Exploring the Relationships Between Motivation and Academic Permormance Among Online and Blended Learners: A Meta-Analytic Review
DOI:
https://doi.org/10.24059/olj.v28i4.4602Keywords:
meta-analysis, online learning, blended learning, motivationAbstract
In higher education, motivational factors are considered one of “the strongest predictors of academic performance” (Honike et al., 2020, p. 1). A meta-analysis of face-to-face (f2f) courses (Richardson et al., 2012) supports these claims, finding a strong correlation between performance self-efficacy and academic performance (r = 0.59), as well as accounting for 14% of the variation in academic performance using locus of control, performance self-efficacy, and grade goal as predictors. These f2f results are compelling enough that self-efficacy is often used synonymously with online learning in primary research. However, the results of prior f2f meta-analytic reviews have yet to be extended to online and blended learning contexts. We explored student motivation, specifically subscales for attributional style, self-efficacy, achievement goal orientation, self-determination and task value in relation to student academic performance. Informed by 94 outcomes from 52 studies, our results diverge from f2f findings. The highest correlation was mastery avoidance goals (r = 0.22) and academic self-efficacy (r = 0.19) was substantially lower than f2f findings (r = 0.31; r = 0.59) in Richardson et al., (2012). Using a parsimonious model (i.e., delivery mode, learning self-efficacy, and mastery approach goals), students’ average academic performance failed to identify significantly significant predictors. These results call into question the assumption that student motivation is a strong predictor of academic performance in online and blended courses. The lack of strong relationships and the lack of predictive power hold clear implications for researchers, practitioners, and policymakers that assume these relationships are stronger.
References
Akin, A. (2007). Academic locus of control scale: A study of validity and reliability. Çukurova University Journal of Educational Faculty, 34(3), 9–17. https://www.acarindex.com/dosyalar/makale/acarindex-1423874900.pdf
Alkış, N., & Temizel, T. T. (2018). The impact of motivation and personality on academic performance in online and blended learning environments. Journal of Educational Technology & Society, 21(3), 35–47. https://doi.org/10.30191/ETS.201807_21(3).0004
Alqurashi, E. (2016). Self-efficacy in online learning environments: A literature review. Contemporary Issues in Education Research (Online), 9(1), 45–52.
Amin, E. A.-R. (2016). Using wikis in developing writing performance and motivation among EFL students at Majmaah University. Journal of Faculty of Education—Benha University, 352(3502), 1–31. https://doi.org/10.12816/0028199
Amin, E. A.-R. (2019). A correlational study between some motivational constructs and EFL writing performance in a blended learning environment. International Journal of English Linguistics, 9(3), 238–248. https://doi.org/10.5539/ijel.v9n3p238
Artino, A. R., Jr., & Stephens, J. M. (2009). Beyond grades in online learning: Adaptive profiles of academic self-regulation among naval academy undergraduates. Journal of Advanced Academics, 20(4), 568–601. https://doi.org/10.1177/1932202X0902000402
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice Hall.
Bardach, L., Oczlon, S., Pietschnig, J., & Lüftenegger, M. (2020). Has achievement goal theory been right? A meta-analysis of the relation between goal structures and personal achievement goals. Journal of Educational Psychology, 112(6), 1197–1220. https://doi.org/10.1037/edu0000419
Baturay, M. H., & Yukselturk, E. (2015). The role of online education preferences on student’s achievement. Turkish Online Journal of Distance Education, 16(3), 3–12. https://doi.org/10.17718/tojde.47810
Bell, P. D. (2007). Predictors of college student achievement in undergraduate asynchronous web-based courses. Education, 127(4), 523–533. https://doi.org/10.1016/j.compedu.2023.104776
Bernard, R. M., Abrami, P. C., Wade, A., Borokhovski, E., & Lou, Y. (2004). The effects of synchronous and asynchronous distance education: A meta-analytical assessment of Simonson’s “Equivalency Theory.” 2004 AECT Convention- 27th Annual Proceedings, 1, 102–109. https://eric.ed.gov/?id=ED485078
Bouih, A., Nadif, B., & Benattabou, D. (2021). Assessing the effect of general self-efficacy on academic achievement using path analysis: A preliminary study. Journal of English Language Teaching and Applied Linguistics, 3(4), 18–24. https://doi.org/10.32996/jeltal.2021.3.4.3
Cannon, J. P., Lohtia, R., & Paulich, B. J. (2023). Blended learning in principles of marketing: The effects of student differences on student performance. Journal of Marketing Education, 45(1), 70–90. https://doi.org/10.1177/02734753211058357
Cassidy, S., & Eachus, P. (2002). Developing the Computer User Self-Efficacy (CUSE) scale: Investigating the relationship between computer self-efficacy, gender and experience with computers. Journal of Educational Computing Research, 26(2), 133–153. https://doi.org/10.2190/JGJR-0KVL-HRF7-GCNV
Chang, C. S. (2000). The effect of attitudes and self-efficacy on college student performance in online instruction [Doctoral dissertation, University of Kansas]. ProQuest Dissertations and Theses. https://www.proquest.com/docview/304603922
Chang, C.-S., Liu, E. Z.-F., Sung, H.-Y., Lin, C.-H., Chen, N.-S., & Cheng, S.-S. (2014). Effects of online college student’s Internet self-efficacy on learning motivation and performance. Innovations in Education & Teaching International, 51(4), 366–377. https://doi.org/10.1080/14703297.2013.771429
Chang, M.-M., & Ho, C.-M. (2009). Effects of locus of control and learner-control on web-based language learning. Computer Assisted Language Learning, 22(3), 189–206. https://doi.org/10.1080/09588220902920094
Chen, K.-C., & Jang, S.-J. (2010). Motivation in online learning: Testing a model of self-determination theory. Computers in Human Behavior, 26(4), 741–752.
Cho, M.-H., & Shen, D. (2013). Self-regulation in online learning. Distance Education, 34(3), 290–301. https://doi.org/10.1080/01587919.2013.835770
Chung, J., McKenzie, S., Schweinsberg, A., & Mundy, M. E. (2022, February). Correlates of academic performance in online higher education: A systematic review. Frontiers in Education, 7, 820567. https://doi.org/10.3389/feduc.2022.820567
Crandall, V. C., Katkovsky, W., & Crandall, V. J. (1965). Children’s beliefs in their own control of reinforcements in intellectual-academic achievement situations. Child Development, 36(1), 91–109. https://doi.org/10.2307/1126783
Deci, E. L., & Ryan, R. M. (1985). Conceptualizations of intrinsic motivation and self-determination. In Intrinsic motivation and self-determination in human behavior (pp. 11–40). Plenum Press.
DeTure, M. (2004). Cognitive style and self-efficacy: Predicting student success in online distance education. American Journal of Distance Education, 18(1), 21–38.
Dokhykh, R. A. (2021). The impact of motivation on the academic performance of university students. Journal of Humanities & Social Sciences, 5(13), 103–113. https://doi.org/10.26389/AJSRP.R060221
Dray, B. J., Lowenthal, P. R., Miszkiewicz, M. J., Ruiz‐Primo, M. A., & Marczynski, K. (2011). Developing an instrument to assess student readiness for online learning: A validation study. Distance Education, 32(1), 29–47. https://doi.org/10.1080/01587919.2011.565496
Duncan, T. G., & McKeachie, W. J. (2005). The making of the Motivated Strategies for Learning Questionnaire. Educational Psychologist, 40(2), 117–128. https://doi.org/10.1207/s15326985ep4002_6
Eastin, M. S., & LaRose, R. (2000). Internet self-efficacy and the psychology of the digital divide. Journal of Computer-Mediated Communication, 6(1), JCMC611. https://doi.org/10.1111/j.1083-6101.2000.tb00110.x
Eccles, J., Adler, T., & Meece, J. L. (1984). Sex differences in achievement: A test of alternate theories. Journal of Personality and Social Psychology, 46(1), 26–43.
Elliot, A. J., & McGregor, H. A. (2001). A 2 × 2 achievement goal framework. Journal of Personality and Social Psychology, 80(3), 501–519. https://doi.org/10.1037/0022-3514.80.3.501
Elliot, A. J., & Murayama, K. (2008). On the measurement of achievement goals: Critique, illustration, and application. Journal of Educational Psychology, 100(3), 613–628. https://doi.org/10.1037/0022-0663.100.3.613
Ergul, H. (2004). Relationship between student characteristics and academic achievement in distance education and application on students of Anadolu University. Turkish Online Journal of Distance Education, 5(2), 81-90.
Fadda, H. A. (2019). The relationship between self-regulations and online learning in an ESL blended learning context. English Language Teaching, 12(6), 87–93. https://doi.org/10.5539/elt.v12n6p87
Finney, S. J., & Schraw, G. (2003). Self-efficacy beliefs in college statistics courses. Contemporary Educational Psychology, 28(2), 161–186. https://doi.org/10.1016/S0361-476X(02)00015-2
Friedman, B. A., & Mandel, R. G. (2011). Motivation predictors of college student academic performance and retention. Journal of College Student Retention: Research, Theory & Practice, 13(1), 1–15. https://doi.org/10.2190/CS.13.1.a
Gerlich, R., Mills, L., & Sollosy, M. (2009). An evaluation of predictors of achievement on selected outcomes in a self-paced online course. Research in Higher Education, 4, 1–14.
Goad, T., Jones, E., Bulger, S., Daum, D., Hollett, N., & Elliott, E. (2021). Predicting student success in online physical education. American Journal of Distance Education, 35(1), 17–32. https://doi.org/10.1080/08923647.2020.1829254
Grasgreen, A. (2012, July 5). Here’s Hoping. Inside Higher Ed. https://www.insidehighered.com/news/2012/07/06/researchers-apply-hope-theory-boost-college-student-success
Grolnick, W. S., & Ryan, R. M. (1987). Autonomy in children’s learning: An experimental and individual difference investigation. Journal of Personality and Social Psychology, 52(5), 890–898. https://doi.org/10.1037/0022-3514.52.5.890
Guamer Erickson, A. S., & Noonan, P. M. (2018). Self-efficacy formative questionnaire. In The skills that matter: Teaching interpersonal and intrapersonal competencies in any classroom (pp. 175–176). Corwin.
Guiffrida, D. A., Lynch, M. F., Wall, A. F., & Abel, D. S. (2013). Do reasons for attending college affect academic outcomes?: A test of a motivational model from a self-determination theory perspective. Journal of College Student Development, 54(2), 121–139. https://doi.org/10.1353/csd.2013.0019
Goulão, M. (2014). The relationship between self-efficacy and academic achievement in adults’ learners. Athens Journal of Education, 1, 237–246.
Gusenbauer, M., & Haddaway, N. R. (2020). Which academic search systems are suitable for systematic reviews or meta-analyses? Evaluating retrieval qualities of Google Scholar, PubMed, and 26 other resources. Research Synthesis Methods, 11(2), 181–217. https://doi.org/10.1002/jrsm.1378
Hamilton, I., & Freeman, V. (2023, May 24). By the numbers: The rise of online learning in the U.S. Forbes Advisor.
Hamm, J. M., Perry, R. P., Chipperfield, J. G., Parker, P. C., & Heckhausen, J. (2019). A motivation treatment to enhance goal engagement in online learning environments: Assisting failure-prone college students with low optimism. Motivation Science, 5(2), 116–134. https://doi.org/10.1037/mot0000107
Hobson, T. D., & Puruhito, K. K. (2018). Going the distance: Online course performance and motivation of distance learning students. Online Learning, 22(4), 129–140. https://doi.org/10.24059/olj.v22i4.1516
Hodges, C. B. (2008). Self-efficacy, motivational email, and achievement in an asynchronous math course. The Journal of Computers in Mathematics and Science Teaching, 27(3), 265–285. https://www.learntechlib.org/primary/p/25282/
Honicke, T., & Broadbent, J. (2016). The influence of academic self-efficacy on academic performance: A systematic review. Educational Research Review, 17, 63–84. https://doi.org/10.1016/j.edurev.2015.11.002
Honicke, T., Broadbent, J., & Fuller-Tyszkiewicz, M. (2020). Learner self-efficacy, goal orientation, and academic achievement: Exploring mediating and moderating relationships. Higher Education Research & Development, 39(4), 689–703. https://doi.org/10.1080/07294360.2019.1685941
Howard, J. L., Bureau, J. S., Guay, F., Chong, J. X. Y., & Ryan, R. M. (2021). Student motivation and associated outcomes: A meta-analysis from Self-Determination Theory. Perspectives on Psychological Science, 16(6), 1300–1323. https://doi.org/10.1177/1745691620966789
Hrastinski, S. (2019). What do we mean by blended learning? TechTrends, 63(5), 564–569. https://doi.org/10.1007/s11528-019-00375-5
Huang, C. (2012). Discriminant and criterion-related validity of achievement goals in predicting academic achievement: A meta-analysis. Journal of Educational Psychology, 104(1), 48–73. https://doi.org/10.1037/a0026223
Hulleman, C. S., Barron, K. E., Kosovich, J. J., & Lazowski, R. A. (2016). Student motivation: Current theories, constructs, and interventions within an Expectancy-Value framework. In A. A. Lipnevich, F. Preckel, & R. D. Roberts (Eds.), Psychosocial skills and school systems in the 21st Century (pp. 241–278). Springer International Publishing.
Hulleman, C. S., Schrager, S. M., Bodmann, S. M., & Harackiewicz, J. M. (2010). A meta-analytic review of achievement goal measures: Different labels for the same constructs or different constructs with similar labels? Psychological Bulletin, 136(3), 422–449. https://doi.org/10.1037/a0018947
Hung, M.-L., Chou, C., Chen, C.-H., & Own, Z.-Y. (2010). Learner readiness for online learning: Scale development and student perceptions. Computers & Education, 55(3), 1080–1090. https://doi.org/10.1016/j.compedu.2010.05.004
Husman, J., Derryberry, W. P., Crowson, H. M., & Lomax, R. (2004). Instrumentality, task value, and intrinsic motivation: Making sense of their independent interdependence. Contemporary Educational Psychology, 29(1), 63–76.
Hwang, G.-J., Yang, L.-H., & Wang, S.-Y. (2013). A concept map-embedded educational computer game for improving students’ learning performance in natural science courses. Computers & Education, 69, 121–130. https://doi.org/10.1016/j.compedu.2013.07.008
Jacobs, G., Opdenacker, L., & Waes, L. V. (2005). A multilanguage online writing center for professional communication: Development and testing. Business Communication Quarterly, 68(1), 8–22. https://doi.org/10.1177/1080569904273330
Jadric, M., Bubas, G., & Hutinski, Z. (2010). Dispositional predictors of student success in e-learning courses. Proceedings of the ITI 2010, 32nd International Conference on Information Technology Interfaces, 361–366.
Joo, Y. J., Lim, K. Y., & Kim, J. (2013). Locus of control, self-efficacy, and task value as predictors of learning outcome in an online university context. Computers & Education, 62, 149–158. https://doi.org/10.1016/j.compedu.2012.10.027
Kauffman, H. (2015). A review of predictive factors of student success in and satisfaction with online learning. Research in Learning Technology, 23, 26507. https://doi.org/10.3402/rlt.v23.26507
Kim, J.-Y. (2012). A study on learners’ perceptional typology and relationships among the learner’s types, characteristics, and academic achievement in a blended e-Education environment. Computers & Education, 59(2), 304–315. https://doi.org/10.1016/j.compedu.2012.01.010
Krippendorff, K. (2004). Reliability in content analysis: Some common misconceptions and recommendations. Human Communication Research, 30(3), 411–433. https://doi.org/10.1111/j.1468-2958.2004.tb00738.x
Lantolf, J. P., & Thorne, S. L. (2006). Sociocultural theory and the genesis of second language development. Oxford University Press.
Berners-Lee, T., Cailliau, R., Luotonen, A., Nielsen, H. F., & Secret, A. (1994). The World-Wide Web. Communications of the ACM, 37(8), 76–82. https://doi.org/10.1145/179606.179671
Lee, Y., & Choi, J. (2013). A structural equation model of predictors of online learning retention. The Internet and Higher Education, 16, 36–42. https://doi.org/10.1016/j.iheduc.2012.01.005
Lefcourt, H. M., Von Baeyer, C. L., Ware, E. E., & Cox, D. J. (1979). The multidimensional-multiattributional causality scale: The development of a goal specific locus of control scale. Canadian Journal of Behavioural Science, 11(4), 286–304. https://doi.org/10.1037/h0081598
Levenson, H. (1981). Differentiating among internality, powerful others, and chance. In H. M. Lefcourt (Ed.), Research with the locus of control construct (pp. 1–15). Academic Press.
Levy, Y. (2007). Comparing dropouts and persistence in e-learning courses. Computers & Education, 48(2), 185–204. https://doi.org/10.1016/j.compedu.2004.12.004
Liu, C., Sands-Meyer, S., & Audran, J. (2019). The effectiveness of the student response system (SRS) in English grammar learning in a flipped English as a foreign language (EFL) class. Interactive Learning Environments, 27(8), 1178–1191. https://doi.org/10.1080/10494820.2018.1528283
Lynch, R., & Dembo, M. (2004). The relationship between self-regulation and online learning in a blended learning context. International Review of Research in Open and Distributed Learning, 5(2), 1–16. https://doi.org/10.19173/irrodl.v5i2.189
Marakas, G., Johnson, R., & Clay, P. F. (2007). The evolving nature of the computer self-efficacy construct: An empirical investigation of measurement construction, validity, reliability and stability over time. Journal of the Association for Information Systems, 8(1). https://doi.org/10.17705/1jais.00112
Martin, F., Tutty, J. I., & Su, Y. (2010). Influence of learning management systems self-efficacy on e-learning performance. Journal on School Educational Technology, 5(3), 26–35.
McPhaul-Moore, E. (2013). Predictors of online learning success in a rural community college [Doctoral dissertation, Northcentral University]. ProQuest Dissertations and Theses. https://www.proquest.com/docview/1444627614
Meece, J. L., Anderman, E. M., & Anderman, L. H. (2006). Classroom goal structure, student motivation, and academic achievement. Annual Review of Psychology, 57, 487–503. https://doi.org/10.1146/annurev.psych.56.091103.070258
Midgley, C., Maehr, M. L., Hruda, L. Z., Anderman, E. M., Freeman, K. E., & Urdan, T. (2000). Manual for the Patterns of Adaptive Learning Scales (PALS). University of Michigan.
Miltiadou, M., & Savenye, W. C. (2003). Applying social cognitive constructs of motivation to enhance student success in online distance education. AACE Review, 11(1), 78–95. https://www.learntechlib.org/primary/p/17795/
Miltiadou, M., & Yu, C. H. (2000). Validation of the Online Technologies Self-Efficacy Scale (OTSES). https://eric.ed.gov/?id=ED445672
Moos, D. C., & Azevedo, R. (2009). Learning with computer-based learning environments: A literature review of computer self-efficacy. Review of Educational Research, 79(2), 576–600. https://doi.org/10.3102/0034654308326083
Morris, L. V., Wu, S.-S., & Finnegan, C. L. (2005). Predicting retention in online general education courses. American Journal of Distance Education, 19(1), 23–36. https://doi.org/10.1207/s15389286ajde1901_3
Multon, K. D., Brown, S. D., & Lent, R. W. (1991). Relation of self-efficacy beliefs to academic outcomes: A meta-analytic investigation. Journal of Counseling Psychology, 38(1), 30–38. https://doi.org/10.1037/0022-0167.38.1.30
National Center for Education Statistics. (2022a, March). Digest of Education Statistics, 2021. U.S. Department of Education, National Center for Education Statistics. https://nces.ed.gov/programs/digest/d21/tables/dt21_311.33.asp
National Center for Education Statistics. (2022b, December). Digest of Education Statistics, 2022. U.S. Department of Education, National Center for Education Statistics. https://nces.ed.gov/programs/digest/d22/tables/dt22_311.15.asp
Neroni, J., Meijs, C., Kirschner, P. A., Xu, K. M., & de Groot, R. H. M. (2022). Academic self-efficacy, self-esteem, and grit in higher online education: Consistency of interests predicts academic success. Social Psychology of Education, 25, 951–975. https://doi.org/10.1007/s11218-022-09696-5
Ng, C. (2019). Shifting the focus from motivated learners to motivating distributed environments: A review of 40 years of published motivation research in Distance Education. Distance Education, 40(4), 469–496. https://doi.org/10.1080/01587919.2019.1681892
Noe, R. A., & Schmitt, N. (1986). The influence of trainee attitudes on training effectiveness: Test of a model. Personnel Psychology, 39(3), 497–523. https://doi.org/10.1111/j.1744-6570.1986.tb00950.x
Pajares, F., & Graham, L. (1999). Self-efficacy, motivation constructs, and mathematics performance of entering middle school students. Contemporary Educational Psychology, 24(2), 124–139. https://doi.org/10.1006/ceps.1998.0991
Pajares, F., Hartley, J., & Valiante, G. (2001). Response format in writing self-efficacy assessment: Greater discrimination increases prediction. Measurement and Evaluation in Counseling and Development, 33(4), 214–221. https://doi.org/10.1080/07481756.2001.12069012
Peng, H., Wang, Y., Huang, R., & Chen, G. (2006). Self-efficacy of distance learning: Structure and related factor. Open Education Research, 2, 41–45.
Pintrich, P. R. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ). National Center for Research to Improve Postsecondary Teaching and Learning.
Pintrich, P. R., & De Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82(1), 33. https://doi.org/10.1037/0022-0663.82.1.33
Remedios, R., & Richardson, J. T. E. (2013). Achievement goals in adult learners: Evidence from distance education. British Journal of Educational Psychology, 83(4), 664–685. https://doi.org/10.1111/bjep.12001
Richardson, M., Abraham, C., & Bond, R. (2012). Psychological correlates of university students’ academic performance: A systematic review and meta-analysis. Psychological Bulletin, 138(2), 353–387. https://doi.org/10.1037/a0026838
Robbins, S. B., Lauver, K., Le, H., Davis, D., Langley, R., & Carlstrom, A. (2004). Do psychosocial and study skill factors predict college outcomes? A meta-analysis. Psychological Bulletin, 130(2), 261–288. https://doi.org/10.1037/0033-2909.130.2.261
Roblyer, M. D., Davis, L., Mills, S. C., Marshall, J., & Pape, L. (2008). Toward practical procedures for predicting and promoting success in virtual school students. American Journal of Distance Education, 22(2), 90–109. https://doi.org/10.1080/08923640802039040
Rosenzweig, E. Q., Wigfield, A., & Hulleman, C. S. (2020). More useful or not so bad? Examining the effects of utility value and cost reduction interventions in college physics. Journal of Educational Psychology, 112(1), 166–182. https://doi.org/10.1037/edu0000370
Rotter, J. B. (1966). Generalized expectancies for internal versus external control of reinforcement. Psychological Monographs: General and Applied, 80(1), 1–28. https://doi.org/10.1037/h0092976
Runyon, J. M. (2013). The first-time online learner: Readiness and successful course completion [Doctoral dissertation, Northcentral University]. ProQuest Dissertations and Theses. https://eric.ed.gov/?id=ED556388
Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54–67. https://doi.org/10.1006/ceps.1999.1020
Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemporary Educational Psychology, 61, 101860. https://doi.org/10.1016/j.cedpsych.2020.101860
Sankaran, S. R., & Bui, T. (2001). Impact of learning strategies and motivation on performance: A study in web-based instruction. Journal of Instructional Psychology, 28(3), 191–198. https://www.learntechlib.org/p/95445/
Seaman, J., Allen, E., & Seaman, J. (2018). Grade increase: Tracking distance education in the United States. Babson Survey Research Group. https://www.bayviewanalytics.com/reports/gradeincrease.pdf
Scheier, M. F., & Carver, C. S. (1985). Optimism, coping, and health: Assessment and implications of generalized outcome expectancies. Health Psychology, 4(3), 219–247. https://doi.org/10.1037/0278-6133.4.3.219
Schmidt, F. L., & Hunter, J. E. (2015). Methods of meta-analysis: Correcting error and bias in research findings (3rd ed.). Sage.
Schwarzer, R., & Jerusalem, M. (1995). Generalized Self-Efficacy scale. In J. Weinman, S. Wright, & M. Johnston (Eds.), Measures in health psychology: A user’s portfolio. Causal and control beliefs (pp. 35–37). NFER-Nelson. http://userpage.fu-berlin.de/~health/selfscal.htm
Shell, D. F., Murphy, C. C., & Bruning, R. H. (1989). Self-efficacy and outcome expectancy mechanisms in reading and writing achievement. Journal of Educational Psychology, 81(1), 91–100. https://doi.org/10.1037/0022-0663.81.1.91
Shen, D., Cho, M.-H., Tsai, C.-L., & Marra, R. (2013). Unpacking online learning experiences: Online learning self-efficacy and learning satisfaction. The Internet and Higher Education, 19, 10–17. https://doi.org/10.1016/j.iheduc.2013.04.001
Simmering, M. J., Posey, C., & Piccoli, G. (2009). Computer self-efficacy and motivation to learn in a self-directed online course. Decision Sciences Journal of Innovative Education, 7(1), 99–121. https://doi.org/10.1111/j.1540-4609.2008.00207.x
Spence, D. J. (2004). Engagement with mathematics courseware in traditional and online learning environments: Relationship to motivation, achievement, gender, and gender orientation. Dissertation Abstracts International Section A: Humanities and Social Sciences, 65(2-A), 480.
Stephen, J. S., Rockinson-Szapkiw, A. J., & Dubay, C. (2020). Persistence model of non-traditional online learners: Self-efficacy, self-regulation, and self-direction. American Journal of Distance Education, 34(4), 306–321. https://doi.org/10.1080/08923647.2020.1745619
Strawser, M. G., Gaffney, A. L. H., Kercsmar, S. E., & Pennell, M. (2019). A blended basic course examination of communication apprehension and self-efficacy: A comparative analysis. Basic Communication Course Annual, 29, 53–73. https://ecommons.udayton.edu/bcca/vol29/iss1/6
Stritto, M. E. D., Aguiar, N. R., & Andrews, C. (2023). From online learner readiness to life-long learning skills: A validation study. Online Learning, 27(4).
Sulla, F., Aquino, A., & Rollo, D. (2022). University students’ online learning during COVID-19: The role of grit in academic performance. Frontiers in Psychology, 13.
Sun, Y., & Rogers, R. (2021). Development and validation of the Online Learning Self-efficacy Scale (OLSS): A structural equation modeling approach. American Journal of Distance Education, 35(3), 184–199. https://doi.org/10.1080/08923647.2020.1831357
Tai, H.-C. (2016). Effects of collaborative online learning on EFL learners’ writing performance and self-efficacy. English Language Teaching, 9(5), 119–133. http://dx.doi.org/10.5539/elt.v9n5p119
Tang, Y. M., Chen, P. C., Law, K. M., Wu, C., Lau, Y., Guan, J., He, D., & Ho, G. (2021). Comparative analysis of student’s live online learning readiness during the coronavirus (COVID-19) pandemic in the higher education sector. Computers & Education, 168, 104211. https://doi.org/10.1016/j.compedu.2021.104211
Tladi, L. S. (2017). Perceived ability and success: Which self-efficacy measures matter? A distance learning perspective. Open Learning: The Journal of Open, Distance and e-Learning, 32(3), 243–261. https://doi.org/10.1080/02680513.2017.1356711
Torun, E. D. (2020). Online distance learning in higher education: E-learning readiness as a predictor of academic achievement. Open Praxis, 12(2), 191–208. https://search.informit.org/doi/10.3316/informit.352722164544178
Totonchi, D., Huelskoetter, E., Ferrer, B., & Hulleman, C. (2022, June 26–29). Improving community college students’ STEM motivation and achievement by implementing utility-value interventions. [Conference Paper]. 2022 ASEE Annual Conference & Exposition, Minneapolis, MN, United States. https://peer.asee.org/improving-community-college-students-stem-motivation-and-achievement-by-implementing-utility-value-interventions
Trice, A. D. (1985). An academic locus of control scale for college students. Perceptual and Motor Skills, 61(3 suppl), 1043–1046. https://doi.org/10.2466/pms.1985.61.3f.1043
Tsai, C.-C., Chuang, S.-C., Liang, J.-C., & Tsai, M.-J. (2011). Self-efficacy in internet-based learning environments: A literature review. Journal of Educational Technology & Society, 14(4), 222–240. https://www.jstor.org/stable/jeductechsoci.14.4.222
Urdan, T., & Kaplan, A. (2020). The origins, evolution, and future directions of achievement goal theory. Contemporary Educational Psychology, 61, 101862. https://doi.org/10.1016/j.cedpsych.2020.101862
Vallerand, R. J., Pelletier, L. G., Blais, M. R., Briere, N. M., Senecal, C., & Vallieres, E. F. (1992). The Academic Motivation Scale: A measure of intrinsic, extrinsic, and amotivation in education. Educational and Psychological Measurement, 52(4), 1003–1017. https://doi.org/10.1177/0013164492052004025
Wadsworth, L., Husman, J., Duggan, M., & Pennington, N. (2007). Online mathematics achievement: Effects of learning strategies and self-efficacy. Journal of Developmental Education, 30, 6–14.
Wang, A. Y., & Newlin, M. H. (2000). Characteristics of students who enroll and succeed in psychology Web-based classes. Journal of Educational Psychology, 92(1), 137–143. https://doi.org/10.1037/0022-0663.92.1.137
Wang, A. Y., & Newlin, M. H. (2002). Predictors of web-student performance: The role of self-efficacy and reasons for taking an on-line class. Computers in Human Behavior, 18(2), 151–163. https://doi.org/10.1016/S0747-5632(01)00042-5
Wang, Y., Peng, H., Huang, R., Hou, Y., & Wang, J. (2008). Characteristics of distance learners: Research on relationships of learning motivation, learning strategy, self‐efficacy, attribution and learning results. Open Learning: The Journal of Open, Distance and e-Learning, 23(1), 17–28. https://doi.org/10.1080/02680510701815277
Warren, L., Reilly, D., Herdan, A., & Lin, Y. (2020). Self-efficacy, performance and the role of blended learning. Journal of Applied Research in Higher Education, 13(1), 98–111. https://doi.org/10.1108/JARHE-08-2019-0210
White, H. (2019). Scientific communication and literature retrieval. In H. Cooper, L. V. Hedges, & J. C. Valentine (Eds.), The handbook of research synthesis and meta-Analysis (3rd ed., pp. 51–72). Russell Sage Foundation.
Wigfield, A., Muenks, K., & Eccles, J. S. (2021). Achievement motivation: What we know and where we are going. Annual Review of Developmental Psychology, 3(1), 87–111. https://doi.org/10.1146/annurev-devpsych-050720-103500
Wipawayangkool, K., Lilly, J., & Grogan, A. (2022). Knowledge management strategy-based learning preferences and self-efficacy on academic performance: An online vs. face-to-face study. International Journal of Knowledge and Learning, 15(2), 165–184.
Wuellner, M. R. (2015). Student success factors in two online introductory-level natural resource courses. Natural Sciences Education, 44(1), 51–59. https://doi.org/10.4195/nse2014.12.0029
Xu, J., Lio, A., Dhaliwal, H., Andrei, S., Balakrishnan, S., Nagani, U., & Samadder, S. (2021). Psychological interventions of virtual gamification within academic intrinsic motivation: A systematic review. Journal of Affective Disorders, 293, 444–465. https://doi.org/10.1016/j.jad.2021.06.070
Yurdugul, H., & Alsancak Sarikaya, D. (2013). The scale of online learning readiness: A study of validity and reliability. Education and Science, 38(169), 391–406. https://www.proquest.com/openview/c6b0a56d9385205d7bf3759a9bedd68d/1
Yurdugul, H., & Demir, O. (2017). An investigation of pre-service teachers' readiness for e-learning at undergraduate level teacher training programs: The case of Hacettepe University. Hacettepe Üniversitesi Eğitim Fakültesi Dergisi, 32(4), 896–915.
Zhang, J., Li, F., Duan, C., & Wu, G. (2001). Research on self-efficacy of distance learning and its influence to learners’ attainments. In C. H. Lee (Ed.), Proceedings of the International Conference on Computers in Education (ICEE). Incheon National University of Education. https://www.semanticscholar.org/paper/Research-on-Self-Efficacy-of-Distance-Learning-and-Zhang-Li/b297555da2325e320eebbc1640c62ad849530a92
Zhou, Y., & Wang, J. (2019). Goal orientation, learning strategies, and academic performance in adult distance learning. Social Behavior and Personality: An International Journal, 47(7), 1–20. https://doi.org/10.2224/sbp.8195
Zimmerman, B. J., Bandura, A., & Martinez-Pons, M. (1992). Self-motivation for academic attainment: The role of self-efficacy beliefs and personal goal setting. American Educational Research Journal, 29(3), 663–676. https://doi.org/10.2307/1163261
Zimmerman, W. A. (2017). Predicting success in an online course using expectancies, values, and typical mode of instruction. International Journal of E-Learning & Distance Education, 32(1). https://eric.ed.gov/?id=EJ1155812
Zimmerman, W. A., & Kulikowich, J. M. (2016). Online learning self-efficacy in students with and without online learning experience. American Journal of Distance Education, 30(3), 180–191. https://doi.org/10.1080/08923647.2016.1193801
Additional Files
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Andrew Walker, Naomi R. Aguiar, Raechel N. Soicher, Yu-Chun Kuo, Jessica Ressig
This work is licensed under a Creative Commons Attribution 4.0 International License.
As a condition of publication, the author agrees to apply the Creative Commons – Attribution International 4.0 (CC-BY) License to OLJ articles. See: https://creativecommons.org/licenses/by/4.0/.
This licence allows anyone to reproduce OLJ articles at no cost and without further permission as long as they attribute the author and the journal. This permission includes printing, sharing and other forms of distribution.
Author(s) hold copyright in their work, and retain publishing rights without restrictions
