A Cross-Institutional Comparison of Undergraduate Research Project Supervision Models: Individual Versus Group Formats at Busitema University, Uganda and Maseno University, Kenya

Final-year undergraduate research project outcomes vary widely across institutions, yet existing literature rarely compares institutional contexts with different supervision models. This study examined institutional differences in technical challenges associated with different supervision models by comparing Mathematics and Statistics students at Busitema University, Uganda (individual project model, n=78) and Maseno University, Kenya (group project model, n=99). A comparative cross-sectional survey design employed structured questionnaires measuring 12 technical challenges (5-point Likert). Analysis used independent-samples t-tests with Welch correction, Cohen's d (0.2 small, 0.5 medium, 0.8 large), and multiple regression controlling for 12 supervisor guidance items. Classification thresholds: Low=1.00-2.33; Medium=2.34-3.67; High=3.68-5.00. Optimal decision rule: retain as institution-dependent if p<0.05 AND |d|>=0.5. Busitema students reported higher computer skills challenges (Mean=3.51, SD=1.38 vs 2.63, SD=1.27, p<.001, d=-0.67, Medium vs Medium). Maseno students reported higher use of data analysis software (Mean=2.63, SD=1.26 vs 1.65, SD=1.17, p<.001, d=0.80, Medium vs Low) and statistical models (Mean=2.52, SD=1.15 vs 1.66, SD=1.03, p<.001, d=0.78). Data entry was statistically significant (Mean diff -0.52, t (145.19) =-2.34, p=.021) but did not meet practical significance (d=0.36) and is interpreted as small effect not meeting the decision rule. Eight items showed no difference. University remained predictor after controlling for guidance (software: β=0.80, SE=0.19, 95%CI [0.42, 1.18], p<.001, VIF=1.45; computer skills: β=-0.70, SE=0.22, CI [-1.13,-0.27], p=.002, VIF=1.45; models: β=0.95, SE=0.18, CI [0.60, 1.30], p<.001, VIF=1.45). Diagnostics: VIF 1.12-2.84 (all <5), Shapiro-Wilk p=0.18, Breusch-Pagan p=0.22, Cook's distance <0.15. We recommend mandatory computer skills training for individual-project contexts and formal technical role allocation for group-project contexts. However, because project format was confounded with institution, these findings are hypothesis-generating; future multi-institutional research should disentangle format effects using within-institution comparisons.

Undergraduate Research; Supervision Models; Cross-Institutional Comparison; Research Challenges

1. Adhikari, G. R. (2020). Strategies for selecting a research topic. Mining Engineers' Journal, 22(7), 12-15. [Google Scholar] [Crossref]

2. Astin, A. W. (1993). What matters in college? Four critical years revisited. Jossey-Bass. [Google Scholar] [Crossref]

3. Bikanga Ada, M. (2021). Master's students' perceptions of final year project supervision: On-campus vs online. Journal of Further and Higher Education, 45(8), 1111-1123. [Google Scholar] [Crossref]

4. Bitzer, E. M. (2007). Academic writing and research skills in higher education. Acta Academica, 39(2), 228-232. [Google Scholar] [Crossref]

5. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates. [Google Scholar] [Crossref]

6. Healey, M., & Jenkins, A. (2009). Developing undergraduate research and inquiry. The Higher Education Academy. [Google Scholar] [Crossref]

7. Hunter, A.-B., Laursen, S. L., & Seymour, E. (2007). Becoming a scientist: The role of undergraduate research in students' cognitive, personal, and professional development. Science Education, 91(1), 36-74. https://doi.org/10.1002/sce.20173 [Google Scholar] [Crossref]

8. Lee, A. (2008). How are doctoral students supervised? Concepts of doctoral research supervision. Studies in Higher Education, 33(3), 267-281. https://doi.org/10.1080/03075070802049202 [Google Scholar] [Crossref]

9. Lobo, J. (2023). Students' challenges and barriers in thesis writing. International Journal of Research and Innovation in Social Science, 7(3), 45-52. [Google Scholar] [Crossref]

10. Muthukrishnan, P., Krishnan, S., Kumar, A., & Wong, K. T. (2022). Key factors influencing graduation on time among postgraduate students. International Journal of Evaluation and Research in Education, 11(1), 123-132. [Google Scholar] [Crossref]

11. Pyhältö, K., Vekkaila, J., & Keskinen, J. (2015). Fit matters in the supervisory relationship: Doctoral students and supervisors perceptions about the supervisory activities. Innovations in Education and Teaching International, 52(1), 4-16. [Google Scholar] [Crossref]

12. Roberts, L. D., & Seaman, K. (2018). Good undergraduate project supervision: perspectives from psychology. Psychology Teaching Review, 24(1), 45-55. [Google Scholar] [Crossref]

13. Thondhlana, S., Musingarirarwa, P., & Henry, N. (2011). Factors affecting completion of research projects by students: A case of the Open University of Zimbabwe. Journal of Education and Practice, 2(2), 1-10. [Google Scholar] [Crossref]

14. Von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., & Vandenbroucke, J. P. (2007). The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. Annals of Internal Medicine, 147(8), 573-577. https://doi.org/10.7326/0003-4819-147-8-200710160-00010 [Google Scholar] [Crossref]

15. Xia, J. (2013). A mixed-method study on students' experiences in a research methods course. Journal of Applied Research in Higher Education, 5(2), 190-205. [Google Scholar] [Crossref]

16. Yuan, H., Zhang, L., & Chen, Y. (2024). Navigating the uncertainty: Challenges and strategies of undergraduate research. Humanities and Social Sciences Communications, 11, 123. [Google Scholar] [Crossref]

17. R Core Team (2023). R: A language and environment for statistical computing (Version 4.3.1) [Computer software]. R Foundation for Statistical Computing. https://www.R-project.org/ [Google Scholar] [Crossref]

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