This article presents a summary of main findings from FY18 and FY19 cycles of the Programmatic Learning Agenda (PLA). Below you will also find the links to the extended reports.
FY18 Programmatic Learning Agenda (Pilot Year)
The team conducted the two following analyses about our program:
1) What are mentor characteristics and program elements associated with pair full length of match completion?
By comparing those pairs that completed their match with those that did not, this research came up with the following takeaways:
- Mentor socio-demographic characteristics do not predict match persistence. - mentor age, gender, first generation status, race/ethnicity, or level of education does not predict match persistence (we don’t have to profile our mentors).
- Shared ethnicity/race or first-generation status within pairs does not predict match persistence. Pairs where mentor and mentee share the same ethnicity/race, or first generation college status do not differ in their match persistence.
- Persistence steadily drops across high school years, greatest drop off between year 2 and year 3 of the College Ready program.
- Pairs that met online and in person benchmarks were more likely to complete their full length of match.
- In predicting match persistence:
- In person meetings are more important than online communication during the first two years.
- Online communication is more important than in person meetings during the last year.
- 26% of match closures were "within our control." Based off a preliminary analysis of match closures where reasons for the closure were categorized as "within our control" or "out of our control."
- The impact of Schools, PMs, and cohort size effects:
- Number of PMs has an effect on match persistence but only within schools.
- School has a strong effect on match persistence.
- More analysis is needed to learn why some schools are more successful than others
- No statistical difference in match persistence based on cohort size.
- Strong Pair Relationships (SPR) as a marker for match persistence: Pairs that persist and pairs that don’t persist develop relationships similarly. The strength of the relationship may not be a decisive factor as to why a pair does not persist.
Click here for the extended report.
2) Student college matriculation
a. Do students who only have one PM during high school enroll in college at a different rate than students who have multiple PMs?
- The number of PMs a student has during HS does not appear to be a significant predictor of college enrollment.
- There are a lot of anecdotes/narratives around the impact of the PM. PM tenure may have an impact on other important aspects of programming outside of college enrollment.
- Schools may have other college access/success programs.
- iMentor internal support/training is enough to minimize impact of PM transition on student college enrollment.
b. Once a student enrolls in college, do they stay?
- 59% of students in the sample were continuously enrolled through Fall 2017.
- Continuous enrollment at a 4-yr institution was the most common pathway.
- Non-continuous enrollment at 2-yr & 4-yr institutions represent over a third of our students.
- Students in transfer pathways account for 16% of students in college.
- Percentage of students continuously enrolled drops over time.
c. Once a student enrolls in college, does their pathway differ based on First Generation college educated (FG) or Free/Reduced Lunch eligibility status?
- Non-FG enrollees appear at a 4-yr institution at a greater rate than FG peers.
- Non-FG students appear at a private institution at a greater rate than FG peers.
- Non-FG students appear at a 4-yr SUNY or Private school at a greater rate than FG peers.
d. Summer Melt - Who are the types of students who are accepted, confirm intent, graduate HS, and don’t enroll in college?
Melt was defined a student who was (1) accepted to college, (2) confirmed intent to enroll, and (3) graduated high school, but did not appear in college in the fall after HS graduation.
- 24% melt rate
- “Melters” had a larger proportion of First Generation college students (58%) than “Non-Melters” (49%)
Follow this link for more details about this research.
FY19 Programmatic Learning Agenda
Below is the Executive Summary of the main takeaways from the FY19 PLA process. The extended report can be found here. The OLI team held sessions on Zoom to share out these results with All Staff in June 2019. Access to the recordings of these webinars can be found here.
A note about the below FY19 PLA questions:
These five questions were identified through a consultative process with iMentor leadership and teams’ representatives. Questions needed to follow these criteria:
- Implications for program design action
- Implications for program implementation action
- Prime for action based on work of teams
- Data is available to answer the question
- Connected to short- and/or long-term org-wide strategy, learning, and planning
- Connected to external stakeholder interest
Question 1 - Exploring program elements relation to High-School Graduation and College Enrollment
Main takeaways:
- The iMentor program is having a positive impact on high school graduation and college enrollment.
- Certain elements of our program are more important for students’ chances of graduating high school and enrolling in college. Those elements are:
- Out of Program meetings
- Lessons completed
- Length matched with a mentor
Question 2 - Exploring strong mentoring relationships at iMentor
a) What non-programmatic characteristics and programmatic elements contribute to the development of strong pair relationships?
iMentor Program Managers insights about strong pair relationships (SPR):
- the mentor “meets the mentee where they are at”
- the pair relationship is a dynamic process
- the relationship strength is a process, not an endpoint
- meeting in person is essential
- internal/external factors play a role
b) What program elements predict Strong Pair Relationships?
- iMentor program is having a positive impact on the development of strong pair relationships.
- Meeting in-person is the most important predictor of the strength of the pair relationship.
- SPR increases with time: it can be expected to have stronger pair relationships when the student moves to a second year of program (10th grade) and when in Senior year.
Question 3 – What does Participation look like at iMentor?
- Pairs in the College Ready and College Transition programs:
- tend to communicate more often via conversations than lessons
- the percentage of meetings that qualify as pair expedition/Out of Program (OOP) increases over time
- more pairs text over program years
- The biggest dip in online communication is between 2nd and 3rd year for the College Ready program
- Analysis revealed that a pairs’ number of meetings in their first year, positively predicts the number of meetings they have in their final year (more meetings in year one, more meetings in the student’s final year of high-school)
Question 4 - What does the fidelity of program implementation look like at iMentor?
- Participating pairs reached programmatic benchmarks -curricular engagement, online and in-person; full length of match; and pair support- at different rates. Only 3% of the pairs reached all four benchmarks.
- Pairs in the College Transition program were more likely to achieve more of these programmatic benchmarks than those in the College Ready program.
Question 5 - What is the relationship between enrollment in the PSP program and college persistence
- Students in the iMentor Post-Secondary Program (PSP) enroll in college on-time at higher rates (76%) than students who don’t sign up for PSP (65%).
- PSP students persist into the second year of college at higher rates (66% vs. 62%) than non-PSP students, especially at two-year colleges (50% vs. 41%). The college persistence rate is defined by the % of students who enroll in college the fall and remain enrolled in any college the fall of their second year of college.
