Influence of Time Management Skills and Technostress on Academic Performance Among the Private University Students: A Conceptual Framework DOI: https://doi.org/10.33093/ijomfa.2026.7.1.3
Main Article Content
Abstract
Digital tools enhance learning but can also cause technostress, which can impact focus and academic performance. Balancing technology use with effective time management and social engagement is key to student success. Students in Malaysia's Klang Valley reported increased feelings of loneliness, mental health issues, and technostress, particularly as a result of the shift to online learning. This study aims to propose a conceptual framework based on the Study Demand-Resources Theory, examining how time management skills and technostress dimensions influence academic performance through the mediating role of student engagement. A quantitative and cross-sectional survey will be conducted by distributing Likert scale surveys to private university students in the Klang Valley. The data will be analysed using Partial Least Squares Structural Equation Modeling, as it is suitable for handling complex models. A total of 300 respondents were targeted for this study, as this sample size is sufficient for structural equation modelling and ensures reliable and generalisable results. The questionnaire will be distributed online via email, WhatsApp, and academic and social media platforms to ensure a broad and efficient reach. The expected outcome is to provide insights into how students balance technostress and time management to improve academic performance, with student engagement as a key mediator.
Article Details
References
Abdullah, N. S. S., Majid, M. Z. A., & Shahid, S. (2022). Learning of higher education and economic growth in Malaysia. International Journal of Academic Research in Business and Social Sciences, 12(6). https://doi.org/10.6007/ijarbss/v12-i6/13948
Abdulrahman, K. A. B., Alshehri, A. S., Alkhalifah, K. M., Alasiri, A., Aldayel, M. S., Alahmari, F. S., Alothman, A. M., & Alfadhel, M. A. (2023). The relationship between motivation and academic performance among medical students in Riyadh. Cureus. https://doi.org/10.7759/cureus.46815
Ali, F., Yasar, B., Khan, U., Ali, L., & Ryu, K. (2024). Can the compulsive use of e-learning lead to lower academic performance? The role of technology fatigue and technostress in hospitality and tourism students. Journal of Hospitality Leisure Sport & Tourism Education, 34, 100478. https://doi.org/10.1016/j.jhlste.2024.100478
Ali, S. I., Devi, V. A., & Kharbanda, M. (2022). Influence of television on procrastination amongst students. Studies in Media and Communication, 10(1), 104. https://doi.org/10.11114/smc.v10i1.5429
Alloway, T. P., & Alloway, R. G. (2009). Investigating the predictive roles of working memory and IQ in academic attainment. Journal of Experimental Child Psychology, 106(1), 20–29. https://doi.org/10.1016/j.jecp.2009.11.003
Al-Maskari, A., Al-Riyami, T., & Kunjumuhammed, S. K. (2021). Students academic and social concerns during COVID-19 pandemic. Education and Information Technologies, 27(1), 1–21. https://doi.org/10.1007/s10639-021-10592-2
Alyami, A., Abdulwahed, A., Azhar, A., Binsaddik, A., & Bafaraj, S. M. (2021). Impact of time management on the student's academic performance: a cross-sectional study. Creative Education, 12(03), 471–485. https://doi.org/10.4236/ce.2021.123033
Alzabidi, T., Sahari, N. M., & Saleh, R. R. (2024). Academic performance and academic self-efficacy among pre-university students in Malaysia. IIUM Journal of Educational Studies, 12(1), 4–23. https://doi.org/10.31436/ijes.v12i1.455
Amin, M. R. M., Ismail, I., & Sivakumaran, V. M. (2025). Revolutionizing education with artificial intelligence (ai)? challenges, and implications for open and distance learning (ODL). Social Sciences & Humanities Open, 11, 101308. https://doi.org/10.1016/j.ssaho.2025.101308
Anthonysamy, L., Koo, A. C., & Hew, S. H. (2020). Self-regulated learning strategies in higher education: Fostering digital literacy for sustainable lifelong learning. Education and Information Technologies, 25(4), 2393–2414. https://doi.org/10.1007/s10639-020-10201-8
Aziz, N. N. A., Kader, M. A. R. A., & Halim, R. A. (2021). The impact of technostress on student satisfaction and performance expectancy. Asian Journal of University Education, 17(4), 538. https://doi.org/10.24191/ajue.v17i4.16466
Bell, E., & Bryman, A. (2006). the ethics of management research: an exploratory content analysis. British Journal of Management, 18(1), 63–77. https://doi.org/10.1111/j.1467-8551.2006.00487.x
Bevens, W., Stoeckl, S. E., Schueller, S. M., Kim, J., Cha, B. S., Chwa, C., Stadnick, N. A., Best, N. C., & Sorkin, D. H. (2024). Loneliness, online learning and student outcomes in college students living with disabilities: results from the National College Health Assessment Spring 2022. Frontiers in Psychology, 15. https://doi.org/10.3389/fpsyg.2024.1408837
Britton, B. K., & Tesser, A. (1991). Effects of time-management practices on college grades. Journal of Educational Psychology, 83(3), 405–410. https://doi.org/10.1037/0022-0663.83.3.405
Broadbent, J., Panadero, E., Lodge, J. M., & Fuller-Tyszkiewicz, M. (2022). The self-regulation for learning online (SRL-O) questionnaire. Metacognition and Learning, 18(1), 135–163. https://doi.org/10.1007/s11409-022-09319-6
Brod, C. (1982). Managing technostress: optimizing the use of computer technology. PubMed, 61(10), 753–757. https://pubmed.ncbi.nlm.nih.gov/10258012
Buchanan, R., & Mooney, E. (2022). Unpacking moments of success in teacher Education: Discovery of nuance through Collaborative Self-Study. Studying Teacher Education, 19(1), 5–23. https://doi.org/10.1080/17425964.2022.2095509
Califf, C. B., & Brooks, S. (2020). An empirical study of techno-stressors, literacy facilitation, burnout, and turnover intention as experienced by K-12 teachers. Computers & Education, 157, 103971. https://doi.org/10.1016/j.compedu.2020.103971
Calonia, J. T., Pagente, D. P., Desierto, D. J. C., Capio, R. T., Tembrevilla, J. a. P., Guzman, C. A., & Nicor, A. J. S. (2023). Time management and academic achievement: examining the roles of prioritization, procrastination and socialization. Zenodo (CERN European Organization for Nuclear Research). https://doi.org/10.5281/zenodo.8115965
Cao, X., Wu, Y., Cheng, B., & Ali, A. (2023). An investigation of the social media overload and academic performance. Education and Information Technologies, 29(8), 10303–10328. https://doi.org/10.1007/s10639-023-12213-6
Cataldo, A., Bravo-Adasme, N., Araya, P., & Ormeño, V. (2023). Why university students are technostressed with remote classes: Study-Family conflict, satisfaction with university life, and academic performance. Telematics and Informatics, 80, 101982. https://doi.org/10.1016/j.tele.2023.101982
Chan, T. J., & Dai, M. (2023). Factors influencing academic achievement of university students. Journal of Communication, Language and Culture, 3(2), 14–26. https://doi.org/10.33093/jclc.2023.3.2.2
Chen, C., Bian, F., & Zhu, Y. (2023). The relationship between social support and academic engagement among university students: the chain mediating effects of life satisfaction and academic motivation. BMC Public Health, 23(1). https://doi.org/10.1186/s12889-023-17301-3
Cheng, S., & Chiang, J. C. (2019). Roles and Contributions of Private Tertiary Education in Malaysia.
Claessens, B. J., Van Eerde, W., Rutte, C. G., & Roe, R. A. (2007). A review of the time management literature. Personnel Review, 36(2), 255–276. https://doi.org/10.1108/00483480710726136
Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159. https://doi.org/10.1037/0033-2909.112.1.155
Córdova, A., Caballero-García, A., Drobnic, F., Roche, E., & Noriega, D. C. (2023). Influence of stress and emotions in the learning process: The example of COVID-19 on University Students: A Narrative review. Healthcare, 11(12), 1787. https://doi.org/10.3390/healthcare11121787
Covey, S. R. (1989). The 7 Habits of Highly Effective People Personal Workbook. http://perpus.univpancasila.ac.id/index.php?p=show_detail&id=124415
Credé, M., & Kuncel, N. R. (2008). Study Habits, Skills, and Attitudes: the third pillar supporting collegiate academic performance. Perspectives on Psychological Science, 3(6), 425–453. https://doi.org/10.1111/j.1745-6924.2008.00089.x
Credé, M., Roch, S. G., & Kieszczynka, U. M. (2010). Class attendance in college. Review of Educational Research, 80(2), 272–295. https://doi.org/10.3102/0034654310362998
Demerouti, E., & Bakker, A. B. (2011). The Job Demands–Resources model: Challenges for future research. SA Journal of Industrial Psychology, 37(2). https://doi.org/10.4102/sajip.v37i2.974
Demerouti, E., Bakker, A. B., Nachreiner, F., & Schaufeli, W. B. (2001). The job demands-resources model of burnout. Journal of Applied Psychology, 86(3), 499–512. https://doi.org/10.1037/0021-9010.86.3.499
Dubovi, I., & Tabak, I. (2020). An empirical analysis of knowledge co-construction in YouTube comments. Computers & Education, 156, 103939. https://doi.org/10.1016/j.compedu.2020.103939
Fernández-Fernández, M., Martínez-Navalón, J., Gelashvili, V., & Román, C. P. (2023). The impact of teleworking technostress on satisfaction, anxiety, and performance. Heliyon, 9(6),e17201. https://doi.org/10.1016/j.heliyon.2023.e17201
Galvin, J., Evans, M. S., Nelson, K., Richards, G., Mavritsaki, E., Giovazolias, T., Koutra, K., Mellor, B., Zurlo, M. C., Smith, A. P., & Vallone, F. (2022). Technostress, coping, and anxious and depressive symptomatology in university students during the Covid-19 pandemic. Europe's Journal of Psychology, 18(3), 302–318. https://doi.org/10.5964/ejop.4725
Gopalan, M., & Brady, S. T. (2019). College Students' Sense of Belonging: A National perspective. Educational Researcher, 49(2), 134–137. https://doi.org/10.3102/0013189x19897622
Grandhi, S. A., Jones, Q., & Hiltz, S. R. (2009). Technology overload: Is there a technological panacea? AIS Electronic Library (AISeL). https://aisel.aisnet.org/amcis2005/493
Hair, J. F. (2010). Multivariate data analysis: a global perspective. In Pearson eBooks. https://ci.nii.ac.jp/ncid/BB03463866
Haleem, A., Javaid, M., Qadri, M. A., & Suman, R. (2022). Understanding the role of digital technologies in education: A review. Sustainable Operations and Computers, 3, 275–285. https://doi.org/10.1016/j.susoc.2022.05.004
Hamid, H. A. (2022). Malaysian Higher Education and Economic Growth: A Causality analysis. http://www.krinstitute.org/
Hanaysha, J. R., Shriedeh, F. B., & In'airat, M. (2023). Impact of classroom environment, teacher competency, information and communication technology resources, and university facilities on student engagement and academic performance. International Journal of Information Management Data Insights, 3(2), 100188. https://doi.org/10.1016/j.jjimei.2023.100188
Hernandez, A., Busquets, P., Jimenez, R., & Scanlan, J. (2024). Mood states and academic performance in the objective structured clinical examination. The mediating effect of self-efficacy. Nurse Education Today, 135, 106116. https://doi.org/10.1016/j.nedt.2024.106116
Honicke, T., & Broadbent, J. (2015). The influence of academic self-efficacy on academic performance: A systematic review. Educational Research Review, 17, 63–84. https://doi.org/10.1016/j.edurev.2015.11.002
Hussain, M. a. M. B., Jegatheswaran, L., & Mohamed, H. M. (2023). A qualitative study on post pandemic mental health of private university students in Klang Valley. International Journal of Academic Research in Progressive Education and Development, 12(2). https://doi.org/10.6007/ijarped/v12-i2/17301
Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607–610. https://doi.org/10.1177/001316447003000308
Kuadey, N. A., Ankora, C., Tahiru, F., Bensah, L., Agbesi, C. C. M., & Bolatimi, S. O. (2023). Using machine learning algorithms to examine the impact of technostress creators on student learning burnout and perceived academic performance. International Journal of Information Technology, 16(4), 2467–2482. https://doi.org/10.1007/s41870-023-01655-3
Kuh, G. D., Kinzie, J., Buckley, J. A., Bridges, B. K., Hayek, J. C., & Indiana University Bloomington. (2006). What matters to student success: A review of the literature. https://nces.ed.gov/npec/pdf/kuh_team_execsumm.pdf
Kulikowski, K., Przytula, S., Sulkowski, L., & Rašticová, M. (2022). Technostress of students during COVID-19-a sign of the time?. Human Technology, 18(3), 234-249.
Kumar, P. S. (2024). TECHNOSTRESS: A comprehensive literature review on dimensions, impacts, and management strategies. Computers in Human Behavior Reports, 16, 100475. https://doi.org/10.1016/j.chbr.2024.100475
Lesener, T., Pleiss, L. S., Gusy, B., & Wolter, C. (2020). The Study Demands-Resources Framework: An Empirical Introduction. International Journal of Environmental Research and Public Health, 17(14), 5183. https://doi.org/10.3390/ijerph17145183
Liu, M. (2022). The Relationship between Students' Study Time and Academic Performance and its Practical Significance. BCP Education & Psychology, 7, 412–415. https://doi.org/10.54691/bcpep.v7i.2696
Madani, H. E., Aarab, C., Tachfouti, N., Fakir, S. E., Aalouane, R., & Berraho, M. (2024). Correlates of perceived stress with anxiety symptoms sleep quality and academic performance among Moroccan students. Educación Médica, 25(6), 100953. https://doi.org/10.1016/j.edumed.2024.100953
Mahapatra, H., Bankira, S., Sahoo, N. K., & Bhuyan, S. (2023). Relationship between Techno Stress and Academic Performance of University Students. Journal of Education Society and Behavioural Science, 36(10), 45–55. https://doi.org/10.9734/jesbs/2023/v36i101266
Malaysia Indicator. (2019, September 13). Selangor has the highest number of higher education institutes in Malaysia, with 149 IPTSs. https://malaysiaindicator.com/selangor-houses-the-highest-number-of-higher-education-institute-in-malaysia-with-149-iptss/
Ministry of Education. (2013). Malaysia Education Blueprint 2013 - 2025. In Executive Summary.
Molino, M., Ingusci, E., Signore, F., Manuti, A., Giancaspro, M. L., Russo, V., Zito, M., & Cortese, C. G. (2020). Wellbeing Costs of Technology Use during Covid-19 Remote Working: An Investigation Using the Italian Translation of the Technostress Creators Scale. Sustainability, 12(15), 5911. https://doi.org/10.3390/su12155911
Moussa, N. M., & Ali, W. F. (2021). Exploring the relationship between students' academic success and happiness levels in the higher education settings during the lockdown period of COVID-19. Psychological Reports, 125(2), 986–1010. https://doi.org/10.1177/0033294121994568
Odum, M., Meaney, K. S., & Knudson, D. V. (2021, February 5). Active learning classroom design and student engagement: An exploratory study. Odum | Journal of Learning Spaces. https://libjournal.uncg.edu/jls/article/view/2102
Ragu-Nathan, T. S., Tarafdar, M., Ragu-Nathan, B. S., & Tu, Q. (2008). The consequences of technostress for end users in Organizations: Conceptual development and empirical validation. Information Systems Research, 19(4), 417–433. https://doi.org/10.1287/isre.1070.0165
Rajamanikam, S. (2023). The drawbacks of online hybrid education in Malaysia. International Journal of Advanced Research in Education and Society. https://doi.org/10.55057/ijares.2023.5.3.33
Ren, X., Tong, Y., Peng, P., & Wang, T. (2020). Critical thinking predicts academic performance beyond general cognitive ability: Evidence from adults and children. Intelligence, 82, 101487. https://doi.org/10.1016/j.intell.2020.101487
Sabbott. (2016, February 18). Student Engagement Definition. The Glossary of Education Reform. https://www.edglossary.org/student-engagement/?utm_source
Sajeevanie, T. L. (2020). Prioritization and academic success of the university lecturers in state universities in Sri Lanka.. In Asian Journal of Management Sciences & Education.
Saleem, F., Chikhaoui, E., & Malik, M. I. (2024). Technostress in students and quality of online learning: role of instructor and university support. Frontiers in Education, 9. https://doi.org/10.3389/feduc.2024.1309642
Salmela-Aro, K., Tang, X., & Upadyaya, K. (2022b). Study Demands-Resources Model of student engagement and burnout. In Springer eBooks (pp. 77–93). https://doi.org/10.1007/978-3-031-07853-8_4
Schnitzler, K., Holzberger, D., & Seidel, T. (2020). All better than being disengaged: Student engagement patterns and their relations to academic self-concept and achievement. European Journal of Psychology of Education, 36(3), 627–652. https://doi.org/10.1007/s10212-020-00500-6
Schwerter, J., Stang-Rabrig, J., Kleinkorres, R., Bleher, J., Doebler, P., & McElvany, N. (2024). Importance of students' social resources for their academic achievement and well-being in elementary school. European Journal of Psychology of Education, 39(4), 4515–4552. https://doi.org/10.1007/s10212-024-00877-8
Shahzad, M. F., Xu, S., Lim, W. M., Yang, X., & Khan, Q. R. (2024). Artificial intelligence and social media on academic performance and mental well-being: Student perceptions of positive impact in the age of smart learning. Heliyon, 10(8), e29523. https://doi.org/10.1016/j.heliyon.2024.e29523
Shi, Y., & Qu, S. (2022). Analysis of the effect of cognitive ability on academic achievement: Moderating role of self-monitoring. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.996504
Sirin, S. R. (2005). Socioeconomic Status and Academic Achievement: A Meta-Analytic Review of Research. Review of Educational Research, 75(3), 417–453. https://doi.org/10.3102/00346543075003417
Sukor, R., Ayub, A. F. M., Rashid, N. K. M. a. R. A., & Halim, F. A. (2021). Relationship Between Students Engagement with Academic Performance Among Non-Food Science Students Enrolled in Food Science Course. Journal of Turkish Science Education, 18(4), 638–648. https://doi.org/10.36681/tused.2021.95
Tan, E. W., & Prihadi, K. D. (2022). Fear of failure and academic procrastination among university students: The role of achievement expectancy and year of study. International Journal of Evaluation and Research in Education (IJERE), 11(1), 69. https://doi.org/10.11591/ijere.v11i1.22201
Turnbull, D., Chugh, R., & Luck, J. (2023). Learning management systems and social media: a case for their integration in higher education institutions. Research in Learning Technology, 31. https://doi.org/10.25304/rlt.v31.2814
Upadhyaya, P., & Vrinda, N. (2020). Impact of technostress on academic productivity of university students. Education and Information Technologies, 26(2), 1647–1664. https://doi.org/10.1007/s10639-020-10319-9
Wang, X., & Wang, Y. (2024). The impact of perceived social support on e-learning engagement among college students: serial mediation of growth mindset and subjective well-being. European Journal of Psychology of Education, 39(4), 4163–4180. https://doi.org/10.1007/s10212-024-00853-2
Wang, X., Li, Z., Ouyang, Z., & Xu, Y. (2021). The Achilles heel of technology: How does technostress affect university students' wellbeing and Technology-Enhanced learning. International Journal of Environmental Research and Public Health, 18(23), 12322. https://doi.org/10.3390/ijerph182312322
Wang, X., Tan, S. C., & Li, L. (2020). Measuring university students' technostress in technology-enhanced learning: Scale development and validation. Australasian Journal of Educational Technology, 96–112. https://doi.org/10.14742/ajet.5329
Weidman, J. C. (2020). Conceptualizing student socialization in Higher Education: an intellectual journey. In Knowledge studies in higher education (pp. 11–28). https://doi.org/10.1007/978-3-030-33350-8_2
Wolters, C. A., & Brady, A. C. (2020). College Students' Time Management: a Self-Regulated Learning Perspective. Educational Psychology Review, 33(4), 1319–1351. https://doi.org/10.1007/s10648-020-09519-z
Wong, S. S., Wong, C. C., Ng, K. W., Bostanudin, M. F., & Tan, S. F. (2023). Depression, anxiety, and stress among university students in Selangor, Malaysia during COVID-19 pandemics and their associated factors. PLoS ONE, 18(1), e0280680. https://doi.org/10.1371/journal.pone.0280680
Xu, L., Duan, P., Padua, S. A., & Li, C. (2022). The impact of self-regulated learning strategies on academic performance for online learning during COVID-19. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.1047680
Yoel, S. R., Akiri, E., & Dori, Y. J. (2022). Fostering graduate students' interpersonal communication skills via online group interactions. Journal of Science Education and Technology, 32(6), 931–950. https://doi.org/10.1007/s10956-022-09998-5
Zhao, G., Wang, Q., Wu, L., & Dong, Y. (2021). Exploring the structural relationship between university support, students' technostress, and burnout in technology-enhanced learning. The Asia-Pacific Education Researcher, 31(4), 463–473. https://doi.org/10.1007/s40299-021-00588-4
Zimmerman, B. J. (1989). A social cognitive view of self-regulated academic learning. Journal of Educational Psychology, 81(3), 329–339. https://doi.org/10.1037/0022-0663.81.3.329