CCA COMMON COMPLETION METRICS 2015 DATA COLLECTION. Webinar April 8, 2015

Transcription

1 CCA COMMON COMPLETION METRICS 2015 DATA COLLECTION Webinar April 8, 2015

2 Presenters Bruce Vandal, Vice President, Complete College America John Armstrong, Information Analyst, State Higher Education Executive Officers

3 Overview Introduction of CCA Metrics & State Accomplishments Changes to CCA Common Completion Metrics Data Quality & Accuracy Customer Service and User Roles 2015 Data Collection System Questions

4 35 Members DC

5 Why collect common completion metrics?

6 Why collect common completion metrics? 1. Performance Funding 2. Corequisite Remediation 3. Full-Time is Structured Schedules 5. Guided Pathways to Success

7 What are common completion metrics? Outcome Metrics Degrees Awarded Annually (# and change over time) Graduation Rates Transfer Rates Credits and Time to Degree* * Not included in IPEDS

8 What are common completion metrics? Progress Metrics Remediation: Entry and Success* Success in first-year college courses* (1st yr. math and English) Credit Accumulation* Retention Rates Course Completion* * Not included in IPEDS

9 What are common completion metrics? Gender Disaggregations Race/Ethnicity Income (Pell Grant recipients)* Age Group (where applicable)* Full-time/Part-time /Transfer Entry Status* Discipline/Degree-type* Remedial Status* * Not included in IPEDS

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12 How states are using the metrics 27 states used completion metrics to prepare for completion academies. 6 states used campus-level completion metrics to prepare for in-state completion academies. Indiana used completion metrics to generate state institutional reports on progress toward state completion goals. States including Illinois and Oklahoma integrated CCA Metrics into performance funding models. West Virginia used data to drive system-wide reform of remedial education. 6 states are using gateway success data to support state math pathway initiatives.

13 Capitalizing on the Database Big Data helps understand current state of completion in states. Tracking progress over time. Measuring the impact of reforms at the institutional and state level. Identifying lead states and institutions. Generating more reports and analysis.

14 2015 Data Collection Goals Full participation in data collection all metrics from all Alliance members. Dramatic increase in participation from institutions. Expansion to new states.

15 Metrics/Variable Additions 1. Outcomes Metric 2 / 2A: Collects 200% completion data for the 2006 Bachelor s Cohort in new workbook Collect graduated or transferred to a 2-year institution for associates cohorts 2. Progress Metric 1&2: Added a row for corequisite remedial students (and defined corequisite remedial 3. Progress Metric 2&3: Started collecting 1-year gateway completion in addition to 2-year 4. Progress Metric 5: Made spring beyond the first academic year optional

16 Data Quality and Accuracy Example 1: Remedial and Gateway Completion 2-Year Institutions Enrolled in Remedial Entering Cohort National Median 2YR - Two-Year Institutions TOTAL Students 57.59% 56.32% 61.78% Age: Directly from High School (17-19 years old) 59.76% 57.17% 60.00% Age: Other (20-24 years old) 55.80% 57.72% 60.05% Age: Age 25 and over 47.61% 56.16% 58.50% State X TOTAL Students 54.37% 64.21% 86.43% Age: Directly from High School (17-19 years old) 73.02% 70.02% % Age: Other (20-24 years old) 51.76% 61.70% 79.01% Age: Age 25 and over 23.02% 52.71% 63.91%

17 Data Quality and Accuracy Example 2: Remedial and Gateway Completion 2-Year Institutions Completed All Remedial Enrolled In Remedial Students Completing Associated Gateway Entering Cohort State Y TOTAL Students 68.97% 66.46% 68.99% 19.17% 30.07% 21.14% Age: Directly from High School (17-19 years old) 66.98% 67.32% 70.04% 19.63% 31.46% 22.92% Age: Other (20-24 years old) 70.65% 63.71% 64.36% 18.60% 28.89% 15.71% Age: Age 25 and over 75.20% 66.39% 69.81% 17.98% 27.14% 20.57% State Z TOTAL Students 61.31% 55.35% 57.26% 21.52% 9.65% 19.61% Age: Directly from High School (17-19 years old) 62.79% 56.78% 58.49% 24.12% 12.03% 24.07% Age: Other (20-24 years old) 55.15% 47.58% 50.25% 15.57% 4.85% 12.10% Age: Age 25 and over 63.20% 59.43% 61.16% 18.92% 7.15% 16.07%

18 Data Quality and Accuracy Example 3: Remedial and Gateway Completion 2-Year Institution Completed All Remedial Enrolled In Remedial Students Completing Associated Gateway Entering Cohort State Q TOTAL Students 65.31% 25.95% 62.92% 28.10% 28.46% Age: Directly from High School (17-19 years old) 65.43% 26.22% 63.18% 28.12% 27.63% Age: Other (20-24 years old) 59.57% 18.84% 53.59% 22.43% 22.48% Age: Age 25 and over 71.05% 31.44% 65.09% 34.50% 32.33% State R TOTAL Students 67.29% 51.23% 20.36% 20.05% Age: Directly from High School (17-19 years old) 67.96% 47.08% 24.40% 19.25% Age: Other (20-24 years old) 62.79% 51.23% 11.72% 19.67% Age: Age 25 and over 68.55% 60.66% 15.86% 22.33%

19 Understanding Your User Roles State Agency Keyholder State Coordination/Quality Managing institutions Designating Keyholders Data Approval Adding Operators Upload/View Data Designated Keyholder Data Approval Adding Operators Upload/View data Operator Operator Upload/View data

20 2015 Upload Process & Options From The Web Site Upload and Validate, Review and Approve With the Optional Workbook Manually Prepare data and Produce a batch file 1) Upload And Validate Data In One Step 2) Review and Approve Collection Database Optionally use the Excel Workbook to Prepare Data

21 Demo

22 SHEEO/CCA Customer Service Team SHEEO/CCA Customer Support Contact Information Angela Sanchez First Point of Contact Katie Zaback Metrics Content and Validation John Armstrong Metrics Content and Validation