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Student Effort, Consistency, and Online Performance
ARTICLE

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Journal of Educators Online Volume 8, Number 2, ISSN 1547-500X Publisher: Journal of Educators Online

Abstract

This paper examines how student effort, consistency, motivation, and marginal learning, influence student grades in an online course. We use data from eleven Microeconomics courses taught online for a total of 212 students. Our findings show that consistency, or less time variation, is a statistically significant explanatory variable, whereas effort, or total minutes spent online, is not. Other independent variables include GPA and the difference between a pre-test and a post-test. The GPA is used as a measure of motivation, and the difference between a post-test and pre-test as marginal learning. As expected, the level of motivation is found statistically significant at a 99% confidence level, and marginal learning is also significant at a 95% level. (Contains 3 tables.)

Citation

Patron, H. & Lopez, S. (2011). Student Effort, Consistency, and Online Performance. Journal of Educators Online, 8(2),. Retrieved May 17, 2022 from .

© 2011 Journal of Educators Online

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  1. Allen, G., Lerner, W., & Hinrichsen, J.J. (1972). Study behaviors and their relationships to test anxiety and academic performance. Psychological Reports (30), 407-410.
  2. Britton, B.K., & Tesser, A. (1991). Effects of Time-Management Practices on College Grades. Journal of Educational Psychology, 83 (3), 405-410.
  3. Cheo, R. (2003). Making the Grade through Class Effort Alone. Economic Papers, 22, 55-65.
  4. Crede, M., Roch, S., & Kieszczynka, U. (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 (2), 272-295.
  5. Damianov, D., Kupczynski, L., Calafiore, P., Damianova, E., Soydemir, G., & Gonzalez, E. (2009). Time Spent Online and Student Performance in Online Business Courses: A Multinomial Logit Analysis. Journal of Economics and Finance Education, 8 (2), 11-19.
  6. Durden, G.C., & Ellis, L.V. (1995). The Effects of Attendance on Student Learning in Principles of Economics. American Economic Review, 85 (2), 343-346.
  7. Greenwald, A., & Gillmore, G.M. (1997). No pain, no gain? The importance of measuring course workload in student ratings of instruction. Journal of Educational Psychology, 89 (4), 743-751.
  8. Harrell, A., Kapsak, K., Cisin, I.H., & Wirtz, P.W. (1986). The Validity of Self-Reported Drug Use Data: The Accuracy of Responses on Confidential-Administered Answered Sheets. Social Research Group, The George Washington University. National Institute on Drug Abuse.
  9. Jacobs, J.A. (1998, December). Measuring time at work: are self-reports accurate? Monthly Labor Review, 43-52.
  10. Johnson, S., Aragon, S.R., Shaik, N., & Palma-Rivas, N. (2000). Comparative Analysis of Learner Satisfaction and Learning Outcomes in Online and Face-to-Face Learning Environment. Journal of Interactive Learning Research., 11 (1), 29-49.
  11. Kennedy, P. (2008). A Guide to Econometrics (6th Edition ed.). Malden, MA, USA: Blackwell Publishing Ltd.
  12. Leamer, E.E. (2007). A Flat World, a Level Playing Field, a Small World After All, or More of the Above? A Review of Thomas L Friedman's The World is Flat. Journal of Economics Literature (45), 83-126.
  13. Michinov, N., Brunot, S., Le Bohec, O., Jacques, J., & Marine, D. (2011). Procrastination, participation, and performance in online learning environments. Computers and Education (56), 243-252.
  14. Olivares, O. (2000). Radical Pedagogy. Retrieved December 10, 2010, from ICAAP: http://radicalpedagogy.icaap.org/content/issue4_1/06_olivares.html
  15. Park, K.H., & Kerr, P.M. (1990). Determinants of Academic Performance: A Multinomial Logit Approach. Journal of Economic Education, 21 (2), 101-111.
  16. Ramos, C., & Yudko, E. (2008). "Hits" (not "Discussion Posts") predict student success in online courses: A double-cross validation study. Computers and Education (50), 1174-1182.
  17. Rau, W., & Durand, A. (2000). The academic ethic and college grades: Does hard work help students to "make the grade"? Sociology of Education (1973), 19-38.
  18. Romer, D. (1993). Do Students Go to Class? Should They? Journal of Economic Perspectives, 7, 167-174.
  19. Schuman, H., Walsh, E., Olson, C., & Etheridge, B. (1985). Effort and Reward: The Assumption that College Grades Are Affected by Quantity of Study. Social Forces, 63 (4), 945-966.
  20. Spector, L., & Mazzeo, M. (1980). Probit Analysis and Economic Education. Journal of Economic Education, 11, 37-44.
  21. Stinebrickner, R., & Stinebrickner, T.R. (2004). Time-Use and College Outcomes. Journal of Econometrics (121), 243-269.
  22. Taraban, R., Williams, M., & Rynearson, K. (1999). Measuring study time distributions: Implications for designing computer-based courses. Behavior Research Methods & Instruments, 31 (2), 263-269.
  23. Wagstaff, R., & Mahmoudi, H. (1976). Relation of study behaviors and employment to academic performance. Psychological Reports, 38, 380-382.
  24. Waschull, S.B. (2005). Predicting Success in Online Psychology Courses: Self-Discipline and Motivation. Teaching of Psychology, 32 (3), 190-208.
  25. Wetzel, J.E. (1977). Measuring Student Scholastic Effort: An Economic Theory of Learning Approach. The Journal of Economic Education, 34-41.
  26. Wong, W.-K. (2008). How Much Time-Inconsistency Is There and Does it Matter? Evidence on Self-Awareness, Size, and Effects. Journal of Economic Behavior and Organization, 68 (3-4), 645-656.

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