Course Project: Choose A Type Of Program. Reflect On The Typ ✓ Solved

Course Project: Choose a Type of Program. Reflect on the typ

Course Project: Choose a Type of Program. Reflect on the types of programs and services you discovered. Which of those programs or services are currently available in your institution? Which ones are not? Consider what new programs or services you would like to see offered at your institution to enhance the student experience and facilitate success for all students. How might you use assessment data to analyze the feasibility of a proposed program? Submit a 3- to 4-page paper that includes the following: Identify one new program for your institution. Describe how you can determine the current need that exists for the program. Explain how you will monitor the progress of the program if it is adopted. Describe how you plan to assess the success of the program once it has been fully implemented.

Paper For Above Instructions

Executive Summary

This paper proposes a New Student Peer Mentoring and Digital Onboarding Program designed to improve first-year integration, retention, and academic success. The program combines trained peer mentors, structured orientation cohorts, and an adaptive digital onboarding platform to support academic, social, and administrative transition needs. The proposal outlines methods to determine current need, monitoring approaches during implementation, and an evaluation plan to assess long-term success.

Program Description

The New Student Peer Mentoring and Digital Onboarding Program pairs incoming students with trained upper-level peer mentors from their college or major and provides a digital onboarding portal with campus maps, academic checklists, resource links, and modular learning on policies and supports. Peer mentors facilitate small cohort meetings, guided campus tours, academic skills workshops, and referrals to campus services. The digital component tracks engagement, delivers micro-lessons, and collects baseline assessment data.

Determining the Current Need

To determine institutional need, a mixed-methods needs assessment will be conducted. Quantitative sources include institutional data on first-year retention and course completion, academic probation rates, withdrawal rates, and use of existing student services (student affairs, advising, counseling) (Tinto, 1993; Pascarella & Terenzini, 2005). Surveys of recently matriculated cohorts will assess perceived gaps in orientation, academic preparedness, and social integration (NSSE, 2018). Qualitative data will come from focus groups with new students, interviews with frontline staff (advisors, residence life, tutoring centers), and suggestions from faculty (Creswell, 2014).

Key indicators for need: first-year retention below peer benchmarks, high DFW (D/F/Withdraw) rates in gateway courses, low engagement scores on NSSE-type measures, low utilization or delayed use of support services, and student self-reports of confusion about processes/policy (Kuh, 2008; Bean, 1980). Benchmarking against peer institutions and national retention data will contextualize whether observed rates reflect a local problem or broader trends (Astin, 1993).

Program Implementation and Progress Monitoring

Implementation will follow a phased pilot design across one or two colleges within the institution for an academic year, then scale pending results. Core elements: recruitment and training of peer mentors (selection criteria, training curriculum), development of the digital onboarding portal, and coordinated orientation cohort schedules.

Monitoring will use continuous data collection and routine reporting cycles (monthly during early roll-out, quarterly thereafter). Process metrics include number of mentor-mentee matches, attendance at cohort meetings/workshops, digital portal logins and module completions, time-to-first-advisor-appointment, and referrals to support services (Habley & McClanahan, 2004). Qualitative progress checks include mentor reflective journals and brief student satisfaction pulse surveys. A program dashboard visualizing KPI trends will be accessible to program leadership and stakeholders for course correction (Lewallen et al., 2015).

Assessment of Program Success

Outcome evaluation will assess short-, medium-, and long-term outcomes. Short-term outcomes (end of first term) include increased orientation completion rates, higher engagement with campus resources, and improved self-reported campus belonging and academic self-efficacy (Kuh, 2008). Medium-term outcomes (end of first year) include first-year GPA, course pass rates in gateway courses, and retention to sophomore year. Long-term outcomes include time-to-degree and graduation rates (Tinto, 1993; Pascarella & Terenzini, 2005).

Evaluation design: a quasi-experimental design comparing pilot cohort outcomes to a matched comparison group (students with similar characteristics who did not participate) using propensity score matching to reduce selection bias (Creswell, 2014). Statistical analyses will assess mean differences in GPA, retention, and pass rates; logistic regression models will control for demographic and academic preparation covariates. In addition, qualitative evaluation (focus groups, mentor interviews) will explore mechanisms of impact and student experience (Terrion & Leonard, 2007).

Key performance indicators (KPIs): 1) increase in first-year retention by X percentage points relative to baseline; 2) increase in gateway course pass rates; 3) higher NSSE engagement subscale scores; 4) positive student satisfaction ratings (>80%); and 5) sustained mentor program participation beyond pilot. Targets will be set using baseline institutional averages and peer benchmarks.

Using Assessment Data to Analyze Feasibility

Feasibility analysis will integrate cost, capacity, and projected impact. Cost data: staff time for mentor supervision, mentor stipends or course credit, digital platform development or licensing, and training costs. Capacity assessment: number of available trained mentors relative to incoming cohort size and office capacity for coordination. Impact projection: using historical retention-to-revenue models, the financial return on investment can be estimated by calculating revenue retained if retention increases (Stiglitz & Rosengard, 2015). Sensitivity analysis will explore scenarios (low/medium/high uptake) to inform scale decisions.

Stakeholders, Timeline, and Sustainability

Stakeholders: student affairs, academic advising, IT/digital learning, residence life, faculty champions, institutional research, and student government. Timeline: months 1–3 planning and portal development; months 4–6 mentor recruitment and training; month 7 pilot launch at orientation; months 8–12 monitoring and iterative improvement; end of year: formal evaluation and scale decision. Sustainability plan includes institutionalizing mentor roles through course credit or work-study funding, integrating the portal into onboarding workflows, and transferring data ownership to institutional research for continued monitoring.

Conclusion

A combined peer mentoring and digital onboarding program offers an evidence-informed approach to improve student integration and outcomes. Using mixed-methods needs assessment, process monitoring, quasi-experimental evaluation, and feasibility analysis ensures decisions are data-driven and scalable. If successful, the program should demonstrate measurable gains in engagement, retention, and academic success while providing a cost-effective model for broader institutional adoption (Tinto, 1993; Kuh, 2008).

References

  • Astin, A. W. (1993). What matters in college: Four critical years revisited. Jossey-Bass.
  • Bean, J. P. (1980). Dropout determinants in higher education: An empirical synthesis of recent research. Review of Educational Research, 50(4), 215–239.
  • Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). SAGE Publications.
  • Habley, W. R., & McClanahan, R. (2004). The status of academic advising: Findings from the ACT Sixth National Survey. NACADA Journal.
  • Kuh, G. D. (2008). High-impact educational practices: What they are, who has access to them, and why they matter. AAC&U.
  • Lewallen, T. C., Hunt, H., Potts-Datema, W., Zaza, S., & Giles, W. (2015). The whole school, whole community, whole child model: A new approach for improving educational attainment and healthy development for students. Journal of School Health, 85(11), 729–739.
  • NSSE (National Survey of Student Engagement). (2018). Engagement insights: Survey findings on the quality of undergraduate education.
  • Oudshoorn, M. J., Clear, A., Carter, J., et al. (2017). Integrating international students into computer science programs: Challenges and strategies for success. In Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education. ACM.
  • Pascarella, E. T., & Terenzini, P. T. (2005). How college affects students: A third decade of research. Jossey-Bass.
  • Terrion, J. L., & Leonard, D. (2007). A taxonomy of the characteristics of student peer mentors in higher education: Findings from a literature review. Mentoring & Tutoring: Partnership in Learning, 15(2), 149–164.

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