Teacher’s Perspective on e-Assessment: A Case Study from Germany
Bastian K
1,2 a
and Ulrik Schroeder
1 b
Learning Technologies Research Group, RWTH Aachen University, Ahornstraße 55, Aachen, Germany
IT Center, RWTH Aachen University, Seffenter Weg 23, Aachen, Germany
Electronic Examinations, Electronic Assessment, Computer Based Assessment, Bring Your Own Device.
In order to verify common findings in the literature regarding teacher’s (pre)conception of e-Assessment in
general and e-Assessment on students’ devices, we carried out a survey among teachers of two institutes of
higher education in Germany. From the achieved results, it can be concluded that teachers seem to be open-
minded regarding e-Assessment in general. However, major concerns were mentioned regarding the fairness
and security of e-Assessment on students’ devices. These concerns have to be tackled and clearer in order to
successfully establish e-Assessment as an integral part of the examination landscape in higher education.
The attitude of the examiners towards electronic as-
sessment (EA) is rather cautious according to avail-
able literature (Rolim and Isaias, 2018). A main rea-
son for this is the possibility of fraud, which, as Mel-
lar et al. have found, is likely to increase, especially
in bring your own device (BYOD) scenario:
Teachers in all four contexts thought that there
would be an increase in cheating, with the
teachers in the distance education context be-
ing the most concerned. However, teachers
also described a number of ways in which
cheating might be reduced through assess-
ment design, and the opportunities that e-
Assessment offered for increased control of
the assessment process.
(Mellar et al., 2018, p. 19)
The last segment of the quote is in line with
another study by Peytcheva-Forsyth et al., which
comes to the conclusion that the role of technolo-
gies for prevention (rather than occurrence) of cheat-
ing and plagiarism in the assessment is emphasized
(Peytcheva-Forsyth et al., 2018). In general, there
is little information on the examiner’s view on e-
Assessment or digital teaching in general as is pointed
out by Thoring et al.:
The number of papers and studies which fo-
cus on the digitalization in higher education
has increased recently. Most of them focus
on the situation of students [. . . ]. As Cope
and Ward [. . . ] point out, not just the stu-
dents’ perspective is important but also the
perspective of the teaching person. While a
good overview of the status quo of digital-
ization in the US is provided by the annual
ECAR studies by EDUCAUSE quantitative
surveys conducted with approximately 50,000
students [. . . ] and 13,000 lecturers [. . . ] –,
comparable statistics from Europe are miss-
ing. In Germany, the discourse still is driven
mainly by politics, not science, and in conse-
quence publications are often working papers
with a normative character or guidelines based
on experts’ opinions [. . . ].
(Thoring et al., 2018, pp. 295-296)
Hence, a survey was carried out to understand
the examiner’s view on e-Assessment and BYOD and
which factors influence it. This papers describes this
research and is organized as follows in the second sec-
tion, we give a brief overview of the findings already
presented in the literature. In the third section, we
discuss the setup of our survey, followed by a discus-
sion of the achieved results in the fourth section. The
paper closes with a summary and an outlook.
Küppers, B. and Schroeder, U.
Teacher’s Perspective on e-Assessment: A Case Study from Germany.
DOI: 10.5220/0009578105030509
In Proceedings of the 12th International Conference on Computer Supported Education (CSEDU 2020) - Volume 1, pages 503-509
ISBN: 978-989-758-417-6
2020 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
As already pointed out, there is only little related re-
search available. Thoring et. al. come to the conclu-
sion that “E-assessment is of little importance in most
disciplines, but has become a standard at the Depart-
ment of Medicine [of M
unster University] where ex-
ams are usually multiple-choice. Since there is a lot
of criticism of multiple-choice test, e-assessment pro-
cedures are currently refined to be able to test practi-
cal knowledge (e.g. by using a digital microscope).
(Thoring et al., 2018). While this conclusion is drawn
from a qualitative study, it still hints to why there is
so little research available: If the teachers do not rec-
ognize e-Assessment as a valuable tool, they do not
bother to deal with their own perspective on it.
Jamil et. al. conducted a survey to be able to
compare computer-based (CB) and paper-based (PB)
examinations. Their findings draw a rather positive
picture on the teacher’s view on EA. They state that
CB examinations saves time and also facilitate the
students to improve their understanding which ulti-
mately improve their GPA therefore a country-wide
policy should be prepared at university level regard-
ing CB examinations”(Jamil et al., 2012). They found
that all of the personal attributes they took into account
do influence the view on e-Assessment in a certain
way. However, the field of expertise (“Department”),
the qualification and the experience with technology
(“Computer Training Certificate”) seem to have the
biggest influence. This is in line with the findings
by Imtiaz and Maarop who state that [t]he lectur-
ers have a positive intention towards e-assessment use
and would use it in the future (Imtiaz and Maarop,
On a different note, Kuikka et. al. come to the
conclusion that Learning systems are not necessar-
ily created based on teachers’ needs but based on the
creativity of developers. An approach where systems
are developed starting from pedagogical and teach-
ing perspectives - how to teach new skills- should
be promoted. This eases teachers’ entry into using
the systems, and creates systems with better usabil-
ity (Kuikka et al., 2014). Due to their investigation,
they come to the conclusion that Timesaving is cru-
cial for teachers. Features such as automatic evalua-
tion and sharing of exercises help teachers save time.
In order to utilise this fully, teachers can no longer
work by keeping their questions private but instead co-
operation between teachers is necessary. Moreover, in
order to get teachers to use e-exam more widely,it is vi-
tal to provide support and to reserve enough time for
them for the introduction of e-examination. (Kuikka
et al., 2014). This is a first hint at things that teachers
consider important.
We constructed a survey to answer our research
Q: Which factors influence the teacher’s perspec-
tive on e-Assessment?
We anticipated that the perspective on e-Assessment
is influence by the following attributes:
Gender [G]
Age [A]
Technology Affinity [TA]
Field of Expertise (e.g. STEM) [FE]
Teaching Experience [TE]
Institution (University vs. University of Applied
Sciences) [I]
These factors were adapted from our study on the
students’ perspective on e-Assessment (K
uppers and
Schroeder, 2019). Since we expected that the results
would also be influenced by the general affinity of the
teachers for technology, we needed to be able to dis-
tinguish between teachers with an affinity for tech-
nology and those without. To measure the technol-
ogy affinity, the TA-EG questionnaire by Karrer et
al. (Karrer et al., 2009) was used. The items of the
TA-EG questionnaire have been rearranged to elimi-
nate effects that might be caused by the clustered an-
swers of the original questionnaire. Furthermore, we
wanted to conduct the survey at several IHEs and for
different study programmes, in contrast to the exist-
ing surveys. This resulted in the, originally German,
survey which is available in the appendix. The survey
was carried out amongst teachers at RWTH Aachen
University and FH Aachen University of Applied Sci-
ences. Due to the wide range of teachers at two insti-
tutes of higher education, no assumptions about the
characteristics of this group can be made. For exam-
ple, there is no information available on how informed
on e-Assessment the teachers were prior to the survey.
In total, 110 teachers responded to the survey with de-
mographics (A, G) as shown in Table 1. About three
quarters of the participating teachers are male, a lit-
tle less than one fifth is female and about five percent
consider themselves none of the former. Regarding
the age distribution, about five percent are younger
than 30, two fifths are between 30 and 50 years old
and the rest is older than 50 years. The teaching areas
CSEDU 2020 - 12th International Conference on Computer Supported Education
Table 1: Demographics of the participating teachers.
Male Female Diverse Σ
< 30 0.9 % 2.73 % 0 % 3.63 %
30–50 26.36 % 11.82 % 1.82 % 40 %
> 50 50 % 4.55 % 1.82 % 56.37 %
Σ 77.26 % 19.1 % 3.64 % 100 %
Figure 1: Distribution of the most important FE.
of the participants span a variety of fields, as Figure
1 shows. However, the majority of the participants
teaches a STEM topic (68.17 %) and has been teach-
ing for over 20 semesters (66.39 %), as shown in Ta-
ble 2.
The TA-EG questionnaire covers a suitable set of
features for performing a cluster analysis on. Figures
2 and 3 depict comparisons between the two clusters
that have been revealed by the cluster analysis us-
ing a k-medoids algorithm (Kaufmann, 1987; Jin and
Han, 2011). Figure 2 shows a comparison between
the minimum and maximum values of both clusters.
Figure 3 shows a comparison of the median of both
Figure 2: TA-EG: Clustering 1.
Additionally, the data set was split into subsets to
determine the influence of gender, age, field of ex-
pertise, teaching experience and institution. These
Figure 3: TA-EG: Clustering 2.
subsets were then analyzed for significant differences
with a χ
Test for r × c Tables (Sheskin, 2003, pp.
493-572). The resulting p-values for the Likert-scaled
items can be found in Table 3.
Given these p-values, conclusions on the influ-
ence of gender, age, technology affinity, field of ex-
pertise, teaching experience and institution can be
drawn to a certain extent. As it turns out, gender and
age have a statistically significant influence The data
indicate that male teachers are more convinced that
a BYOD approach can be beneficial for assessment
than other groups. The age of the examiners influ-
ences their view on question E3. The data suggests
that with increasing age, the preconceptions regard-
ing e-Assessment rise as well. For question E3, the
distribution of the age leads to the conclusion that ex-
aminers of ages above 50 do not see e-Assessment
as a suitable replacement for paper-based examina-
tions, whereas younger teachers have a rather posi-
tive view on e-Assessment replacing paper-based ex-
aminations. As already mentioned, the cluster anal-
ysis revealed two clusters that were derived using a
k-medoids clustering algorithm (Kaufmann, 1987; Jin
and Han, 2011). These clusters represent one group
that clearly has high affinity to technology (Cluster
0) and another, more reserved group (Cluster 1). For
these clusters, statistically significant differences be-
tween the clusters were found for question E1. The
participants in Cluster 0 have a more positive atti-
tude towards e-Assessment than the participants in
Cluster 1. The field of expertise has a significant
influence on question E3. Teachers from the fields
of medicine and social Sciences see e-Assessment as
a suitable replacement for paper-based examinations.
Teachers from other fields (humanities, engineering,
sciences) are more reluctant regarding e-Assessment
Teacher’s Perspective on e-Assessment: A Case Study from Germany
Table 2: TE (in semesters) and FE of the participating teachers.
1 5 S. 6 10 S. 11 20 S. > 20 S. [NA] Σ
Engineering 4.55 % 7.23 % 4.55 % 19.1 % 0.91 % 36.34 %
Medicine 0.91 % 0 % 0.91 % 10 % 0 % 11.82 %
Sciences 0 % 0.91 % 7.27 % 23.65 % 0 % 31.83 %
Social Sciences 0 % 0.91 % 4.55 % 4.55 % 0 % 10.01 %
Other 0 % 0 % 0 % 2.73 % 0 % 2.73 %
Humanities 0 % 0 % 0 % 6.36 % 0 % 6.36 %
[NA] 0 % 0 % 0.91 % 0 % 0 % 0.91 %
Σ 5.46 % 9.05 % 18.19 % 66.39 % 0.91 % 100 %
Table 3: p for the χ
E1 0.98 0.17 0.002 [< α
] 0.11 0.49 0.73
E2 0.32 0.52 0.23 0.42 0.84 0.66
E3 0.17 0.014 [< α
] 0.69 0.024 [< α
] 0.44 0.59
B1 0.005 [< α
] 0.15 0.06 0.14 0.51 0.16
C1 0.75 0.22 0.19 0.28 0.72 0.73
C2 0.59 0.33 0.46 0.38 0.63 0.21
replacing paper-based examinations. The reason for
this might well be the present examination policies in
these fields. For example, as [m]ultiple-choice ques-
tions [. . . ] are still used in high stakes exams world-
wide to assess the knowledge of medical students
(Freiwald et al., 2014, p. 1), it is easy to see how
teachers in medicine using this mode of examinations
perceive it as suitably replaceable by EA. The exam-
iners generally agree that e-Assessment is a good sup-
plement to paper-based examinations, while their es-
timate on the opportunities of cheating does not show
a clear tendency. However, there seems to be a con-
sensus that it is easier to cheat in e-Assessment than
in a paper-based examinations.
Perceived Advantages and Disadvantages of e-
Assessment. From the teachers’s perspective, the
main advantage of e-Assessment is faster correction
(91.8%), while aspects like more realistic examina-
tions (15.5%) and more diverse examination tasks
(30%) are not as relevant. It turned out to be use-
ful to cluster and analyze the free text comments to
get a clearer picture of the examiners’ opinion on EA.
The examiners submitted 71 comments in total, in-
cluding 25 comments regarding the advantages and
46 comments concerning the disadvantages. The re-
sults of clustering the comments appear in Figures 4
and 5. The clusters of the advantages are intercon-
nected, i.e. they affect each other. For example, bet-
ter readability of exam answers leads to simpler cor-
rection. The same holds for the clusters of the dis-
advantages, where for example inappropriate assign-
ments can lead to stress. It is important to note that
the number of clusters that were created for the dis-
advantages exceeds the number of clusters found for
Exam Management
Learning - &
Figure 4: EA: Free Text Comments about Advantages.
Stress /
Technical Problems /
Assignment / Exams
Figure 5: EA: Free Text Comments about Disadvantages.
the advantages. This could be caused by the positive-
negative asymmetry (Pietri et al., 2013; Baumeister
et al., 2001; Mittal et al., 1998), yet this can not be
safely concluded from the data.
CSEDU 2020 - 12th International Conference on Computer Supported Education
Compulsory Device
Figure 6: BYOD: Free Text Comments about Disadvan-
Figure 7: BYOD: Shares of Clusters of Disadvantages.
Perceived Advantages and Disadvantages of
BYOD. According to the data collected, teachers
have a fairly clear view of e-Assessment in a BYOD
scenario: they do not support it. In total, only eleven
comments on the benefits of BYOD were made in
the survey. However, four of these comments stated
things like no benefits (no benefits) or no benefits
(none), leaving only seven positive comments. In
contrast, a total of 36 comments were made on the
disadvantages of BYOD. The resulting clustering and
the proportions of each cluster for the disadvantages
are shown in the figures 6 and 7.
The data collected lead to several aspects that the
examiners consider to be critical. The examiners
see several positive aspects of EA, such as better
exam management, including student administration
and statistics, and innovative tasks, possibly includ-
ing multimedia. On the other hand, examiners are
concerned about certain tasks or even entire exams
that are not suitable for an electronic environment,
or about problems with organizational matters. Over-
all, the positive and negative aspects of e-Assessment
balance each other out, but when it comes to e-
Assessment in a BYOD setting, examiners clearly re-
ject this idea. Almost no positive aspects were men-
tioned by the examiners, and most negative aspects
concern the possibility of fraud. It is therefore ex-
tremely important to address these issues in the con-
cept of a framework to convince the examiners that
e-Assessment can succeed in a BYOD setting without
opening the doors to fraud. From the data collected,
the following list of important aspects to be consid-
ered was derived:
1. An e-Assessment software has to . . .
(a) . . . offer a way to carry out management com-
fortably (register students, create assignments,
correct, archive, ...).
(b) . . . offer a software interface to implement and
adapt types of assignments to the examiners’
2. Measures have to be taken to prevent . . .
(a) . . . unfair advantages for particular students.
(b) . . . cheating during the EA.
(c) . . . manipulation of the students’ answers.
(d) . . . data loss during the exam, e.g. due to a sys-
tem crash.
3. The whole e-Assessment process has to be trans-
parent to the examiners to clear up doubts.
This paper describes a survey on e-Assessment that
was carried out amongst teachers at RWTH Aachen
University and FH Aachen University of Applied Sci-
ences. The analysis of the results revealed that a
teacher’s view on e-Assessment is influenced by per-
sonal attributes such as age or teaching experience.
Generally, it seems that teachers are cautious regard-
ing e-Assessment, because they see a high risk of
cheating, especially if students are allowed to use
their own devices. Nevertheless, the teachers also rec-
ognize advantage of e-Assessment, for example the
possibility of a faster correction. From our point of
view, the most important result of the analysis is the
need for transparency when utilizing e-Assessment.
Only by implementing a transparent process for e-
Assessment, it will be possible to convince the teach-
ers to accept e-Assessment as an integral part of the
examination landscape in higher education.
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The survey is shown in Figure 8. Particular options
for the tagged items are:
1. < 30 Years; 30–50 Years; > 50 Years
2. Humanities
Archaeology, Ethics, History, Cultural Studies, Lit-
erature Studies, Philosophy, Theology, Linguistics,
Other Humanities
Civil Engineering, Biotechnology, Electrical Engi-
neering, Information Technology, Mechanical Engi-
neering, Medical Engineering, Environmental Engi-
neering, Process Engineering, Materials Engineer-
ing, Other Engineering Science
Medical Sciences
Health Sciences, Human Medicine, Pharmaceutics,
Veterinary Medicine, Dental Medicine, Other Medi-
cal Science
Natural Sciences
Biology, Chemistry, Geoscience, Computer Sci-
ences, Mathematics, Physics, Other Natural Science
Social Sciences
Comparative Education, Human Geography, Com-
munication Studies, Media Studies, Political Sci-
ences, Psychology, Laws, Sociology, Economics,
Other Social Science
3. Diverse, Female, Male
4. 1 5 Semesters; 6 10 Semesters; 10 20
Semesters; > 20 Semesters;
5. Faster Correction, More Realistic Examinations,
More Diverse Examination Tasks, Other (free
6. Security, Usability, Fairness, Uncertain Legal Sit-
uation, Other (free text)
7. Familiar Device, Location-independent Examina-
tions, Cost Reduction for the IHE, Other (free
8. Security, Differences Between Devices, Other
(free text)
CSEDU 2020 - 12th International Conference on Computer Supported Education
Figure 8: Survey (translated to English).
Teacher’s Perspective on e-Assessment: A Case Study from Germany