on higher education (AISHE) 2019–20. https://cdnbbsr.s3waas.gov.in/s392049debbe566ca5782a3045cf300a3c/uploads/2025/06/20250604434323531.pdf
Ministry of Human Resource Development. (2020). National Education Policy 2020. https://www.education.gov.in/sites/upload_files/mhrd/files/NEP_Final_English_0.pdf
Muthuprasad, T., Aiswarya, S., Aditya, K. S., & Jha, G. K. (2021). Students’ perception and preference for online education in India during COVID-19 pandemic. Social Sciences and Humanities Open, 3(1), 1–11. https://doi.org/10.1016/j.ssaho.2020.100101
Office of the Registrar General & Census Commissioner. (2011). Provisional population totals: India, Census 2011. https://censusindia.gov.in/nada/index.php/catalog/1428
Pintrich, P., Smith, D., García, T., & McKeachie, W. (1991). A manual for the use of the motivated strategies for learning questionnaire (MSLQ). University of Michigan.
R, N., & Radha, B. (2024). Digital divide: a comparison of undergraduate female students’ use of social media platforms in urban and rural areas. Indian Journal of Educational Technology, 6(1), 43–53. https://journals.ncert.gov.in/IJET/article/view/395
Richardson, J. C., & Lowenthal, P. (2017). Instructor social presence: learners’ needs and a neglected component of the community of inquiry framework. In A. L. Whiteside, A. G. Dikkers, & K. Swan (Eds.), Social presence in online learning: multiple perspectives on practice and research (pp. 86–98). Stylus.
Rockinson-Szapkiw, A. J., Sharpe, K., & Wendt, J. (2022). Promoting self-efficacy, mentoring competencies, and persistence in STEM: a case study evaluating racial and ethnic minority women’s learning experiences in a virtual STEM peer mentor training. Journal of Science Education and Technology, 31, 386–402. https://doi.org/10.1007/s10956-022-09962-3
Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78. https://doi.org/10.1037/0003-066X.55.1.68
Sarkar, B., Islam, N., Das, P., Miraj, A., Dakua, M., Debnath, M., & Roy, R. (2022). Digital learning and the lopsidedness of the education in government and private primary schools during the COVID-19 pandemic in West Bengal, India. E-Learning and Digital Media, 20(5), 473–497. https://doi.org/10.1177/20427530221117327
Singh, V., & Thurman, A. (2019). How many ways can we define online learning? A systematic literature review of definitions of online learning (1988–2018). American Journal of Distance Education, 33(4), 289–306. https://doi.org/10.1080/08923647.2019.1663082
Tewari, A., & Tewari, A. K. (2025). E-learning vs. traditional learning in India: challenges and opportunities in rural education. International Journal of Humanities Social Science and Management, 5(2), 219–226. https://ijhssm.org/issue_dcp/E%20Learning%20vs.%20Traditional%20Learning%20in%20India%20Challenges%20and%20Opportunities%20in%20Rural%20Education.pdf
Vanitha, P. S., & Alathur, S. (2021). Factors influencing e-learning adoption in India: learners’ perspective. Education and Information Technologies, 26(5), 5199–5236. https://doi.org/10.1007/s10639-021-10504-4
Yu, Z., & Deng, X. (2022). A meta-analysis of gender differences in e-learners’ self-efficacy, satisfaction, motivation, attitude, and performance across the world. Frontiers in Psychology, 13, Article 897327. https://doi.org/10.3389/fpsyg.2022.897327
Zhao, L., Cao, C., Li, Y., & Li, Y. (2022). Determinants of the digital outcome divide in e-learning between rural and urban students: empirical evidence from the COVID-19 pandemic based on capital theory. Computers in Human Behavior, 130, Article 107177. https://doi.org/10.1016/j.chb.2021.107177
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). Academic Press. https://doi.org/10.1016/B978-012109890-2/50031-7
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