Authors : Oludolapo O. Akinyosoye–Gbonda; Alhaji Ibrahim Jalloh; Joseph V. Sesay; Abu Bakarr Bangura

Volume/Issue : Volume 11 - 2026, Issue 2 - February

Google Scholar : https://tinyurl.com/4nuwyfua

Scribd : https://tinyurl.com/367hpvzh

DOI : https://doi.org/10.38124/ijisrt/26feb1457

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Student Information Management Systems (SIMS) are vital for managing academic and administrative processes. At the Institute of Public Administration and Management - University of Sierra Leone (IPAM - USL), current practices remain largely manual, leading to delays, errors, and inefficiencies. This study explores the challenges and prospects of implementing an AI-powered SIMS at IPAM. The objectives include assessing existing practices, identifying user expectations, and examining factors influencing adoption. A mixed-methods approach was employed. Structured questionnaires were administered to 60 students and 11 lecturers. Quantitative data were analysed using descriptive statistics, while qualitative responses were examined through thematic analysis. Findings reveal under-utilisation of the current SIMS and strong demand for real-time updates, automation, and mobile access. It is recommended that IPAMUSL adopt a fully integrated, AI-powered SIMS with mobile optimisation and user training to enhance efficiency and engagement.

Keywords : Student Information Management Systems, Artificial Intelligence, University of Sierra Leone, Academic, Administrative, Mobile.

References :

1. Adebayo, S. O. and Abdulhamid, S. I. (2019) Determinants of user acceptance of a student information system in a Nigerian university. Journal of Education and Practice, 10(14), pp. 1–10.
2. Alalwan, A. A., Dwivedi, Y. K. and Rana, N. P. (2017) Integrating UTAUT2 with additional factors for mobile banking adoption: a systematic review. International Journal of Information Management, 37(6), pp. 628–643.
3. Al-Fraihat, D., Joy, M., Masa'deh, R., & Sinclair, J. (2020). Evaluating E-Learning Systems Success: An Empirical Study. Computers in Human Behavior, 102, pp. 67-86.
4. Aldowah, S., Rehman, S. and Ghazal, S. (2017) Critical factors for adopting e-learning systems in a higher education institution: an empirical study. Interactive Technology and Smart Education, 14(4), pp. 310–330.
5. Alhassan, A., Sam, J., Agyemang, G. and Osei, B. (2021) Factors influencing the adoption of a student information system in a Ghanaian university. Education and Information Technologies, 26(1), pp. 1–20.
6. Alonso, F., Manrique, M. A., & Moreno-Ger, P. (2020). A survey on the use of recommender systems in education. Computers in Human Behavior, 102, pp. 24–34.
7. Alrawashdeh, H., Al-Mashaqbeh, H., & Almajali, D. (2019). The impact of information technology infrastructure on the success of an enterprise resource planning system. International Journal of Computer and Information Technology, 8(3), pp. 43–52.
8. Baker, T., Smith, M., & Ananiadou, S. (2021). Towards ethical AI in education: A framework for responsible design and implementation. Journal of Educational Technology & Society, 24(1), pp. 12–25.
9. Bell, E., Harley, B. and Bryman, A. (2022) Business Research Methods. Oxford: Oxford University Press.
10. Braun, V. and Clarke, V. (2006) ‘Using thematic analysis in psychology’, Qualitative Research in Psychology, 3(2), pp. 77–101.
11. Bryman, A. (2016) Social Research Methods. 5th edn. Oxford: Oxford University Press.
12. Cabitza, F., Campagner, A., & Simone, M. (2020). Ethical challenges of artificial intelligence in healthcare: A systematic review of the literature. Journal of Medical Internet Research, 22(12), pp. e25191.
13. Chatterjee, S. and Bhattacharjee, K. K. (2020) ‘Adoption of artificial intelligence in higher education: a quantitative analysis using structural equation modelling’, Education and Information Technologies, 25(5), pp. 3443–3463.
14. Chaudhry, M. A., Cukurova, M. and Luckin, R. (2022) ‘A transparency index framework for AI in education’, in International Conference on Artificial Intelligence in Education. Cham: Springer International Publishing, pp. 195–198.
15. Chen, L., Chen, P. and Lin, Z. (2020) ‘Artificial intelligence in education: a review’, IEEE Access, 8, pp. 75264–75278.
16. Chen, J., Chen, H. and Lin, R. (2022) A conceptual framework of user-centered design for student information systems. Computers & Education, 182, pp. 104470.
17. Creswell, J. W. (2014) Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. 4th edn. Thousand Oaks, CA: Sage Publications.
18. Creswell, J. W. and Clark, V. L. P. (2017) Designing and Conducting Mixed Methods Research. Thousand Oaks, CA: SAGE Publications.
19. Davis, F. D. (1989) ‘Perceived usefulness, perceived ease of use, and user acceptance of information technology’, MIS Quarterly, 13(3), pp. 319–340.
20. DeLone, W. H. and McLean, E. R. (2003) ‘The DeLone and McLean model of information systems success: a ten-year update’, Journal of Management Information Systems, 19(4), pp. 9–30.
21. Demirkol, D. and Seneler, C. (2019) ‘Evaluation of student information system (SIS) in terms of user emotion, performance and perceived usability: a Turkish university case (an empirical study)’, Procedia Computer Science, 158, pp. 1033–1051.
22. Deschênes, M. (2020) ‘Recommender systems to support learners’ agency in a learning context: a systematic review’, International Journal of Educational Technology in Higher Education, 17(1), p. 50.
23. Dillman, D. A., Smyth, J. D. and Christian, L. M. (2014). Internet, phone, mail, and mixed-mode surveys: the tailored design method. 4th edn. Hoboken, NJ: John Wiley & Sons.
24. Etikan, I., Musa, S. A. and Alkassim, R. S. (2016) Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), pp. 1–4.
25. Fowler, F. J. (2014) Survey research methods. 5th edn. Thousand Oaks, CA: Sage Publications.
26. Gürkut, C. and Nat, M. (2017) ‘Important factors affecting student information system quality and satisfaction’, EURASIA Journal of Mathematics, Science and Technology Education, 14(3), pp. 923–932.
27. Gürkut, C., Elçi, A. and Nat, M. (2023) ‘An enriched decision-making satisfaction model for student information management systems’, International Journal of Information Management Data Insights, 3(2), p. 100195.
28. Holden, R. J. and Karsh, B. T. (2010) The technology acceptance model: its application in healthcare and future directions for healthcare information technology research. Journal of Biomedical Informatics, 43(1), pp. 159–170.
29. Ifenthaler, D. and Yau, J. S. (2020) Student and lecturer perceptions of an academic information system. Education and Information Technologies, 25(3), pp. 2011–2029.
30. Ifinedo, P. (2017) A model of user-based adoption of information systems in Nigerian universities: the case of student information system. Information Systems Management, 34(1), pp. 49–62.
31. Israel, M. and Hay, I. (2006) Research ethics for social scientists: between theory and practice. London: Sage Publications.
32. Johnson, R. B. and Onwuegbuzie, A. J. (2004) Mixed methods research: a research paradigm whose time has come. Educational Researcher, 33(7), pp. 14–26.
33. Lwoga, E. (2014) ‘Critical success factors for adoption of web-based learning management systems in Tanzania’, International Journal of Education and Development using ICT, 10(1).
34. Mtebe, J.S. and Raisamo, R. (2014) Investigating students’ acceptance of e-learning systems in Tanzania. Education and Information Technologies, 19(1), pp. 101–118.
35. Nagy, P. (2018) The digital university: a view from the administrative side. EDUCAUSE Review, 53(2), pp. 10–17.
36. Okonkwo, C. W. and Ade-Ibijola, A. (2021) ‘Chatbots applications in education: a systematic review’, Computers and Education: Artificial Intelligence, 2, p. 100033.
37. Pina, A. A. (2012) The impact of student information systems on student retention and success. Journal of Educational Technology Development and Exchange, 5(1), pp. 1–15.
38. Rabaai, A. (2009) ‘Identifying critical success factors of ERP systems at the higher education sector’, in Proceedings of the Third International Symposium on Innovation in Information and Communication Technology. Swindon: British Computer Society, pp. 133–147.
39. Rogers, E. M. (2003) Diffusion of innovations. 5th edn. New York: Free Press.
40. Saunders, M., Lewis, P. and Thornhill, A. (2009) Research Methods for Business Students. Harlow: Pearson Education.
41. Schwendimann, B. A., Rodriguez-Triana, M.J., Vozniuk, A., Prieto, L.P., Boroujeni, M.S., Holzer, A., Gillet, D. and Dillenbourg, P. (2017) ‘Perceiving learning at a glance: a systematic literature review of learning dashboard research’, IEEE Transactions on Learning Technologies, 10(1), pp. 30–41.
42. Tarhini, A., Masa’deh, R. E., Al-Busaidi, K. A., Mohammed, A. B. and Maqableh, M. (2017) ‘Factors influencing students’ adoption of e-learning: a structural equation modelling approach’, Journal of International Education in Business, 10(2), pp. 164–182.
43. Tashakkori, A. and Teddlie, C. (2021) SAGE Handbook of Mixed Methods in Social and Behavioral Research. Thousand Oaks, CA: SAGE Publications.
44. Venkatesh, V., Morris, M., Davis, G. and Davis, F. (2003) User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), pp. 425–478.
45. Venkatesh, V., Thong, J. and Xu, X. (2012) Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), pp. 157–178.
46. Wang, M., Yu, H. and Fong, J. (2019) An overview of learning analytics and educational data mining. Journal of Computer Assisted Learning, 35(1), pp. 1–13.
47. Yusof, M.M., Kuljis, J., Papazafeiropoulou, A. and Stergioulas, L.K. (2008) An evaluation framework for health information systems: human, organization and technology-fit factors (HOT-fit). International Journal of Medical Informatics, 77(6), pp. 386–398.
48. Zawacki-Richter, O., Marín, V.I., Bond, M. & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in education – a review of articles. Education and Information Technologies, 24(5), pp. 3519–3544.
49. Zawacki-Richter, O., Marín, V.I., Bond, M. & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education—where are the educators? International Journal of Educational Technology in Higher Education, 16(1), pp. 1-27.