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From a Culture of Guesstimates to a Culture of Evidence. About Speakers. Blaine Bennett Dick Whipple Hector Gonzales Michael Taft Michael Nguyen. About SWTJC. Large service area 11 Counties (16,812 sq. miles) HSI - 82% 50%+ need remediation 42% financial aid AtD 2005 – Round 1.
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About Speakers • Blaine Bennett • Dick Whipple • Hector Gonzales • Michael Taft • Michael Nguyen
About SWTJC • Large service area • 11 Counties (16,812 sq. miles) • HSI - 82% • 50%+ need remediation • 42% financial aid • AtD 2005 – Round 1
About AtD • AtD Goals • Increase percentage who: • Succeed in dev ed classes • Enroll / succeed in gatekeeper classes • Return • Graduate
In The Beginning… • Fall 2005 – Data difficult to acquire. Need to know what’s going on (AtD data driven) with students. • Began development of a student data warehouse - Estudias • Wanted to study the dev-ed to gateway process more closely • (e.g. How long does it take a student to go through dev-ed and complete the gateway course?)
Data and Questions????? • Is data readily accessible for real time planning & decision making? • Can advisors readily access a comprehensive look at a student? • Can cohorts of students be easily identified ? • Can gaps in student progress be readily identified?
Example: Completion Rates? • Hard to get basic info from Datatel • Solution: Estudias Data Warehouse
Access to Data Leads to More Questions • Developmental placement? • Success rates? Duration? • By course, faculty, cohort, high school, placement score, modes of instruction • Which are the gateway courses? • Post-gateway success? • Probability, time-to-degree/transfer • Interventions? • What kind? What audience? Do they work?
Before Estudias • Levels were tied with course enrollment to gauge a student’s capacity for success in a course. • Prior to Estudias, a student/advisor would see something like this in the course description: • Student must be at math level 1 to enroll; i.e., Accuplacer 30 or greater.
Before Estudias • Developmental prerequisites at this time were best guesstimates!
From guesstimates to evidence • Placement ranges were not based on refined data analysis • Cutoff scores hard to remember, many tests, course completions • Data were not fine-grained / diagnostic
Too Much Data, Not Enough Information Looking at class and test history, impossible to see where student is in dev ed sequence
Solution • Logistical regression on scores • Incorporate grades • Higher grades = higher scores Test History Bottom Line Class History è
Example Susan Smith • Accuplacer 78 (high level 2) Aaron Abel • Accuplacer 63 (barely level 2) Although these students are both in Level 2, they are very different students
Solution: new level based on better data The score accurately reflects the fact that each of these students has completed one developmental class and more precisely illustrates the differences between them
Data and Questions????? • Can advisors readily access a comprehensive look at a student? • Can cohorts of students be easily identified ? • Can gaps in student progress be readily identified? • Is data readily accessible for real time planning & decision making?
Find Bubble Students • Credits > 50 • GPA > 2.5 • Math: Level 2(high)
Compare Cohorts Started 2005 FA Performance of: • Cohort 1: Placed into Level 2 • Cohort 2: Placed into Gateway How many completed Gateway over time?
Examine Cohort in Detail Cohort 1: 2005FA, placed into Level 2. How many: • Enrolled in Level 2 • Completed Level 2 • Enrolled Gateway • Completed Gateway
Examine Cohort in Detail How many: Enrolled in Level 2, Completed Level 2, Enrolled Gateway, Completed Gateway
Questions Blaine Bennett blaine.bennett@swtjc.cc.tx.us Dick Whipple dwhipple@swtjc.cc.tx.us Hector Gonzales hector.gonzales@swtjc.cc.tx.us Michael Taft mtaft@zogotech.com Michael Nguyen mnguyen@zogotech.com Slides at: www.zogotech.com/atd