POC PHASE DATA. 6 institutions

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2 POC PHASE DATA 6 institutions 1 calendar year (2010) All ONLINE Bachelors and below courses All DevEd regardless of format Two principle outcome measures investigated Did the student SUCCEED in their current course (C or better OR Fail/Withdraw) At the end of the time period, were they still active (Gone/Not Gone)

3 INTERNALLY DEFINED VARIABLES New Student At some point during the POC No transfer credits No prior credits earned No prior term gpa DHRatio / Credit Ratio Credits Earned / Credits Attempted at this institution Other variables were simplified from continuous to buckets Age (>26, <=26) Transfer Credits (0, >0) DevEd Courses (0,>0) Course Grade (Pass, Fail, Withdrew) Passing defined as C or better (Success) Passing defined as per institutional rules

4 OVERALL THEMES In the presence of behavioral data, demographic variables (race, gender, age) tend to lose significance New students are at substantially higher levels of risk of dropping out or failing. Once a student has some experience, they tend to keep going. The more concurrent online courses for the new students, the more they struggle. (Excludes UoP)

5 ALL STUDENTS (DESCRIPTIVE) 58% of online students are female 55% are over age 26 At the end of the POC time period (1 calendar year) 49.3% still active 15.2% graduated 35.6% disenrolled/dropped out 59% have no transfer credits 11% attempted at least 1 dev ed course

6 ALL STUDENTS Predicting Gone/Not Gone: (Logistic Regression + CHAID) Credit ratio most predictive (+) Courses completed at this institution (+2%/course) Military classification important (+) Age, but only for the most accomplished students (+) Predicting Pass with C-or-better/Not Pass (Logistic Regression + CHAID) Prior term withdrawals (-45%) Any Dev Ed courses (-33%) One of the few places that Race appeared meaningfully, with Black, Hispanic, and multi-racial students separated from white and Asian students. In the case of Black, Hispanic and multiracial students who have a previous term withdrawal, younger students (<= 26) are at greatest risk of failure.

7 ALL STUDENTS Factor analysis identified several clumps of predictive variables: Doing Well courses completed, credit ratio, courses attempted Degree Level Bachelors (+), Associates (-) and transfer credits DevEd attempted and completed (minimal impact) Focus multiple majors, program changes (minimal impact) Doing well was consistently the most predictive of continued enrollment (logistic regression)

8 NEW STUDENTS (23%) No transfer credits No prior completed courses More concurrent courses at first can lead to lower chance of passing ~10% per course Any dev ed reduces the likelihood of a student passing this course by at least 25% (up to 61% for bachelors students) New students more likely to never pass a single class during POC year Associates 34% of new compared with 20% of continuing Bachelors 30% of new compared with 10% of continuing Withdrawals are addicting Each prior term withdrawal reduces the likelihood of passing by ~50% Students who withdraw once tend to do it more and more Past success breeds future success Each additional course completed makes it more likely that the student will still be active: 12.5% for associates, 23% for bachelors Program changes make a student 41-47% more likely to still be enrolled

9 DEVELOPMENTAL EDUCATION (DEVED) ALL STUDENTS Not all schools have dev ed courses, but looking at those that do: Each additional dev ed course reduces the likelihood of a C or Better by 34% Associates Degree Students: 28% Undeclared Students: 43% Certificate Students: 37% Significant predictor of gone/not gone, although small effect size for all students, larger for new students High withdrawal rate for Dev Ed courses (32%) Students who took at least one dev ed course more likely to withdraw from non-dev ed courses as well (18%)

10 ANALYTIC LESSONS LEARNED Substantial differences in sample sizes between institutions need to be accounted for. Level of analysis matters (student vs. course). Some variables would be more useful at a different levels. Be careful of circularly defined variables. Analysis needs to be split by degree level, since in nearly every case bachelors students behaved differently from associates.