quantitative research about time management of students

Accessibility Links

• Skip to content
• Skip to search IOPscience
• Skip to Journals list
• Accessibility help
• Accessibility Help

Click here to close this panel.

Purpose-led Publishing is a coalition of three not-for-profit publishers in the field of physical sciences: AIP Publishing, the American Physical Society and IOP Publishing.

Together, as publishers that will always put purpose above profit, we have defined a set of industry standards that underpin high-quality, ethical scholarly communications.

We are proudly declaring that science is our only shareholder.

The Impact of Time Management on Students' Academic Achievement

S N A M Razali 1 , M S Rusiman 1 , W S Gan 1 and N Arbin 2

Published under licence by IOP Publishing Ltd Journal of Physics: Conference Series , Volume 995 , International Seminar on Mathematics and Physics in Sciences and Technology 2017 (ISMAP 2017) 28–29 October 2017, Hotel Katerina, Malaysia Citation S N A M Razali et al 2018 J. Phys.: Conf. Ser. 995 012042 DOI 10.1088/1742-6596/995/1/012042

Article metrics

113185 Total downloads

Share this article

Author affiliations.

1 Department of Mathematics and Statistic, Faculty of Applied Science and Technology University Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia.

2 Department of Mathematic, Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris, 35900 Perak, Malaysia.

Buy this article in print

Time management is very important and it may actually affect individual's overall performance and achievements. Students nowadays always commented that they do not have enough time to complete all the tasks assigned to them. In addition, a university environment's flexibility and freedom can derail students who have not mastered time management skills. Therefore, the aim of this study is to determine the relationship between the time management and academic achievement of the students. The factor analysis result showed three main factors associated with time management which can be classified as time planning, time attitudes and time wasting. The result also indicated that gender and races of students show no significant differences in time management behaviours. While year of study and faculty of students reveal the significant differences in the time management behaviours. Meanwhile, all the time management behaviours are significantly positively related to academic achievement of students although the relationship is weak. Time planning is the most significant correlated predictor.

Export citation and abstract BibTeX RIS

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence . Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

College Students’ Time Management: a Self-Regulated Learning Perspective

• Review Article
• Published: 27 October 2020
• Volume 33 , pages 1319–1351, ( 2021 )

Cite this article

• Christopher A. Wolters   ORCID: orcid.org/0000-0002-8406-038X 1 &
• Anna C. Brady 1  

26k Accesses

59 Citations

10 Altmetric

Explore all metrics

Despite its recognized importance for academic success, much of the research investigating time management has proceeded without regard to a comprehensive theoretical model for understanding its connections to students’ engagement, learning, or achievement. Our central argument is that self-regulated learning provides the rich conceptual framework necessary for understanding college students’ time management and for guiding research examining its relationship to their academic success. We advance this larger purpose through four major sections. We begin by describing work supporting the significance of time management within post-secondary contexts. Next, we review the limited empirical findings linking time management and the motivational and strategic processes viewed as central to self-regulated learning. We then evaluate conceptual ties between time management and processes critical to the forethought, performance, and post-performance phases of self-regulated learning. Finally, we discuss commonalities in the antecedents and contextual determinants of self-regulated learning and time management. Throughout these sections, we identify avenues of research that would contribute to a greater understanding of time management and its fit within the framework of self-regulated learning. Together, these efforts demonstrate that time management is a significant self-regulatory process through which students actively manage when and for how long they engage in the activities deemed necessary for reaching their academic goals.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Similar content being viewed by others

Examining the relations of time management and procrastination within a model of self-regulated learning

Willing, able, and engaged: roles of action-state orientation, intrinsic academic motivation, and time management on academic engagement

Are Mastery-Oriented College Students Better Time Managers?

Adams, G. A., & Jex, S. M. (1999). Relationships between time management, control, work family conflict, and strain. Journal of Occupational Health Psychology, 4 (1), 72–77.

Google Scholar  

Aeon, B., & Aguinis, H. (2017). It’s about time: new perspectives and insights on time management. Academy of Management Perspectives, 31 , 309–330.

Ames, C. (1992). Classrooms: goals, structures, and student motivation. Journal of Educational Psychology, 84 , 261–271.

Asikainen, H., & Gijbels, D. (2017). Do students develop towards more deep approaches to learning during studies? A systematic review on the development of students’ deep and surface approaches to learning in higher education. Educational Psychology Review, 29 , 205–234.

Balduf, M. (2009). Underachievement among college students. Journal of Advanced Academics, 20 , 274–294.

Banahan, L., & Mullendore, R. (2014). Navigating the first college year. A guide for parents and families . Columbia: University of South Carolina, National Resource Center for The First-Year Experience and Students in Transition.

Bandura, A. (1986). The explanatory and predictive scope of self-efficacy theory. Journal of Social and Clinical Psychology, 4 , 359–373.

Bartels, J. M., Magun-Jackson, S., & Ryan, J. J. (2010). Dispositional approach-avoidance achievement motivation and cognitive self-regulated learning: the mediation of achievement goals. Individual Differences Research, 8 , 97–110.

Basila, C. (2014). Good time management and motivation level predict student academic success in college on-line courses. International Journal of Cyber Behavior, Psychology and Learning, 4 , 45–52.

Bembenutty, H. (2009). Academic delay of gratification, self-regulation of learning, gender differences, and expectancy-value. Personality and Individual Differences, 46 , 347–352.

Beuhler, R., Griffin, D., & Peetz, J. (2010). The planning fallacy: cognitive, motivational, and social origins. Advances in Experimental Social Psychology, 43 , 1–62.

Bidjerano, T., & Dai, D. Y. (2007). The relationship between the big-five model of personality and self-regulated learning strategies. Learning and Individual Differences, 17 , 69–81.

Boekaerts, M. (1996). Self-regulated learning at the junction of cognition and motivation. European Psychologist, 1 , 100–112.

Boekaerts, M., & Corno, L. (2005). Self-regulation in the classroom: a perspective on assessment and intervention. Applied Psychology: An International Review, 54 , 199–231.

Bond, M. J., & Feather, N. T. (1988). Some correlates of structure and purpose in the use of time. Journal of Personality and Social Psychology, 55 , 321–329.

Britton, B. K., & Glynn, S. M. (1989). Mental management and creativity: a cognitive model of time management for intellectual productivity. In J. Glover, R. Ronning, & C. Reynolds (Eds.), Handbook of creativity (pp. 429–440). New York: Plenum.

Britton, B. K., & Tesser, A. (1991). Effects of time-management practices on college grades. Journal of Educational Psychology, 83 , 405–410.

Buehler, R., & Griffin, D. (2015). When plans lead to optimistic forecasts. In M. D. Mumford & M. Frese (Eds.), The psychology in planning in organizations: research and applications (pp. 31–57). New York: Routledge.

Burlison, J. D., Murphy, C. S., & Dwyer, W. O. (2009). Evaluation of the Motivated Strategies for Learning Questionnaire for predicting academic performance in college students of varying scholastic aptitude. College Student Journal, 43 , 1313–1323.

Burnette, J., O’Boyle, E., VanEpps, E., Pollack, J., & Finkel, E. (2013). Mind-sets matter: a meta-analytic review of implicit theories and self-regulation. Psychological Bulletin, 139 (3), 655–701.

Burt, C. D., Weststrate, A., Brown, C., & Champion, F. (2010). Development of the time management environment (TiME) scale. Journal of Managerial Psychology, 25 , 649–668.

Butler, D., & Winne, P. (1995). Feedback and self-regulated learning: a theoretical synthesis. Review of Educational Research, 65 , 245–281.

Cano, F. (2006). An in-depth analysis of the Learning and Study Strategies Inventory (LASSI). Educational and Psychological Measurement, 66 , 1023–1038.

Capdeferro, N., Romero, M., & Barberà, E. (2014). Polychronicity: review of the literature and a new configuration for the study of this hidden dimension of online learning. Distance Education, 35 , 294–310.

Cassidy, S. (2011). Self-regulated learning in higher education: identifying key component processes. Studies in Higher Education, 36 , 989–1000.

Chang, A., & Nguyen, L. T. (2011). The mediating effects of time structure on the relationships between time management behaviour, job satisfaction, and psychological well-being. Australian Journal of Psychology, 63 , 187–197.

Choi, B. (2016). How people learn in an asynchronous online learning environment: the relationships between graduate students’ learning strategies and learning satisfaction. Canadian Journal of Learning and Technology, 42 , 1–15.

Chuderski, A. (2016). Time pressure prevents relational learning. Learning and Individual Differences, 49 , 361–365.

Claessens, B. J. C., van Eerde, W., Rutte, C. G., & Roe, R. A. (2007). A review of the time management literature. Personnel Review, 36 , 255–276.

Conti, R. (2001). Time flies: investigating the connection between intrinsic motivation and the experience of time. Journal of Personality, 69 (1), 1–26.

Corno, L., Cronbach, L. J., Kupermintz, H., Lohman, D. F., Mandinach, E. B., Porteus, A. W., & Talbert, J. E. (2002). Remaking the concept of aptitude: extending the legacy of Richard E Snow . Mahwah: Lawrence Erlbaum Associates Publishers.

Crede, 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.

Crede, M., & Phillips, L. A. (2011). A meta-analytic review of the Motivated Strategies for Learning Questionnaire. Learning and Individual Differences, 21 , 337–346.

Crede, M., Roch, S. G., & Kieszczynka, U. M. (2010). Class attendance in college: a meta-analytic review of the relationship of class attendance with grades and student characteristics. Review of Educational Research, 80 , 272–295.

Csikszentmihalyi, M. (1996). Creativity: flow and the psychology of discovery and invention . New York: HarperCollins Publishers.

Dembo, M. H., & Eaton, M. J. (2000). Self-regulation of academic learning in middle-level schools. The Elementary School Journal, 100 , 473–490.

Dent, A., & Koenka, A. (2016). The relation between self-regulated learning and academic achievement across childhood and adolescence: a meta-analysis. Educational Psychology Review, 28 , 425–474.

Díaz-Morales, J. F., Ferrari, J. R., & Cohen, J. R. (2008). Indecision and avoidant procrastination: the role of morningness—eveningness and time perspective in chronic delay lifestyles. The Journal of General Psychology, 135 (3), 228–240.

Donker, A., de Boer, H., Kostons, D., Dignath van Ewijk, C., & van der Werf, M. (2014). Effectiveness of learning strategy instruction on academic performance: a meta-analysis. Educational Psychology Review, 11 , 1–26.

Douglas, H. E., Bore, M., & Munro, D. (2016). Coping with university education: the relationships of time management behaviour and work engagement with the five factor model aspects. Learning and Individual Differences, 45 , 268–274.

Doumen, S., Broeckmans, J., & Masui, C. (2014). The role of self-study time in freshmen’s achievement. Educational Psychology, 34 , 385–402.

Duncan, T. G., & McKeachie, W. J. (2005). The making of the motivated strategies for learning questionnaire. Educational Psychologist, 40 , 117–128.

Duncheon, J. C., & Tierney, W. G. (2013). Changing conceptions of time: implications for educational research and practice. Review of Educational Research, 83 , 236–272.

Dunlosky, J., & Ariel, R. (2011). Self-regulated learning and the allocation of study time. In B. Ross (Ed.), Psychology of learning and motivation (Vol. 54, pp. 103–140). San Diego: Academic Press.

Dunning, D., Heath, C., & Suls, J. (2004). Flawed self-assessments. Psychological Science in the Public Interest, 5 (3), 69–106.

Efklides, A. (2011). Interactions of metacognition with motivation and affect in self-regulated learning: the MASRL model. Educational Psychologist, 46 , 6–25.

Eilam, B., & Aharon, I. (2003). Students’ planning in the process of self-regulated learning. Contemporary Educational Psychology, 28 , 304–334.

Ferrari, J. R., & Díaz-Morales, J. F. (2007). Procrastination: different time orientations reflect different motives. Journal of Research in Personality, 41 , 707–714.

Flake, J. K., Barron, K. E., Hulleman, C., McCoach, B. D., & Welsh, M. E. (2015). Measuring cost: the forgotten component of expectancy-value theory. Contemporary Educational Psychology, 41 , 232–244.

Flanigan, A. E., & Kiewra, K. A. (2018). What college instructors can do about student cyber-slacking. Educational Psychology Review, 30 , 585–597.

Francis-Smythe, J. A., & Robertson, I. T. (1999a). On the relationship between time management and time estimation. British Journal of Psychology, 90 , 333–347.

Francis-Smythe, J. A., & Robertson, I. T. (1999b). Time-related individual differences. Time & Society, 8 , 273–292.

Fromme, K., Corbin, W., & Kruse, M. (2008). Behavioral risks during the transition from high school to college. Developmental Psychology, 44 (5), 1497–1504.

Gable, P. A., & Poole, B. D. (2012). Time flies when you’re having approach-motivated fun: effects of motivational intensity on time perception. Psychological Science, 23 (8), 879–886.

Gevers, J. M., Rutte, C. G., & Van Eerde, W. (2006). Meeting deadlines in work groups: implicit and explicit mechanisms. Applied Psychology, 55 , 52–72.

Green, P., & Skinner, D. (2005). Does time management training work? An evaluation. International Journal of Training and Development, 9 , 124–139.

Gulec, M., Selvi, Y., Boysan, M., Aydin, A., Oral, E., & Aydin, E. F. (2013). Chronotype effects on general well-being and psychopathology levels in healthy young adults. Biological Rhythm Research, 44 , 457–468.

Guzman, G., Goldberg, T., & Swanson, H. (2018). A meta-analysis of self-monitoring on reading performance of K-12 students. School Psychology Quarterly, 33 (1), 160–168.

Hadwin, A., & Oshige, M. (2011). Self-regulation, coregulation, and socially shared regulation: exploring perspectives of social in self-regulated learning theory. Teachers College Record, 113 , 240–264.

Hafner, A., Stock, A., Pinneker, L., & Strohle, S. (2014). Stress prevention through a time management training intervention: an experimental study. Educational Psychology, 34 , 403–416.

Hahn, C., Cowell, J. M., Wiprzycka, U. J., Goldstein, D., Ralph, M., Hasher, L., & Zelazo, P. D. (2012). Circadian rhythms in executive function during the transition to adolescence: the effect of synchrony between chronotype and time of day. Developmental Science, 15 (3), 408–416.

Harkin, B., Webb, T. L., Chang, B. P. I., Prestwich, A., Conner, M., Kellar, I., et al. (2016). Does monitoring goal progress promote goal attainment? A meta-analysis of the experimental evidence. Psychological Bulletin, 142 (2), 198–229.

Hattie, J., Biggs, J., & Purdie, N. (1996). Effects of learning skills interventions on student learning: a meta-analysis. Review of Educational Research, 66 , 99–136.

Haynes, N., Comer, J., & Hamilton-Lee, M. (1988). Gender and achievement status differences on learning factors among Black high school students. Journal of Educational Research, 81 , 233–237.

Hensley, L. C., Wolters, C. A., Won, S., & Brady, A. C. (2018). Academic probation, time management, and time use in a college success course. Journal of College Reading and Learning, 48 , 105–123.

Hicks, T., & Heastie, S. (2008). High school to college transition: a profile of the stressors, physical and psychological health issues that affect the first-year on-campus college students. Journal of Cultural Diversity, 15 (3), 143–147.

Hilbrecht, M., Zuzanek, J., & Mannell, R. C. (2008). Time use, time pressure and gendered behavior in early and late adolescence. Sex Roles, 58 , 342–357.

Hofer, B. K., Yu, S. L., & Pintrich, P. R. (1998). Teaching college students to be self-regulated learners. In D. H. Schunk & B. J. Zimmerman (Eds.), Self-regulated learning: from teaching to self-reflective practice (pp. 57–85). New York: Guilford Press.

Horstmanshof, L., & Zimitat, C. (2007). Future time orientation predicts academic engagement among first-year university students. British Journal of Educational Psychology, 77 (Pt 3), 703–718.

Huie, F. C., Winsler, A., & Kitsantas, A. (2014). Employment and first-year college achievement: the role of self-regulation and motivation. Journal of Education and Work, 27 , 110–135.

Husman, J., & Lens, W. (1999). The role of the future in student motivation. Educational Psychologist, 34 , 113–125.

Kanfer, R., Frese, M., & Johnson, R. (2017). Motivation related to work: a century of progress. Journal of Applied Psychology, 102 (3), 338–355.

Kantrowitz, T. M., Grelle, D. M., Beaty, J. C., & Wolf, M. B. (2012). Time is money: polychronicity as a predictor of performance across job levels. Human Performance, 25 , 114–137.

Kauderer, S., & Randler, C. (2013). Differences in time use among chronotypes in adolescents. Biological Rhythm Research, 44 , 601–608.

Kaufman-Scarborough, C., & Lindquist, J. D. (1999). Time management and polychronicity: comparisons, contrasts, and insights for the workplace. Journal of Managerial Psychology, 14 , 288–312.

Keating, D. P. (2012). Cognitive and brain development in adolescence. Enfance, 64 , 267–279.

Kesici, Ş., Baloğlu, M., & Deniz, M. E. (2011). Self-regulated learning strategies in relation with statistics anxiety. Learning and Individual Differences, 21 , 472–477.

Kim, K. R., & Seo, E. H. (2015). The relationship between procrastination and academic performance: a meta-analysis. Personality and Individual Differences, 82 , 26–33.

Kitsantas, A., Winsler, A., & Huie, F. (2008). Self-regulation and ability predictors of academic success during college: a predictive validity study. Journal of Advanced Academics, 20 , 42–68.

Koch, C. J., & Kleinmann, M. (2002). A stitch in time saves nine: behavioural decision-making explanations for time management problem. European Journal of Work and Organizational Psychology, 11 , 199–217.

Komarraju, M., Karau, S. J., & Schmeck, R. R. (2009). Role of the Big Five personality traits in predicting college students’ academic motivation and achievement. Learning and Individual Differences, 19 , 47–52.

Konig, C. J., & Waller, M. J. (2010). Time for reflection: a critical examination of polychronicity. Human Performance, 23 , 173–190.

Kooij, D. T. A. M., Kanfer, R., Betts, M., & Rudolph, C. W. (2018). Future time perspective: a systematic review and meta-analysis. Journal of Applied Psychology, 103 (8), 867–893.

Krumrei-Mancuso, E. J., Newton, F. B., Kim, E., & Wilcox, D. (2013). Psychosocial factors predicting first-year college student success. Journal of College Student Development, 54 , 247–266.

Landrum, R. E., Turrisi, R., & Brandel, J. M. (2006). College students’ study time: course level, time of semester, and grade earned. Psychological Reports, 98 (3), 675–682.

Liborius, P., Bellhauser, H., & Schmitz, B. (2017). What makes a good study day? An intraindividual study on university students’ time investment by means of time-series analyses. Learning and Instruction.

Linnenbrink-Garcia, L., & Patall, E. (2016). Motivation. In L. Corno & E. Anderman (Eds.), Handbook of educational psychology (3rd ed., pp. 91–1030). New York: Routledge.

Liu, O. L., Rijmen, F., MacCann, C., & Roberts, R. (2009). The assessment of time management in middle-school students. Personality and Individual Differences, 47 , 174–179.

Locke, E., & Latham, G. (2019). The development of goal setting theory: a half-century retrospective. Motivation Science, 5 , 93–105.

Loureiro, F., & Garcia-Marques, T. (2015). Morning or evening person? Which type are you? Self-assessment of chronotype. Personality and Individual Differences, 86 , 168–171.

Lynch, D. J. (2010). Application of online discussion and cooperative learning strategies to online and blended college courses. College Student Journal, 44 , 920–927.

Macan, T. H. (1994). Time management: test of a process model. Journal of Applied Psychology, 79 , 381–391.

Macan, T. H., Shahani, C., Dipboye, R. L., & Phillips, A. P. (1990). College students’ time management: correlations with academic performance and stress. Journal of Educational Psychology, 82 , 760–768.

MacCann, C., & Roberts, R. D. (2010). Do time management, grit, and self-control relate to academic achievement independently of conscientiousness? In R. E. Hicks (Ed.), Personality and individual differences: current directions (pp. 79–90). Bowen Hills: Australian Academic Press.

MacCann, C., Fogarty, G. J., & Roberts, R. D. (2012). Strategies for success in education: time management is more important for part-time than full-time community college students. Learning and Individual Differences, 22 , 618–623.

McCrae, R., & Lockenhoff, C. (2010). Self-regulation and the five-factor model of personality traits. In R. Hoyle (Ed.), Handbook of personality and self-regulation (pp. 143–168). New York: Wiley.

McInerney, D., & King, R. (2018). Culture and self-regulation in educational contexts. In D. Schunk & J. Greene (Eds.), Handbook of self-regulation of learning and performance (2nd ed., pp. 485–502). New York: Routledge.

Meeuwisse, M., Born, M. P., & Severiens, S. E. (2013). Academic performance differences among ethnic groups: do the daily use and management of time offer explanations? Social Psychology of Education, 16 , 599–615.

Melancon, J. G. (2002). Reliability, structure, and correlates of Learning and Study Strategies Inventory scores. Educational and Psychological Measurement, 62 , 1020–1027.

Miele, D. B., & Scholer, A. A. (2018). The role of metamotivational monitoring in motivation regulation. Educational Psychologist, 53 , 1–21.

Miller, R. B., & Brickman, S. J. (2004). A model of future-oriented motivation and self-regulation. Educational Psychology Review, 16 , 9–33.

Muis, K. R. (2007). The role of epistemic beliefs in self-regulated learning. Educational Psychologist, 42 , 173–190.

Nelson, T., & Narens, L. (1990). Metamemory: a theoretical framework and some new findings. In G. H. Bower (Ed.), The psychology of learning and motivation (pp. 125–173). New York: Academic Press.

Nonis, S., Teng, J., & Ford, C. (2005). A cross-cultural investigation of time management practices and job outcomes. International Journal of Intercultural Relations, 29 , 409–428.

Nonis, S. A., Philhours, M. J., & Hudson, G. I. (2006). Where does the time go? A diary approach to business and marketing students’ time use. Journal of Marketing Education, 28 , 121–134.

Olaussen, B. S., & Bråten, I. (1998). Identifying latent variables measured by the Learning and Study Strategies Inventory (LASSI) in Norwegian college students. The Journal of Experimental Education, 67 , 82–96.

Olejnik, S., & Nist, S. L. (1992). Identifying latent variables measured by the Learning and Study Strategies Inventory (LASSI). The Journal of Experimental Education, 60 , 151–159.

Panadero, E. (2017). A review of self-regulated learning: six models and four directions for research. Frontiers in Psychology, 8 , 1–28.

Panadero, E., Brown, G., & Strijbos, J. (2016). The future of student self-assessment: a review of known and unknowns and potential directions. Educational Psychology Review, 28 (803), 830.

Panek, E. (2014). Left to their own devices: college students’ “guilty pleasure” media use and time management. Communication Research, 41 , 561–577.

Pekrun, R., Goetz, T., Titz, W., & Perry, R. P. (2002). Academic emotions in students’ self-regulated learning and achievement: a program of qualitative and quantitative research. Educational Psychologist, 37 , 91–105.

Pintrich, P. R. (2000). The role of goal orientation in self-regulated learning. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 451–502). San Diego: Academic.

Pintrich, P. R. (2004). A conceptual framework for assessing motivation and self-regulated learning in college students. Educational Psychology Review, 16 , 385–407.

Pintrich, P. R., & Zusho, A. (2007). Student motivation and self-regulated learning in the college classroom. In R. P. Perry & J. C. Smart (Eds.), The scholarship of teaching and learning in higher education: an evidence based perspective (pp. 731–810). New York: Springer.

Pintrich, P. R., Smith, D. A., Garcia, T., & McKeachie, W. J. (1993). Reliability and predictive validity of the Motivated Strategies for Learning Questionnaire. Educational and Psychological Measurement, 53 , 801–813.

Pintrich, P. R., Wolters, C. A., & Baxter, G. P. (2000). Assessing metacognition and self-regulated learning. In G. Schraw & J. Impara (Eds.), Issues in the measurement of metacognition (pp. 43–97). Lincoln: Buros Institute of Mental Measurement.

Plant, E. A., Ericsson, K. A., Hill, L., & Asberg, K. (2005). Why study time does not predict grade point average across college students: implications of deliberate practice for academic performance. Contemporary Educational Psychology, 30 , 96–116.

Prevatt, F., Petscher, Y., Proctor, B. E., Hurst, A., & Adams, K. (2006). The revised Learning and Study Strategies Inventory: an evaluation of competing models. Educational and Psychological Measurement, 66 (3), 448–458.

Pychyl, T. A., Morin, R. W., & Salmon, B. R. (2000). Procrastination and the planning fallacy: an examination of the study habits of university students. Journal of Social Behavior and Personality, 15 , 135–150.

Ranellucci, J., Hall, N. C., & Goetz, T. (2015). Achievement goals, emotions, learning, and performance: a process model. Motivation Science, 1 , 98–120.

Rhodes, M., & Tauber, S. (2011). The influence of delaying judgments of learning on metacognitive accuracy: a meta-analytic review. Psychological Bulletin, 137 (1), 131–148.

Richards, J. H. (1987). Time management—a review. Work & Stress, 1 , 73–78.

Rickert, N. P., Meras, I. L., & Witkow, M. R. (2014). Theories of intelligence and students’ daily self-handicapping behaviors. Learning and Individual Differences, 36 , 1–8.

Roskes, M., Elliot, A. J., Nijstad, B. A., & De Dreu, C. K. (2013). Time pressure undermines performance more under avoidance than approach motivation. Personality and Social Psychology Bulletin, 39 , 803–813.

Rytkonen, H., Parpala, A., Lindblom-Ylanne, S., Virtanen, V., & Postareff, L. (2012). Factors affecting bioscience students’ academic achievement. Instructional Science, 40 , 241–256.

Sanders, L., Reedy, D., & Frizell, M. (Eds.). (2018). Learning centers in the 21 st century: a modern guide for learning assistance professionals in higher education . Bentonville: AR. Iona Press.

Sansgiry, S. S., Bhosle, M., & Sail, K. (2006). Factors that affect academic performance among pharmacy students. American Journal of Pharmaceutical Education, 70 , 1–9.

Schell, K. L., & Conte, J. M. (2008). Associations among polychronicity, goal orientation, and error orientation. Personality and Individual Differences, 44 , 288–298.

Schraw, G. (2006). Knowledge: structures and processes. In P. Alexander & P. Winne (Eds.), Handbook of educational psychology (2nd ed., pp. 245–263). Mahwah: Erlbaum Associates.

Schunk, D. H., & Zimmerman, B. J. (1997). Social origins of self-regulatory competence. Educational Psychologist, 32 , 195–208.

Schunk, D. H., & Zimmerman, B. J. (Eds.). (1998). Self-regulated learning: from teaching to self-reflective practice . New York: Guilford Press.

Sen, S., & Yilmaz, A. (2016). Devising a structural equation model of relationships between preservice teachers’ time and study environment management, effort regulation, self-efficacy, control of learning beliefs, and metacognitive self-regulation. Science Education International, 27 , 301–316.

Shaunessy-Dedrick, E., Suldo, S. M., Roth, R. A., & Fefer, S. A. (2015). Students’ perceptions of factors that contribute to risk and success in accelerated high school courses. The High School Journal, 98 , 109–137.

Shell, D. F., & Husman, J. (2001). The multivariate dimensionality of personal control and future time perspective beliefs in achievement and self-regulation. Contemporary Educational Psychology, 26 (4), 481–506.

Simons, J., Vansteenkiste, M., Lens, W., & Lacante, M. (2004). Placing motivation and future time perspective theory in a temporal perspective. Educational Psychology Review, 16 , 121–139.

Sinatra, G., Kienhues, D., & Hofer, B. (2014). Addressing challenges to public understanding of science: epistemic cognition, motivated reasoning, and conceptual change. Educational Psychologist, 49 , 123–138.

Sirois, F. M. (2014). Procrastination and stress: exploring the role of self-compassion. Self and Identity, 13 , 128–145.

Sitzmann, T., & Ely, K. (2011). A meta-analysis of self-regulated learning in work-related training and educational attainment: what we know and where we need to go. Psychological Bulletin, 137 (3), 421–442.

Sitzmann, T., Ely, K., Brown, K., & Bauer, K. (2010). Self-assessment of knowledge: a cognitive learning or affective measure? Academy of Management Learning & Education, 9 , 169–191.

Snow, R. (1989). Cognitive-conative aptitude interactions in learning. In R. Kanfer, P. Ackerman, & R. Cudeck (Eds.), Abilities, motivation, and methodology: the Minnesota symposium on learning and individual differences (pp. 435–474). Hillsdale: Erlbaum Associates.

Snow, R. E., Corno, L., & Jackson III, D. (1996). Individual differences in affective and conative functions. In D. C. Berliner & R. C. Calfee (Eds.), Handbook of educational psychology (pp. 243–310). New York: Macmillan Library Reference.

Soderstrom, N. C., & Bjork, R. A. (2014). Testing facilitates the regulation of subsequent study time. Journal of Memory and Language, 73 , 99–115.

Steel, P. (2007). The nature of procrastination: a meta-analytic and theoretical review of quintessential self-regulatory failure. Psychological Bulletin, 133 (1), 65–94.

Stevens, T., & Tallent-Runnels, M. K. (2004). The learning and study strategies inventory-high school version: issues of factorial invariance across gender and ethnicity. Educational and Psychological Measurement, 64 , 332–346.

Strunk, K. K., Cho, Y., Steele, M. R., & Bridges, S. L. (2013). Development and validation of a 2× 2 model of time-related academic behavior: procrastination and timely engagement. Learning and Individual Differences, 25 , 35–44.

Tanner, J. R., Stewart, G., Maples, G. M., & Totaro, M. W. (2009). How business students spend their time—do they really know? Research in Higher Education Journal, 3 , 1–9.

Terenzini, P., Rendon, L., Upcraft, M. L., Millar, S., Allison, K., Gregg, P., & Jalomo, R. (1994). The transition to college: diverse students, diverse stories. Research in Higher Education, 35 , 57–73.

Trueman, M., & Hartley, J. (1996). A comparison between the time-management skills and academic performance of mature and traditional-entry university students. Higher Education, 32 , 199–215.

Truschel, J., & Reedy, D. L. (2009). National survey—what is a learning center in the 21st century? Learning Assistance Review, 14 , 9–22.

Tsai, H. C., & Liu, S. H. (2015). Relationships between time-management skills, Facebook interpersonal skills and academic achievement among junior high school students. Social Psychology of Education, 18 , 503–516.

U.S. Department of Education, Institute of Education Sciences, What Works Clearinghouse (2016). Studies of interventions for students in developmental education intervention report: first year experience courses for students in developmental education . Retrieved from http://whatworks.ed.gov . Accessed 20 Jan 2020.

Urdan, T., & Schoenfelder, E. (2006). Classroom effects on student motivation: goal structures, social relationships, and competence beliefs. Journal of School Psychology, 44 , 331–349.

Usher, E. L., & Pajares, F. (2008). Sources of self-efficacy in school: critical review of the literature and future directions. Review of Educational Research, 78 , 751–796.

van Den Hurk, M. (2006). The relation between self-regulated strategies and individual study time, prepared participation and achievement in a problem-based curriculum. Active Learning in Higher Education, 7 , 155–169.

van der Meer, J., Jansen, E., & Torenbeek, M. (2010). ‘It’s almost a mindset that teachers need to change’: first-year students’ need to be inducted into time management. Studies in Higher Education, 35 , 777–791.

van Eerde, W. (2015). Time management and procrastination. In M. D. Mumford & M. Frese (Eds.), The psychology of planning in organizations: research and applications (pp. 312–333). New York: Routledge.

Wagner, P., Schober, B., & Spiel, C. (2008). Time students spend working at home for school. Learning and Instruction, 18 , 309–320.

Weiner, B. (2005). Motivation from an attribution perspective and the social psychology of perceived competence. In A. Elliot & C. Dweck (Eds.), Handbook of competence and motivation (pp. 73–84). New York: Guildford.

Weinstein, C. E., Palmer, D. R., & Acee, T. W. (2016). LASSI user’s manual (3th ed.). Clearwater: H & H Pub.

Winne, P. H. (1995). Inherent details in self-regulated learning. Educational Psychologist, 30 , 173–187.

Winne, P. H., & Baker, R. (2013). The potentials of educational data mining for researching metacognition, motivation, and self-regulated learning. Journal of Educational Data Mining, 5 , 1–8.

Winne, P., & Hadwin, A. (1998). Studying as self-regulated learning. In D. Hacker, J. Dunlosky, & A. Graesser (Eds.), Metacognition in educational theory and practice (pp. 277–304). Mahwah: Erlbaum.

Winne, P. H., & Hadwin, A. F. (2008). The weave of motivation and self-regulated learning. Motivation and self-regulated learning: theory, research, and applications (pp. 297–314). New York: Taylor & Francis.

Winne, P., & Perry, N. (2000). Measuring self-regulated learning. In M. Boekaerts, P. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 531–566). San Diego: Academic Press.

Witkow, M. R. (2009). Academic achievement and adolescents’ daily time use in the social and academic domains. Journal of Research on Adolescence, 19 , 151–172.

Wolters, C. A. (2003). Regulation of motivation: evaluating an underemphasized aspect of self-regulated learning. Educational Psychologist, 38 , 189–205.

Wolters, C. A. (2011). Regulation of motivation: contextual and social aspects. Teachers College Record, 113 , 265–283.

Wolters, C. A., & Gonzalez, A. L. (2008). Classroom climate and motivation: a step toward integration. Advances in Motivation and Achievement: Social Psychological Influences, 15 , 493–519.

Wolters, C. A., & Hoops, L. D. (2015). Self-regulated learning interventions for motivationally disengaged college students. In T. L. Cleary (Ed.), Self-regulated learning interventions with at-risk youth: Enhancing adaptability, performance, and well-being (pp. 67–88). Washington: American Psychological Association.

Wolters, C., & Taylor, D. (2012). A self-regulated learning perspective on student engagement. In S. L. Christenson, A. Reschly, & C. Wylie (Eds.), Handbook of research on student engagement (pp. 635–651). New York: Springer.

Wolters, C. A., & Won, S. (2018). Validity and the use of self-report questionnaires to assess self-regulated learning. In D. H. Schunk & J. A. Greene (Eds.), Handbook of self-regulation of learning and performance (pp. 307–322). New York: Routledge.

Wolters, C. A., Won, S., & Hussain, M. (2017). Examining the relations of time management and procrastination within a model of self-regulated learning. Metacognition and Learning, 12 , 381–399.

Won, S., & Yu, S. L. (2018). Relations of perceived parental autonomy support and control with adolescents’ academic time management and procrastination. Learning and Individual Differences, 61 , 205–215.

Woolfolk, A. E., & Woolfolk, R. L. (1986). Time management: an experimental investigation. Journal of School Psychology, 24 , 267–275.

Xie, K., Heddy, B. C., & Greene, B. A. (2019). Affordances of using mobile technology to support experience-sampling method in examining college students’ engagement. Computers & Education, 128 , 183–198.

Xu, J. (2008). Models of secondary school students’ interest in homework: a multilevel analysis. American Educational Research Journal, 45 , 1180–1205.

Xu, J. (2010). Predicting homework time management at the secondary school level: a multilevel analysis. Learning and Individual Differences, 20 , 34–39.

Xu, J., Du, J., & Fan, X. (2013). “Finding our time”: predicting students’ time management in online collaborative groupwork. Computers & Education, 69 , 139–147.

Xu, J., Yuan, R., Xu, B., & Xu, M. (2014). Modeling students’ time management in math homework. Learning and Individual Differences, 34 , 33–42.

Yamada, M., Goda, Y., Matsuda, T., Saito, Y., Kato, H., & Miyagawa, H. (2016). How does self-regulated learning relate to active procrastination and other learning behaviors? Journal of Computing in Higher Education, 28 , 326–343.

Young, D. G., & Hopp, J. M. (2014). 2012-2013 national survey of first-year seminars: exploring high-impact practices in the first college year (Research report No. 4) . Columbia: University of South Carolina.

Zimbardo, P., & Boyd, J. (1999). Putting time in perspective: a valid, reliable individual-differences metric. Journal of Personality and Social Psychology, 77 , 1271–1288.

Zimmerman, B. J. (1989). A social cognitive view of self-regulated academic learning. Journal of Educational Psychology, 81 , 329–339.

Zimmerman, B. J. (2000). Attaining self-regulation: a social cognitive perspective. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation: theory, research, and applications (pp. 13–29). San Diego: Academic Press.

Zimmerman, B. J., & Risemberg, R. (1997). Becoming a self-regulated writer: a social cognitive perspective. Contemporary Educational Psychology, 22 , 73–101.

Zimmerman, B. J., & Schunk, D. (2012). Motivation: an essential dimension of self-regulated learning. In D. Schunk & B. Zimmerman (Eds.), Motivation and self-regulated learning: theory, research and applications (pp. 1–30). New York: Routledge.

Zimmerman, B. J., Greenberg, D., & Weinstein, C. E. (1994). Self-regulating academic study time: a strategy approach. In D. H. Schunk & B. J. Zimmerman (Eds.), Self-regulation of learning and performance: issues and educational applications (pp. 181–199). Hillsdale: Erlbaum.

Zusho, A. (2017). Toward an integrated model of student learning in the college classroom. Educational Psychology Review, 29 , 301–324.

Zusho, A., & Pintrich, P. (2003). Skill and will: the role of motivation and cognition in the learning of college chemistry. International Journal of Science Education, 25 , 1081–1094.

Download references

Author information

Authors and affiliations.

Dennis Learning Center, The Ohio State University, 250B Younkin Success Building, 1640 Neil Ave., Columbus, OH, 43201, USA

Christopher A. Wolters & Anna C. Brady

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Christopher A. Wolters .

Ethics declarations

Conflict of interest.

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Wolters, C.A., Brady, A.C. College Students’ Time Management: a Self-Regulated Learning Perspective. Educ Psychol Rev 33 , 1319–1351 (2021). https://doi.org/10.1007/s10648-020-09519-z

Download citation

Published : 27 October 2020

Issue Date : December 2021

DOI : https://doi.org/10.1007/s10648-020-09519-z

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Self-regulated learning
• Time management
• Postsecondary students
• Find a journal
• Publish with us
• Track your research

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here .

Loading metrics

Open Access

Peer-reviewed

Research Article

Does time management work? A meta-analysis

Roles Conceptualization, Data curation, Formal analysis, Methodology, Software, Validation, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Concordia University, Sir George Williams Campus, Montreal, Quebec, Canada

Roles Methodology, Validation

Affiliation FSA Ulaval, Laval University, Quebec City, Quebec, Canada

Roles Validation, Writing – review & editing

• Brad Aeon, 
• Aïda Faber, 
• Alexandra Panaccio

• Published: January 11, 2021
• https://doi.org/10.1371/journal.pone.0245066
• Reader Comments

Does time management work? We conducted a meta-analysis to assess the impact of time management on performance and well-being. Results show that time management is moderately related to job performance, academic achievement, and wellbeing. Time management also shows a moderate, negative relationship with distress. Interestingly, individual differences and contextual factors have a much weaker association with time management, with the notable exception of conscientiousness. The extremely weak correlation with gender was unexpected: women seem to manage time better than men, but the difference is very slight. Further, we found that the link between time management and job performance seems to increase over the years: time management is more likely to get people a positive performance review at work today than in the early 1990s. The link between time management and gender, too, seems to intensify: women’s time management scores have been on the rise for the past few decades. We also note that time management seems to enhance wellbeing—in particular, life satisfaction—to a greater extent than it does performance. This challenges the common perception that time management first and foremost enhances work performance, and that wellbeing is simply a byproduct.

Citation: Aeon B, Faber A, Panaccio A (2021) Does time management work? A meta-analysis. PLoS ONE 16(1): e0245066. https://doi.org/10.1371/journal.pone.0245066

Editor: Juan-Carlos Pérez-González, Universidad Nacional de Educacion a Distancia (UNED), SPAIN

Received: October 27, 2020; Accepted: December 21, 2020; Published: January 11, 2021

Copyright: © 2021 Aeon et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist

Introduction

Stand-up comedian George Carlin once quipped that in the future a “time machine will be built, but no one will have time to use it” [ 1 ]. Portentously, booksellers now carry one-minute bedtime stories for time-starved parents [ 2 ] and people increasingly speed-watch videos and speed-listen to audio books [ 3 – 5 ]. These behaviors are symptomatic of an increasingly harried society suffering from chronic time poverty [ 6 ]. Work is intensifying—in 1965 about 50% of workers took breaks; in 2003, less than 2% [ 7 ]. Leisure, too, is intensifying: people strive to consume music, social media, vacations, and other leisure activities ever more efficiently [ 8 – 11 ].

In this frantic context, time management is often touted as a panacea for time pressure. Media outlets routinely extol the virtues of time management. Employers, educators, parents, and politicians exhort employees, students, children, and citizens to embrace more efficient ways to use time [ 12 – 16 ]. In light of this, it is not surprising that from 1960 to 2008 the frequency of books mentioning time management shot up by more than 2,700% [ 17 ].

Time management is defined as “a form of decision making used by individuals to structure, protect, and adapt their time to changing conditions” [ 18 ]. This means time management, as it is generally portrayed in the literature, comprises three components: structuring, protecting, and adapting time. Well-established time management measures reflect these concepts. Structuring time, for instance, is captured in such items as “Do you have a daily routine which you follow?” and “Do your main activities during the day fit together in a structured way?” [ 19 ]. Protecting time is reflected in items such as “Do you often find yourself doing things which interfere with your schoolwork simply because you hate to say ‘No’ to people?” [ 20 ]. And adapting time to changing conditions is seen in such items as “Uses waiting time” and “Evaluates daily schedule” [ 21 ].

Research has, furthermore, addressed several important aspects of time management, such as its relationship with work-life balance [ 22 ], whether gender differences in time management ability develop in early childhood [ 23 ], and whether organizations that encourage employees to manage their time experience less stress and turnover [ 24 ]. Despite the phenomenal popularity of this topic, however, academic research has yet to address some fundamental questions [ 25 – 27 ].

A critical gap in time management research is the question of whether time management works [ 28 , 29 ]. For instance, studies on the relationship between time management and job performance reveal mixed findings [ 30 , 31 ]. Furthermore, scholars’ attempts to synthesize the literature have so far been qualitative, precluding a quantitative overall assessment [ 18 , 32 , 33 ]. To tackle this gap in our understanding of time management, we conducted a meta-analysis. In addressing the question of whether time management works, we first clarify the criteria for effectiveness. In line with previous reviews, we find that virtually all studies focus on two broad outcomes: performance and wellbeing [ 32 ].

Overall, results suggest that time management enhances job performance, academic achievement, and wellbeing. Interestingly, individual differences (e.g., gender, age) and contextual factors (e.g., job autonomy, workload) were much less related to time management ability, with the notable exception of personality and, in particular, conscientiousness. Furthermore, the link between time management and job performance seems to grow stronger over the years, perhaps reflecting the growing need to manage time in increasingly autonomous and flexible jobs [ 34 – 37 ].

Overall, our findings provide academics, policymakers, and the general audience with better information to assess the value of time management. This information is all the more useful amid the growing doubts about the effectiveness of time management [ 38 ]. We elaborate on the contributions and implications of our findings in the discussion section.

What does it mean to say that time management works?

In the din of current debates over productivity, reduced workweeks, and flexible hours, time management comes to the fore as a major talking point. Given its popularity, it would seem rather pointless to question its effectiveness. Indeed, time management’s effectiveness is often taken for granted, presumably because time management offers a seemingly logical solution to a lifestyle that increasingly requires coordination and prioritization skills [ 39 , 40 ].

Yet, popular media outlets increasingly voice concern and frustration over time management, reflecting at least part of the population’s growing disenchantment [ 38 ]. This questioning of time management practices is becoming more common among academics as well [ 41 ]. As some have noted, the issue is not just whether time management works. Rather, the question is whether the techniques championed by time management gurus can be actually counterproductive or even harmful [ 26 , 42 ]. Other scholars have raised concerns that time management may foster an individualistic, quantitative, profit-oriented view of time that perpetuates social inequalities [ 43 , 44 ]. For instance, time management manuals beguile readers with promises of boundless productivity that may not be accessible to women, whose disproportionate share in care work, such as tending to young children, may not fit with typically male-oriented time management advice [ 45 ]. Similarly, bestselling time management books at times offer advice that reinforce global inequities. Some manuals, for instance, recommend delegating trivial tasks to private virtual assistants, who often work out of developing countries for measly wages [ 46 ]. Furthermore, time management manuals often ascribe a financial value to time—the most famous time management adage is that time is money. But recent studies show that thinking of time as money leads to a slew of negative outcomes, including time pressure, stress, impatience, inability to enjoy the moment, unwillingness to help others, and less concern with the environment [ 47 – 51 ]. What’s more, the pressure induced by thinking of time as money may ultimately undermine psychological and physical health [ 52 ].

Concerns over ethics and safety notwithstanding, a more prosaic question researchers have grappled with is whether time management works. Countless general-audience books and training programs have claimed that time management improves people’s lives in many ways, such as boosting performance at work [ 53 – 55 ]. Initial academic forays into addressing this question challenged those claims: time management didn’t seem to improve job performance [ 29 , 30 ]. Studies used a variety of research approaches, running the gamut from lab experiments, field experiments, longitudinal studies, and cross-sectional surveys to experience sampling [ 28 , 56 – 58 ]. Such studies occasionally did find an association between time management and performance, but only in highly motivated workers [ 59 ]; instances establishing a more straightforward link with performance were comparatively rare [ 31 ]. Summarizing these insights, reviews of the literature concluded that the link between time management and job performance is unclear; the link with wellbeing, however, seemed more compelling although not conclusive [ 18 , 32 ].

It is interesting to note that scholars often assess the effectiveness time management by its ability to influence some aspect of performance, wellbeing, or both. In other words, the question of whether time management works comes down to asking whether time management influences performance and wellbeing. The link between time management and performance at work can be traced historically to scientific management [ 60 ]. Nevertheless, even though modern time management can be traced to scientific management in male-dominated work settings, a feminist reading of time management history reveals that our modern idea of time management also descends from female time management thinkers of the same era, such as Lillian Gilbreth, who wrote treatises on efficient household management [ 43 , 61 , 62 ]. As the link between work output and time efficiency became clearer, industrialists went to great lengths to encourage workers to use their time more rationally [ 63 – 65 ]. Over time, people have internalized a duty to be productive and now see time management as a personal responsibility at work [ 43 , 66 , 67 ]. The link between time management and academic performance can be traced to schools’ historical emphasis on punctuality and timeliness. In more recent decades, however, homework expectations have soared [ 68 ] and parents, especially well-educated ones, have been spending more time preparing children for increasingly competitive college admissions [ 69 , 70 ]. In this context, time management is seen as a necessary skill for students to thrive in an increasingly cut-throat academic world. Finally, the link between time management and wellbeing harks back to ancient scholars, who emphasized that organizing one’s time was necessary to a life well-lived [ 71 , 72 ]. More recently, empirical studies in the 1980s examined the effect of time management on depressive symptoms that often plague unemployed people [ 19 , 73 ]. Subsequent studies surmised that the effective use of time might prevent a host of ills, such as work-life conflict and job stress [ 22 , 74 ].

Overall, then, various studies have looked into the effectiveness of time management. Yet, individual studies remain narrow in scope and reviews of the literature offer only a qualitative—and often inconclusive—assessment. To provide a more quantifiable answer to the question of whether time management works, we performed a meta-analysis, the methods of which we outline in what follows.

Literature search and inclusion criteria

We performed a comprehensive search using the keywords “time management” across the EBSCO databases Academic Search Complete , Business Source Complete , Computers & Applied Sciences Complete , Gender Studies Database , MEDLINE , Psychology and Behavioral Sciences Collection , PsycINFO , SocINDEX , and Education Source . The search had no restrictions regarding country and year of publication and included peer-reviewed articles up to 2019. To enhance comprehensiveness, we also ran a forward search on the three main time management measures: the Time Management Behavior Scale [ 21 ], the Time Structure Questionnaire [ 19 ], and the Time Management Questionnaire [ 20 ]. (A forward search tracks all the papers that have cited a particular work. In our case the forward search located all the papers citing the three time management scales available on Web of Science .)

Time management measures typically capture three aspects of time management: structuring, protecting, and adapting time to changing conditions. Structuring refers to how people map their activities to time using a schedule, a planner, or other devices that represent time in a systematic way [ 75 – 77 ]. Protecting refers to how people set boundaries around their time to repel intruders [ 78 , 79 ]. Examples include people saying no to time-consuming requests from colleagues or friends as well as turning off one’s work phone during family dinners. Finally, adapting one’s time to changing conditions means, simply put, to be responsive and flexible with one’s time structure [ 80 , 81 ]. Furthermore, time management measures typically probe behaviors related to these three dimensions (e.g., using a schedule to structure one’s day, making use of downtime), although they sometimes also capture people’s attitudes (e.g., whether people feel in control of their time).

As shown in Fig 1 , the initial search yielded 10,933 hits, excluding duplicates.

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0245066.g001

The search included no terms other than “time management” to afford the broadest possible coverage of time management correlates. Nevertheless, as shown in Table 1 , we focused exclusively on quantitative, empirical studies of time management in non-clinical samples. Successive rounds of screening, first by assessing paper titles and abstracts and then by perusing full-text articles, whittled down the number of eligible studies to 158 (see Fig 1 ).

https://doi.org/10.1371/journal.pone.0245066.t001

Data extraction and coding

We extracted eligible effect sizes from the final pool of studies; effect sizes were mostly based on means and correlations. In our initial data extraction, we coded time management correlates using the exact variable names found in each paper. For instance, “work-life imbalance” was initially coded in those exact terms, rather than “work-life conflict.” Virtually all time management correlates we extracted fell under the category of performance and/or wellbeing. This pattern tallies with previous reviews of the literature [ 18 , 32 ]. A sizable number of variables also fell under the category of individual differences and contextual factors, such as age, personality, and job autonomy. After careful assessment of the extracted variables, we developed a coding scheme using a nested structure shown in Table 2 .

https://doi.org/10.1371/journal.pone.0245066.t002

Aeon and Aguinis suggested that time management influences performance, although the strength of that relationship may depend on how performance is defined [ 18 ]. Specifically, they proposed that time management may have a stronger impact on behaviors conducive to performance (e.g., motivation, proactiveness) compared to assessments of performance (e.g., supervisor rankings). For this reason, we distinguish between results- and behavior-based performance in our coding scheme, both in professional and academic settings. Furthermore, wellbeing indicators can be positive (e.g., life satisfaction) or negative (e.g., anxiety). We expect time management to influence these variables in opposite ways; it would thus make little sense to analyze them jointly. Accordingly, we differentiate between wellbeing (positive) and distress (negative).

In our second round of coding, we used the scheme shown in Table 2 to cluster together kindred variables. For instance, we grouped “work-life imbalance,” “work-life conflict” and “work-family conflict” under an overarching “work-life conflict” category. The authors reviewed each variable code and resolved rare discrepancies to ultimately agree on all coded variables. Note that certain variables, such as self-actualization, covered only one study (i.e., one effect size). While one or two effect sizes is not enough to conduct a meta-analysis, they can nonetheless be grouped with other effect sizes belonging to the same category (e.g., self-actualization and sense of purpose belong the broader category of overall wellbeing). For this reason, we included variables with one or two effect sizes for comprehensiveness.

Meta-analytic procedures

We conducted all meta-analyses following the variables and cluster of variables outlined in Table 2 . We opted to run all analyses with a random effects model. The alternative—a fixed effects model—assumes that all studies share a common true effect size (i.e., linking time management and a given outcome) which they approximate. This assumption is unrealistic because it implies that the factors influencing the effect size are the same in all studies [ 83 ]. In other words, a fixed effects model assumes that the factors affecting time management are similar across all studies—the fallacy underlying this assumption was the main theme of Aeon and Aguinis’s review [ 18 ]. To perform our analyses, we used Comprehensive Meta-Analysis v.3 [ 84 ], a program considered highly reliable and valid in various systematic assessments [ 85 , 86 ].

In many cases, studies reported how variables correlated with an overall time management score. In some cases, however, studies reported only correlations with discrete time management subscales (e.g., short-range planning, attitudes toward time, use of time management tools), leaving out the overall effect. In such cases, we averaged out the effect sizes of the subscales to compute a summary effect [ 83 ]. This was necessary not only because meta-analyses admit only one effect size per study, but also because our focus is on time management as a whole rather than on subscales. Similarly, when we analyzed the link between time management and a high-level cluster of variables (e.g., overall wellbeing rather than specific variables such as life satisfaction), there were studies with more than one relevant outcome (e.g., a study that captured both life satisfaction and job satisfaction). Again, because meta-analyses allow for only one effect size (i.e., variable) per study, we used the mean of different variables to compute an overall effect sizes in studies that featured more than one outcome [ 83 ].

Overall description of the literature

We analyzed 158 studies for a total number of 490 effect sizes. 21 studies explored performance in a professional context, 76 performance in an academic context, 30 investigated wellbeing (positive), and 58 distress. Interestingly, studies did not systematically report individual differences, as evidenced by the fact that only 21 studies reported correlations with age, and only between 10 and 15 studies measured personality (depending on the personality trait). Studies that measured contextual factors were fewer still—between 3 and 7 (depending on the contextual factor). These figures fit with Aeon and Aguinis’s observation that the time management literature often overlooks internal and external factors that can influence the way people manage time [ 18 ].

With one exception, we found no papers fitting our inclusion criteria before the mid-1980s. Publication trends also indicate an uptick in time management studies around the turn of the millennium, with an even higher number around the 2010s. This trend is consistent with the one Shipp and Cole identified, revealing a surge in time-related papers in organizational behavior around the end of the 1980s [ 87 ].

It is also interesting to note that the first modern time management books came out in the early 1970s, including the The Time Trap (1972), by Alec MacKenzie and How to Get Control of your Time and your Life (1973), by Alan Lakein. These books inspired early modern time management research [ 21 , 58 , 88 ]. It is thus very likely that the impetus for modern time management research came from popular practitioner manuals.

To assess potential bias in our sample of studies, we computed different estimates of publication bias (see Table 3 ). Overall, publication bias remains relatively low (see funnel plots in S1). Publication bias occurs when there is a bias against nonsignificant or even negative results because such results are seen as unsurprising and not counterintuitive. In this case, however, the fact that time management is generally expected to lead to positive outcomes offers an incentive to publish nonsignificant or negative results, which would be counterintuitive [ 89 ]. By the same token, the fact that some people feel that time management is ineffective [ 38 ] provides an incentive to publish papers that link time management with positive outcomes. In other words, opposite social expectations surrounding time management might reduce publication bias.

https://doi.org/10.1371/journal.pone.0245066.t003

Finally, we note that the link between time management and virtually all outcomes studied is highly heterogeneous (as measured, for instance, by Cochran’s Q and Higgins & Thompson’s I 2 ; see tables below). This high level of heterogeneity suggests that future research should pay more attention to moderating factors (e.g., individual differences).

Time management and performance in professional settings

Overall, time management has a moderate impact on performance at work, with correlations hovering around r = .25. We distinguish between results-based and behavior-based performance. The former measures performance as an outcome (e.g., performance appraisals by supervisors) whereas the latter measures performance as behavioral contributions (e.g., motivation, job involvement). Time management seems related to both types of performance. Although the effect size for results-based performance is lower than that of behavior-based performance, moderation analysis reveals the difference is not significant (p > .05), challenging Aeon and Aguinis’s conclusions [ 18 ].

Interestingly, the link between time management and performance displays much less heterogeneity (see Q and I 2 statistics in Table 4 ) than the link between time management and other outcomes (see tables below). The studies we summarize in Table 4 include both experimental and non-experimental designs; they also use different time management measures. As such, we can discount, to a certain extent, the effect of methodological diversity. We can perhaps explain the lower heterogeneity by the fact that when people hold a full-time job, they usually are at a relatively stable stage in life. In school, by contrast, a constellation of factors (e.g., financial stability and marital status, to name a few) conspire to affect time management outcomes. Furthermore, work contexts are a typically more closed system than life in general. For this reason, fewer factors stand to disrupt the link between time management and job performance than that between time management and, say, life satisfaction. Corroborating this, note how, in Table 6 below, the link between time management and job satisfaction ( I 2 = 58.70) is much less heterogeneous than the one between time management and life satisfaction ( I 2 = 95.45).

https://doi.org/10.1371/journal.pone.0245066.t004

Moreover, we note that the relationship between time management and job performance (see Fig 2 ) significantly increases over the years ( B = .0106, p < .01, Q model = 8.52(1), Q residual = 15.54(9), I 2 = 42.08, R 2 analog = .75).

https://doi.org/10.1371/journal.pone.0245066.g002

Time management and performance in academic settings

Overall, the effect of time management on performance seems to be slightly higher in academic settings compared to work settings, although the magnitude of the effect remains moderate (see Table 5 ). Here again, we distinguish between results- and behavior-based performance. Time management’s impact on behavior-based performance seems much higher than on results-based performance—a much wider difference than the one we observed in professional settings. This suggests than results-based performance in academic settings depends less on time management than results-based performance in professional settings. This means that time management is more likely to get people a good performance review at work than a strong GPA in school.

https://doi.org/10.1371/journal.pone.0245066.t005

In particular, time management seems to be much more negatively related to procrastination in school than at work. Although we cannot establish causation in all studies, we note that some of them featured experimental designs that established a causal effect of time management on reducing procrastination [ 90 ].

Interestingly, time management was linked to all types of results-based performance except for standardized tests. This is perhaps due to the fact that standardized tests tap more into fluid intelligence, a measure of intelligence independent of acquired knowledge [ 91 ]. GPA and regular exam scores, in contrast, tap more into crystallized intelligence, which depends mostly on accumulated knowledge. Time management can thus assist students in organizing their time to acquire the knowledge necessary to ace a regular exam; for standardized exams that depend less on knowledge and more on intelligence, however, time management may be less helpful. Evidence from other studies bears this out: middle school students’ IQ predicts standardized achievement tests scores better than self-control while self-control predicts report card grades better than IQ [ 92 ]. (For our purposes, we can use self-control as a very rough proxy for time management.) Relatedly, we found no significant relationship between time management and cognitive ability in our meta-analysis (see Table 8 ).

Time management and wellbeing

On the whole, time management has a slightly stronger impact on wellbeing than on performance. This is unexpected, considering how the dominant discourse points to time management as a skill for professional career development. Of course, the dominant discourse also frames time management as necessary for wellbeing and stress reduction, but to a much lesser extent. Our finding that time management has a stronger influence on wellbeing in no way negates the importance of time management as a work skill. Rather, this finding challenges the intuitive notion that time management is more effective for work than for other life domains. As further evidence, notice how in Table 6 the effect of time management on life satisfaction is 72% stronger than that on job satisfaction.

https://doi.org/10.1371/journal.pone.0245066.t006

Time management and distress

Time management seems to allay various forms of distress, although to a lesser extent than it enhances wellbeing. The alleviating effect on psychological distress is particularly strong ( r = -0.358; see Table 7 ).

https://doi.org/10.1371/journal.pone.0245066.t007

That time management has a weaker effect on distress should not be surprising. First, wellbeing and distress are not two poles on opposite ends of a spectrum. Although related, wellbeing and distress are distinct [ 93 ]. Thus, there is no reason to expect time management to have a symmetrical effect on wellbeing and distress. Second, and relatedly, the factors that influence wellbeing and distress are also distinct. Specifically, self-efficacy (i.e., seeing oneself as capable) is a distinct predictor of wellbeing while neuroticism and life events in general are distinct predictors of distress [ 94 ]. It stands to reason that time management can enhance self-efficacy. (Or, alternatively, that people high in self-efficacy would be more likely to engage in time management, although experimental evidence suggests that time management training makes people feel more in control of their time [ 89 ]; it is thus plausible that time management may have a causal effect on self-efficacy. Relatedly, note how time management ability is strongly related to internal locus of control in Table 8 ) In contrast, time management can do considerably less in the way of tackling neuroticism and dampening the emotional impact of tragic life events. In other words, the factors that affect wellbeing may be much more within the purview of time management than the factors that affect distress. For this reason, time management may be less effective in alleviating distress than in improving wellbeing.

https://doi.org/10.1371/journal.pone.0245066.t008

Time management and individual differences

Time management is, overall, less related to individual differences than to other variables.

Age, for instance, hardly correlates with time management (with a relatively high consistency between studies, I 2 = 55.79, see Table 8 above).

Similarly, gender only tenuously correlates with time management, although in the expected direction: women seem to have stronger time management abilities than men. The very weak association with gender ( r = -0.087) is particularly surprising given women’s well-documented superior self-regulation skills [ 95 ]. That being said, women’s time management abilities seem to grow stronger over the years ( N = 37, B = -.0049, p < .05, Q model = 3.89(1), Q residual = 218.42(35), I 2 = 83.98, R 2 analog = .03; also see Fig 3 below). More realistically, this increase may not be due to women’s time management abilities getting stronger per se but, rather, to the fact that women now have more freedom to manage their time [ 96 ].

https://doi.org/10.1371/journal.pone.0245066.g003

Other demographic indicators, such as education and number of children, were nonsignificant. Similarly, the relationships between time management and personal attributes and attitudes were either weak or nonsignificant, save for two notable exceptions. First, the link between time management and internal locus of control (i.e., the extent to which people perceive they’re in control of their lives) is quite substantial. This is not surprising, because time management presupposes that people believe they can change their lives. Alternatively, it may be that time management helps people strengthen their internal locus of control, as experimental evidence suggests [ 89 ]. Second, the link between time management and self-esteem is equally substantial. Here again, one can make the argument either way: people with high self-esteem might be confident enough to manage their time or, conversely, time management may boost self-esteem. The two options are not mutually exclusive: people with internal loci of control and high self-esteem levels can feel even more in control of their lives and better about themselves through time management.

We also note a very weak but statistically significant negative association between time management and multitasking. It has almost become commonsense that multitasking does not lead to performance [ 97 ]. As a result, people with stronger time management skills might deliberately steer clear of this notoriously ineffective strategy.

In addition, time management was mildly related to hours spent studying but not hours spent working. (These variables cover only student samples working part- or full-time and thus do not apply to non-student populations.) This is consistent with time-use studies revealing that teenagers and young adults spend less time working and more time studying [ 98 ]. Students who manage their time likely have well-defined intentions, and trends suggest those intentions will target education over work because, it is hoped, education offers larger payoffs over the long-term [ 99 ].

In terms of contextual factors, time management does not correlate significantly with job autonomy. This is surprising, as we expected autonomy to be a prerequisite for time management (i.e., you can’t manage time if you don’t have the freedom to). Nevertheless, qualitative studies have shown how even in environments that afford little autonomy (e.g., restaurants), workers can carve out pockets of time freedom to momentarily cut loose [ 100 ]. Thus, time management behaviors may flourish even in the most stymying settings. In addition, the fact that time management is associated with less role overload and previous attendance of time management training programs makes sense: time management can mitigate the effect of heavy workloads and time management training, presumably, improves time management skills.

Finally, time management is linked to all personality traits. Moreover, previous reviews of the literature have commented on the link between time management and conscientiousness in particular [ 32 ]. What our study reveals is the substantial magnitude of the effect ( r = 0.451). The relationship is not surprising: conscientiousness entails orderliness and organization, which overlap significantly with time management. That time management correlates so strongly with personality (and so little with other individual differences) lends credence to the dispositional view of time management [ 101 – 103 ]. However, this finding should not be taken to mean that time management is a highly inheritable, fixed ability. Having a “you either have it or you don’t” view of time management is not only counterproductive [ 104 ] but also runs counter to evidence showing that time management training does, in fact, help people manage their time better.

Does time management work? It seems so. Time management has a moderate influence on job performance, academic achievement, and wellbeing. These three outcomes play an important role in people’s lives. Doing a good job at work, getting top grades in school, and nurturing psychological wellbeing contribute to a life well lived. Widespread exhortations to get better at time management are thus not unfounded: the importance of time management is hard to overstate.

Contributions

Beyond answering the question of whether time management works, this study contributes to the literature in three major ways. First, we quantify the impact of time management on several outcomes. We thus not only address the question of whether time management works, but also, and importantly, gauge to what extent time management works. Indeed, our meta-analysis covers 53,957 participants, which allows for a much more precise, quantified assessment of time management effectiveness compared to qualitative reviews.

Second, this meta-analysis systematically assesses relationships between time management and a host of individual differences and contextual factors. This helps us draw a more accurate portrait of potential antecedents of higher (or lower) scores on time management measures.

Third, our findings challenge intuitive ideas concerning what time management is for. Specifically, we found that time management enhances wellbeing—and in particular life satisfaction—to a greater extent than it does various types of performance. This runs against the popular belief that time management primarily helps people perform better and that wellbeing is simply a byproduct of better performance. Of course, it may be that wellbeing gains, even if higher than performance gains, hinge on performance; that is to say, people may need to perform better as a prerequisite to feeling happier. But this argument doesn’t jibe with experiments showing that even in the absence of performance gains, time management interventions do increase wellbeing [ 89 ]. This argument also founders in the face of evidence linking time management with wellbeing among the unemployed [ 105 ], unemployment being an environment where performance plays a negligible role, if any. As such, this meta-analysis lends support to definitions of time management that are not work- or performance-centric.

Future research and limitations

This meta-analysis questions whether time management should be seen chiefly as a performance device. Our questioning is neither novel nor subversive: historically people have managed time for other reasons than efficiency, such as spiritual devotion and philosophical contemplation [ 72 , 106 , 107 ]. It is only with relatively recent events, such as the Industrial Revolution and waves of corporate downsizing, that time management has become synonymous with productivity [ 43 , 65 ]. We hope future research will widen its scope and look more into outcomes other than performance, such as developing a sense of meaning in life [ 108 ]. One of the earliest time management studies, for instance, explored how time management relates to having a sense of purpose [ 73 ]. However, very few studies followed suit since. Time management thus stands to become a richer, more inclusive research area by investigating a wider array of outcomes.

In addition, despite the encouraging findings of this meta-analysis we must refrain from seeing time management as a panacea. Though time management can make people’s lives better, it is not clear how easy it is for people to learn how to manage their time adequately. More importantly, being “good” at time management is often a function of income, education, and various types of privilege [ 42 , 43 , 46 , 109 ]. The hackneyed maxim that “you have as many hours in a day as Beyoncé,” for instance, blames people for their “poor” time management in pointing out that successful people have just as much time but still manage to get ahead. Yet this ill-conceived maxim glosses over the fact that Beyoncé and her ilk do, in a sense, have more hours in a day than average people who can’t afford a nanny, chauffeur, in-house chefs, and a bevy of personal assistants. Future research should thus look into ways to make time management more accessible.

Furthermore, this meta-analysis rests on the assumption that time management training programs do enhance people’s time management skills. Previous reviews have noted the opacity surrounding time management interventions—studies often don’t explain what, exactly, is taught in time management training seminars [ 18 ]. As a result, comparing the effect of different interventions might come down to comparing apples and oranges. (This might partly account for the high heterogeneity between studies.) We hope that our definition of time management will spur future research into crafting more consistent, valid, and generalizable interventions that will allow for more meaningful comparisons.

Finally, most time management studies are cross-sectional. Yet it is very likely that the effect of time management compounds over time. If time management can help students get better grades, for instance, those grades can lead to better jobs down the line [ 110 ]. Crucially, learning a skill takes time, and if time management helps people make the time to learn a skill, then time management stands to dramatically enrich people’s lives. For this reason, longitudinal studies can track different cohorts to see how time management affects people’s lives over time. We expect that developing time management skills early on in life can create a compound effect whereby people acquire a variety of other skills thanks to their ability to make time.

Overall, this study offers the most comprehensive, precise, and fine-grained assessment of time management to date. We address the longstanding debate over whether time management influences job performance in revealing a positive, albeit moderate effect. Interestingly, we found that time management impacts wellbeing—and in particular life satisfaction—to a greater extent than performance. That means time management may be primarily a wellbeing enhancer, rather than a performance booster. Furthermore, individual and external factors played a minor role in time management, although this does not necessarily mean that time management’s effectiveness is universal. Rather, we need more research that focuses on the internal and external variables that affect time management outcomes. We hope this study will tantalize future research and guide practitioners in their attempt to make better use of their time.

Supporting information

S1 checklist. prisma 2009 checklist..

https://doi.org/10.1371/journal.pone.0245066.s001

S1 File. Funnel plots.

https://doi.org/10.1371/journal.pone.0245066.s002

S2 File. Dataset.

https://doi.org/10.1371/journal.pone.0245066.s003

Acknowledgments

We would like to take this opportunity to acknowledge our colleagues for their invaluable help: Mengchan Gao, Talha Aziz, Elizabeth Eley, Robert Nason, Andrew Ryder, Tracy Hecht, and Caroline Aubé.

• 1. Carlin G. When will Jesus bring the pork chops? New York, NY: Hyperion; 2004.
• 2. Lewis S, O’Kun L. One-minute bedtime stories. New York, NY: Doubleday; 1982.
• View Article
• Google Scholar
• PubMed/NCBI
• 8. Boerma J, Karabarbounis L. Labor Market Trends and the Changing Value of Time [Internet]. Cambridge, MA: National Bureau of Economic Research; 2019 Sep [cited 2019 Dec 20] p. w26301. Report No.: w26301. Available from: http://www.nber.org/papers/w26301.pdf
• 12. Clinton B. My life. New York, NY: Knopf; 2004. https://doi.org/10.1080/15216540400003425 pmid:15545218
• 16. Pausch R, Zaslow J. The last lecture. New York, NY: Hyperion; 2008.
• 17. Google Ngram Viewer. The rise of time management. Google Books. 2016.
• 40. Southerton D. Re-ordering temporal rhythms: Coordinating daily practices in the UK in 1937 and 2000. In: Shove E, Trentmann F, Wilk R, editors. Time, consumption, and everyday life: Practice, materiality and culture. New York, NY: Berg; 2009. p. 49–63.
• 41. Gregg M. Getting things done: Productivity, self-management, and the order of things. In: Hillis K, Paasonen S, Petit M, editors. Networked Affect. Cambridge, MA: MIT Press; 2015. p. 187–202.
• 42. Reagle JM. Hacking life: Systematized living and its discontents. Cambridge, MA: The MIT Press; 2019. 204 p. (Strong ideas series).
• 43. Gregg M. Counterproductive: Time management in the knowledge economy. Durham, NC: Duke University Press; 2018.
• 46. Costas J, Grey C. Outsourcing your life: Exploitation and exploration in “The 4-hour workweek.” In: Holmqvist M, Spicer A, editors. Managing ‘Human Resources’ by exploiting and exploring people’s potentials (Research in the sociology of organizations, volume 37). Bingley, UK: Emerald; 2013.
• 53. Allen D. Getting things done: The art of stress-free productivity. New York, NY: Penguin; 2001.
• 54. Lakein A. How to get control of your time and your Life. New York, NY: Signet; 1973.
• 55. Sutherland J. Scrum: The art of doing twice the work in half the time. New York, NY: Crown Business; 2014.
• 60. Taylor FW. The principles of scientific management. New York, NY: Harper & Brothers; 1911.
• 63. Landes DS. Revolution in time: Clocks and the making of the modern world. Cambridge, MA: Belknap Press of Harvard University Press; 1983. 482 p.
• 64. Martineau J. Time, capitalism and alienation: A socio-historical inquiry into the making of modern time. Boston, MA: Brill; 2015.
• 66. Alvesson M, Deetz SA. Critical Theory and Postmodernism Approaches to Organizational Studies. In: Clegg SR, Hardy C, Lawrence TB, Nord WR, editors. The SAGE Handbook of Organization Studies. 2nd ed. Thousand Oaks, CA: SAGE; 2006. p. 255–83.
• 70. Ramey G, Ramey V. The Rug Rat Race [Internet]. Cambridge, MA: National Bureau of Economic Research; 2009 Aug [cited 2020 Feb 27] p. w15284. Report No.: w15284. Available from: http://www.nber.org/papers/w15284.pdf
• 71. Aurelius M. Meditations. In: Eliot CW, editor. Harvard Classics vol 2. New York, NY: P.F. Collier & Son; 1909. p. 193–306.
• 72. Seneca LA. On the shortness of life. In: Hardship and Happiness. Chicago, IL: University Of Chicago Press; 2014. p. 110–34.
• 76. Doob LW. Patterning of time. New Haven, CT: Yale University Press; 1971.
• 83. Borenstein M, editor. Introduction to meta-analysis. Chichester, U.K: John Wiley & Sons; 2009. 421 p.
• 84. Borenstein M, Hedges L, Higgins J, Rothstein H. Comprehensive Meta-Analysis Version 3. Englewood, NJ: Biostat; 2013.
• 96. Goodin RE, Rice JM, Parpo A, Eriksson L. Discretionary time: A new measure of freedom. Cambridge, UK: Cambridge University Press; 2008.
• 101. Burrus A. What Does Time Management Mean to You? Exploring Measures of Time Management and Group Differences [Doctoral dissertation]. University of Missouri-St. Louis; 2019.
• 109. Sharma S. In the meantime: Temporality and cultural politics. Durham, NC: Duke University Press; 2014.

A quantitative exploration of time management skills and academic achievement: A case study of agriculture students in Universiti Teknologi Mara Cawangan Melaka

[email protected]

• Article contents
• Figures & tables
• Supplementary Data
• Peer Review
• Reprints and Permissions
• Cite Icon Cite
• Search Site

Farah Nadzirah Jamrus , Fadhlina Izzah Saman; A quantitative exploration of time management skills and academic achievement: A case study of agriculture students in Universiti Teknologi Mara Cawangan Melaka. AIP Conf. Proc. 21 July 2021; 2347 (1): 020128. https://doi.org/10.1063/5.0051500

Download citation file:

• Ris (Zotero)
• Reference Manager

The main objective of this study is to analyse the effect of the time management skill among university students on their academic achievement. In this study, Time Management Questionnaire (TMQ) developed by Britton and Tesser was administered to 120 randomly selected Agriculture students in Universiti Teknologi Mara Cawangan Melaka. The respondents were 55 male and 65 female students. To analyse the effect of the time management, regression analysis was used and showed that there is exist positive linear relationship between time management skill and their academic achievement. When the data analysed with respect to gender variable, the female students obtained higher mean time management score than male students. Then, t-test is conducted and revealed that there is a difference in time management skills among gender statistically.

Sign in via your Institution

Citing articles via, publish with us - request a quote.

Sign up for alerts

• Online ISSN 1551-7616
• Print ISSN 0094-243X
• For Researchers
• For Librarians
• For Advertisers
• Our Publishing Partners  
• Physics Today
• Conference Proceedings
• Special Topics

pubs.aip.org

• Privacy Policy
• Terms of Use

Connect with AIP Publishing

This feature is available to subscribers only.

Sign In or Create an Account

International Journal of Learning, Teaching and Educational Research

• Announcements
• Editorial Board
• Submit a Paper
• Publication Ethics
• ##PAPER TEMPLATE##
• ##Retraction Policy##

Students’ Time Management, Academic Procrastination, and Performance during Online Science and Mathematics Classes

COVID-19 affected all sectors, including academia, which resulted in an increase in online learning. While education continued through online platforms, various students-related problems arose, including improper time management, procrastination, and fluctuating academic performance. It is in this context that this quantitative study was carried out to determine how time management and procrastination affected students’ performance in science and mathematics during the pandemic. We surveyed 650 Filipino high school students using the Procrastination Assessment Scale-Students and Wayne State University’s Time Management questionnaire with a 0.93 reliability coefficient. The findings revealed that in science and mathematics, female students outperformed males. Eleven 12-year-olds had the highest mean grades in science and mathematics, while 15 16-year-olds had the lowest. Younger respondents (11-14) were more likely to have better time management in than older ones. Further, older respondents (15-18) procrastinate more than younger ones. Time management correlates positively with success in science and mathematics. Achievement in science and mathematics is the highest among students with good time management. Procrastination negatively affects achievement. High school students who procrastinated less fare better in mathematics. With this, the study opens possibilities for teaching older learners in time management to boost their performance. Students across ages should be urged to avoid procrastinating as it negatively affects academic performance. As reinforcement, schools may educate learners on time management and procrastination avoidance through orientations and other platforms.

https://doi.org/10.26803/ijlter.21.12.8

Ahmad, S., Batool, A., & Ch, A. H. (2020). Path relationship of time management and academic achievement of students in distance learning institutions. Pakistan Journal of Distance and Online Learning, 5(2). http://journal.aiou.edu.pk/journal1/index.php/PJDOL/article/view/441/89

Ahmad, S., Sultana, N., & Jamil, S. (2022). Students’ Attitude towards Biology and Academic Achievement in Biology at Secondary Level, in Islamabad, Pakistan. American Journal of Educational Research, 10(5), 268-275. https://doi.org/10.12691/education-10-5-1

Alay, S., & Kocak, S. (2003). Relationship between time management and academic achievement of university students. Journal of Educational Management in Theory and Practice, 35, 326-335. https://doi.org/10.1177/014572179902500411

Al-Balushi, S. M., Al-Harthy, I. S., & Almehrizi, R. S. (2022). Attention Drifting Away While Test-Taking: Mind-Wandering in Students with Low-and High-Performance Levels in TIMSS-Like Science Tests. International Journal of Science and Mathematics Education, 1-22. https://doi.org/10.1007/s10763-022-10258-6

Al-Bahrani, A., Apostolova-Mihaylova, M., & Marshall, E. C. (2022). Helping some and harming others: Homework frequency and tradeoffs in student performance. The Journal of Economic Education, 53(3), 197-209. https://doi.org/10.1080/00220485.2022.2075506

Batbaatar, N., & Amin, G. (2021). Students’ time management during online CLASS. In International Conference Universitas Pekalongan 2021 (Vol. 1, No. 1, pp. 189-194). https://proceeding.unikal.ac.id/index.php/icunikal2021/article/view/627

Bernard, R. M., Abrami, P. C., Borokhovski, E., Wade, C. A., Tamim, R. M., Surkes, M. A., & Bethel, E. C. (2009). A meta-analysis of three types of interaction treatments in distance education. Review of Educational research, 79(3), 1243-1289. https://doi.org/10.3102/0034654309333844

bin Mohammed Al-Subaie, A. (2022). Academic Procrastination and Metacognitive Strategies Among Prince Sattam Bin Abdulaziz University Students. Journal of Positive School Psychology, 6(8), 7601-7610. https://journalppw.com/index.php/jpsp/article/view/11109

Bocar, A., & Daga-ang, MG (2013). Time management of work scholars. https://www.researchgate.net/publication/270566011

Capinding, A. T. (2022). Impact of Modular Distance Learning on High School Students Mathematics Motivation, Interest/Attitude, Anxiety and Achievement during the COVID-19 Pandemic. Impact of Modular Distance Learning on High School Students Mathematics Motivation, Interest/Attitude, Anxiety and Achievement during the COVID-19 Pandemic, 11(2), 917-934. https://doi.org/10.12973/eu-jer.11.2.917

DeBeliso, M., Gauthier, H., Sevene, T., Adams, K. J., Lawrence, M. M., Climstein, M., ... & Navalta, J. W. (2022). The time management matrix re-tooled: an instrument for academics navigating the tenure process. International Journal of Multidisciplinary Perspectives in Higher Education, 7(1), 31-51. https://researchportal.scu.edu.au/discovery/delivery/61SCU_INST:ResearchRepository/991012998198802368#1395510230002368

Demuyakor, J. (2020). Analysis of social media utilization by students in higher education: A critical literature review of Ghana. Journal of New Media and Mass Communication, 6(1), 1–7. https://doi.org/10.18488/journal.91.2020.61.1.7

Desmond, A., & Amadi, K. (2022). Influence of Time Management on academic performance of Business Education Students in Universities in Rivers State. Journal homepage: www. ijrpr. com ISSN, 2582, 7421. https://ijrpr.com/uploads/V3ISSUE6/IJRPR5096.pdf

de Vera, J. V., Peteros, E. D., Peconcillo Jr, L. B., Alcantara, G. A., Villarin, E. R., & Fulgencio, M. D. (2022). Assessing differences on students’ attributes in mathematics based on their learning sessions. Open Journal of Social Sciences, 10(3), 170-185. https://doi.org/10.4236/jss.2022.103012

De Paola, M., Gioia, F., & Scoppa, V. (2022). Online teaching, procrastination and students’ achievement: evidence from COVID-19 induced remote learning. http://dx.doi.org/10.2139/ssrn.4114561

Fentaw, Y., Moges, B. T., & Ismail, S. M. (2022). Academic Procrastination Behavior among Public University Students. Education Research International, 2022. https://doi.org/10.1155/2022/1277866

Gagnier, K. M., Holochwost, S. J., & Fisher, K. R. (2022). Spatial thinking in science, technology, engineering, and mathematics: Elementary teachers' beliefs, perceptions, and self?efficacy. Journal of Research in Science Teaching, 59(1), 95-126. https://doi.org/10.1002/tea.21722

Garcia, M. I., Caraig, D. J., Carator, K., Oyco, M. T., Tababa, G. A., Linaugo, J., & De Oca, P. R. (2022). The Influence of Gadget Dependency on the Academic Procrastination Levels of Grade 12 STEM Students. International Journal of Multidisciplinary: Applied Business and Education Research, 3(6), 1197-1210. https://doi.org/10.11594//ijmaber.03.06.22

Gargari, R. B., Sabouri, H., & Norzad, F. (2011) Academic procrastination: The relationship between causal attribution styles and behavioral postponement. Iranian Journal of Psychiatry and Behavioral Sciences, 5(2), 76-82. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3939975/

Geverola, I. J. R., Mutya, R. C., Siason, L. M. B., & Bonotan, A. (2022). Challenges and struggles of public senior high school science teachers during the new normal. Journal of Research, Policy & Practice of Teachers and Teacher Education, 12(1), 49-68. https://doi.org/10.37134/jrpptte.vol12.1.4.2022

Harefa, S., & Sihombing, G. L. A. (2021). Students’ perception of online learning amidst the Covid-19 pandemic: A study of junior, senior high school and college students in a remote area. F1000Research, 10. https://doi.org/10.12688/f1000research.52152.2

Hinderliter, H., Xie, Y., Ladendorf, K., & Muehsler, H. (2022). Path Analysis of Internal and External Factors Associated with Parental Satisfaction over K-12 Online Learning. Computers in the Schools, 38(4), 354-383. https://doi.org/10.1080/07380569.2021.1988319

Karagiannopoulou, E., Milienos, F. S., & Rentzios, C. (2022). Grouping learning approaches and emotional factors to predict students’ academic progress. International Journal of School & Educational Psychology, 10(2), 258-275. https://doi.org/10.1080/21683603.2020.1832941

Kulal, A., & Nayak, A. (2020). A study on perception of teachers and students toward online classes in Dakshina Kannada and Udupi District. Asian Association of Open Universities Journal. https://doi.org/10.1108/AAOUJ-07-2020-0047

Laurie, A., & Hellsten, M. (2002). What Do We Know About Time Management? A Review of the Literature and a Psychometric Critique of Instruments Assessing Time Management University of Saskatchewan, Canada. https://doi.org/10.5772/37248

Lopez-Agudo, L. A., & Marcenaro-Gutierrez, O. D. (2022). Instruction time and students’ academic achievement: a cross-country comparison. Compare: A Journal of Comparative and International Education, 52(1), 75-91. https://doi.org/10.1080/03057925.2020.1737919

Miertschin, S. L., Goodson, C. E., & Stewart, B. L. (2015). Time management skills and student performance in online courses. In 2015 ASEE Annual Conference & Exposition (pp. 26-1585). https://doi.org/10.18260/p.24921

Migliozzi, C. L. (2022). Engaging the Adult College Student: A Case Study on Improving Nontraditional Students’ Persistence. https://scholarworks.umb.edu/instruction_capstone/82

Narci, M. (2022). The Relationship Between Problematic Internet Use and Academic Procrastination and Life Satisfaction of University Students (Doctoral dissertation, University of Alabama Libraries). https://www.proquest.com/openview/59be06329f73db36012c76a7fe6f6745/1.pdf?pq-origsite=gscholar&cbl=18750&diss=y

Naturil-Alfonso, C., Peñaranda, D., Vicente, J., & Marco-Jiménez, F. (2018, October). Procrastination: the poor time management among university students. In 4th International Conference on Higher Education Advances (HEAD'18) (pp. 1-8). Editorial Universitat Politècnica de València. https://doi.org/10.4995/HEAD18.2018.8167

Njuguna, M. N. (2022). Antecedents of Academic Procrastination and its Relationship to Academic Achievement among form Three Students in Kiambu County, Kenya. https://ir-library.ku.ac.ke/bitstream/handle/123456789/23953/Antecedents%20of%20Academic%20Procrastination…..pdf?sequence=1

Noran, F. Y. (2000). Procrastination among students in institutes of higher learning: Challenges for K-Economy. Retrieved December, 30, 2008. https://files.eric.ed.gov/fulltext/EJ1066019.pdf

Ocak, G., & Boyraz, S. (2016). Examination of the Relation between Academic Procrastination and Time Management Skills of Undergraduate Students in Terms of Some Variables. Journal of education and training studies, 4(5), 76-84. https://eric.ed.gov/?id=EJ1092698

Pagaran, G. M., Loremas, M. L., Gultiano, J. D., & Etcuban, J. O. (2022). Mathematics Performance of Senior High School Students in Blended Learning Amidst the Covid-19 Pandemic. Journal of Positive School Psychology, 10593-10613. https://journalppw.com/index.php/jpsp/article/view/9686/6321

Parantika, I. W. A., Suniasih, N. W., & Kristiantari, M. R. (2020). Differences in academic procrastination attitude between fifth grade male and female students. Journal of Psychology and Instruction, 4(1), 10-15. https://doi.org/10.23887/jpai.v4i1.24451

Pilotti, M. A., El-Moussa, O. J., & Abdelsalam, H. M. (2022). Measuring the impact of the pandemic on female and male students’ learning in a society in transition: A must for sustainable education. Sustainability, 14(6), 3148. https://doi.org/10.3390/su14063148

Rabin, A. L., Fogel, J., & Upham-Nutter, E. K. (2011). Academic procrastination in college students: The role of self-reported executive function. Journal of Clinical and Experimental Neuropsychology, 3(3), 344-357. https://doi.org/10.1080/13803395.2010.518597

Shaked, L., & Altarac, H. (2022). The possible contribution of procrastination and perception of self-efficacy to academic achievement. Journal of Further and Higher Education, 1-17. https://doi.org/10.1080/0309877X.2022.2102414

Shepperd, R. S. (2002). Predictors of student success in distance education courses. West Virginia University. https://www.proquest.com/openview/d4c1195ea0c6ffe90fef5b104ea60872/1?pq-origsite=gscholar&cbl=18750&diss=y

Solomon, L. J., & Rothblum, E. (1988). Procrastination assessment scale-students. Dictionary of behavioral assessment techniques, 358-360. https://web.archive.org/web/20091222073641id_/http://www-rohan.sdsu.edu:80/~rothblum/doc_pdf/procrastination/ProcrastinationAssessmentScaleStudents.pdf

Soysal, D., Bani-Yaghoub, M., & Riggers-Piehl, T. A. (2022). Analysis of anxiety, motivation, and confidence of STEM students during the COVID-19 pandemic. International Electronic Journal of Mathematics Education, 17(2), em0684. https://doi.org/10.29333/iejme/11836

Steel, P. (2007). The nature of procrastination: A meta-analytic and theoretical review of quintessential self-regulatory failure, Psychological Bulletin, 133, 65–94. https://doi.org/10.1037/0033-2909.133.1.65

Tezer, M., Çavu?, S., Orkun, M. A., Osum, A., & Ture, A. (2021). Examination of opinions of elementary school students on Mathematics course in the COVID-19 pandemic process. International Journal of Learning and Teaching, 13(1), 42-53. https://doi.org/10.18844/ijlt.v13i1.5279

Time Management Questionnaire. (2014). Wayne State University. Retrieved July 05, 2022 from http://advising.wayne.edu/hndbk/time.php

Treceñe, J. K. D. (2022). COVID-19 and Remote Learning in the Philippine Basic Education System: Experiences of Teachers, Parents, and Students. In Socioeconomic Inclusion During an Era of Online Education (pp. 92-110). IGI Global. https://www.igi-global.com/chapter/covid-19-and-remote-learning-in-the-philippine-basic-education-system/307359

Vooren, M., Haelermans, C., Groot, W., & van den Brink, H. M. (2022). Comparing success of female students to their male counterparts in the STEM fields: an empirical analysis from enrollment until graduation using longitudinal register data. International Journal of STEM Education, 9(1), 1-17. https://doi.org/10.1186/s40594-021-00318-8

Winanda, R. S., Mikail, A., Ahmad, D., Agustina, D., & Rahmawati, R. (2022). University Students' Procrastination: A Mathematical Model (Case Studies: Student in Mathematics Department Universitas Negeri Padang). Eksakta: Berkala Ilmiah Bidang MIPA (E-ISSN: 2549-7464), 23(02), 98-105. https://doi.org/10.24036/eksakta/vol23-iss02/315

Xu, J. (2022). More than minutes: A person-centered approach to homework time, homework time management, and homework procrastination. Contemporary Educational Psychology, 70, 102087. https://doi.org/10.1016/j.cedpsych.2022.102087

Žnidarši?, A., Brezavš?ek, A., Rus, G., & Jerebic, J. (2022). Has the COVID-19 Pandemic Affected Mathematics Achievement? A Case Study of University Students in Social Sciences. Mathematics, 10(13),

https://doi.org/10.3390/math10132314

• There are currently no refbacks.

e-ISSN: 1694-2116

p-ISSN: 1694-2493

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

Students’ Time Management, Academic Procrastination, and Performance during Online Science and Mathematics Classes

International Journal of Learning, Teaching and Educational Research

COVID-19 affected all sectors, including academia, which resulted in an increase in online learning. While education continued through online platforms, various students-related problems arose, including improper time management, procrastination, and fluctuating academic performance. It is in this context that this quantitative study was carried out to determine how time management and procrastination affected students’ performance in science and mathematics during the pandemic. We surveyed 650 Filipino high school students using the Procrastination Assessment Scale-Students and Wayne State University’s Time Management questionnaire with a 0.93 reliability coefficient. The findings revealed that in science and mathematics, female students outperformed males. Eleven 12-year-olds had the highest mean grades in science and mathematics, while 15 16-year-olds had the lowest. Younger respondents (11-14) were more likely to have better time management in than older ones. Further, older res...

Related Papers

Marius Castillo

Quarantines and virtual learning became necessary as a result of the COVID-19 pandemic. This study investigates the challenges and opportunities in virtual classes; and how they affect the academic goals. There were 150 secondary students from Junior and Senior High School levels of education in the Philippines, who were deliberately selected; and they participated in the quantitative online survey that used a 62-item self-made 4-point Likert scale questionnaire, with 0.81 reliability coefficients. The data were evaluated by means of the percentage, the mean, and the standard deviation. Sex and secondary education levels were used, in order to compare the students’ challenges and opportunities. One-way ANOVA compared the male and female respondents’ perceived challenges and opportunities. The results revealed that junior high-school (JHS) girls highlighted academic satisfaction; while school-life balance, and virtual learning helped as challenges and opportunities. The females found...

Mindset plays a vital role in tackling the barriers to improving the preservice mathematics teachers’ (PMTs) conceptual understanding of problem-solving. As the COVID-19 pandemic has continued to pose a challenge, online learning has been adopted. This led this study to determining the PMTs’ mindset and level of conceptual understanding in problem-solving in an online learning environment utilising Google Classroom and the Khan Academy. A quantitative research design was employed specifically utilising a descriptive, comparative, and correlational design. Forty-five PMTs were chosen through simple random sampling and willingly took part in this study. The data was gathered using validated and reliable questionnaires and problem-solving tests. The data gathered was analysed using descriptive statistics, analysis of variance, and simple linear regression. The results revealed that the college admission test, specifically numerical proficiency, influences a strong mindset and a higher ...

AHLAM ALGHAMDI

The outbreak of Covid-19 and consequent school closures created a considerable challenge for educational systems around the world. Many countries have shifted to online learning and other digital alternatives to ensure continuity in education. Within this global and historical context of the Covid 19 pandemic, the present study aimed to explore teachers’ attitudes towards the use of online learning for young children in Saudi Arabia. A total of 346 early childhood teachers were surveyed during school closures and the concomitant shift to online learning and teaching. The teachers who participated were recruited from public and private kindergartens and early childhood centers. The respondents completed a survey consisting of two scales developed for the purposes of this study. The first scale explored teachers’ general attitudes towards using online learning strategies with young children (10 items). The second scale explored teachers’ attitudes towards using online learning with yo...

Muhammad Sofwan Mahmud

With the rapid advancement of internet technology, the increasing prevalence of smartphone ownership at a young age, the uncertainty surrounding the end of the COVID-19 pandemic, and the effect of social media addiction on academic performance among students, social media use will continue to be a major point of contention. However, student-athletes are a distinct group of students who should not be overlooked due to their concurrent commitments to studying, training, and competing. As such, this study sought to investigate the effect of social media addiction on academic performance among Generation Z student-athletes during Malaysia&#39;s COVID-19 lockdown. The research design used in this study was a quantitative cross-sectional survey. This study surveyed 91 respondents and utilized the Social Media Addiction Questionnaire (SMAQ) and Grade Point Average (GPA). The findings indicated that Facebook was the preferred social media platform over Instagram, Twitter, and YouTube, and t...

Rosmah Mat Isa

There is a growing concern for educational institutions to transform and innovate their teaching and learning pedagogy to meet today&#39;s demands. This phenomenon is reflected in the rise of the flipped or inverted classroom. However, the motivation and intention of educators to transform from conventional teaching to flipped classrooms is poorly understood. Therefore, a scoping review of the literature was undertaken to identify important determinants in educators’ motivation and intention within the UTAUT model to use the flipped classroom. Databases searched included the Web of Science, Scopus, and ERIC databases. Arksey and O’Malley’s five-stage framework was utilized as the method for the scoping review process. The findings reveal four main themes and twelve sub-themes regarding educators’ motivation and intention to implement the flipped classroom, of which social factors are the most dominant determinants. By examining the crucial determinants that influence the motivation ...

rohaila yusof

This study aimed to examine the advantages of online socializing and digital learning for the growth of interpersonal, peer learning and collaborative skills. The impact of these three skills on knowledge construction was evaluated. The Salmon five step e-moderation model has been used to explore the many phases of learning in a digital environment. This study examined the first stage of the e-moderation model, which is the respondents&#39; internet accessibility, and the stage of knowledge construction in digital learning. The respondents of this study were 402 undergraduate students from four universities who have completed four semesters of online study. A stratified cluster sampling technique was employed in choosing the samples for this study. The instrument for data collection from the respondents was a 40-item questionnaire. Google Forms was utilized as the medium for data gathering. The main findings show that online learning involves a lot of interpersonal, peer learning, a...

Dianne Balibrea

Due to the impact of the COVID-19 pandemic, distance education has subsequently turned into the dominant mode of teaching, especially in the Philippines, where the majority of schools are still physically closed. Over a year since distance education was fully implemented in the country, it is essential to understand the general attitudes towards distance learning of Filipino teachers who have been teaching at various educational levels, including elementary, secondary, and tertiary levels, particularly in terms of student interaction, student performance, tool use, and availability, the support they have received from their schools, their willingness to handle distance and learning classes, as well as their experience in online teaching. The quantitative study was conducted with 151 respondents, using an online survey. Regarding their general attitude towards distance learning, the majority believe that distance education is not a viable alternative to face-to-face learning. In term...

Nur Ehsan Mohd Said

The outbreak of the novel coronavirus (COVID-19) has affected many areas of human life. It has brought about massive changes to the educational sector as institutions worldwide are forced to close down and students are required to learn from home via online learning. Students were reported to display reluctance and lack of motivation during the online lessons which led to a negative impact on their academic performance during the pandemic. This paper aims to explore the impact of adopting Stephen R.Covey’s 7 Habits of Highly Effective People on students’ academic performance. The study undertaken consists of a descriptive research whereby questionnaires and average score sheets were used to collect data from fifty- six Junior 1 students of a Chinese Independent Secondary School in Selangor, Malaysia. The findings indicate that adopting the prescribed habits brought about substantial impact on students’ academic performance. It helped to deal with the transitional phase in education ...

Evgenia Gkintoni

The present study investigates the role of synchronous and asynchronous education techniques in the context of digital and game-based learning materials through a collaborative study, conducted during the Covid-19 pandemic (October 2020 – June 2021), in an online e-learning environment. The study involved 35 last-year elementary school children, in Western Greece, with learning and behavioral issues. The children were given games with both practical and academic modules throughout their online schooling. For example, a math game was played over WebEx using Kahoot; a game for European institutions was created using the learningapps.org software; and online games from the European Union&#39;s &quot;Learning Corner&quot; as well as the game &quot;Defeat the Virus&quot; were used for the Social and Political Education topic. The findings are based on data collected through synchronous and asynchronous e-learning frameworks (WebEx, e-Class), and were linked to both cognitive learning asp...

RELATED PAPERS

Admire Chibisa

Januarius Mujiyanto

Leon Mugabo

jorrye jakiwa

Ramlee Ismail

joyce cuyangoan

Nahla Moussa

Abdou LJ Jammeh

evi muafiah

Thamsanqa Sihele

Awelani Rambuda

Marchee Picardal

International Journal of Learning, Teaching and Educational Research,

Adigun Olufemi

Laura Arnold

Fidlizan Muhammad

yuli astutik

Walid Aboraya

Fatmah Almoayad

ONG LIN DAR Ong

Sanderson Abel

Omar Al Serhan

Dr Medson Mapuya

Zeba F Alam

Claude Karegeya

Israel Kariyana

pule kalane

MAGDA FRANCISCA CEJAS MARTÍNEZ

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024