Effects of Mid-term Student Evaluations of Teaching as Measured
by End-of-Term Evaluations
An Emperical Study of Course Evaluations
Line H. Clemmensen
, Tamara Sliusarenko
, Birgitte Lund Christiansen
and Bjarne Kjær Ersbøll
Department of Applied Mathematics and Computer Science, Technical University of Denmark, Richard Petersens Plads,
Lyngby, Denmark
LearningLab DTU, Technical University of Denmark, Lyngby, Denmark
Keywords: End-of-Term Evaluations, Midterm Evaluations, Student Evaluation of Teaching.
Abstract: Universities have varying policies on how and when to perform student evaluations of courses and teachers.
More empirical evidence of the consequences of such policies on quality enhancement of teaching and
learning is needed. A study (35 courses at the Technical University of Denmark) was performed to illustrate
the effects caused by different handling of mid-term course evaluations on student’s satisfaction as
measured by end-of-term evaluations. Midterm and end-of-term course evaluations were carried out in all
courses. Half of the courses were allowed access to the midterm results. The evaluations generally showed
positive improvements over the semester for courses with access, and negative improvements for those
without access. Improvements related to: Student learning, student satisfaction, teaching activities, and
communication showed statistically significant average differences of 0.1-0.2 points between the two
groups. These differences are relatively large compared to the standard deviation of the scores when student
effect is removed (approximately 0.7). We conclude that university policies on course evaluations seem to
have an impact on the development of the teaching and learning quality as perceived by the students and
discuss the findings.
For decades, educational researchers and university
teachers have discussed the usefulness of, as well as
the best practice for student evaluations of teaching
(SET). To a large extent discussions have focused on
summative purposes like the use of SETs for
personnel decisions as recruitment and promotion
(Oliver and Sautter 2005; McKeachie, 1997; Yao
and Grady, 2005). The focus in the present study is
the formative aspect, i.e. the use of SETs to improve
the quality of teaching and learning.
Much effort has been put into investigating if
SETs give valid measurements of teaching
effectiveness with students’ learning outcome as the
generally accepted – though complex to measure
core factor (see metastudies of Wachtel, 1998, and
Clayson, 2009). Though SETs can be questioned to
be the best method for measuring teaching
effectiveness (Yao and Grady, 2005), there is a
general agreement that it is the most practical and to
some extent valid measure of teaching effectiveness
(Wachtel, 1998). Additionally, SETs provide
important evidence that can be used for formative
purposes (Richardson, 2005).
Studies of the long-term effect of SETs tend to
lead to the discouraging conclusion that no general
improvement takes place over a period of 3-4 years
or more (Kember et.al., 2002; Marsh and Hocevar,
1991). However, it is generally found that when the
feedback from SETs is supported by other steps,
such as consultations with colleagues or staff
developers, or by a strategic and systematic
approach to quality development at university level,
improvements can be found according to the SET
results (Penny and Coe, 2004; Edström, 2008).
Some attention has also been directed to the
timing of the evaluations – midterm, end-of-term,
before or after the exam (Wachtel, 1998). There is
some evidence that evaluation results depend on
whether they were gathered during the course term
or after course completion (Clayson, 2009;
Richardson, 2005).
Keeping the formative aim in mind, it is of
H. Clemmensen L., Sliusarenko T., Lund Christiansen B. and Kjær Ersbøll B..
Effects of Mid-term Student Evaluations of Teaching as Measured by End-of-Term Evaluations - An Emperical Study of Course Evaluations.
DOI: 10.5220/0004353503030310
In Proceedings of the 5th International Conference on Computer Supported Education (CSEDU-2013), pages 303-310
ISBN: 978-989-8565-53-2
2013 SCITEPRESS (Science and Technology Publications, Lda.)
interest whether midterm evaluations can lead to
improvement within the semester to meet the needs
of the students in a specific class context (Cook-
Sather, 2009). In a meta-analysis of a number of
studies comparing midterm and end-of-term SET
results, Cohen (1980) concluded that on average the
mid-term evaluations had made a modest but
significant contribution to the improvement of
teaching. His analysis confirms findings from other
studies that the positive effect is related to
augmentations of the feedback from students –
typically consultations with experts in teaching and
learning (Richardson, 2005; Penny and Coe, 2004).
In Denmark as in other Nordic countries, the
general use of course evaluations has a shorter
history. SETs have primarily been introduced for
formative purposes as well as an instrument for the
institution to monitor and react on student
satisfaction in general and on specific issues (e.g.
teachers’ English proficiency). As an effect of a
requirement from 2003, all Danish universities make
the outcome of course evaluations public (Andersen
et al., 2009). Thus, key results of the existing SET
processes are also used to provide information to
students prior to course selections.
At the Technical University of Denmark, average
ratings of answers to closed questions related to the
course in general are published on the university’s
web site. Ratings of questions related to individual
teachers and answers to open questions are not
published. The outcome is subject to review in the
department study board that may initiate follow-up
As an extensive amount of time and effort is
spent on the evaluation processes described, it is of
vital interest to examine whether the processes could
be improved to generate more quality enhancement.
Therefore, the present study provides a basis to
consider whether mid-term course evaluations can
be used as a supplement to (or partial substitution of)
end-of-term evaluations to create an immediate
effect on quality of teaching and learning in the
ongoing course.
In the study, the student evaluations are treated
as a source of information on the teaching and
learning process, as perceived by the students, which
can be used as a basis for improvements. An
experimental setup is designed to address the
question: What is the effect of mid-term course
evaluations on student’s satisfaction with the course
as measured by end-of-term evaluations?
The study addresses how general university
policies can influence the quality of courses by
deciding when to perform student evaluations.
Therefore, the course teachers were not obliged to
take specific actions based on the midterm
The paper is organized as follows. The
experimental design is explained in Section 1.
Section 2 gives the methods of analysis, and Section
3 the results. Section 4 discusses the findings, and
we conclude in Section 5.
Since 2001 standard student evaluations at the
Technical University of Denmark are performed
using an online questionnaire posted on
“CampusNet” (the university intra-net) as an end-of-
term evaluation in the last week of the semester
(before the exams and the grades are given). The
semesters last thirteen weeks. On one form the
student is asked questions related to the course in
general (Form A) and on another form questions
related to the individual teacher (Form B). The
questions can be seen in Table 1. The students rate
the questions on a 5 point Likert scale (Likert, 1932)
from 5 to 1, where 5 corresponds to the student
“strongly agreeing” with the statement and 1
corresponds to the student “strongly disagreeing”
with the statement. For questions A.1.6 and A.1.7, a
5 corresponds to “too high” and 1 to “too low”. In a
sense for these two questions a 3 corresponds to
satisfactory and anything else (higher or lower)
corresponds to less satisfactory. Therefore the two
variables corresponding to A.1.6 and A.1.7 were
transformed, namely: 5-abs(2x-6). Then a value of 5
means “satisfactory” and anything less means “less
satisfactory”. Furthermore, the evaluations contain
three open standard questions “What went well –
and why?”, “What did not go so well – and why?”,
and “What changes would you suggest for the next
time the course is offered?” Response rates are
typically not quite satisfactory (a weighted average
of 50%). However, they correspond to the typical
response rates for standard course evaluations. The
results are anonymous when presented to teachers
while they in this study were linked to encrypted
keys in order to connect a student’s ratings from
midterm to end-of-term.
A study was conducted during the fall semester
of 2010 and included 35 courses. An extra midterm
evaluation was setup for all courses in the 6th week
of the semester. The midterm evaluations were
identical to the end-of-term evaluations. The end-of-
term evaluations were conducted as usual in the 13th
week of the semester. The criteria for choosing
Table 1: The evaluation questions.
Id no. Question
Short version of
question (for
I think I am learning a lot in
this course
Learning a lot
I think the teaching method
encourages my active
TM activates
I think the teaching material is
I think that throughout the
course, the teacher has clearly
communicated to me where I
stand academically
I think the teacher creates
good continuity between the
different teaching activities
TAs continuity
5 points is equivalent to 9
hours per week. I think my
performance during the course
Work load
I think the course description's
prerequisites are
In general, I think this is a
good course
I think that the teacher gives
me a good grasp of the
academic content of the
Good grasp
I think the teacher is good at
communicating the subject
I think the teacher motivates
us to actively follow the class
I think that I generally
understand what I am to do in
our practical assignments/lab
work/project work
I think the teacher is good at
helping me understand the
academic content
I think the teacher gives me
useful feedback on my work
I think the teacher's
communication skills in
English are good
courses were that:
1. The expected number of students for the course
should be more than 50
2. There should be only one main teacher in the
3. The course should not be subject to other
teaching and learning interventions (which
often imply additional evaluations)
The courses were randomly split into two groups:
one half where the teacher had access to the results
of the midterm evaluations (both ratings and
qualitative answers to open questions) and another
half where that was not the case (the control group).
The courses were split such that equal proportions of
courses within each Department were assigned to the
two groups. The distribution of responses in the two
groups is given in Table 2. Furthermore the number
of students responding at the midterm and final
evaluations and the number of students who replied
both evaluations are listed. For each question the
number of observations can vary slightly caused by
students who neglected to respond to one or more
questions in a questionnaire.
The majority of the courses were introductory (at
Bachelor level), but also a few Master’s courses
were included. The courses were taken from six
different Departments: Chemistry, Mechanics,
Electronics, Mathematics, Physics, and Informatics.
Table 2: The two groups in the experiment.
Access to
Number of
No. of
Percentage o
Yes 17 687
No 18 602
No further instructions were made to the teachers
on how to utilize the evaluations in their teachings.
It has been disputed whether, and to what extent,
SET ratings are influenced by extraneous factors
(Marsh, 1987; Cohen, 1981). In the present study it
is taken into consideration that student evaluations
may be biased, e.g. by different individual reactions
to the level of grading or varying prior subject
interest (Wachtel, 1998; Richardson, 2005), or as a
result of systematic factors related to the course such
as class size or elective vs. compulsory (McKeachie,
1997; Wachtel, 1998; Alamoni, 1999). In order to
test the differences between midterm and final
evaluations as well as differences between
with/without access to midterm evaluations while
removing factors like students’ expected grade
(Wachtel, 1998; Clayson, 2009) or high/low rated
courses, we performed two kinds of tests.
a) Paired t-tests where a student from midterm to
the final evaluation is a paired observation and we
test the null-hypothesis that there is no difference
between midterm and final evaluations (Johnson et
al., 2011).
b) t-tests for the null-hypothesis that there is no
difference between having access to the midterm
evaluations and not (Johnson et al., 2011).
These tests were based on differences in evaluations
for the same student in the same course from
midterm to end-of-term evaluation in order to
remove course, teacher, and individual factors. In
Table the number of students who answered both
midterm and final evaluations are referred to as the
number of matches.
Pairwise t-tests were conducted for the null-
hypothesis that the mean of the midterm evaluations
were equal to the mean of the end-of-term
evaluations for each question related to either the
course or the course teacher. The results are
summarized in Table 3 and Table 4 for the courses
where the teacher had access to the midterm
evaluation results and those who had not,
Table 3: Summary of pairwise t-tests between midterm
and end-of-term course and teacher evaluations. For
courses without access to the evaluations.
Mean difference
< 0.05
(Learning a lot)
-0.056 (0.96) 0.17 No
(TM activates)
-0.053 (0.98) 0.21 No
A.1.3 (Material) -0.065 (1.0) 0.13 No
A.1.4 (Feedback) 0.081 (1.1) 0.085 No
(TAs continuity)
-0.075 (1.0) 0.095 No
A.1.6 (Work load) -0.040 (0.15) 0.53 No
-0.049 (1.2) 0.32 No
A.1.8 (General) -0.12 (0.97) 0.0038 Yes
B.1.1 (Good grasp) -0.044 (0.86) 0.23 No
-0.066 (0.84) 0.068 No
B.1.3 (Motivate
-0.035 (0.90) 0.36 No
B.2.1 (Instructions) -0.048 (0.99) 0.33 No
-0.012 (0.85) 0.78 No
B.2.3 (Feedback) -0.015 (0.97) 0.76 No
B.3.1 (English) -0.046 (0.79) 0.54 No
Table 4: Summary of pairwise t-tests between midterm
and end-of-term course and teacher evaluations. For
courses with access to the evaluations.
Mean difference
< 0.05
A.1.1 (Learning a
0.089 (0.77) 0.0040 Yes
A.1.2 (TM
0.048 (0.93) 0.20 No
A.1.3 (Material) 0.019 (0.88) 0.59 No
A.1.4 (Feedback) 0.18 (1.0) <0.0001 Yes
A.1.5 (TAs
0.039 (0.92) 0.29 No
A.1.6 (Work load) 0.058 (1.4) 0.30 No
0.053 (0.93) 0.16 No
A.1.8 (General) 0.039 (0.85) 0.26 No
B.1.1 (Good grasp) 0.020 (0.78) 0.50 No
0.039 (0.74) 0.15 No
B.1.3 (Motivate
0.016 (0.89) 0.64 No
B.2.1 (Instructions) -0.038 (0.94) 0.36 No
0 (0.89) 1.0 No
B.2.3 (Feedback) 0.059 (1.0) 0.20 No
B.3.1 (English) -0.071 (0.73) 0.13 No
For the courses without access to the midterm
evaluations the general trend is that the evaluations
are better at midterm than at end-of-term. This is
seen as the mean value of the midterm evaluations
subtracted from the final evaluations are negative for
most questions. In contradiction, the courses with
access to the midterm evaluations have a trend
towards better evaluations at the end-of-term, i.e. the
means of the differences are positive. The question
related to the general satisfaction of the course
(A.1.8) got significantly lower evaluations at end-of-
term when the teacher did not have access to the
midterm evaluations (p = 0.0038). The question
related to the academic feedback throughout the
course (A.1.4) got significantly higher scores at the
end-of-term when the teacher had access to the
midterm evaluations (p < 0.0001). The question
related to whether the student felt he/she learned a
lot (A.1.1) got significantly higher evaluations at
end-of-term when the teacher had access to the
midterm evaluations (p = 0.0040). The increase or
decrease in student evaluations were of average
values in the range [-0.12,0.18]), and significant
changes were of average absolute values [0.089;
0.18], (A.1.1 with access being the lowest and A.1.4
with access being the highest). The size of the
(dis)improvement should be compared with the
standard deviations of the differences divided by the
squareroot of two (approximately 0.7), which is the
standard deviation of the scores where the student
effect has been removed.
For the last analysis the midterm evaluations
were subtracted from the end-of-term evaluations for
each student and each course. The two groups
with/without access to midterm evaluations were
then compared based on these differences using a
two sample t-test for differences between means; the
results are summarized in Table 5.
Table 5: Summary of t-tests of the null-hypothesis that
there is no difference in the evaluation differences from
midterm to end-of-term between courses with and without
access to the midterm evaluations. A folded F-test was
used to test if the variances of the two groups were equal.
If so, a pooled t-test was used, otherwise the
Satterthwaite’s test was used to check for equal means.
With-without access Mean
p-value Significant
(p-value <
A.1.1 (Learning a lot) 0.15 0.0045 Yes
A.1.2 (TM activates) 0.10 0.071 No
A.1.3 (Material) 0.084 0.13 No
A.1.4 (Feedback) 0.099 0.11 No
A.1.5 (TAs continuity) 0.11 0.05 Yes
A.1.6 (Work load) 0.098 0.24 No
A.1.7 (Prerequisites) -0.0037 0.95 No
A.1.8 (General) 0.16 0.0032 Yes
B.1.1 (Good grasp) 0.064 0.18 No
B.1.2 (Communication) 0.11 0.021 Yes
B.1.3 (Motivate activity) 0.051 0.32 No
B.2.1 (Instructions) 0.0095 0.88 No
B.2.2 (Understanding) 0.012 0.84 No
B.2.3 (Feedback) 0.073 0.27 No
B.3.1 (English skills) -0.025 0.77 No
The general trend is that the courses where the
teacher had access to the midterm evaluation results
get a larger improvement in evaluations at the end-
of-term than those where the teachers did not have
that access (the differences are positive). The only
exceptions to this trend are found in two questions
regarding factors that cannot be changed during the
course (course description of prerequisites (A.1.7)
and teacher’s English skills (B.3.1)). However, these
are not significant. The questions related to the
student statements about learning a lot, the
continuity of the teaching activities, the general
satisfaction with the course, and the teacher’s ability
to communicate the subject (A.1.1, A.1.5, A.1.8, and
B.1.2) had significantly higher increases from
midterm to end-of-term when the teachers had
access to the midterm evaluations, compared to the
courses where the teachers did not have access. Note
that the significant differences in means for the
questions are of sizes in the range [0.11, 0.16].
According to subsequent interviews (made by
phone), the percentage of the courses with access to
the midterm evaluations where the teachers say they
shared midterm evaluations with students was 53%,
and the percentage of courses where the teachers say
they made changes according to the midterm
evaluations was 53%. The percentage of the courses
with access to the midterm evaluations where the
teachers say they either shared the evaluations, made
changes in the course, or both was 71%.
The results illustrate that students are generally more
satisfied with their courses and teachers at end-of-
term when midterm evaluations are performed
during the course and teachers are informed about
the results of the evaluations.
According to the evaluations, students perceive
that courses improve when midterm evaluations are
performed and the evaluations and the teachers are
informed. Though the teachers were not instructed
how to react on the results from the mid-term
evaluation, it turned out that almost ¾ of the
teachers followed up on the evaluations by sharing
the results with their students and/or making changes
in the course for the remaining part of the semester.
The fact that ¼ of the teachers acted like the group
who were not allowed access to the midterm results
could cause the effects to be even smaller than if all
teachers acted. The effects are relatively large when
compared to the standard deviation of the scores
where the student effect has been removed:
approximately 0.7.
We expect that the actions upon the midterm
evaluations of the ¾ in many cases have included
elaborated student feedback to the teacher, a
dialogue about possible improvements, and various
interventions in the ongoing teaching and learning
activities, which can explain the increased
satisfaction as expressed in the end-of-term
evaluation. For this to happen, the teachers should
both be motivated and able to make relevant
adjustments (Yao and Grady, 2005). The ability to
make relevant adjustments will usually increase as a
result of participation in teacher training programs
that will also encourage teachers to involve both
students and peers in teaching development
activities. However, less than half of the teachers
responsible for the courses in this study have
participated in formal University teacher training
programs. The proportion of the teachers who have
participated in training programs is the same for
both groups of courses (35 % and 38 %,
respectively). Therefore, the observed effect of the
mid-term evaluation does not seem to be directly
dependent of whether the teacher has participated in
formal teacher training.
For future work it would be of interest to directly
measure the placebo effect of conducting midterm
evaluations as opposed to also measuring the effect
of real improvement.
From the student comments in the evaluation
forms we noticed that there in some courses was a
development pointed out. As an example one student
writes at midterm that: “A has a bad attitude;
Talking down to you when assisting in group work”.
At end-of-term the student writes: “In the beginning
of the course A’s attitude was bad – but here in the
end I can’t put a finger on it”. Such a development
was found in courses with access to the midterm
evaluations and where the instructor said he/she
made changes according to the evaluations. This
illustrates the usefulness of midterm evaluations
when addressing students evaluations within a
In most of the courses the major points of praise
and criticism made by the students are reflected both
at midterm and end-of-term. Examples are: That the
course book is poor, the teaching assistants don’t
speak Danish, the lecturer is good etc. Thus such
points which are easily changed from semester to
semester rather than within a semester are raised
both from midterm and end-of-term evaluations.
Various studies show that mid-term evaluations
may change the attitudes of students towards the
teaching and learning process, and their
communication with the teacher, especially if the
students are involved actively in the process e.g. as
consultants for the teachers (Cook-Sather, 2009,
Fisher and Miller, 2008; Aultman, 2006; Keutzer,
1993) – and it may even affect the students’
subsequent study approaches and achievements
(Greenwald and Gilmore, 1997, Richardson 2005).
Such effects may also contribute to the improved
end-of-term rating in the cases where teachers with
access to the mid-term evaluation results share them
with their students.
There is evidence that SETs in general do not
lead to improved teaching as perceived by the
students (Marsh, 1987) and one specific study
quoted by Wachtel (1998) of faculty reactions to
mandatory SETs indicate that only a minority of the
teachers report making changes based on the
evaluation results.
However, the present study indicates that mid-
term evaluations (as opposed to end-of-term
evaluations) may provide a valuable basis for
adjustments of the teaching and learning in the
course being evaluated.
As the course teachers were not obliged to take
specific actions based on the mid-term evaluations,
the study gives a good illustration of how the
university policies can influence the courses by
deciding when to perform student evaluations.
It seems to be preferable to conduct midterm
evaluations if one is concerned with an improvement
of the courses over a semester (as measured by
student evaluations).
One may argue that both a midterm and an end-
of-term evaluation should be conducted. However, it
is a general experience that response rates decrease
when students are asked to fill in questionnaires
more frequently. If this is a concern, it could - based
on the results of this study - be suggested to use a
midterm evaluation to facilitate improved courses
and student satisfaction.
On the other hand, it is widely appreciated that
the assessment of students’ learning outcome should
be aligned with the intended learning outcomes and
teaching activities (TLAs) of a course in order to
obtain constructive alignment (Biggs and Tang,
2007). Therefore, to obtain student feedback on the
entire teaching and learning process, including the
alignment of assessment with objectives and TLAs,
an end-of-term student evaluation should be
performed after the final exams where all assessment
tasks have been conducted (Edström, 2008). In this
case, teachers can make interventions according to
the feedback only for next semester’s course. This
approach does not facilitate an improvement in
courses according to the specific students taking the
course a given semester.
Based on the results of the present study it could
be suggested to introduce a general midterm
evaluation as a standard questionnaire that focuses
on the formative aspect, i.e. with a limited number
of questions concerning issues related to the
teaching and learning process that can be changed
during the semester. It should conform to the
existing practice of end-of-term evaluations by
including open questions and making it possible for
the teacher to add questions – e.g. inviting the
students to note questions about the course content
that can immediately be addressed in the teaching.
This can serve as a catalyst for improved
communication between students and teacher
(Aultman, 2006).
As a consequence, the standard end-of-term
questionnaire could be reduced and focus on general
questions (like A.1.4, A.1.8. and B.1.1, see Table 1)
and matters that are left out in the mid-term
evaluation (e.g. teachers proficiency in English,
B.3.1). Besides, it could be considered to encourage
the teachers to use different kinds of consultations
by faculty developers and/or peers to interpret the
student feedback (ratings and comments) and
discuss relevant measures to take (Penny and Coe,
The present study considered improvements over
one semester as measured by end-of-term student
evaluations as opposed to long-term improvements
as well as studies including interviews with
instructors and students. These limitations were
discussed in more detail in the introduction of this
An empirical study conducting midterm as well as
end-of-term student evaluations in 35 courses at the
Technical University of Denmark was carried out in
the fall of 2010. In half of the courses the teachers
were allowed access to the midterm evaluations, and
the other half (the control group) was not. The
general trend observed was that courses where
teachers had access to the midterm evaluations got
improved evaluations at end-of-term compared to
the midterm evaluations, whereas the control group
decreased in ratings. In particular, questions related
to the student feeling that he/she learned a lot, a
general satisfaction with the course, a good
continuity of the teaching activities, and the teacher
being good at communicating the subject show
statistically significant differences in changes of
evaluations from midterm to end-of-semester
between the two groups. The changes are of a size
0.1-0.2 which is relatively large compared to the
standard deviation of the scores where the student
effect is removed of approximately 0.7.
If university leaders are to choose university- or
department-wise evaluation strategies, it is worth
considering midterm evaluations to facilitate
improvements of ongoing courses as measured by
student ratings.
The authors would like to thank all the teachers and
students who participated in the study, the Dean of
Undergraduate Studies and Student Affairs Martin
Vigild for supporting the project, and LearningLab
DTU for assistance in carrying out the study.
Furthermore, the authors thank five anonymous
reviewers for their valuable comments.
L. M. Alamoni, 1999. Student Rating Myths Versus
Research Facts from 1924 to 1998: Journal of
Personnel Evaluation in Education, 13(2): 153-166.
Vibeke Normann Andersen, Peter Dahler-Larsen &
Carsten Strømbæk Pedersen, 2009. Quality assurance
and evaluation in Denmark, Journal of Education
Policy, 24(2): 135-147.
L. P. Aultman, 2006. An Unexpected Benefit of Formative
Student Evaluations: College Teaching, 54(3): 251.
J. Biggs and C. Tang, 2007. Teaching for Quality
Learning at University, McGraw-Hill Education, 3
D. E. Clayson, 2009. Student Evaluations of Teaching:
Are They Related to What Students Learn? A Meta-
Analysis and Review of the Literature: Journal of
Marketing Education, 31(1): 16-30.
P. A. Cohen, 1980. Effectiveness of Student-Rating
Feedback for Improving College Instruction: A Meta-
Analysis of Findings: Research in Higher Education,
13(4): 321-341.
P. A. Cohen, 1981. Student rating of instruction and
student achievement. Review of Educational Research,
51(3): 281–309.
A. Cook-Sather, 2009. From traditional accountability to
shared responsibility: the benefits and challenges of
student consultants gathering midcourse feedback in
college classrooms, Assessment & Evaluation in
Higher Education, 34(2): 231-241.
K. Edström, 2008. Doing course evaluation as if learning
matters most: Higher Education Research &
Development, 27(2): pp. 95–106.
R. Fisher and D. Miller, 2008. Responding to student
expectations: a partnership approach to course
evaluation: Assessment & Evaluation in Higher
Education, 33(2): 191–202.
A. G: Greenwald and G. M. Gillmore, 1997. Grading
leniency is a removable contaminent of student
ratings, The American Psychologist, 52(11): 1209-16.
R. Johnson, J. Freund and I. Miller, 2011. Miller and
Freund’s Probability and Statistics for Engineers,
Pearson Education, 8
D. Kember, D. Y. P. Leung and K.P. Kwan, 2002. Does
the use of student feedback questionnaires improve the
overall quality of teaching? Assessment and
Evaluation in Higher Education, 27: 411–425.
C. S. Keutzer, 1993. Midterm evaluation of teaching
provides helpful feedback to instructors, Teaching of
psychology, 20(4): 238-240.
R. Likert, 1932. A Technique for the Measurement of
Attitudes, Archives of Psychology 140: 1–55.
H. W. Marsh, 1987. Students’ evaluations of university
teaching: research findings, methodological issues,
and directions for future research: International
Journal of Educational Research, 11: 253–388.
H.W. Marsh and D. Hocevar, 1991. Students’ evaluations
of teaching effectiveness: The stability of mean ratings
of the same teachers over a 13-year period, Teaching
and Teacher Education, 7: 303–314.
H. W. Marsh and L. Roche, 1993. The Use of Students’
Evaluations and an Individually Structured
Intervention to Enhance University Teaching
Effectiveness, American Educational Research
Journal, 30: 217-251.
W. J. McKeachie, 1997. Student ratings: The Validity of
Use, The American Psychologist, Vol. 52(11): 1218-
R. L. Oliver and E. P. Sautter, 2005. Using Course
Management Systems to Enhance the Value of Student
Evaluations of Teaching, Journal of Education for
Business, 80(4): 231-234.
A. R. Penny and R. Coe, 2004. Effectiveness of
consultation on student ratings feedback: A meta-
analysis.: Review of educational Research, 74 (2):
J. T. E. Richardson, 2005. Instruments for obtaining
student feedback: A review of the literature. Asessment
and Evaluation in Higher Education, 30(4): 387–
415.The Technical University of Denmark, web sites
H. Wachtel, 1998. Student Evaluation of College Teaching
Effectiveness: a Brief Overview. Assessment and
Evaluation in Higher Education, 23(2): 191–213.
Y. Yao, Y. and M. Grady, 2005. How Do Faculty Make
Formative Use of Student Evaluation Feedback?: A
Multiple Case Study. Journal of Personnel Evaluation
in Education, 18: 107–126.