Reaching Out to Retain AtRisk Students

1
Reaching Out to Retain At-Risk Students

• An Exploratory Study Using the Student Adaptation
  to College Questionnaire

Dr. Mike Meacham and Dr. Marsha Krotseng Valdosta
State University June 4, 2007 Funded by a
Faculty Research Grant from Valdosta State
University
2
Introduction

• Student retention increasingly important to
  university administrators, boards, and
  legislators
• Literature review revealed students decisions
  involve
• Academics
• Social reasons
• Personal problems
• Adjustment to school environment

3
The Student Adaptation to College Questionnaire
(SACQ)

• Measures student adaptation on four indices found
  in literature as important
• 67 questions rated from applies very closely
  to me to does not apply to me at all

4
The SACQ (cont.)

• Higher scores indicate better adaptation
• Research on SACQ
• Consistent Internal Reliability
• Numerous studies attest to high reliability and
  validity

5
Steps in the Study

• Received permission from IRB and Freshman
  Experience Courses Director. Reviewed students
  rights.
• Fall 2006, administered to students in program
  above.
• Advisors reviewed results with individual
  students
• Summary data from questionnaires analyzed
  statistically.

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Study Focus

• Exploratory studies frequently change the area of
  focus as data are gathered.
• Original Intent
• Which students are at greatest risk of leaving
  the university?
• What intervention strategies might help VSU
  retain these students?
• Data suggested new hypotheses

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Research Hypotheses

• H1 Student characteristics (demographic
  variables) are not significantly associated with
  institutional attachment.
• H2 Adjustment cluster and subscale scores from
  the SACQ are not significantly associated with
  institutional attachment.
• Which variables, among demographic questions,
  individual items, clusters, and subscale scores
  on the SACQ can be used to predict institutional
  attachment?

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Participant Characteristics Analyzed

• Sample Characteristics similar to the University
• Participants (n74)
• Gender
• Female 61
• Male 39
• Age
• 18 77
• 19 18
• Other 5 (17, 30, 40)
• Ethnic Background
• Caucasian 72 Hispanic 4
• African American 16 Multiracial 4
• Other 4
• Hometown
• Major metro area 32
• Other areas 68

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Other Characteristics Considered

• First-year Residence
• On campus 32
• Off campus 68
• High School GPA
• 3.5 or above 26
• 2.5 to 3.49 54
• 2.49 or below 19
• Class Type
• Cohort (common) 57
• Non-cohort 43
• Enrollment
• Full-time 91
• Part-time 9
• First Semester GPA
• 3.5 or above 34
• 2.5 to 3.49 41
• 2.49 or below 26

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What Differences Exist?

• Three of Four SACQ Subscales significant
• Academic Environment
• Ethnic Background
• Social Environment
• Ethnic Background
• Residence (On campus/Off)
• Class Type (Cohort/Non-cohort)
• Attachment
• Ethnic Background
• Hometown
• High School GPA
• First Semester GPA

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What Differences Exist? (cont.)

• African-American students reported the lowest
  adjustment
• Academic Environment (M 6.25)
• Social Environment (M 5.83)
• Attachment (M 7.68)
• Based on a small number (12)
• Important to test this finding with a larger
  sample

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Focus on Institutional Attachment

• Only three of the 74 did not persist
• Important factor in persistence (Tinto)
• Anecdotal evidence from students
• Attachment differed significantly across four
  demographic variables, including hometown
• Can we use the SACQ to predict institutional
  attachment?

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Institutional Attachment Variable

• Coded as ordinal variable for analysis
• Frequency analysis suggested three ordered
  classifications
• Low Lowest thru 5.99, f 22
• Average 6.0 thru 7.99, f 22
• High 8.0 thru 9.0, f 30

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Analyses

• 
  
• Examined data for statistically significant
  relationships between student characteristics
  and institutional attachment
• No significant correlations found

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Relationship of Institutional Attachment to SACQ
Subscales

• Three adjustment subscales (all statistically
  significant at p lt .01)
• Academic Adjustment .477
• Social .550
• Personal-Emotional .498

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Relationship of Institutional Attachment to SACQ
Clusters

• Ten cluster scores (all statistically significant
  at p lt .01)
• Motivation .520
• Application .285
• Performance .297
• Academic Environment .476
• General Social Adjustment .392
• Other People .446
• Nostalgia .498
• Social Environment .552
• Psychological .424
• Physical .503

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Predicting Institutional Attachment

• Ordinal logistic regression
• Tests with subscales and clusters yielded no
  significant predictors
• At the item level, four predictors emerged
• Item 8 ()
• I am very involved with social activities in
  college.
• Item 30 ()
• I am satisfied with the extracurricular
  activities available at college.
• Item 41 ()
• Im not doing well enough academically for the
  work I put in.
• Item 65 ()
• I am quite satisfied with my social life at
  college.

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Predicting Institutional Attachment

• ? I am very involved with social activities in
  college.
• (B -.281)
• ? I am satisfied with the extracurricular
  activities available at college. (B .320)
• ? Im doing well enough academically for the
  work I put in. (B .266)
• ? I am quite satisfied with my social life at
  college. (B .682)
• This is a negative variable as stated on the
  SACQ and is reworded for interpretation.

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Classifying Cases

• Percent correctly assigned (n 71) using the
  predicted probability
• Low Attachment 13/21 (62)
• Average Attachment 7/21 (33)
• High Attachment 24/29 (83)
• After eliminating outliers, the model consisted
  of 71 cases

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Classifying Cases (cont.)

• Low
• Low HS GPA ( 2.49)
• Less than full-time (Enrollment)
• Low 1st Semester GPA ( 2.49)

• High
• Female
• 18 19
• Caucasian
• All Other (Hometown)
• Mid/High HS GPA ( 2.5)
• Off campus (Residence)
• Cohort (Class type)
• Full-time (Enrollment)
• Mid/High 1st Semester GPA ( 2.5)

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Implications

• Identify students whose scores on those four
  items suggest lower institutional attachment
• Offer targeted interventions

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Discussion

• Established programs to increase student
  retention existed before university began
  intensive focus
• Students provided with individual advisor
• Student Assistance Centers
• Special Assistance Centers in various departments
• Student Counseling Center

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Discussion (cont.)

• Strategic Planning has begun new programs and
  opportunities for students
• Academic Support
• Advising given priority
• Expanded and updated library facilities
• OASIS
• Student Success Center
• Social Support
• Expanded Student Food Services
• Expanded Student Union
• Outdoor recreation centers
• Renovated and built new residence halls
• Student Recreation/Exercise Center

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Discussion (Needs)

• New programs, etc. will address issues for two
  categories of students with indications of
  adaptation problems
• Low high school GPA
• Low first semester GPA
• Closer advising will support non full-time
  students, but other programs likely not to affect
  as strongly. As distance learning courses
  increase, more students likely to be off campus
  and not full-time.

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Limitations

• Small sample size (N 74)
• Ordinal regression required that the nominal
  dependent variable be split into ordered groups
• Low number of students in each group (22/22/30)
  may have limited classification

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Future Research

• Plan follow up administration with larger group
• Subsequent SACQ administration for longitudinal
  comparison.
• What are the effects of living on campus or of
  cohort classroom environments on institutional
  attachment one year after participation?
• Can institutional attachment be used to
  approximate persistence and degree attainment?
• To what degree do students social networks
  influence institutional attachment?
• A social network analysis may reveal important
  information not apparent in perception surveys.

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Discussion and QuestionsContactmgmeacha_at_vald
osta.edu krotseng_at_valdosta.edu
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Analyses

• Descriptive statistics
• Correlation coefficients (rs)
• Chi-squares (?²)
• (Frequency distributions, magnitude and direction
  of association, and significant associations
  between variables)
• Ordinal logistic regression
• (Which independent variables were predictors of
  ordinal institutional attachment?
• Frequency analysis suggested three ordered
  classifications,
• Low Lowest thru 5.99, f 22
• Average 6.0 thru 7.99, f 22
• High 8.0 thru 9.0, f 30

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Student Characteristics

• Of the nine student characteristics, a slight,
  but statistically insignificant association was
  found on one variable, gender ?² (2, n 74)
  4.18, p .124, Cramer's V .238.
• 
  
• No other slightly statistically significant
  associations were found between other student
  characteristics and ordinal institutional
  attachment.

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Regression Coefficients

• B Wald Sig. OR
• Item 8 -.281 5.122 .024 .755
• Item 30 .320 3.841 .050 1.377
• Item 41 .266 4.166 .041 1.305
• Item 65 .682 11.330 .001 1.978

Predictive (8, 30, 41, 65)