A Regression Analysis of Student Motivation and the Effect of SI on Student Success Kathryn Beck Graduate Student, Applied Economics

Supplemental Instruction, SI Academic Support Program – Historically difficult courses – High DFW rates SI Sessions for review and study – Example: Business Statistics 1

Main Questions Does attending SI affect student achievement in a course? – How does SI affect the DFW rate? – Should the program be eliminated or extended?

Theories Attending SI will improve a student’s final grade and increase understanding in the given course – Aid in future courses and increase graduation rates Attending SI may be worse for students who are better off studying differently

Empirical Issues; Endogeneity Motivation – Correlation with attending SI (upward bias) At-risk students – Correlation with attending SI (downward bias) Unclear as to which direction the bias is causing

Literature Review Correlations Only The International Center for Supplemental Instruction Empirical Models Blanc, Debuhr, and Martin (Journal of Higher Education, 1983) Bowles & Jones (Digital 2003)

University of Wisconsin, Rock County Located in Janesville, WI (pop: 60,000) One of 13 campuses of the UW Colleges Enrollment (Fall 2013): 1,120 Average class size: 24 Student profile: 52% part-time 33% non-traditional

SI at UW Rock County Since SI sections offered in conjunction with ten different courses 10 SI leaders 30% participation rate in twice-weekly sessions Mean Course GPA SI participants:2.46 Non-SI participants:1.93

Data University of Wisconsin Rock County – Student data from Spring 2011 until Fall 2013 – 824 total observations

Model 1: Baseline Model Value-Added Education Production Function X ijt denotes a vector of student level characteristics for student i in class j in t semester Z jt denotes a vector of course level characteristics for j class in t semester ( βα…) are estimated coefficients

Model 2: IV Estimation 1 st Stage: – Where W itj includes the instrumental variables 2 nd Stage:

Results Baseline Models: – With all imputations, attendance is significant – Without imputations, attendance not significant IV Estimations: – With all imputations, attendance significant – Without imputations, not significant – Without variables that have missing, attendance is significant

Table 1: Baseline Models ImputationsNo Imputations SI Attendance *** (0.010) (0.015) ACT *** (0.014) (0.02) HS GPA 0.272*** (0.082) 0.212* (0.12) Class Size (0.006) (0.009) Female * (0.087) (0.119) Minority *** (0.138) * (0.192) Credits Enrolled 0.038*** (0.015) 0.038* (0.021) N Unit of Observation is the numberof SI attended. The number in parenthesis is the standard error. *,**,***: Significant at the 10,5, and 1% level, respectively

Table 2: IV, First Stage ImputationsNo Imputations Age 0.100*** (0.0289) (0.158) Miles (in %) (0.117) (0.15) Likeliness 0.476*** (0.121) 0.564*** (0.162) ACT (0.049) 0.05 (0.059) HS GPA (0.303) (0.388) Class Size (0.023) ** (0.038) Female 0.973*** (0.323) 0.87* (0.449) Minority (0.574) (0.686) Credits Enrolled (0.054) (0.076) N F-Test Unit of Observation is the numberof SI attended. The number in parenthesis is the standard error. *,**,***: Significant at the 10,5, and 1% level, respectively

Table 3: IV, Second Stage ImputationsNo Imputations SI Attendance 0.198*** (0.057) (0.089) ACT 0.057*** (0.015) (0.02) HS GPA 0.297*** (0.083) (0.121) Class Size (0.007) (0.011) Female *** (0.121) (0.161) Minority *** (0.147) ** (0.202) Credits Enrolled 0.041*** (0.016) (0.021) N Over-ID Test Unit of Observation is the number of SI attended. The number in parenthesis is the standard error. *,**,***: Significant at the 10,5, and 1% level, respectively

Table 4: IV, First Stage Imputations Age 0.116*** (0.028) Average Size of SI 0.463*** (0.170) Class Size (0.023) Female 1.21*** (0.302) Minority (0.56) Credits Enrolled (0.054) N704 F-Test17.07 Unit of Observation is the number of SI attended. The number in parenthesis is the standard error. *,**,***: Significant at the 10,5, and 1% level, respectively

Table 5: IV, Second Stage Imputations SI Attendance 0.232*** (0.072) Average Size of SI (0.071) Class Size (0.008) Female -0.33** (0.132) Minority -0.66*** (0.162) Credits Enrolled 0.07*** (0.017) N704 Over-ID Test Unit of Observation is the number of SI attended. The number in parenthesis is the standard error. *,**,***: Significant at the 10,5, and 1% level, respectively

Summary Running Baseline Models: – Attending SI is significant for larger sample with imputations included – Without imputations and reduced sample, attendance is no longer significant IV Models: – Age, Logmiles, and Likeliness as instruments – Correlated with Attending SI – Uncorrelated with final grade – Smaller Samples, nothing significant – Without missing variables, attendance is significant

All Observations5 or More Sessions0 Sessions Final Grade 2.07 (1.22) 2.79 (0.98) 1.89 (1.25) Female 0.45 (0.498) 0.64 (0.48) (0.495) Minority (0.281) (0.323) (0.276) Sophomore Status> (0.494) 0.58 (0.496) (0.486) Credits Enrolled (3.2) (3.33) (3.26) ACT (3.24) (2.86) (3.31) HS GPA 2.93 (0.58) 2.95 (0.665) 2.93 (0.573) Previous College GPA 2.71 (0.47) 2.79 (0.433) (0.48) Already SI Participant (0.273) (0.408) (0.209) Required Course (0.491) (0.503) (0.486) Expected Grade (4pt ) 3.36 (0.56) 3.45 (0.527) 3.34 (0.565) Female Professor (0.498) (0.377) (0.498) Class Size (8.68) (8.51) (8.59) Average Size of SI 2.59 (1.22) (0.897) 2.32 (1.22) Same Day as Class 0.54 (0.498) (0.484) (0.5) Female SI Leader (0.494) (0.434) (0.50) Section Average GPA 2.09 (0.338) 2.15 (0.359) 2.05 (0.33) N Appendix

Variables