This study investigates the pre-existing knowledge of first-year students in Computer Programming courses, analysing the impact of secondary education backgrounds on their learning experiences. Over the course of five academic years, students at the University of Maribor were assessed through surveys and practical tests to determine their pre-knowledge of algorithmic thinking and problem-solving skills. The research highlights the influence of learning opportunities and the subsequent rise in students with prior programming experience. The findings present differences in self-reported programming knowledge across generations, emphasising the need for adaptive teaching strategies to bridge the knowledge gap. The results show the importance of early programming education and suggest a trend towards digital literacy in secondary education.
Students who have previous experience in programming are usually more self-assured in their
knowledge, which often misleads their actual capabilities and thus sometimes perform worse than
students who take their time to properly study the required constructs and concepts [
During the COVID pandemic, much of the educational process has moved online. Theoretical and
practical classes in Computer Programming became more focused on providing solutions that would
assist students in their learning process while also incorporating different online tools for providing
feedback [
In this work, we present a study where we analysed answers from students with different secondary education level backgrounds through the years on their different levels of pre-knowledge of Computer Programming, algorithmic thinking, problem-solving, and their self-perceived knowledge of the subject. The analysis was performed with active students at the start of the course and after they had attended the course's theoretical lessons and solved practical laboratory assignments. The experiment was conducted with students who took the course Fundamentals of
The structure of the paper is as follows. The description of the research methods is provided in Section 2 and the main contribution of the paper is in Section 3, where the results are presented.
The study evaluated the pre-knowledge of the students in the Fundamentals of Web Programming course using a test. Further details are presented in the following sub-sections.
At the start of the semester, the students attending the course Fundamentals of Web Programming were allowed to fill out a survey that would assess their skills and knowledge of Computer Programming in any programming language. This study was done in 5 consecutive years (from 2019/2020 to 2023/2024), and we will compare the results of generations. The study was done among students of Media Communications (MC) at the Faculty of Electrical Engineering and Computer Science, University of Maribor. In the first three years of research, the course was also an elective course in the study program Information and Communication Technologies (IaCT). As presented in Table 1, there were a total of 425 participants over five consecutive years.
Measurement items were tested with a 7-point Likert scale and some yes/no questions. The measurement items and criteria are presented in Table 2. The survey consists of 25 questions, where 13 of which are used to acquire demographic information, information on previous education, and self-evaluation of the programming knowledge, which were only asked during the pre-test of the survey. The following 12 questions consist of theoretical and practical examples that test the preknowledge of programming in JavaScript.
In Figure 1, the 100% loaded bar chart presents what students have reported on the topic if they have ever attended any programming course before entering the University by year of enrollment. As can be seen in the figure, the COVID-19 generation had a bit of a setback, whereas the number of students who received some prior programming knowledge before entering University has been rising again for the last two years. As programming is an important skill in today’s digital world, we can presume that this number will be even higher in the next years.
2023/2024 yes no
(before enrolling on the faculty)?
previous question “YES”. (Multiple choice) 3 How long have you been learning programming? • Answer only if you answered “YES” to question 1 4 Where did you learn programming? Answer • only if you answered “YES” to question 1 (multiple • choice) • •
JavaScript. 7 I know how to use one of the available programming languages. 8 I know how to use variables.
10 I know how to use conditional statements. 11 I know how to use loops. 12 I know how to use functions. 12 I know how to use objects. 13 I know how to use DOM.
Y / N
C C++ C#
• • • • • • • • • • • • • • • • • • • • • •
six months or less
school Online 1 – strongly disagree
In Figure 2, the programming languages that the students used when taking programming courses are presented. As can be seen from the figure, the most commonly learned programming languages are C++ and JavaScript. However, we can also notice increasing interest in C# whereas the interest in C++ and Java interests are decreasing in the last years.
90 80 70 60 50 40 30 20 10 0
C
C++
C#
Java
JavaScript
Pascal 2019/2020 2020/2021 2021/2022 2022/2023
Python 2023/2024
PHP
In Figure 3, the information on where the students learned computer programming before coming to the University is presented. As presented on the graph, most commonly students learned programming in a course in secondary school. Not many students learned programming in primary school or at extracurricular activities in schools.
Finally, we conducted an ANOVA test to compare five different generations in their self-reported knowledge of programming. We have calculated a mean for each student for questions 5-13 (7-point Likert scale). In Table 4, we have presented the mean and standard deviation by study year for these questions together. The Levene statistics significance is greater than .05 (.065), therefore we can assume equal variances across all groups. The ANOVA test showed that the knowledge of programming is significantly different among different generations (p-value <.001, F-score 4.723, df = (4, 418)).
Independently
In a course in primary school
In a course in At extracurricular secondary school activities in school
Online 2019/2020 2020/2021 2021/2022 2022/2023 2023/2024
We also conducted a Bonferroni posthoc test where we saw significant differences between the 2020/2021 and 2022/2023 groups (mean .95, p-value .01) as well as 2020/2021 and 2023/2024 groups (mean 1.07, p-value 0.00).
The findings indicate significant differences in the pre-knowledge of students enrolled in the Fundamentals of Web Programming course over five academic years. The data suggests that the COVID-19 pandemic may have impacted students’ opportunities to gain programming knowledge before enrollment in the university, as can be seen in Figure 1, where between COVID-19 in 2021/2022, there was a big step down of students who ever attended programming courses before entering University. However, the rise in students with prior programming experience is encouraging and aligns with the increasing importance of digital literacy in the modern world.
The diversity in programming languages learned before university, with C++ and JavaScript being the most prevalent, reflects the broad spectrum of educational backgrounds among the students. The shift in interest from C++ to C# could be indicative of industry trends influencing educational choices. As also presented in Figure 2, we can observe a lower interest in C++ and Java technologies, whereas C, C#, and JavaScript technologies are rising among the interests of students. Moreover, the fact that most students learned programming in secondary school courses, as presented in Figure 3, suggests that early exposure to programming could be crucial in shaping future university curricula to better prepare students for advanced courses. All results of the study were gained by students who selfreported their knowledge, so this might be a misleading aspect in terms of the validity of the study.
The study demonstrates that there is a significant difference in the self-reported programming knowledge among five consecutive generations of students. There could be a number of reasons for this; some factors could include changes in secondary education curricula, the impact of the COVID19 pandemic, evolving industry demands and, thus, higher interest in programming among younger generations. The results underscore the need for universities to continually adapt their introductory programming courses to accommodate the varying levels of pre-knowledge students bring to the classroom. Future research could focus on the effectiveness of these adaptations and their impact on student’s academic performance and career readiness in the field of computer science.
The authors acknowledge the financial support from the Slovenian Research and Innovation