Factors Predicting Student Success

This week I would like to share my 300th SoTL post!

Although the topic of AI in education remains an active conversation, I would like to refocus this week’s article on foundational SoTL. I believe that the recent May 2023 article entitled, “Salient Factors in Predicting Student Success, Including Course Modality ” by Nalbone, et al. may be of interest. The results indicate that a set of characteristics predicting student success can be identified, and that course modality affects overall success.

The authors implemented a modified theoretical model based on Lalonde and Gardner (1993). The original model contained five major factors including mathematical aptitude predicted situational anxiety and achievement; situational anxiety predicted attitude-motivation index, which in turn predicted effort, which in turn also predicted achievement. The modified model uses a hierarchical regression approach. The hypotheses were that each of the following sets of predictors would significantly predict student achievement:

1. situational anxiety

2. attitude/motivation

3. effort

4. perceived student achievement

5. course modality

The results supported four of the five hypotheses predicting overall student achievement, in that measures of attitude/motivation, effort, and perceived student achievement were significant predictors of achievement. Further, the results demonstrated that six variables (academic control, intrinsic motivation, time management, perceived competence, and academic self-assessment) were significant predictors of achievement. The findings regarding modality (online students outperformed face-to-face students in terms of final course average) showed that students taking ONLINE courses were predicted to earn higher final grades. This result could be due to a shift toward higher student performance in online environments, or unique aspects of the pandemic, during which many instructors devoted considerable time and energy to ensuring that their online courses were of high quality.

Analysis indicated that a set of characteristics were predictive of a LACK of student success:

• those who were least satisfied with online courses

• used the fewest study techniques

• procrastinated the most

• were lowest in academic control, intrinsic motivation, perceived competence, learning confidence, and academic self-assessment

Finally, the results suggest key strategies that we can use to increase the likelihood of success:

1. Emphasize aspects over which students have direct control–including better time management, less procrastination, and exerting greater academic control;

2. Encouraging students to develop an intrinsic interest in the subject; and

3. Engaging in activities that foster self-efficacy.

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BTW, for those interested in AI in teaching and learning, I will be finishing a manuscript with colleagues Hill, Little and Bharadwaj in a couple of weeks and I am happy to collaborate with others this summer if I can assist.

I will be taking a break from now until August 9. I hope that your summers are productive and enjoyable.

References

Nalbone, D., Ashoori, M., Fasanya, K., Pelter, M. & Rengstorf, A. (2023) Salient factors in predicting student success, including course modality," International Journal for the Scholarship of Teaching and Learning, 17(1). Available at: https://doi.org/10.20429/ijsotl.2023.17111