Research in Higher Education

, Volume 60, Issue 4, pp 521–552 | Cite as

Does Inducing Students to Schedule Lecture Watching in Online Classes Improve Their Academic Performance? An Experimental Analysis of a Time Management Intervention

  • Rachel BakerEmail author
  • Brent Evans
  • Qiujie Li
  • Bianca Cung


Time management skills are an essential component of college student success, especially in online classes. Through a randomized control trial of students in a for-credit online course at a public 4-year university, we test the efficacy of a scheduling intervention aimed at improving students’ time management. Results indicate the intervention had positive effects on initial achievement scores; students who were given the opportunity to schedule their lecture watching in advance scored about a third of a standard deviation better on the first quiz than students who were not given that opportunity. These effects are concentrated in students with the lowest self-reported time management skills. However, these effects diminish over time such that we see a marginally significant negative effect of treatment on the last week’s quiz grade and no difference in overall course scores. We examine the effect of the intervention on plausible mechanisms to explain the observed achievement effects. We find no evidence that the intervention affected cramming, procrastination, or the time at which students did work.


Scheduling Procrastination Online courses Persistence Performance Achievement 



The authors are grateful for feedback and advice from the Investigating Virtual Learning Environments and Digital Learning Lab groups at UCI’s School of Education, particularly Di Xu, Fernando Rodriguez, and Mark Warschauer; seminar participants at AEFP; and the instructor with whom we partnered to implement this intervention. This work was supported by grant number 1535300 from the National Science Foundation.


  1. Allen, E., Seaman, J., Poulin, R., & Straut, T. (2016). Online report card: Tracking online education in the United States. Babson Survey Research Group and Quahog Research Group, LLC.Google Scholar
  2. Angelino, L., Williams, F., & Natvig, D. (2007). Strategies to engage online students and reduce attrition rates. The Journal of Educators Online, 4, 1–14.CrossRefGoogle Scholar
  3. Ariely, D., & Wertenbroch, K. (2002). Procrastination, deadlines, and performance: Self-control by precommitment. Psychological Science, 13, 219–224.CrossRefGoogle Scholar
  4. Arum, R., & Roksa, J. (2011). Academically adrift: Limited learning on college campuses. Chicago, IL: University of Chicago Press.Google Scholar
  5. Ashraf, N., Karlan, D., & Yin, W. (2006). Tying Odysseus to the mast: Evidence from a commitment savings product in the Philippines. Quarterly Journal of Economics, 121, 635–672.CrossRefGoogle Scholar
  6. Babcock, P., & Marks, M. (2011). The falling time cost of college: Evidence from half a century of time use data. The Review of Economics and Statistics, 93, 468–478.CrossRefGoogle Scholar
  7. Baker, R., Evans, B., & Dee, T. (2016). A randomized experiment testing the efficacy of a scheduling nudge in a Massive Open Online Course (MOOC). AERA Open, 2, 1–18.CrossRefGoogle Scholar
  8. Beattie, G., Laliberté, J. P., Michaud-Leclerc, C., & Oreopoulos, P. (2017). What sets college thrivers and divers apart? A contrast in study habits, attitudes, and mental health. National Bureau of Economic Research Working Paper No. 23588.Google Scholar
  9. Bjorklund, S. A., Parente, J. M., & Sathianathan, D. (2004). Effects of faculty interaction and feedback on gains in student skills. Journal of Engineering Education, 93(2), 153–160.CrossRefGoogle Scholar
  10. Black, A. E., & Deci, E. L. (2000). The effects of instructors’ autonomy support and students’ autonomous motivation on learning organic chemistry: A self-determination theory perspective. Science Education, 84(6), 740–756.CrossRefGoogle Scholar
  11. Bowen, W. G., Chingos, M. M., Lack, K. A., & Nygren, T. I. (2014). Interactive learning online at public universities: Evidence from a six-campus randomized trial. Journal of Policy Analysis & Management, 33, 94–111.CrossRefGoogle Scholar
  12. Bowers, J., & Kumar, P. (2015). Students’ perceptions of teaching and social presence: A comparative analysis of face-to-face and online learning environments. International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), 10(1), 27–44.CrossRefGoogle Scholar
  13. Britton, B. K., & Tesser, A. (1991). Effects of time-management practices on college grades. Journal of Educational Psychology, 83, 405–410.CrossRefGoogle Scholar
  14. Broadbent, J., & Poon, W. L. (2015). Self-regulated learning strategies and academic achievement in online higher education learning environments: A systematic review. The Internet and Higher Education, 27, 1–13.CrossRefGoogle Scholar
  15. Carrell, S. E., Maghakian, T., & West, J. E. (2011). A’s from Zzzz’s? The causal effect of school start time on the academic achievement of adolescents. American Economics Journal: Economic Policy, 3, 62–81.Google Scholar
  16. Cochran, J. D., Campbell, S. M., Baker, H. M., & Leeds, E. M. (2014). The role of student characteristics in predicting retention in online courses. Research in Higher Education, 55, 27–48.CrossRefGoogle Scholar
  17. Deming, D. J., Goldin, C., Katz, L. F., & Yuchtman, N. (2015). Can online learning bend the higher education cost curve? American Economic Review, 105, 496–501.CrossRefGoogle Scholar
  18. Elvers, G. C., Polzella, D. J., & Graetz, K. (2003). Procrastination in online courses: Performance and attitudinal differences. Teaching of Psychology, 30, 159–162.CrossRefGoogle Scholar
  19. Evans, B., Baker, R., & Dee, T. (2016). Persistence patterns in Massive Open Online Courses (MOOCs). Journal of Higher Education, 87, 206–242.CrossRefGoogle Scholar
  20. Figlio, D., Rush, M., & Yin, L. (2013). Is it live or is it internet? Experimental estimates of the effects of online instruction on student learning. Journal of Labor Economics, 31, 763–784.CrossRefGoogle Scholar
  21. Frederick, S., Loewenstein, G., & O’donoghue, T. (2002). Time discounting and time preference: A critical review. Journal of economic literature, 40(2), 351–401.CrossRefGoogle Scholar
  22. Gine, Xavier, Karlan, Dean, & Zinman, Jonathan. (2010). Put your money where your butt is: A commitment contract for smoking cessation. American Economic Journal: Applied Economics, 2, 213–225.Google Scholar
  23. Goldstein, D., Hahn, C. S., Hasher, L., Wiprzycka, U. J., & Zelazo, P. D. (2007). Time of day, intellectual performance, and behavioral problems in morning versus evening type adolescents: Is there a synchrony effect? Personality and Individual Differences, 42, 431–440.CrossRefGoogle Scholar
  24. Griffith, A. L. (2010). Persistence of women and minorities in STEM field majors: Is it the school that matters? Economics of Education Review, 29, 911–922.CrossRefGoogle Scholar
  25. Guàrdia, L., Maina, M., & Sangrà, A. (2013). MOOC design principles. A pedagogical approach form the learner’s perspective. eLearning Papers, 33, 1–6.Google Scholar
  26. Hart, C. (2012). Factors associated with student persistence in an online program of study: A review of the literature. Journal of Interactive Online Learning, 11, 19–42.Google Scholar
  27. Hartwig, M. K., & Dunlosky, J. (2012). Study strategies of college students: Are self-testing and scheduling related to achievement? Psychonomic Bulletin & Review, 19, 126–134.CrossRefGoogle Scholar
  28. Heiman, T. (2008). The effects of e-mail messages in a distance learning university on perceived academic and social support, academic satisfaction, and coping. Quarterly Review of Distance Education, 9(3), 237.Google Scholar
  29. Kang, M., & Im, T. (2013). Factors of learner–instructor interaction which predict perceived learning outcomes in online learning environment. Journal of Computer Assisted Learning, 29(3), 292–301.CrossRefGoogle Scholar
  30. Kaur, S., Kremer, M., & Mullainathan, S. (2013). Self-control at work. Duke University working paper.Google Scholar
  31. Kizilcec, R. F., Pérez-Sanagustín, M., & Maldonado, J. J. (2016). Recommending self-regulated learning strategies does not improve performance in a MOOC. Learning @ Scale Work in Progress.Google Scholar
  32. Koch, A. K., & Nafziger, J. (2017). Motivational goal bracketing: An experiment (No. 10955). Institute for the Study of Labor (IZA) Discussion Paper.Google Scholar
  33. Kruger, J., & Dunning, D. (1999). Unskilled and unaware of it: How difficulties in recognizing one’s own incompetence lead to inflated self-assessments. Journal of Personality and Social Psychology, 77(6), 1121.CrossRefGoogle Scholar
  34. Lack, K. A. (2013). Current status of research on online learning in postsecondary education. ITHAKA S + R.Google Scholar
  35. Leeds, E. M., Campbell, S. M., Baker, H., Ali, R., & Brawley, D. (2013). The impact of student retention strategies: An empirical study. International Journal of Management in Education, 7, 22–43.CrossRefGoogle Scholar
  36. 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.CrossRefGoogle Scholar
  37. Michinov, N., Brunot, S., Le Bohec, O., Juhel, J., & Delaval, M. (2011). Procrastination, participation, and performance in online learning environments. Computers & Education, 56, 243–252.CrossRefGoogle Scholar
  38. Miltiadou, M., & Savenye, W. C. (2003). Applying social cognitive constructs of motivation to enhance student success in online distance education. AACE Journal, 11(1), 78–95.Google Scholar
  39. Misra, R., & McKean, M. (2000). College students’ academic stress and its relation to their anxiety, time management, and leisure satisfaction. American Journal of Health Studies, 16, 41–51.Google Scholar
  40. Moody, J. (2004). Distance education: Why are the attrition rates so high? Quarterly Review of Distance Education, 5, 205–210.Google Scholar
  41. Mullen, G. E., & Tallent-Runnels, M. K. (2006). Student outcomes and perceptions of instructors’ demands and support in online and traditional classrooms. The Internet and Higher Education, 9(4), 257–266.CrossRefGoogle Scholar
  42. National Center for Education Statistics. (NCES). (2015). Digest of Education Statistics, Table 311.15.Google Scholar
  43. Nawrot, I., & Doucet, A. (2014). Building engagement for MOOC students: Introduction support for time management on online learning platforms. In Proceedings of the 23rd international conference on the World Wide Web (pp. 1077–1082). New York, NY: ACM.Google Scholar
  44. Patterson, R. W. (2014). Can behavioral tools improve online student outcomes? Experimental evidence from a Massive Open Online Course. Working paper.Google Scholar
  45. Perna, L. W., Ruby, A., Boruch, R. F., Wang, N., Scull, J., Ahmad, S., et al. (2014). Moving through MOOCs: Understanding the progression of users in Massive Open Online Courses. Educational Researcher, 43, 421–432.CrossRefGoogle Scholar
  46. Pintrich, P. R. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ).Google Scholar
  47. Rask, K., & Tiefenthaler, J. (2008). The role of grade selectivity in explaining the gender imbalance in undergraduate economics. Economics of Education Review, 27, 676–687.CrossRefGoogle Scholar
  48. Roper, A. R. (2007). How students develop online learning skills. Educause Quarterly, 30, 62–65.Google Scholar
  49. Rostaminezhad, M. A., Mozayani, N., Norozi, D., & Iziy, M. (2013). Factors related to e-learner dropout: Case study of IUST elearning center. Procedia, 83, 522–527.Google Scholar
  50. Rovai, A. P. (2003). In search of higher persistence rates in distance education online programs. The Internet and Higher Education, 6, 1–16.CrossRefGoogle Scholar
  51. Schudde, L., & Scott-Clayton, J. (2016). Pell Grants as performance-based scholarships? An examination of satisfactory academic progress requirements in the nation’s largest need-based aid program. Research in Higher Education, 57, 943–967.CrossRefGoogle Scholar
  52. Schwartz, B., & Ward, A. (2004). Doing better but feeling worse: The paradox of choice. In P. A. Linley & S. Joseph (Eds.), Positive Psychology in Practice (pp. 86–104). Hoboken, NJ: Wiley.Google Scholar
  53. Song, L., Singleton, E. S., Hill, J. R., & Koh, M. H. (2004). Improving online learning: Student perceptions of useful and challenging characteristics. Internet and Higher Education, 7, 59–70.CrossRefGoogle Scholar
  54. Stratton, L. S., O’Toole, D. M., & Wetzel, J. N. (2008). A multinomial logit model of college stopout and dropout behavior. Economics of Education Review, 27, 319–331.CrossRefGoogle Scholar
  55. 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.CrossRefGoogle Scholar
  56. Tuckman, B. W. (2005). Relations of academic procrastination, rationalizations, and performance in a web course with deadlines. Psychological Reports, 96(3_suppl), 1015–1021.CrossRefGoogle Scholar
  57. 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.CrossRefGoogle Scholar
  58. What Works Clearinghouse. (2017). Standard handbook version 4.0. Washington, DC: Institute of Education Sciences.Google Scholar
  59. Xu, D., & Jaggars, S. S. (2013). The impact of online learning on students’ course outcomes: Evidence from a large community and technical college system. Economics of Education Review, 37, 46–57.CrossRefGoogle Scholar
  60. Zhan, Z., & Mei, H. (2013). Academic self-concept and social presence in face-to-face and online learning: Perceptions and effects on students’ learning achievement and satisfaction across environments. Computers & Education, 69, 131–138.CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.University of California, Irvine – School of EducationIrvineUSA
  2. 2.Peabody CollegeVanderbilt UniversityNashvilleUSA

Personalised recommendations