Transforming Challenges into Solutions: Improving the Online Learning Experience for Working Adult Students
Abstract
Online learning has emerged as a crucial alternative for working adults seeking higher education as the need for flexible learning alternatives grows. This study explores how students who are employed see online learning in higher education, emphasizing the particular opportunities and difficulties they face. Given the growing popularity of online learning models, it is essential to comprehend how working students see these systems' adaptability, usability, and efficacy. The study uses a descriptive analysis and collects data from working adult students taking online courses using both quantitative and qualitative methodologies. The main research tool was a survey questionnaire with a target sample size of 96 respondents. The study addresses the drawbacks of conventional face-to-face learning while examining a number of aspects that affect student happiness, such as technical convenience, flexibility, course structure, and instructor support. The data's reliability was evaluated using Cronbach's Alpha, and the underlying patterns were examined using factor analysis. The results demonstrate that, despite ongoing issues with time management and engagement, online learning provides job holders with a great deal of flexibility. These findings advance our knowledge of the best ways to support students juggling work and school obligations through online learning.
References
ALLEN, I. E. & SEAMAN, J. 2017. Digital Compass Learning: Distance Education Enrollment Report 2017. Babson survey research group.
ANGRAINI, L. M., KANIA, N. & GÜRBÜZ, F. 2024. Students' Proficiency in Computational Thinking Through Constructivist Learning Theory. International Journal of Mathematics and Mathematics Education, 45-59.
BEATTY, B. & ULASEWICZ, C. 2006. Faculty perspectives on moving from Blackboard to the Moodle learning management system. TechTrends, 50, 36-45.
BROWN, C. 2024. The test of grocery shopping skills. Assessments in Occupational Therapy Mental Health. Routledge.
CLIFF, N. 1988. The eigenvalues-greater-than-one rule and the reliability of components. Psychological bulletin, 103, 276.
DEVI, K. S. & APARNA, M. 2020. Moodle–An effective learning management system for 21st century learners. Alochana Chakra Journal, 9, 4474-4485.
DHAWAN, S. 2020. Online learning: A panacea in the time of COVID-19 crisis. Journal of educational technology systems, 49, 5-22.
DZIUBAN, A. 2024. Imposed mobility, legal ambiguity, institutionalized abandonment: exploring the sex work crimscape in contemporary Poland. Critical Criminology, 1-18.
FELDER, R. & SILVERMAN, L. 1988. Teaching and learning styles in engineering education. Engineering Education, 78, 680.
GARRISON, D. R. & KANUKA, H. 2004. Blended learning: Uncovering its transformative potential in higher education. The internet and higher education, 7, 95-105.
HAMADA, A. A. 2024. Two Stage Lasso in Principal Component Analysis With an Application. International Journal of Applied Mathematics and Computing, 1, 19-30.
ICE, P. & DZIUBAN, C. 2024. Data analytics and adaptive learning: Increasing the odds. Data Analytics and Adaptive Learning. Routledge.
ISLAM, M. M. & ISLAM, M. A. 2023. Effectiveness Of Shariah Supervisory Board And Performance Of Islamic Banks: The Mediating Role Of Board Of Directors. Journal of Islamic Banking & Finance, 40.
ISLAM, M. M. & KASSIM, A. A. M. 2023. The Effect of Accounting Software on Conventional and Islamic Banks in Bangladesh: A Comparative Study. International Journal of Advanced Research in Economics and Finance, 5, 97-112.
ISLAM, M. M., SHAMA, M. S. & JALIL, M. A. 2024. A Critical Examination of Bangladeshi's Educational Institutions to Evaluate the Interaction of Moral Values between Servant Leadership and Power Distance. Asian Journal of Research in Education and Social Sciences, 6, 328-342.
JUÁREZ-DÍAZ, C. & PERALES, M. 2021. Language teachers’ emergency remote teaching experiences during the COVID-19 confinement. Profile Issues in TeachersProfessional Development, 23, 121-135.
KOLB, D. A. 2007. The Kolb learning style inventory, Hay Resources Direct Boston, MA.
KÜMMEL, E., MOSKALIUK, J., CRESS, U. & KIMMERLE, J. 2020. Digital learning environments in higher education: A literature review of the role of individual vs. social settings for measuring learning outcomes. Education Sciences, 10, 78.
MAYER, A. & GREENSPAN, H. 2009. An adaptive mean-shift framework for MRI brain segmentation. IEEE transactions on medical imaging, 28, 1238-1250.
MERCADO, J. 2024. Self-Directed Learning in STEM Teaching and Learning: A Systematic Review of Empirical Evidence. Scientechno: Journal of Science and Technology, 3, 53-84.
PICCIANO, A. G. 2012. The evolution of big data and learning analytics in American higher education. Journal of asynchronous learning networks, 16, 9-20.
RADOVAN, M. 2024. Workplace Flexibility and Participation in Adult Learning. Sustainability, 16, 5950.
SAXENA, P. & PATEL, D. 2024. A Study of Online Teaching Strategies During Covid-19 of Secondary School Teachers. RESEARCH REVIEW International Journal of Multidisciplinary, 9, 39-59.
WARD, L., GORDON, A. & KIRKMAN, A. 2024. Innovative and effective education strategies for adult learners in the perioperative setting. AORN journal, 119, 120-133.
ZWICK, W. R. & VELICER, W. F. 1986. Comparison of five rules for determining the number of components to retain. Psychological bulletin, 99, 432.