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WHO DOESN’T RESPOND AND WHY? AN
ANALYSIS OF NONRESPONSE TO ONLINE
STUDENT EVALUATIONS OF TEACHING
Meredith J.D. Adams & Paul D. Umbach
CONTEXT
• Participation decline while survey requests are
increasing. (Nonresponse increases the risk for
error.)
• Ongoing change from paper to web-based
course evaluations.
• Results from course evaluations are used for
research and decision-making processes about
personnel.
FRAMEWORK
• Survey Theories
– Salience (Dillman et al., 2002; Groves et al., 2004,
2009)
– Survey Fatigue (Groves et al., 2004; Porter &
Whitcomb, 2005)
• Academic Disciplines framework (Holland,
1966; Rosen et al., 1997; Smart et al., 2000)
• Previous survey and course evaluation research
at postsecondary institutions
PURPOSE OF STUDY AND RQs
• Purpose of study is to investigate factors of
participation in course evaluations
• Research questions
– To what extent did course salience increase the
likelihood of response? To what extent did between-
level interactions influence these results?
– To what extent did survey fatigue influence
response?
METHODS OF ANALYSIS
• Study measured likelihood of response
• Hierarchical modeling techniques
• 30 variables
– Students (demographics, housing, number of surveys
students completed)
– Course (if department of course and student’s major
matched; grade earned)
RESULTS
Statistically significant
factors associated with
nonrepsonse:
– Gender (Male)
– Ethnicity (African-American,
Asian)
– Housing (off-
campus/commuters)
– Athletes
– Grades (Ds, Fs,
ungraded
students/courses)
– Age (traditional age)
– Nontransfers
– Class rank
(sophomores & juniors)
– Students with more
than 10 SETs to
complete
48.9%
response rate
(overall)
RESULTS (continued)
• Using Holland’s six major academic types
– Realistic majors were more likely to respond than
social, artistic, conventional, enterprising, and
investigative disciplines.
– Social majors were less likely to respond than all
other students if the course was in the same
department as the student’s major.
• Most variables were no longer statistically
significant when the course was in the same
department as their major.
ASHE 2010 - Course Evaluation Nonresponse
DISCUSSION
• Mostly aligned with previous research and
theories of survey participation*
– Exceptions = Environment of major/course, class
rank
• Introduced new potential influences on
participation
– Campus housing, athletes, transfer status, etc.
* Avery et al., 2006; Cohen, 1981; Clarksberg, et al., 2008; Dey, 1997; Dillman et al., 2002, 2009; Fidelman, 2007; Groves et
al., 2004, 2009; Johnson et al., 2002; Jones, 2009; Kaplowitz et al., 2004; Lepkowski & Couper, 2002; Marsh, 2007; Moore &
Tarnai, 2002; Porter et al., 2004; Porter & Umbach, 2006a; Porter & Whitcomb, 2005; Sax et al., 2003, 2008
DISCUSSION
• Nonresponse Bias
• Salience
– Course Location
– Grades
– Environment of Student’s Major
• Survey Fatigue
LIMITATIONS
• Only one institution
• Only undergraduates
• Limited information about the course, the
faculty, class size, etc.
IMPLICATIONS
• Evaluate the major’s environment/culture
– How to increase salience?
• Encourage students unlikely to respond
• Examine how we utilize course evaluations
FOR MORE INFORMATION
meredith_adams@ncsu.edu
This paper can be found at:
1. https://cedupload.ncsu.edu/dropbox/uploads/Adams%20Um
bach%20Course%20Evaluation%20Nonresponse%20ASHE
%202010.pdf
2. http://bit.ly/9zjMAY
3. http://goo.gl/ByiZo
4. This PowerPoint Presentation is available at
http://www.slideshare.net/meredithNCSU/ashe-2010-course-
eval-nonresponse

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ASHE 2010 - Course Evaluation Nonresponse

  • 1. WHO DOESN’T RESPOND AND WHY? AN ANALYSIS OF NONRESPONSE TO ONLINE STUDENT EVALUATIONS OF TEACHING Meredith J.D. Adams & Paul D. Umbach
  • 2. CONTEXT • Participation decline while survey requests are increasing. (Nonresponse increases the risk for error.) • Ongoing change from paper to web-based course evaluations. • Results from course evaluations are used for research and decision-making processes about personnel.
  • 3. FRAMEWORK • Survey Theories – Salience (Dillman et al., 2002; Groves et al., 2004, 2009) – Survey Fatigue (Groves et al., 2004; Porter & Whitcomb, 2005) • Academic Disciplines framework (Holland, 1966; Rosen et al., 1997; Smart et al., 2000) • Previous survey and course evaluation research at postsecondary institutions
  • 4. PURPOSE OF STUDY AND RQs • Purpose of study is to investigate factors of participation in course evaluations • Research questions – To what extent did course salience increase the likelihood of response? To what extent did between- level interactions influence these results? – To what extent did survey fatigue influence response?
  • 5. METHODS OF ANALYSIS • Study measured likelihood of response • Hierarchical modeling techniques • 30 variables – Students (demographics, housing, number of surveys students completed) – Course (if department of course and student’s major matched; grade earned)
  • 6. RESULTS Statistically significant factors associated with nonrepsonse: – Gender (Male) – Ethnicity (African-American, Asian) – Housing (off- campus/commuters) – Athletes – Grades (Ds, Fs, ungraded students/courses) – Age (traditional age) – Nontransfers – Class rank (sophomores & juniors) – Students with more than 10 SETs to complete
  • 8. RESULTS (continued) • Using Holland’s six major academic types – Realistic majors were more likely to respond than social, artistic, conventional, enterprising, and investigative disciplines. – Social majors were less likely to respond than all other students if the course was in the same department as the student’s major. • Most variables were no longer statistically significant when the course was in the same department as their major.
  • 10. DISCUSSION • Mostly aligned with previous research and theories of survey participation* – Exceptions = Environment of major/course, class rank • Introduced new potential influences on participation – Campus housing, athletes, transfer status, etc. * Avery et al., 2006; Cohen, 1981; Clarksberg, et al., 2008; Dey, 1997; Dillman et al., 2002, 2009; Fidelman, 2007; Groves et al., 2004, 2009; Johnson et al., 2002; Jones, 2009; Kaplowitz et al., 2004; Lepkowski & Couper, 2002; Marsh, 2007; Moore & Tarnai, 2002; Porter et al., 2004; Porter & Umbach, 2006a; Porter & Whitcomb, 2005; Sax et al., 2003, 2008
  • 11. DISCUSSION • Nonresponse Bias • Salience – Course Location – Grades – Environment of Student’s Major • Survey Fatigue
  • 12. LIMITATIONS • Only one institution • Only undergraduates • Limited information about the course, the faculty, class size, etc.
  • 13. IMPLICATIONS • Evaluate the major’s environment/culture – How to increase salience? • Encourage students unlikely to respond • Examine how we utilize course evaluations
  • 14. FOR MORE INFORMATION meredith_adams@ncsu.edu This paper can be found at: 1. https://cedupload.ncsu.edu/dropbox/uploads/Adams%20Um bach%20Course%20Evaluation%20Nonresponse%20ASHE %202010.pdf 2. http://bit.ly/9zjMAY 3. http://goo.gl/ByiZo 4. This PowerPoint Presentation is available at http://www.slideshare.net/meredithNCSU/ashe-2010-course- eval-nonresponse

Notas do Editor

  1. Realistic Majors =
  2. To what extent did course salience increase the likelihood of response? To what extent did between-level interactions influence these results? To what extent did survey fatigue influence response?
  3. INSTRUMENT: Lab questions then the lab is surveyed too. ADMIN: Cut down on opportunity costs (off-campus students, athletes) ENVIRONMENT: Smart et al., 2000 (academic disciplines book)