PowerPoint Presentation - Student Evaluations: What do they mean?

Report
Mark Troy – Data and Research Services
– [email protected]
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How low are they?
How concerned should faculty and
administration be about low rates?
Can response rates be improved?
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PICA average
◦ 50%-60%
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Paper average
◦ 70%-80%

100% response rate
◦ Less than 10% of courses, whether evaluated with
paper forms or PICA achieve 100% responses
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Extremely low response rate
◦ Less than 10% of courses, whether evaluated with
paper forms or PICA have response rates lower than
10%
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PICA Mean Response Rate, Spring 2012
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Mean response rates for departments with 10 or more courses evaluated in PICA
TAMU departments are in red. (Total courses = 2597)
TAMUG departments are in green. (Total courses = 420)
The mean response rate for all courses evaluated in PICA, Spring 2012 = 50% (red line)
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70
60
50
40
30
20
10
MARB
MARE
MARS
GACD
MARA
MASE
MART
BUSH
CLTM
BIOL
WFSC
EPSY
TLAC
CHEN
ALEC
PETE
EAHR
AERO
BMEN
ENGL
NUEN
ATMO
CSCE
COMM
CLEN
CLLA
HLKN
CLGE
ANTH
CLVM
BAEN
OCNG
GEOG
GEPL
ELIN
MEEN
ECEN
SCSC
RPTS
0
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Non-response bias
◦ The bias that arises when students who do not
respond have different course experiences than
those who do respond.
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Random effects
◦ If the response rate is low, the mean is susceptible
to the influence of extreme scores, either high or
low.
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Only those who really like you and those who
really hate you will do the evaluations
You will get responses only from the students
who like you.
Only the students who hate you will bother to
respond.
The students who really hate you will choose
not to play the game at all.
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If only those who like you and those who hate
you respond, the means might not change
(assuming equal numbers of both groups),
but the shape of the distribution and the
variance of the scores would change.
If only those who like you respond, the mean
should increase and the distribution and
variance would change.
If only those who hate you respond, the mean
should decrease and the distribution and
variance would change.
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No significant
mean
differences
were observed.
An upward
trend is visible
in the chart,
but that began
before the
switch from
paper to PICA.
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Paper
PICA
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No mean
differences
were observed.
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Mean
3
Mean + 1SD
Mean - 1SD
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Biology Department
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0
07a
07c
08a
08c
09a
09c
The standard
deviations did
not change
significantly
after the switch
to PICA.
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70
Overall, this was a good course.
60
50
Percent of
students
responding
40
PICA (43%)
Paper (81%)
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20
10
0
A
B
Strongly agree Agree
C
D
E
Undecided Disagree Strongly disagree
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60.00%
50.00%
40.00%
Fall 11 (85%)
30.00%
Spring 12 (35%)
20.00%
Fall 2011- paper
Spring 2012 - PICA
10.00%
0.00%
5
4
3
2
1
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A comparison of courses taught by the same
instructor in consecutive semesters showed that
half of the ratings went up after the switch to PICA
and half went down.
Overall, there was no significant difference in
means of paper evaluations compared to PICA
evaluations.
Significant mean differences were observed in 3
out of 70 courses (which would be expected by
chance alone.)
The three significant differences were observed in
courses with less than 30% response rate in PICA.
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The correlation between response rate and
class size for paper administration = -.161
(Fall 2009)
The correlation between response rate and
class size for PICA administration = -.056
(Fall 2009)
Conclusion: Although the relationship
between class size and response rate is weak,
there is a greater tendency for response rates
to decrease as class size increases with paper
administration than with PICA.
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Most differences between means can be
attributed to chance variation and not to the
method of evaluation.
Response rate does not appear to have an
impact on means.
EXCEPTION: Extreme scores, whether high or
low, exert greater influence on the mean
when the number of responses is low.
◦ Equally true for 100% response rate from a class of
ten as for 10% response rate from a class of 100.
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1. Non-response bias is a systematic effect that, if
present, would appear as a difference in mean
ratings, or as an increase in the variance of the
ratings, and as a change in the distributions of the
scores. Such differences are not seen. (Although that
does not mean the non-response bias doesn’t exist.)
2. Random effects. In any evaluation, some ratings
will be higher than others and some will be lower.
The more responses, the less influence the extremes,
either high or low, will have on the mean. A low
response rate allows an unusually high or low rating
to pull the average in its direction, therefore higher
response rates are better than lower response rates.
These random effects are often seen with low
response rates.
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YES
The average response rate per department
tends to increase over time as faculty and
students attain familiarity with the system.
There are some strategies faculty can use to
increase response rate.
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Motivation
◦ Students need to be motivated to do online
evaluations
◦ Students do not need to be motivated to do paper
evaluations
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Attendance
◦ Students need to be in class to do paper evaluations
◦ Students do not need to be in class to do online
evaluations
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Research on student evaluations in higher
education shows:
◦ Students’ most desired outcome from evaluations is
improvement in teaching.
◦ Students’ second desired outcome is improvement in
course content.
◦ Students’ motivation to submit evaluations is severely
impacted by their expectation that the faculty and
administration pay attention to the evaluations.
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The bottom line is that students submit evaluations
if they believe their opinions will be valued and
considered.
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Survey conducted of a random sample of students in classes that used
PICA, Fall 2008.
95 students submitted an appraisal online (Response), 94 students did
not submit an appraisal although requested to do so (Non-response).
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Receiving an invitation from MARS to do the
evaluation has no impact on the response rate.
By a factor of 3 to 1, students are more likely to
submit an evaluation:
◦ If the request comes from their instructor.
◦ If their instructor discusses the importance of the
evaluation.
◦ If their instructor tells how the evaluations have been used
or will be used to improve the course.
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Incentives are less effective than discussing the
importance and the use of the evaluations.
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A survey of students who had not submitted
evaluations online in PICA, though requested
to do so found the following reasons for not
submitting.
◦ Forgot — 48%
◦ Missed the deadline — 26%
◦ No other reason was given by more than 10%
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The bottom line is that frequent reminders
are important.
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Texas A&M faculty have an opportunity to conduct mid-term
evaluations (Actually fifth-week evaluations) in PICA
The purpose of the mid-terms is to provide formative
information for improving the course at a point that changes
are possible.
An examination of response rates at the end of the term
shows that courses for which there was a mid-term
evaluation have on average a 10% higher response rate than
other courses on end-of-term evaluations.
The likely explanation for the effect on response rate is that
faculty who do mid-terms can demonstrate to students that
their opinions are considered.
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Incentives appear to be not as effective a
motivator as the intrinsic motivation to help
improve teaching and the course.
A token incentive, however, can reinforce
intrinsic motivation by communicating the
importance of the evaluation.
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The Faculty Senate (Resolution FS 27.122) opposes
granting academic credit for evaluations because
such credit is not related to any learning outcomes,
so it could have the effect that two students who
learned the same amount would receive different
grades.
Some faculty offer a token incentive to the entire
class if some threshold of response rate is reached,
thereby communicating the importance of the
evaluation, but not disadvantaging a student who
chooses not to do an evaluation.
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Use mid-term
evaluations to help
students see how
to give feedback
and what feedback
is useful. Show
students that their
feedback is acted
upon in a positive
way.
Discuss the
importance of the
evaluation and the
use of the results
in improving the
course and your
teaching.
Remind students
frequently.
Reminders are
most effective
when they come
from the faculty.
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