University SET data, with faculty and courses characteristics
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Project Citation:
journal, Under blind review in refereed . University SET data, with faculty and courses characteristics. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2021-09-12. https://doi.org/10.3886/E149801V1
Project Description
Summary:
View help for Summary
Appendix 1. The SET questionnaire was used for this paper. Evaluation survey of the teaching staff of [university name] Please, complete the following evaluation form, which aims to assess the lecturer’s performance. Only one answer should be indicated for each question. The answers are coded in the following way: 5- I strongly agree; 4- I agree; 3- Neutral; 2- I don’t agree; 1- I strongly don’t agree.
This paper explores a unique dataset of all the SET ratings provided by
students of one university in Poland at the end of the winter semester of the
2020/2021 academic year. The SET questionnaire used by this university is
presented in Appendix 1. The dataset is unique for several reasons. It covers all
SET surveys filled by students in all fields and levels of study offered by the
university. In the period analysed, the university was entirely in the online
regime amid the Covid-19 pandemic. While the expected learning outcomes formally
have not been changed, the online mode of study could have affected the grading
policy and could have implications for some of the studied SET biases. This
Covid-19 effect is captured by econometric models and discussed in the paper.
The average SET scores
were matched with the characteristics of the teacher for degree, seniority,
gender, and SET scores in the past six semesters; the course characteristics for
time of day, day of the week, course type, course breadth, class duration, and
class size; the attributes of the SET survey responses as the percentage of
students providing SET feedback; and the grades of the course for the mean,
standard deviation, and percentage failed. Data on course grades are also
available for the previous six semesters. This rich dataset allows many of the
biases reported in the literature to be tested for and new hypotheses to be formulated,
as presented in the introduction section.
The unit of observation
or the single row in the data set is identified by three parameters: teacher
unique id (j), course unique id (k) and the question number in
the SET questionnaire (n ϵ {1, 2, 3, 4, 5, 6, 7, 8, 9} ). It means that
for each pair (j,k), we have nine rows, one for each SET survey
question, or sometimes less when students did not answer one of the SET
questions at all. For example, the dependent variable SET_score_avg(j,k,n) for the triplet (j=Calculus, k=John Smith,
n=2) is calculated as the average of all Likert-scale answers to question
nr 2 in the SET survey distributed to all students that took the Calculus
course taught by John Smith. The data set has 8,015 such observations or rows.
The full list of
variables or columns in the data set included in the analysis is presented in the attached filesection. Their description refers to the triplet (teacher id = j, course id
= k, question number = n). When the last value of the triplet (n) is
dropped, it means that the variable takes the same values for all n ϵ {1, 2,
3, 4, 5, 6, 7, 8, 9}.
Two attachments:
- word file with variables description
- Rdata file with the data set (for R language).
Appendix 1.
Appendix 1. The SET questionnaire was used for this paper. Evaluation survey of the teaching staff of [university name] Please, complete the following evaluation form, which aims to assess the lecturer’s performance. Only one answer should be indicated for each question. The answers are coded in the following way: 5- I strongly agree; 4- I agree; 3- Neutral; 2- I don’t agree; 1- I strongly don’t agree.
Questions
1
2
3
4
5
I learnt a lot during the
course.
○
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I think that the knowledge
acquired during the course is very useful.
○
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○
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The professor used
activities to make the class more engaging.
○
○
○
○
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If it was possible, I would
enroll for the course conducted by this lecturer again.
○
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The classes started on time.
○
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The lecturer always used
time efficiently.
○
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The lecturer delivered the
class content in an understandable and efficient way.
○
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The lecturer was available
when we had doubts.
○
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○
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The lecturer treated all
students equally regardless of their race, background and ethnicity.
○
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