Advising as Policy: Institutional Advising Models as Levers for Retention and Career Readiness in U.S. STEM Education

Lydia Githinji; Fadeke Atobatele

doi:10.56201/ijssmr.vol.12no2.2026.pg384.407

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Advising as Policy: Institutional Advising Models as Levers for Retention and Career Readiness in U.S. STEM Education

Lydia Githinji, Fadeke Atobatele

Abstract

United States science, technology, engineering, and mathematics education enters 2026 amid strong demand and persistent concern about supply. STEM employment continues to grow faster than the rest of the labor market and to pay a clear premium, yet too many students who begin STEM study do not complete it, and a labor market that now hires on demonstrated skills rather than credentials alone leaves many graduates unable to evidence their readiness. Recent scholarship has also complicated the familiar leaky pipeline story, showing that movement into and out of STEM is more varied than a simple unidirectional loss, which sharpens rather than dissolves the case for deliberate institutional support. This paper argues that academic advising, long treated as a routine service, should be recognized and resourced as institutional policy infrastructure, and that the deliberate design of an advising model is a measurable lever on both retention and career readiness. It distinguishes relational advising approaches, which describe how advisors engage students, from structural advising models, which describe how advising is organized, and it identifies caseload, coordination, and accountability as the parameters that determine whether good practice is possible. It presents recent causal evidence that targeted, proactive advising informed by learning analytics improves grades and persistence, shows how an advising relationship can integrate competency development into a skills based labor market, and assesses the arrival of artificial intelligence and early warning systems in advising, arguing that these tools can scale proactive outreach but cannot replace the human relationship and must be governed for equity and privacy. The paper then turns to implementation, addressing sequencing, cost, workforce professionalization, and measurement, before offering eight policy recommendations for institutional leaders, accreditors, and funders, answering the principal objections to them, and identifying the limits of the present argument and the questions that future research should resolve.

Keywords

academic advising; STEM retention; student persistence; career readiness; skills- based hiring; proactive advising; predictive analytics; early warning systems; advising caseload; higher education pol

References

Aliliele, C., Mbonu, I. S., & Iwuanyanwu, U. (2023). Advances in predictive analytics models for student retention and institutional risk management systems. International Journal of Advanced Multidisciplinary Research and Studies, 3(6), 2692 to 2711. Alloug, I., Daoudi, M., & Oumaira, I. (2026). AI-based academic advising across the student lifecycle: A systematic literature review. Information, 17(4), 335. Ayari, O. N., Chizoba, C. E., & Ahmed, M. O. (2026). A digital solution for student internship: Tracking and enhancing student's experience. Asian Journal of Basic Science and Research, 8(1), 23 to 36. Boakye, K., Ofori, S. D., Ogbona, C. S., Yeboah, T. J., & Bobga, M. A. (2021). Bridging the gap: A comparative study of mathematics curriculum reforms in Ghana and the United States. Iconic Research and Engineering Journals, 5(3), 429 to 450. Caballero, C. L., Hansen, L., Walker, A., Rosenberg, C., Orr, P., Claringbold, G., Sturre, V. L., & Forsyth, L. (2026). Untangling graduate employability and work readiness to inform evidence-based practice in higher education. Higher Education Research & Development. Advance online publication. Fawehinmi, Y. O., Okereke, G. M. T., Williams, P., Chijioke-Churuba, J. N., & Asare-Badu, B. (2026). AI-human collaboration in education and psychology: Personalised learning, language acquisition and student support systems. Journal of Political Science and International Relationship, 3(1), 54 to 64. Ladapo, O. O., Dosunmu, A. A., Jooda, D., & Abolaji, T. O. (2022). Human-in-the-loop machine learning: A state of the art. Journal of Frontiers in Multidisciplinary Research, 3(1), 656 to 669. Ladapo, O. O., Jooda, D., Dosunmu, A. A., & Abolaji, T. O. (2024). Keeping humans in the loop: Human-centered automated annotation with generative AI. International Journal of Multidisciplinary Futuristic Development, 5(1), 81 to 95. Michael, O. N., & Ogunsola, O. E. (2025). Evaluating the impact of sustainable agriculture curriculum integration on STEM education and career outcomes. Journal of Social Science and Human Research Studies, 1(5), 178 to 194. National Association of Colleges and Employers. (2026). Employer use of skills-based hiring practices grows. Bethlehem, PA: National Association of Colleges and Employers. National Science Board. (2026). Science and engineering indicators 2026: The STEM labor force of the United States (NSB-2026-1). Alexandria, VA: National Science Foundation, National Center for Science and Engineering Statistics. Ogbona, C. S., Yeboah, T. J., Bobga, M. A., & Boakye, K. (2020). Coaching education and career transition pathways: Comparative perspectives from Nigeria and the United States. Iconic Research and Engineering Journals, 4(5), 367 to 384. Ogbona, C. S., Bobga, M. A., Boakye, K., & Yeboah, T. J. (2024). Leadership practices supporting Black student-athletes' mental health in collegiate sport: A qualitative inquiry. International Journal of Multidisciplinary Research and Growth Evaluation, 5(5), 1192 to 1208. Onwubuya, L. I., Fawehinmi, Y. O., Sunday, D., Igwenagu, M. O., Adeniran, A. O., & Agyapong, E. A. (2026). Adaptive learning systems powered by artificial intelligence for STEM education improvement. Asian Journal of Education and Social Studies, 52(6), 553 to 566. Rust, M. M., & Motz, B. A. (2026). Incorporating an LMS learning analytic into proactive advising: Validity and use in a randomized experiment. The Internet and Higher Education, 68. Salzman, H., Douglas, D., & Khudododov, K. (2026). Reconceptualizing college STEM pathways: Is leaving STEM the problem? Journal for STEM Education Research. Advance online publication. Seun, A., Ajayi, A., Bobga, M. A., Yeboah, T. J., Apelehin, A. A., Ofori, S. D., Elumilade, R. A., & Abutu, D. E. (2023). PearlAI and motivation paths: Advancing student engagement through AI-powered personalization in basic education. International Journal of Scientific Research in Science, Engineering and Technology, 10(4), 391 to 403. Seun, A., Ajayi, A., Yeboah, T. J., Ofori, S. D., Elumilade, R. A., Apelehin, A. A., Abutu, D. E., & Bobga, M. A. (2024). The PearlAI framework: Leveraging artificial intelligence to transform education in Africa. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 10(3), 1120 to 1132. Yeboah, T. J., Bobga, M. A., Boakye, K., & Ogbona, C. S. (2019). Professional development and teacher competence in managing exceptional learners: A Ghanaian perspective. Iconic Research and Engineering Journals, 2(12), 618 to 636. Yeboah, T. J., Bobga, M. A., Boakye, K., & Ogbona, C. S. (2022). Data-driven teaching: Using student progress data to personalize learning in special education classrooms. Journal of Frontiers in Multidisciplinary Research, 3(2), 225 to 240. Yeboah, T. J., Bobga, M. A., Boakye, K., & Ogbona, C. S. (2024). Technology integration in special education: Enhancing student engagement and accessibility. International Journal of Advanced Multidisciplinary Research and Studies, 4(6), 2978 to 2993.

Advising as Policy: Institutional Advising Models as Levers for Retention and Career Readiness in U.S. STEM Education

Abstract

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