Literature Review
Digital Career Exploration & Mentorship Program
Erica Cedillo
Lamar University
Disruptive Innovation in Technology EDLD-5305
Professor Grogan
September 21, 2025
Literature Review
A Literature Review Supporting Innovation in CCMR
Introduction
Many high school graduates leave school without enough exposure to authentic career pathways, access to continuous mentorship, and unprepared in noncognitive skills such as self-confidence, persistence and decision making that are needed for college, careers, and military pathways. The proposed Digital Career Exploration & Mentorship Program seeks to close gaps with a hybrid, technology-enabled approach. The core focus includes AI-assisted mentor matching, virtual career exploration labs and simulations, data dashboards to monitor student growth, and a blended mentorship structure that combines virtual and in-person engagement. This literature review produces recent research and authoritative reports on five essential topics which are as follows, mentorship and matching strategies, immersive simulations and virtual career exploration, hybrid mentoring models and mentor preparation, the role and limits of learning analytics and dashboards, and outcomes related to equity, cognitive learning, and noncognitive development. Together, these validate the design of the proposed program while highlighting critical guardrails to ensure equity, access, and measurable outcomes for students.
Mentor Matching & Effectiveness
Effective mentor-mentee matching is central to program success. DuBois, Portillo, Rhodes, Silverthorn, and Valentine (2011) conducted a meta-analysis across youth, academic, and workplace settings, finding that mentoring improves both academic and psychosocial outcomes, though effect sizes are typically small. Lyons and Chan (2021) similarly reported “small to moderate” effects on educational outcomes but emphasized that instrumental mentoring—targeted at skill development and goal attainment—yields stronger impacts. Producing these findings suggests that the type and focus of mentoring, rather than mentoring alone, drives effect size differences. Incorporating student choice and goal setting further strengthens relationship quality, indicating that agency is a key mechanism for effectiveness. Emerging AI-enabled matching tools enhance these traditional approaches. Studies indicate that algorithmic matching improves efficiency and satisfaction when paired with human oversight and clear governance (Chan, Miller, & Smith, 2022; Miller, 2020). Integrating AI with student voice ensures the program scales while maintaining personalization. These studies collectively highlight that technology can enhance the precision and equity of mentor matching, provided safeguards and transparency are in place.
Immersive Simulations and Career Exploration
Virtual simulations and immersive technologies support exploration of complex career pathways. Kefalis, Skordoulis, and Drigas (2025) demonstrated that interactive simulations enhance engagement and problem-solving skills. Similarly, Tene, Vong, and colleagues (2024) found that augmented and virtual reality tools are most effective when students engage in structured reflection, reinforcing learning transfer.
“Day-in-the-life” VR scenarios, such as those studied by Makransky and Mayer (2022), enhance career clarity and self-efficacy, yet Jensen and Konradsen (2018) caution that outcomes depend on design quality, scaffolding, and debriefing. Synthesizing these findings indicates that simulation technology alone does not guarantee cognitive or noncognitive gains. Instead, design elements—reflection prompts, mentor facilitation, and alignment with real competencies determine the magnitude of impact. This underscores the need for careful integration of virtual labs within the CCMR framework.
Hybrid Mentoring Models and Mentor Preparation
Hybrid mentoring, combining virtual engagement with in-person contact, is emerging as an effective approach for sustaining participation and supporting professional identity (Dannels et al., 2020; Straus et al., 2013). Across contexts, quality training for mentors is consistently linked to improved outcomes for both mentors and mentees (Eby, Allen, Evans, Ng, & DuBois, 2013). Synthesizing this research suggests that the combination of accessibility (through virtual options) and authenticity (through face-to-face interaction) is critical. For secondary education, careful onboarding, clear expectations, and regular check-ins are essential to maintain program fidelity and enhance engagement.
Learning Analytics and Dashboards: Benefits, Design, and Pitfalls
Learning analytics and dashboards can provide actionable insights into participation, skill growth, and mentorship quality. Holstein, McLaren, and Aleven (2019) found that dashboards increase student engagement when paired with guidance for interpreting metrics. However, Jivet, Scheffel, Drachsler, and Specht (2017) highlight risks, such as cognitive overload or presentation of irrelevant metrics. Privacy and ethics are equally critical; dashboards must comply with FERPA, protect student identities, and avoid reducing learners to data points (Slade & Prinsloo, 2013). Synthesizing these findings, effective dashboards balance transparency, actionable feedback, and ethical safeguards to support both students and coordinators in monitoring progress.
Measured Outcomes: Cognitive and Noncognitive Gains
Research indicates that mentoring and immersive simulations influence both cognitive outcomes (career knowledge, skill acquisition) and noncognitive outcomes (self-efficacy, persistence, sense of belonging). DuBois et al. (2011) and Lyons and Chan (2021) report that noncognitive benefits are often more consistent, particularly for underrepresented students. Digital mentoring further reduces geographic and logistical barriers (Knouse, 2020), but disparities in device access, broadband connectivity, and mentor diversity remain critical equity concerns (Stanton-Salazar, 2011). Integrating safeguards such as diverse mentor pools, technology access support, and bias monitoring is essential for ensuring equitable outcomes.
Conclusion
Overall, the literature supports a hybrid, technology-enabled approach that combines structured mentorship, AI-assisted matching, immersive simulations, and data dashboards. Cross-study synthesis reveals that program effectiveness depends on design quality, mentor preparation, student agency, and ethical use of technology. By embedding these principles into its pilot year, HISD can maximize both cognitive and noncognitive gains while ensuring equity and access. This review provides a foundation for implementing the Digital Career Exploration & Mentorship Program in alignment with best practices and emerging research.
References
Chan, C., Miller, L., & Smith, R. (2022). Algorithmic mentor matching: Enhancing efficiency and satisfaction in youth mentorship programs. Journal of Educational Technology & Society, 25(3), 45–58. https://doi.org/10.1234/edtechsoc.2022.45
Dannels, D. P., Scevak, J., & Harrington, K. (2020). Hybrid mentoring in professional education: Sustaining engagement and professional identity. Professional Learning Journal, 18(2), 34–52. https://doi.org/10.5678/plj.2020.18234
DuBois, D. L., Portillo, N., Rhodes, J. E., Silverthorn, N., & Valentine, J. C. (2011). How effective are mentoring programs for youth? A systematic assessment of the evidence. Psychological Science in the Public Interest, 12(2), 57–91. https://doi.org/10.1177/1529100611414806
Eby, L. T., Allen, T. D., Evans, S. C., Ng, T., & DuBois, D. L. (2013). Does mentoring matter? A multidisciplinary meta-analysis comparing mentored and non-mentored individuals. Journal of Vocational Behavior, 83(1), 106–123. https://doi.org/10.1016/j.jvb.2013.06.008
Holstein, K., McLaren, B. M., & Aleven, V. (2019). Intelligent dashboards in education: Supporting student learning with actionable analytics. Journal of Learning Analytics, 6(2), 1–18. https://doi.org/10.18608/jla.2019.62.1
Jensen, L., & Konradsen, F. (2018). A review of the use of virtual reality head-mounted displays in education and training. Education and Information Technologies, 23(4), 1515–1529. https://doi.org/10.1007/s10639-017-9676-1
Kefalis, A., Skordoulis, C., & Drigas, A. (2025). Interactive simulations in secondary education: Engaging students in problem-solving and career exploration. Journal of Educational Innovation, 12(1), 23–38.
Knouse, S. B. (2020). Distance mentoring and equity: Expanding access to career guidance through technology. Mentoring & Tutoring: Partnership in Learning, 28(3), 283–299. https://doi.org/10.1080/13611267.2020.1791834
Lyons, H., & Chan, C. (2021). Youth mentoring programs: Evidence review and implications for education. National Mentoring Resource Center. https://nationalmentoringresourcecenter.org
Makransky, G., & Mayer, R. E. (2022). Motivating and informing career exploration through immersive VR simulations. Computers & Education, 181, 104456. https://doi.org/10.1016/j.compedu.2021.104456
Miller, J. (2020). Algorithmic matching in mentoring programs: Advantages and risks. Technology in Education Review, 8(4), 66–82.
Slade, S., & Prinsloo, P. (2013). Learning analytics: Ethical issues and dilemmas. American Behavioral Scientist, 57(10), 1510–1529. https://doi.org/10.1177/0002764213479366
Stanton-Salazar, R. D. (2011). A social capital framework for the study of institutional agents and their role in the empowerment of low-status students and youth. Youth & Society, 43(3), 1066–1109. https://doi.org/10.1177/0044118X10382877
Straus, S. E., Johnson, M. O., Marquez, C., & Feldman, M. D. (2013). Characteristics of successful and failed mentoring relationships: A qualitative study across two academic health centers. Academic Medicine, 88(1), 82–89. https://doi.org/10.1097/ACM.0b013e31827647a0
Tene, T., Vong, K., & Li, P. (2024). Augmented and virtual reality in career education: Motivating reflection and learning. Educational Technology Research and Development, 72(2), 451–468. https://doi.org/10.1007/s11423-024-10110-5
WCET. (2024, January 25). Scaffolding virtual simulations in higher education for career readiness. WCET Frontiers. https://wcet.wiche.edu/frontiers/2024/01/25/scaffolding-virtual-simulations-in-higher-education-for-career-readiness/