The Perceived Learning Behaviors and Assessment Techniques of
First-Year Students in Computer Science: An Empirical Study
Manuela Petrescu
and Tudor Dan Mihoc
Department of Computer Science, Babes¸ Bolyai University, Cluj-Napoca, Romania
Learning, Online, Students, Computer Science, Survey, Evaluation, Stress.
The objective of our study is to ascertain the present learning behaviors, driving forces, and assessment tech-
niques as perceived by first-year students, and to examine them through the lens of the most recent devel-
opments (pandemic, shift to remote instruction, return to in-person instruction). Educators and educational
institutions can create a more accommodating learning environment that takes into account the varied needs
and preferences of students by recognizing and implementing these findings, which will ultimately improve
the quality of education as a whole. Students believe that in-person instruction is the most effective way to
learn, with exercise-based learning, group instruction, and pair programming. Our research indicates that, for
evaluation methods, there is a preference for practical and written examinations. Our findings also underscore
the importance of incorporating real-world scenarios, encouraging interactive learning approaches, and creat-
ing engaging educational environments.
Education in the present day faces a number of novel
challenges. These problems originate either from
global unfortunate events, such as the pandemic, or
from mandated educational activities, such as dis-
tance e-learning, as a result of these events (Gutierrez-
Aguilar et al., 2023). These difficulties have had a
substantial impact on the quality of education and stu-
dents’ ability to learn. As a result, students may strug-
gle to keep track of their schoolwork and fall behind;
their academic performance may suffer as a result, as
will their motivation. This will eventually jeopardize
their ability to achieve their academic objectives and
realize their full potential. Therefore, it is critical that
teachers provide enough support and resources to help
students overcome these obstacles and stay on track
with their studies.
The COVID-19 pandemic forced both teachers
and students to switch from traditional in-person in-
struction to online learning environments (Lemay
et al., 2021).
Although most campuses have faculty members
with training to guarantee the quality of the content,
few have created strategies for this type of interac-
tion with students. Some suggestions to improve stu-
dent participation and engagement in online learn-
ing environments are provided in (Neuwirth et al.,
2021). They proposed a framework that academic de-
partments might use to create policies that cover best
practices and recommendations for post-pandemic
synchronous and asynchronous virtual classrooms.
Any attempt to solve these problems is hampered
by the lack of knowledge about the preferences and
study habits of the students after the quarantine pe-
riod. We attempt to close this knowledge gap in this
study by finding out what students think is the best ap-
proach to carrying out the teaching and learning pro-
Several strategies have been proposed to increase the
efficacy of instruction (Liu et al., 2022; Seikkula-
Leino et al., 2010), with many focusing on com-
puter science teaching methods (Salas, 2017; George,
2020). In addition, some offer resources to computer
science instructors (Hazzan et al., 2020), and suggest
technical professional development and collaboration
tactics for teachers (Wang et al., 2021).
Several research papers have been published on
the topic of online student motivation (Baquerizo
Petrescu, M. and Mihoc, T.
The Perceived Learning Behaviors and Assessment Techniques of First-Year Students in Computer Science: An Empirical Study.
DOI: 10.5220/0012674000003693
Paper published under CC license (CC BY-NC-ND 4.0)
In Proceedings of the 16th International Conference on Computer Supported Education (CSEDU 2024) - Volume 2, pages 405-412
ISBN: 978-989-758-697-2; ISSN: 2184-5026
Proceedings Copyright © 2024 by SCITEPRESS Science and Technology Publications, Lda.
et al., 2020), online course assessments (Vegliante
et al., 2018), and focus of elements such as teacher
collaboration strategies and technical professional de-
velopment (Wang et al., 2021).
Online classes have the benefit of allowing stu-
dents to learn at their own pace using text or video
resources, which can facilitate learning. Before lec-
tures, students can access the materials, which allows
them to ask more questions and complete more diffi-
cult assignments. (Sobral, 2020).
The student dropout rate is a problem educators
face on a regular basis. The percentage of students en-
rolled who do not graduate with a degree or dropout
varied significantly in European countries, from a low
14,4% in the UK, to approximately 29% in Germany,
according to (Heublein et al., 2017). The highest
value, according to EU reports (Centre for Higher Ed-
ucation Policy Studies, 2015) is 60,6% in France. On-
line or hybrid learning environments (de Sousa et al.,
2022) were also considered as a response to dropout
rates in traditional classroom settings. There are other
factors that affect the dropout rate, including aca-
demic achievement, starting age, and parental educa-
tional background (Araque et al., 2009).
Fear of failure can also be a factor that slows
academic development. (Martino, 1993) offers some
goal-setting strategies that can help young students
avoid becoming failure-accepting students.
There is a lot of literature related to mechanisms
that can be employed by people when faced with chal-
lenging circumstances that carry a high risk of failure
and possible harm to their self-esteem (Norem and
Cantor, 1986). In the literature, as guideline for ed-
ucators, the main approach to this matter is mostly
by creating a supportive and nurturing environment,
provide educational treatment, and use autonomy-
supportive teaching styles.
Scope: We aim to determine the current learning
habits, motivations, and evaluation methods in the
freshmen students opinion and analyze them from the
perspective of the changes in the last period (COVID,
transition to online teaching, transition back to face-
to-face teaching).
The COVID-19 pandemic’s restrictions on this
generation of students also had a direct impact on
their initial years of high school study: social isola-
tion, a sudden switch to online instruction for a year,
and after to a return to in-person instruction from
We were interested in students’ perspective on a
stage in life when, after graduating high school and
enrolling at the university , they had little time to ad-
just to the new academic environment.
We aim with this up-to-date data to fill in the gaps
in our understanding of the students.
The research questions are:
- What drives students’ primary motivation to ac-
quire knowledge?
- Which evaluation method is considered by stu-
dents to be the most equitable, and why?
- What do students think are the most effective
ways to learn?
The authors formulated these research questions
after defining the study objective.
Setup. In order to explore the answers to our research
questions, we designed a survey addressed to young
students. We sent the survey link to students in the
eighth week of the first semester, which were ran-
domly allocated to one of the authors of this research
in the Computer Science Architecture.
We outline the purpose of collecting their input
and the intended use of the gathered data in an effort
to boost engagement. A brief speech about our re-
search and expressing our appreciation for their time
in responding served as the sole source of motivation.
We also noted the anonymity of the survey.
Participants. A group of 43 students enrolled in the
first year of computer science in the English line of
study participated in the survey. The initial set of
participants consisted of 67 students, of whom 43 de-
cided to participate. The selection of the 67 students
that were required to participate was aleatory; the stu-
dents were randomly selected from the students as-
signed to classes with one of the authors of this study.
There was no discrimination between the students;
all received the survey link. Participation was op-
tional and we did not use any reward mechanism for
participation, except for the motivational speech men-
tioned above. We obtained 64.17% responses from
the initial set of participants.
Study Design. After analyzing and deciding on the
research questions, we designed the survey. The pro-
cess of elaborating the questions was made up of a
series of steps: each author proposed some questions
that formed the first draft and we discussed, analyzed,
and modified the questions until we reached consen-
We used open questions because they provide
more information about the students’ thoughts and
can better reflect their perceptions of reality. The
questions were asked in the student’s native language,
even if the participants were enrolled in the English
line to obtain more descriptive and complex answers.
CSEDU 2024 - 16th International Conference on Computer Supported Education
We asked positive and negative questions to avoid
bias, and we asked the students to motivate their re-
sponses rather than specify a reason or a learning
method. We provide the learning methods examples
only in the last question as we did not want to influ-
ence previous responses. The list of survey questions
is shown in Table 1.
3.1 Methodology
In the eighth week of the second semester, we con-
ducted an online survey using both accountable and
open questions. Accountable questions facilitate
working with and interpreting some facts, and open
questions offer a further level of insight. To eval-
uate and interpret responses to open questions, we
used quantitative techniques, particularly question-
naire surveys, according to the guidelines established
by the empirical community (Ralph, Paul (ed.), 2021).
For the interpretation of the text, we apply the defini-
tion of theme analysis found in (Braun et al., 2019).
These techniques have already been applied in other
studies related to computer science (Petrescu and Mo-
togna, 2023; Motogna et al., 2021; Petrescu et al.,
The following steps constitute the text analysis
(1) In order to identify the keys in the text, two
researchers performed an independent analysis.
(2) Using techniques that include generalization,
removal, and reassignment of significant items with
low prevalence to similar themes or classes, we clas-
sified important items based on shared themes or
(3) In the last phase, all authors review the pro-
cess with careful consideration in order to assess the
degree of trust in the methodology. Examining and
debating numerous topics, explanations and corrobo-
rating data related to the categorization procedure was
part of this process.
We calculated the frequency of the keywords used
in the answers. Some student submissions featured
only one or two ideas, while others provided up to
four arguments to support their choice of research top-
ics. Thus, an answer could include additional things
or significant words. We used the calculated preva-
lence of several key items, classified them, and com-
pared them with the total number of responses re-
ceived. As a result, the total percentages will exceed
Data Collection. Several steps were taken in the pro-
cess of developing survey questions. Initially, we de-
veloped the study objectives and determined the scope
of the article. Each author supplied a list of survey
questions based on these. We studied and debated
the proposed collection of questions before deciding
which questions would be selected for the survey.
The questions were translated from English into
the students’ native language, allowing them to re-
spond in their preferred language. We used this
strategy to promote student participation. We em-
ployed automatic language translation technologies to
translate them into English before having the authors
double-check the translation.
To increase the number of responses, we left the
survey open for two weeks. We distributed the survey
link to the student group so we could gather responses
anonymously, allowing students to respond when and
how they chose.
The collected answers were pre-processed prior to
analysis, eliminating some special characters, empty
lines, and spaces.
3.2 Q1 - What Drives Students’
Primary Motivation to Acquire
Motivation is a key component in the learning pro-
cess, it can be positively or negatively influenced, de-
pending on a sum of factors. We wanted to explore
which are these factors for first-year students in com-
puter science, as in this period, the are still deeply in-
volved in the learning process but are mature enough
to appreciate and take into consideration a large broad
range of factors. We asked them to describe what fac-
tors motivate them to learn a course and what factors
discourage them.
What Are the Factors that Motivate Students to
Learn the Content of the Course?
We grouped the factors mentioned by students in two
major classes, one set of factors are related to eco-
nomical perspectives and the second set of factors re-
lated to personal reasons:
Economic: Will help me in the future, Useful, To
pass (the exam), Important
Personal: Interesting, I like (the topics), I like the
A set of factors such as ”To learn how different com-
puter programs work” have a small prevalence, so we
decided to place them in the class ”Other”. The per-
centages of motivational factors, grouped by classes,
mentioned by the students are presented in Figure 1.
Economic factors seem to have a higher preva-
lence compared to personal / emotional factors. The
responses of many students reflected this aspect: ”If
the things I learn in the course are up-to-date and will
help me in the future job”,”If the course is useful to
The Perceived Learning Behaviors and Assessment Techniques of First-Year Students in Computer Science: An Empirical Study
Table 1: Survey Questions.
Q1 What are the factors that motivate you to learn?
Q2 What are the factors that discourage learning a topic or a course?
Q3 What do you consider to be the worst form of evaluation and why?
Q4 What do you consider to be the best form of evaluation and why?
Q5 Which are in your opinion the best teaching methods?
Q6 Which teaching methods worked best for you? What do you use?
(online courses, face-to-face teaching, pair programming)
Figure 1: Factors that motivate students to learn.
me, I study it, if not, I don’t”, ”The main reason is
represented by the existence of an exam that forces
me to study”.
Personal and emotional factors are related to each
individual’s passions: ”I am curious and I like to
learn new things”, ”Because I like it”, ”If it is a topic
that interests me”. The personal relationship with the
teacher seems to count less at this level, only 5.88%
of the students mentioning it, compared to 35.29% of
students mentioning ”Interesting” as a learning fac-
What Are the Factors That Discourage Learning a
Topic or a Course?
The main discouraging factors are the mirror reflec-
tion of the most motivating factors: Not Interesting
and Not useful ”It is hard, the teacher is demand-
ing, exams are hard, I don’t find it interesting, it
wouldn’t help me in the future”, ”It is useless in my
development”, ” It does not captivates my attention”,
”the uselessness of course in life”. Not liking the
course and the topics or the teacher are discouraging
factors: ”Disinterest in the topic”, ”If I am not
interested”, ”Because I do not like the teacher or the
A large group mentioned too much effort to be a
discouraging factor, others referred to stress, lack of
time, theoretical and unuseful learning materials: ”If
there is too much to learn and I do not have the time
necessary to retain everything”, ”Exam stress”, ”If it
involves memorization and not thinking”.
Other answers reflect a learning mindset and a
positive attitude: ”There are no many reasons, it is
always worth trying to learn something”. The per-
centages for the factors that discourage learning are
shown in Figure 2.
Figure 2: Factors that discourage students to learn.
In Conclusion. Based on the answers to the ques-
tions, we can establish that the most important rea-
sons are the how useful is the learned information and
how interesting are the topics in the course. Personal
relationship with the teacher seem to be less impor-
tant, however, other factors such as too much effort or
lack of time can negatively impact learning.
3.3 Q2 - Which Evaluation Method Is
Considered by Students to Be the
Most Equitable and Why?
To find out, we decided to ask the students which
forms of evaluation are in their opinion the best and
which are the worst and why. Students prefer to
be evaluated on written exams, practical projects, or
practical examinations, or to have projects during the
course. The percentages are shown in Figure 3.
As we did not want to create bias, we asked about
the worst form of evaluation. If the oral evaluation
scored low in the best forms of evaluation, it scored
high in the worst form of evaluation. The surprise test
was the second worst form of evaluation mentioned,
as can be seen in Figure 4. Written examination was
mentioned third as a bad form of evaluation, but only
for programming courses: ”Tests written on paper,
especially for topics that are run in computer pro-
grams”, ”Reproducing, in writing, the theory or pro-
CSEDU 2024 - 16th International Conference on Computer Supported Education
Figure 3: Best forms of evaluations methods in student’s
gram sequence step-by-step, especially when a def-
inition is formulated strangely and/or I do not have
the possibility to test, in real time, what my program
Figure 4: Worst forms of evaluations methods in student’s
The students based their opinion on different rea-
sons, the most important being stressful situations,
not enough time and learning memorizing / Unuse-
ful information.
Students do not like stressful situations that ap-
pear during exams, especially in oral examinations;
the stress is induced by the situation and the poten-
tial lack of time ”Personally, I do not like oral listen-
ing”, ”The oral assessment because it is very stress-
ful and you do not have much time to think”, Oral
test because the student does not have enough time
to think about the answers”, ”Practical assessment
in a short time, because it does not assess logic but
speed”. A large group mentions the theoretical ex-
amination, some students just mention it without ad-
ditional explanations: ”Theory exams”, while others
provide a more detailed reasoning: evaluation of theo-
retical knowledge, because not all information is use-
ful in practice, or used, other claim that testing the
assimilation of theoretical notions it is shifting the fo-
cus from the actual learning of the subject to some
information that will be forgotten in a short time. The
percentages can be visualized in Figure 5.
Figure 5: Reasons for worst forms of evaluations methods
in student’s opinions.
In conclusion, students prefer practical examina-
tion and written examination, but not when it involves
writing programs on a piece of paper. Oral examina-
tion is considered by far the worst method of evalu-
ation due to induced stress and lack of time. Also,
a large group does not like theoretical exams that re-
quire information that is not useful in the long run.
3.4 Q3 - What Do Students Think Are
the Most Effective Ways to Learn?
This set of participants has special characteristics:
students spend two years in high school in the COVID
19 pandemic, where most of the learning activities
were online. Their exposure to online learning and
courses has given them an extended experience over
previous generations, so a high percentage, around
30% of students mentioned it as an effective learning
method. However, face-to-face was still the preferred
learning method, scoring more than 50% in student
options. Programming in pairs, group learning, indi-
vidual work, or practical problems also scored high in
student’s options as can be seen in Figure 6. As a re-
mark, some students mentioned more than one learn-
ing method: ”Different online tutorials, face-to-face
teaching and consulting the opinions of colleagues”,
so the sum of percentages exceeds 100%.
Figure 6: Most effective learning methods in student’s opin-
The Perceived Learning Behaviors and Assessment Techniques of First-Year Students in Computer Science: An Empirical Study
Some students did not provide reasons for their
learning preferences: ”Different online tutorials,
face-to-face teaching and consulting the opinions of
colleagues”, ”face-to-face teaching, study groups”,
”Online courses and programming (learning) with a
group of friends”. Others provided a detailed reason-
ing for their choice: ”Doing homework alone. Be-
fore doing my homework, I study the subject and then
apply the learned things to the problems. I notice
that the information settles very well in this way, not
only in this course. Another good method of learning
would be to teach a colleague / explain to someone
who does not understand. Learning by exercise is
another method mentioned by students: ”for me the
best way of learning is practice. By doing many exer-
cises, I learn much easier”.
In conclusion, face-to-face learning is in the stu-
dent’s opinions the most effective learning method,
followed by learning using exercises, group learning,
and programming in pairs. So even for a generation
that has extensive experience with online learning,
they still prefer face-to-face learning,
Through the verification and application of commu-
nity standards as described in (Ralph, Paul (ed.),
2021), we attempted to reduce potential risks and ad-
dressed the validity threats mentioned in software en-
gineering research (Ralph, Paul (ed.), 2021). We con-
sidered the following possible threats: construct va-
lidity, internal validity, and external validity.
The target participant set, participant selection,
dropout contingency measures, and author biases
were among the issues we focused on for internal va-
Selection and Participant Set. We selected for
the set of participants students who were enrolled in
classes taught by one of the study’s authors, chosen at
Ethical Concerns. Before all students received the
survey link, we informed them that participation was
anonymous and voluntary. We also presented the
scope of the research and how the collected data will
be used.
Rates of Dropouts. We had few options to increase
participation in the study, as we were restricted by its
voluntary nature. The only influence on the participa-
tion of the students in the study was to ensure that they
understood the purpose of the survey. In addition, in
an attempt to boost participation, we kept the survey
open for two weeks and translated the questions into
the students’ native tongue.
Author Subjectivity. We have taken measures to ad-
dress the possibility of subjectivity in our data pro-
cessing methodology. Following suggested data pro-
cessing procedures, we as authors made sure that our
work was cross-validated by examining each other’s
External Validity. We examine the possibility of ex-
tending and applying the study findings to the IT sec-
tor. The general research topic of the study is related
to industry and the difficulties that various teams face
when developing their human resources. We can con-
clude that the results of the study are useful to the
local IT industry due to the topic.
Validity of the Construction. We examined the sur-
veys’ questions for coherence, relevance, and perti-
nence. We developed the set of questions in three
stages: first, a set of questions was proposed by the
authors. All authors discussed and examined the
questions to increase clarity. Only a subset of the
questions that were most relevant to our study were
chosen to be included in the survey (second step). In
the final step, we verified the questions and decided
which questions were required and which were op-
tional. After these procedures were completed, we
created and distributed the survey to the participants.
Since the data were gathered anonymously, the au-
thors were unaware of the identities of the respon-
Upon examination of the data, we found that the stu-
dents primarily attribute their learning to two things:
the course’s or the topics’ level of interest and utility.
Practical Aspects. There is a definite tendency to
value and adhere to practical and passionate aspects.
Students dislike mechanical learning or theoretical
examinations where they are ”asked to know infor-
mation without use” or where they ”will later forget.
This tendency toward practical aspects is reinforced
through answers to other questions. For example,
their preference for projects or continuous evaluation
are different aspects of the same disposition.
An intriguing feature about the students’ view on
evaluation is the absence of opinions regarding its
fairness; preferences are solely based on stress, pref-
erences, workload, and practicability.
Fear and Stress. Numerous students indicated that
the evaluation results were significantly impacted by
their ability to control their emotions and stress. Stu-
dents believe that oral evaluations are the worst due to
stressful circumstances, time constraints, and teacher
discussion all of which make it difficult for them
CSEDU 2024 - 16th International Conference on Computer Supported Education
to handle. We have to ask ourselves after looking at
these results Are these signs of a more emotional gen-
eration? One more argument would be the fact that
some of them acknowledge, admit, and express that
they”are afraid”. Stress and fear are strong emotions
that can affect performance, attitude toward learning
in general, and school / university specifically. Fail-
ure in a sphere of accomplishment can be a challeng-
ing experience that elicits feelings of guilt and fear,
ranging from mild to severe conditions, such as aty-
chiophobia, which can affect an individual’s behav-
ior and performance (Atkinson, 1957). Fear of being
wrong, of being judged appears as a collateral reason
for written examination: ”because I can make mis-
takes without fear of being judged”.
Given that first-year students in the participant set
had recently completed their high school education,
these findings should raise concerns about the teach-
ing methods and attitudes of high school teachers.
Reluctance to Work. Some students stated that they
would prefer simpler courses that do not require a lot
of work or learning time and effort when asked for
the reasons why they do not learn. Although there are
certain factors that can make learning more difficult,
such as scheduling classes during challenging times
of the day, such as 6 to 8 p.m. or half past seven or
eight a.m., they should not have a significant effect
on learning. More future research can determine how
these factors affect learning. However, stating that the
time spent learning something new is too much could
be a reflection of a recent development: students’ un-
willingness to put in the necessary effort to learn.
Although the outcomes can serve as a guide for
future modifications to instructional strategies, stu-
dent preferences should not be the only factor con-
sidered. Their point of view should be regarded more
as a guide for determining the best means of motivat-
ing and constraining them in order to optimize their
academic performance.
For instance, it’s not always detrimental that a
large portion of students exhibit a fear of failing. Be-
cause they consider learning hard and fear failure, it
does not mean that we should simplify the learning
content. Much better would be to search for methods
to bias the natural tendency for anxious people to set
either extremely low or very high aspirations in favor
of the last, or to reduce the anxiety related to failure.
Our investigation of the students’ primary motivations
to acquire knowledge reveals that the most crucial fac-
tors are the perceived usefulness of the learned infor-
mation and the level of interest in the course topics.
Although personal relationships with teachers were
found to be less influential, external factors, such as
excessive effort or time constraints, can negatively
impact the learning experience. These findings under-
score the importance of aligning educational content
with real-world applications and fostering student en-
gagement to improve motivation.
Students believe that in-person instruction is the
most effective way to learn, with exercise-based
learning, group instruction, and pair programming
coming in second and third.
Regarding the evaluation methods preferred by
students, our research indicates a preference for prac-
tical and written examinations. However, it should be
noted that the inclusion of writing programs on paper
is met with resistance. Oral examinations emerged as
the least favored method, attributed to induced stress
and perceived time constraints. Additionally, a sub-
stantial portion of students expressed dissatisfaction
with theoretical exams that they perceive as provid-
ing information that lacks practical utility in the long
run. These insights highlight the need for educators to
consider various assessment strategies that align with
students’ preferences and alleviate unnecessary stress.
Furthermore, our investigation of effective learn-
ing methods uncovered valuable information. The
emphasis on practical and applicable knowledge is
evident in students’ preferences for hands-on learn-
ing experiences. Our findings underscore the impor-
tance of incorporating real-world scenarios and en-
couraging interactive learning approaches. As edu-
cators and institutions strive to optimize the learning
process, understanding and integrating these prefer-
ences can contribute significantly to creating a more
effective and engaging educational environment.
In summary, our research provides valuable infor-
mation on the complex interplay of factors that in-
fluence students’ motivations, preferences in evalu-
ation methods, and effective learning strategies. By
acknowledging and incorporating these findings, ed-
ucators and educational institutions can foster a more
conducive learning environment that reflects the di-
verse needs and preferences of students, ultimately
enhancing the overall educational experience.
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