Publication Outline

Publication Outline CCMR

Erica Cedillo

EDLD-5317

Dr. Harrison

February 1, 2026

Publication Outline

Focus

This article explores how a thoughtfully designed, technology-integrated College, Career, and Military Readiness (CCMR) model can support both cognitive and noncognitive student outcomes, particularly for underserved student populations. Drawing from my experience as a CCMR Coordinator, the article examines how AI-assisted mentor matching, virtual career exploration, and data dashboards can operate as a cohesive, student-centered system rather than as disconnected tools. The purpose is to move beyond surface-level technology adoption toward a human-centered, equity-driven CCMR ecosystem that supports informed decision-making, sustained engagement, and postsecondary readiness.

Relevance

This publication highlights how intentionally integrated technology can strengthen postsecondary readiness by:

  • Increasing student engagement, self-awareness, and informed decision-making
  • Expanding access to meaningful mentorship and career exploration opportunities
  • Streamlining CCMR processes and data use for educators and leaders

The work is especially relevant for districts serving historically underserved students who often experience limited access to social capital, career exposure, and personalized guidance.

Publication Platforms & Guidelines

Journal of Research on Technology in Education (JRTE)

  • Focus: Educational technology research that bridges theory, practice, and policy
  • Audience: Educators, administrators, and researchers
  • Note: Primary target journal

Journal of Educational Technology & Society

  • Focus: Technology within social, institutional, and organizational contexts
  • Alignment: Systems-level CCMR implementation

International Journal of Educational Technology in Higher Education

  • Focus: Learning analytics, mentoring, and student transitions
  • Relevance: Secondary-to-postsecondary readiness

Connecting Technology to My Innovation Plan

This article aligns with my Digital Career Exploration and Mentorship Program, a hybrid CCMR initiative designed to:

  • Integrate mentoring, career exploration, and learning analytics into a unified system
  • Support cognitive outcomes (e.g., career knowledge, planning behaviors) and noncognitive outcomes (e.g., engagement, self-efficacy)
  • Balance technological tools with human facilitation, reflection, and relationship-building
  • Prioritize equity, ethical data use, and intentional design over isolated technology adoption

Key Insights and Strategies

  • Integrated CCMR Design: AI-assisted mentor matching, virtual simulations, and dashboards function together
  • Student-Centered Experience: Students engage in mentoring, exploration, reflection, and goal-setting
  • Support for Underserved Students: Expanded access to mentorship and career knowledge
  • Human-Centered Implementation: Educators facilitate relationships and meaning-making
  • Data-Informed Decision Making: Dashboards support growth while maintaining student agency
  • Equity Safeguards: Design choices reduce bias, overload, and exclusion

What Can We Learn?

Lessons Learned

  • Technology is most effective when embedded in a coordinated CCMR system
  • Human relationships remain central to student readiness
  • Educator capacity and context shape implementation

What the Study Seeks to Learn

  • Long-term impacts on engagement, persistence, and postsecondary outcomes
  • Best practices for scaling hybrid mentoring models
  • How dashboards can promote agency rather than compliance

Digital Resources

  • AI-supported mentorship platforms with equity safeguards
  • Virtual career exploration tools and simulations
  • Learning analytics and CCMR data dashboards
  • Interest, reflection, and goal-setting frameworks
  • District case examples of hybrid CCMR implementation

Preliminary Article Structure

  1. Introduction: The evolving demands of CCMR and integrated technology needs
  2. Literature Review: Mentoring, career exploration, hybrid learning, analytics, noncognitive outcomes
  3. Conceptual Framework: Digital Career Exploration and Mentorship Program
  4. Model in Practice: A student-centered CCMR experience
  5. Implementation Considerations: Design decisions, rollout, challenges
  6. Data Dashboards in CCMR: Ethical use and student agency
  7. Observed Outcomes and Implications: Cognitive, noncognitive, organizational impacts
  8. Discussion: Implications for practitioners, leaders, and researchers
  9. Conclusion: Connecting CCMR practice to future educational technology research

References

Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman.

Dede, C., Richards, J., & Saxberg, B. (2019). Learning analytics as a tool for closing equity gaps. Journal of Learning Analytics, 6(2), 1–15. https://doi.org/10.18608/jla.2019.62.1

Kram, K. E. (1985). Mentoring at work: Developmental relationships in organizational life. Scott, Foresman.

Means, B., Bakia, M., & Murphy, R. (2014). Learning online: What research tells us about whether, when and how. Routledge.

Nagaoka, J., Farrington, C. A., Ehrlich, S. B., & Heath, R. D. (2015). Foundations for young adult success: A developmental framework. University of Chicago Consortium on School Research.

Penuel, W. R., Fishman, B. J., Cheng, B. H., & Sabelli, N. (2011). Organizing research and development at the intersection of learning, implementation, and design. Educational Researcher, 40(7), 331–337. https://doi.org/10.3102/0013189X11421826

Rosenbaum, J. E., Stephan, J. L., & Rosenbaum, J. E. (2010). Beyond one-size-fits-all college dreams: Alternative pathways to desirable careers. American Educator, 34(3), 2–13.

Sahin, M., & Shelley, M. (2020). Educational technology integration as a systemic reform effort. Journal of Research on Technology in Education, 52(1), 37–53. https://doi.org/10.1080/15391523.2019.1667311