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Capturing the Student Perspective: A New Instrument for Measuring Advising Satisfaction
Marilee L. Teasley, Erin M. Buchanan, Ph.D.
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Why is Academic Advising Important?
•Kuh (2008): Quality of advising is a powerful predictor of campus satisfaction
•Metzner (1989): Lower attrition rates for high quality advising▫But some advising is better than none!
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What Should Be Measured?
•Types of advising (Crookston, 1972):▫Prescriptive▫Developmental
•Which is better?
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Measuring Advising: Reliability & Validity•Reliability: Consistency of scores•Validity: How well do you measure what
you are claiming to measure?
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Measuring Advising: Factor Analysis•Exploratory Factor Analysis (EFA)•Confirmatory Factor Analysis (CFA)
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Exploratory Factor Analysis
Wonderful
TERRIBLEHappiness
Joyful
Exciting
FRUSTRATING
TRAGEDYANGRY
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Confirmatory Factor Analysis
Wonderful
TERRIBLEHappiness
Joyful
Exciting
FRUSTRATING
TRAGEDY
ANGRY
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Existing Measures
•Very few standardized assessments exist•Validity and Reliability?•Qualitative versus Quantitative methods
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Original Research Question
•How do our students feel about their past and present academic advising experiences?
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Additional Research Question
•Can we extend the existing advising assessment research by creating a new scale with statistical reliability and validity?
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Our Questionnaire: Version 1• Investigated:
▫Advisor Traits (patience, trustworthiness)▫Prescriptive Functions (course selection,
graduation requirements)▫Developmental Functions (campus/community
involvement, overall student development)
•Seven-point Likert scale▫1 = strongly disagree, 4 = neutral, 7 =
strongly agree
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Experiment 1 Experiment 2 Experiment 3
Age 20.8 (4.8) 19.76 (4.44) 19.31 (2.45)
Gender
Female 62.5% 75.7% 78.1%
Male 37.5% 24.3% 21.9%
Classification
Freshman 47.4% 69.6% 63.9%
Sophomore 28.3% 16.6% 22.4%
Junior 13.2% 9.4% 8.8%
Senior 11.2% 4.4% 4.8%
Transfer Students
Transfer 23.8% 19.3% 19.7%
Non-Transfer 76.2% 80.7% 80.3%
Ethnicity
Caucasian 82.9% 80.1% 83.0%
Other 17.1% 19.9% 17.0%
Major
Decided 85.5% 80.7% 87.1%
Undecided 14.5% 19.3% 12.9%
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Our Study: Experiment 1
•155 total students, 152 complete questionnaires
•Demographics + 24 advising questions
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How did we do? (Version 1)
•Exploratory Factor Analysis (EFA):▫One factor model, poor overall fit
•Compound questions & clarity issues▫“My advisor encourages me to speak freely
and listens to what I have to say.”
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Our Study: Take 2!
•181 total students, 177 complete questionnaires, 157 remaining after outlier analysis
•Original demographics questions + 30 revised advising questions
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How Did We Do? (Version 2)
•Exploratory Factor Analysis (EFA) showed that one or two factors would be appropriate
•Best fit: two factors, 24 questions
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The Two Factor Model
•Advising Functions▫“Advising appointments are worth my time”▫“I find academic advising appointments to
be a positive experience.”•Outreach Functions
▫“I learn how I can contribute to the surrounding community during my advising appointments.”
▫“My advisor lets me know about the importance of our public affairs mission.”
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One More Time… (Experiment 3)•184 total students, 167 remaining after
outlier analysis•59 returning students from Experiment 2
for test-retest reliability purposes ▫24 final advising questions, no
demographics•New participants:
▫Demographics + 24 final advising questions
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How Did We Do? (Version 3)
•Confirmatory Factor Analysis▫Good overall fit
•High test-retest reliability
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What About Our Original Question?•Both factors had high averages (above
“neutral”)•Advising factor > Outreach factor
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What’s Next?
•NACADA Journal, 33(2)▫Late Fall/Early Winter 2013
•The goal: impact advising assessment!
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Thank You!
•For questions about our project or usage of our scale, please contact either one of us:
Marilee Teasley ([email protected])
or Dr. Erin Buchanan
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Questions?