Sixty percent of the time it works every

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Sixty percent of the time, it works every time: Peer leaders and data Louise

Sixty percent of the time, it works every time: Peer leaders and data Louise Vasher Whitney Hawkins First Year Experience

Today’s Agenda • The importance of peer-to-peer relationships in supporting the success of at-risk

Today’s Agenda • The importance of peer-to-peer relationships in supporting the success of at-risk students • Committing time and resources in order to use data to drive decisions 2

Who We Were 3

Who We Were 3

Program Focused • Using programs to fix problems • Hoping the right students attend

Program Focused • Using programs to fix problems • Hoping the right students attend • Interacting with students who are already responsive to help • Not reaching students that could benefit the most from intrusive support 4

We realized this strategy was not meeting our goal of improving students’ success, and

We realized this strategy was not meeting our goal of improving students’ success, and ultimately retention, particularly for at-risk populations. We needed to find a new solution. 5

Who We Are 6

Who We Are 6

Peer Driven, Data Informed We moved to be an office that focused on datainformed

Peer Driven, Data Informed We moved to be an office that focused on datainformed outreach and relationship building to influence at-risk student behavior and decision-making. 7

Peer Driven Approach 30 Peer Leaders at the center of our work Peer Leader

Peer Driven Approach 30 Peer Leaders at the center of our work Peer Leader Orientation Pre. Enrollment First Year Trust and Relationship Building 8

Data Informed Approach ? Peer Leader First Year Students 9

Data Informed Approach ? Peer Leader First Year Students 9

Data Informed Approach DATA Peer Leader First Year Students 10

Data Informed Approach DATA Peer Leader First Year Students 10

Leverage Strengths 11

Leverage Strengths 11

Leading Data • • Early collection strategies Captures non-academic factors Peer-assessed (Stoplight) National norms

Leading Data • • Early collection strategies Captures non-academic factors Peer-assessed (Stoplight) National norms (CSI) Lagging Data • • “Wait and see” End of semester metrics Academic-only focus After critical period 12

Evaluating Our Process Admissions Process Orientation First Semester Second Semester Opportunity Demographics Grades Retention

Evaluating Our Process Admissions Process Orientation First Semester Second Semester Opportunity Demographics Grades Retention 13

Rapid Assessment – “Stoplight” • • • Academic, Social, Engagement Point-of-entry peer assessment Leverage

Rapid Assessment – “Stoplight” • • • Academic, Social, Engagement Point-of-entry peer assessment Leverage of orientation experience Intentionally designed dialogues Highly trained Peer Leaders Categorization of responses 14

Stoplight Results Academic Stoplight Social Stoplight Engagement Stoplight 3% 2% 2% 3% 6% 5%

Stoplight Results Academic Stoplight Social Stoplight Engagement Stoplight 3% 2% 2% 3% 6% 5% 21% 33% 31% 59% 60% 74% Green Yellow Red NEI 15

Student Survey – “CSI” • • • College Student Inventory Ruffalo Noel-Levitz product Student

Student Survey – “CSI” • • • College Student Inventory Ruffalo Noel-Levitz product Student self-assessment Very high rate of coverage Drill-down capability Student-specific recommendations 16

CSI Stoplight High Priority Students Demographics 17

CSI Stoplight High Priority Students Demographics 17

Pair and Share 18

Pair and Share 18

What data do you currently have access to and how are you using it?

What data do you currently have access to and how are you using it? What question(s) does your office have that you need additional data to answer? What opportunities do you have to collect data from students your office interacts with that you are not utilizing? 19

Useful Data 20

Useful Data 20

Power of Well-Informed Peers Use data to augment and inform the work Peer Leaders

Power of Well-Informed Peers Use data to augment and inform the work Peer Leaders do to build relationships and influence decisionmaking. Focus on coaching PLs, using data, incentivizing data-driven interactions to support success and retention. 21

Coaching • • • Consistent supervision and feedback Month-long training, weekly meetings Weekly, hour-long

Coaching • • • Consistent supervision and feedback Month-long training, weekly meetings Weekly, hour-long 1: 1 s Explain “the why behind the what” Encourage critical, strategic thinking 22

Using Data • Carefully select which data to share • Focus on practical applications

Using Data • Carefully select which data to share • Focus on practical applications • Drive and inform in-person interactions 600, 000 data points Less is more Filter 1: 1 Useful not just interesting 23

Incentivizing Interactions 24

Incentivizing Interactions 24

Continuous Collection • Value of longitudinal assessment • Taking stock midway through year •

Continuous Collection • Value of longitudinal assessment • Taking stock midway through year • Students using data to prioritize work • Collection serves dual purpose • Driving student outreach • Driving internal process assessment 25

What’s Next? 26

What’s Next? 26

Planning Evaluation Implementation Data Collection Interpretation 27

Planning Evaluation Implementation Data Collection Interpretation 27

Pair and Share 28

Pair and Share 28

1. What has you most excited? How might this inform the committee’s work or

1. What has you most excited? How might this inform the committee’s work or your workgroup’s effort? 2. What’s your muddiest point? What do you want to know more about? 3. What partnerships will you need to develop to help meet your goals? 29

Q&A Whitney Hawkins (hawkins. 557 s@osu. edu) Louise Vasher (vasher. 2 s@osu. edu) 30

Q&A Whitney Hawkins (hawkins. 557 s@osu. edu) Louise Vasher (vasher. 2 s@osu. edu) 30