Retention of CASNR Undergraduate Students Brianna Hitt, University of Nebraska-Lincoln

Motivation  Previous work  Enrollment predictions  Model retention with financial data, all colleges  New Student Enrollment surveys  Programming  How can CASNR better support students?

Data  New Student Enrollment (NSE) survey  Academic Management Information System (AMIS)  base_enrollment database  Student demographics  Academic information for each semester enrolled  Over 150 variables  Linked by Student NUID through Microsoft® Access®

NSE variables  Pre-professional programs  Working on/off campus  Weekly work hours  Best subject  Worst subject  Concerns about college  Number of activities  Campus activities

Student Demographics  Age  Gender  Ethnicity  AP / CLEP credits  ACT scores  High school GPA  High school class size  High school class rank

Semester Academic Information  Retention  First-time freshman  JD Edwards  Honors program  FERPA  Resident status  Veteran status  Full-time  Total term credits  High school graduation  Cumulative GPA  Cumulative earned hours  Cumulative transfer hours  Transfer student  Previous college credits

Methods  Means and proportions  Kendall’s tau-b correlation  Logistic regression  Stepwise selection  Modeling semester retention  Linear effects for all indicators  Scoring  Used new students to check the model  Predicted probabilities  Confidence intervals  Overall fit statistics

Fall 2013 Students

Retention from 2013 NSE to Fall 2013 Effect P-valueEstimateOdds Ratio Intercept Pre-health Planning to work off campus Best subject science Best subject writing Worst subject math Worst subject science Worst subject writing Worried about time management Worried about too large an environment Worried about making friends Planning to participate in Greek life Planning to participate in honors program

Retention from 2013 NSE to Fall 2013  Variables not included  Pre-professional programs other than Pre-Health  Planned weekly work hours

Retention from 2013 NSE to Spring 2014 Effect P-valueEstimateOdds Ratio Intercept Planning to work off campus  Variables included, then removed  Full-time status  Variables not included  Pre-professional programs  Planned weekly work hours  Best/worst subjects  Concerns about college  Activities  Demographics  Fall 2013 academic information

Retention from 2013 NSE to Fall 2014 Effect P-valueEstimateOdds Ratio Intercept Planning to work more than 15 hours White ethnicity High school grad in the last 12 months (fall 2013) Previous college (fall 2013) Total term credit hours (spring 2014) Cumulative GPA (spring 2014)

Retention from 2013 NSE to Fall 2014  Variables included, then removed  Hawaiian/Pacific Islander ethnicity indicator  Variables not included  Pre-professional programs  Planned location of work  Best/worst subjects  Concerns about college  Demographics  Fall 2013 retention  Resident status  Veteran status  Full-time status  Cumulative GPA, earned, and transfer hours from Fall 2013  All variables from Spring 2014 other than cumulative GPA

Fit Statistics for SCORE Data Total Frequency417SC Log Likelihood R-Square Error Rate0.0312Max-Rescaled R-Square AIC AUC AICC Brier Score BIC  Model built using Fall 2013 first-time freshman  Used Fall 2014 first-time freshman to check the model  3.12% error rate in predicting which students retained Retention from 2013 NSE to Fall 2013

Shared Characteristics for Student Not Retained NR = Not Retained

Shared Characteristics for Majors QuestionNR Fall 1NR Spring 1NR FS 1NR Fall 2NR Spring 2NR FS 2Overall Number Agribusiness 0%3.5%3.4%3.6%3.1%3.0% 10.3% Agricultural Journ. 6.7% 1.7% 1.8%1.5% 1.6% Animal Science13.3% 8.6%8.5%8.2%8.4%8.3% 13.9% Biochemistry 13.3% 6.9%6.8%5.5%5.3% 4.4%  Less likely to major in Agribusiness or Animal Science  More likely to major in Agricultural Journalism or Biochemistry (first fall only)

Shared Characteristics for Majors QuestionNR Fall 1NR Spring 1NR FS 1NR Fall 2NR Spring 2NR FS 2Overall Number Env. Studies 6.7%6.9%6.8%5.5%4.6% 3.1% Forensic Sci. 13.3%17.2%17.0%14.6%16.0%15.9% 9.3% Fish & Wildlife6.7% 12.1%11.9%10.9%9.2%9.1% 5.7% Pre-Vet Med.13.3% 17.2%17.0%15.5%16.0%15.9% 13.7% Vet Science6.7% 8.6%8.5%8.2%8.4%8.3% 5.7%  More likely to major in Environmental Studies, Forensic Science, Fisheries and Wildlife, Pre-Veterinary Medicine, or Veterinary Science

Shared Characteristics for NSE QuestionNR Fall 1NR Spring 1NR FS 1NR Fall 2NR Spring 2NR FS 2Overall Number Pre-health 20.0%10.3%10.1%11.8%11.5%11.4% 7.0% Off-campus work 40.0%34.5%35.6%30.0% 20.0% 28.8% 19.3% On-campus work 20.0%29.3%28.8% 35.5%35.1%35.6%35.8% Future work33.3% 27.6%27.1%25.5%28.2%28.0% 33.8%  More likely to plan on Pre-Health  More likely to plan to work off-campus  Less likely to plan to work on-campus (first year only)  Less likely to plan to work in the future

Shared Characteristics for NSE QuestionNR Fall 1NR Spring 1NR FS 1NR Fall 2NR Spring 2NR FS 2Overall Number hours 20.0%24.1%23.7%28.2%27.5%27.3% 17.8% Not working 6.7% 10.3%10.2%10.0%8.4%8.3%11.1% Future work hours 26.7%24.1%23.7%21.8%24.4%24.2% 31.2%  More likely to plan to work more than 15 hours  Less likely to plan not to work (first fall only)  Less likely to plan to work future hours

Shared Characteristics for NSE QuestionNR Fall 1NR Spring 1NR FS 1NR Fall 2NR Spring 2NR FS 2Overall Number Good math46.7% 36.2%37.3%38.2%40.5%40.2% 49.2% Good science 53.3% 65.5%64.6%68.2%67.9%68.2%68.0% Good writing 20.0% 29.3%28.8%28.2%29.8%29.5%29.1%  Less likely to consider math their best subject  Less likely to consider science or writing their best subject (first fall only)

Shared Characteristics for NSE QuestionNR Fall 1NR Spring 1NR FS 1NR Fall 2NR Spring 2NR FS 2Overall Number Bad math 53.3%53.4%52.5%53.6%50.4%50.8% 44.3% Bad science 6.7%10.3%10.2%11.8%11.5%11.4% 14.9% Bad writing 53.3% 41.4%42.4%39.1%39.7%40.2%43.8%  More likely to consider math their worst subject  Less likely to consider science their worst subject  More likely to consider writing their worst subject (first fall only)

Shared Characteristics for NSE QuestionNR Fall 1NR Spring 1NR FS 1NR Fall 2NR Spring 2NR FS 2Overall Number Worried about doing well 33.3%55.2%54.2%50.9%50.4%50.8% 44.8% …paying for college 46.7%43.1%44.1%47.3%45.8%45.5% 36.9%  Less likely to be worried about doing well (first fall only)  More likely to be worried about doing well (after first fall)  More likely to be worried about paying for college

Shared Characteristics for NSE QuestionNR Fall 1NR Spring 1NR FS 1NR Fall 2NR Spring 2NR FS 2Overall Number …managing time 6.7% 25.9%25.4%26.4%24.4%25.00%24.5% …finding help 33.3% 20.7%20.3%19.1%21.4%21.2%25.8% …larger environment 13.3%13.8%15.3%15.5%16.0%15.9% 22.4% …making friends 33.3% 12.1%11.9%9.1%10.7%10.6%11.3%  Less likely to be worried about managing time (first fall only)  More likely to be worried about finding help, making friends (first fall only)  Less likely to be worried about college being too big

Shared Characteristics for NSE QuestionNR Fall 1NR Spring 1NR FS 1NR Fall 2NR Spring 2NR FS 2Overall Number Greek life 13.3% 29.3%28.8%26.4%28.4%28.0%28.1% No activities 33.3%36.2%35.6%32.7%29.8%30.0% 24.5% Athletics6.7% 10.3%10.2%9.1%8.4%8.3% 4.6%  Less likely to plan to participate in Greek life (first fall only)  More likely to plan not to participate in activities  More likely to plan to participate in athletics

Shared Characteristics for Demographics QuestionNR Fall 1NR Spring 1NR FS 1NR Fall 2NR Spring 2NR FS 2Overall Number Black 6.8%6.7%6.2%5.9% 2.1% Hispanic 11.4%13.3%11.3%9.3%9.2% 7.0% White 90.9%88.9%86.6%88.1%88.2% 94.1% Multi-racial 13.6%13.3% 11.3%9.3%9.2%8.0%  More likely to be Black or Hispanic  Less likely to be white/Caucasian  More likely to be multi-racial (first year only)

Shared Characteristics for Demographics QuestionNR Fall 1NR Spring 1NR FS 1NR Fall 2NR Spring 2NR FS 2Overall Number High school class size High school rank  Larger high school classes (by about 50 students)  Lower high school class rank (by about 30 students)

Shared Characteristics for Academics  Students NR after the first fall semester:  Were less likely to be in the Honors program  Were more likely to have graduated in the past 12 months  Had fewer cumulative earned hours on average  Had fewer cumulative transfer hours in the second year  Were less likely to have had previous college experience

Future Work  Enrollment predictions  More and different data  Checking accuracy of other models  Trends in class size and majors  Investigate students without NSE data  Did not attend  Attended with different plans  Compare Fall 2013 and Fall 2014 students  Combine to look at trends

Acknowledgements  Dr. Erin Blankenship – MS Advisor  Dr. Stephen Kachman – MS Committee Member  Dr. Tiffany Heng-Moss - Associate Dean of CASNR, MS Committee Member  Dr. Steven Waller - Dean of CASNR  Vanessa Roof - Inst. Retention and Assessment Research Analyst, Academic Affairs  Judy Carter - Programmer Analyst, IANR Finance & Personnel  Traci Kaslon - Inst. Research Analyst, Office of Inst. Research and Planning  Dr. Pamela Fellers  Section on Statistical Education

Contact Information  Brianna Hitt  University of Nebraska-Lincoln 