Informatics in Education

This paper presents research findings on primary school students’ awareness of the ethical aspects of using artificial intelligence (AI) tools for homework. The study used a self-constructed online questionnaire administered to 301 primary school students from grades five to eight attending two primary schools in Northwestern Croatia. The results show that 57.8% of students already use AI tools to complete their homework. Students in higher grades use it more often than those in lower grades. A significant Spearman correlation exists between respondents’ daily time spent on social media and the use of AI tools (r = 0.34, p < .001). Only 36.5% of students in the sample believe it is unacceptable to copy AI-generated answers when completing their homework. The results underscore the need to integrate AI education into the primary school informatics curriculum in the Republic of Croatia, including introducing content that addresses the ethical aspects of using AI tools.

While research on Learning Analytics (LA) is plentiful, it often prioritises perspectives on LA systems over the practical ways instructors use data to analyse and refine the learning process per se. The present study addresses this inadequacy by investigating how student data is employed by educators in UK Higher Education Institutions (HEIs) and how it could be optimised. Specifically, a mixed-methods approach was employed combining survey data, mainly from one institution (N = 85) with insights gleaned from interviews with academics (N = 11). The findings reveal a real desire for better data capabilities and access, underscoring the need for HEIs to enhance data capture, better integrate systems and invest in professional development to enhance data literacy and foster a culture of data-driven decision-making. Importantly, a similar emphasis to that given to assessment and attendance needs to be given to data for the differentiation and personalisation of learning.

The integration of management education with information technology tools, such as simulation games and business analysis platforms, is playing an increasingly important role in developing students’ decision-making skills as well as earn and acquire best business practices. It is particularly useful to test the didactic process effectiveness by the use of simulation game, i.e. to investigate the specificities of the use of the same software by teams from two countries. The analysis of the literature has shown that there are many cases where the same simulation tool is used by educationalists from different countries. The computer business game “Kietas riešutas” has been widely used in Lithuanian universities and colleges. The question naturally arises which aspects of the simulation game are perceived similarly by members of international teams and which are different. A questionnaire for students was developed for this purpose, on the basis of which the study was conducted. An additional questionnaire was used to investigate the relationship between the game and the uptake and usefulness of the game in computer science subjects for decision making. The paper compares the achievements obtained in the game, discusses the results of the simulation of international teams and the rationality of the decisions taken. The study showed that the business game not only helps to understand the purposeful use of information technology, but also motivates people to use it to achieve better game results.

Tables are fundamental tools for handling data and play a crucial role in developing both computational thinking (CT) and mathematical thinking (MT). Despite this, they receive limited attention in research and design. This study investigates pupils’ attitudes toward and approaches to working with tables in informatics education, focusing on the systematic development of CT. Specifically, we examine how primary school pupils (aged 8–10) think and act when engaging with two-dimensional frequency tables integrated into Programming with Emil. Our objective is to deepen the understanding of pupils’ cognitive processes when entering data into tables and interpreting their contents. Data were collected through individual semi-structured interviews and analysed using qualitative inductive coding. Identified codes were then iteratively consolidated into broader categories and final themes. Key findings include: (a) the opportunity to solve a problem by programming a character is highly motivating for pupils, and (b) the appropriate integration of different contexts and concepts, such as tables, into an engaging programming environment has the potential to foster advanced cognitive skills beyond CT.

Algebraic Thinking (AT) and Computational Thinking (CT) are pivotal competencies in modern education, fostering problem-solving skills and logical reasoning among students. This study presents the initial hypotheses, theoretical framework, and key steps undertaken to explore characterized learning paths and assign practice-relevant tasks. This article investigates the relationship between AT and CT, their parallel development, and the creation of integrated learning paths. Analyses of mathematics and computer science/informatics curricula across six countries (Finland, Hungary, Lithuania, Spain, Sweden, and Türkiye) informed the development of tasks aligned with consolidated national curricula. Curricula were analysed using statistical methods, and content analysis to identify thematic patterns. To validate the effectiveness of the developed tasks for AT and CT, an assessment involving 208 students in K-12 across various grade levels (students aged 9–14) was conducted, with results analysed both statistically and qualitatively. Subsequently, a second quantitative study was carried out among teachers participating in a workshop, providing further insights into the practical applicability of the tasks. The research process was iterative, encompassing cycles of analysis, synthesis, and testing. The study also paid special attention to unplugged activities – tasks that help students learn CT without using computers or digital tools. A local workshop in Hungary, where 26 tasks were tested with students from different grade levels, showed that developing CT and AT effectively requires more time and practice, especially in key topics. The findings underscore the importance of integrating AT and CT through thoughtfully designed learning paths and tasks, including unplugged activities, to enhance students’ proficiency in these areas. This study contributes to the development of innovative educational programs that address the evolving digital competencies required in contemporary education.

The assessment of computational thinking (CT) is crucial for improving pedagogical practice, identifying areas for improvement, and implementing efficient educational interventions. Despite growing interest in CT in primary education, existing assessments often focus on specific dimensions, providing a fragmented understanding. In this research, a CT system of assessments for primary education was assembled and applied in a cross-sectional survey study with 1306 students from the 6th grade in a region of Spain. A three-way ANOVA and correlation analyses explored the effects of programming experience, educational context, and gender on CT skills and self-efficacy. Results highlighted a significant effect of programming experience but no significant effects of context or gender, alongside low overall correlations between CT skills and self-efficacy. These findings highlight the need to avoid focusing CT assessments on a single variable and support the combined use of multiple assessment instruments to measure CT accurately and effectively.

This study aims to provide a descriptive and bibliometric analysis of the trend of artificial intelligence (AI) application in the development of computational thinking (CT) skills in publications from 2007 to 2024. A total of 191 articles were obtained from Scopus database with certain keywords, and analyzed using Biblioshiny and VOSviewer. The results show that publications fluctuated in 2007–2014, then increased sharply since 2019, with a compound annual growth rate (CAGR) of 22.8% in the period 2019–2024. Early publications received the highest number of citations, such as in 2007 (18 citations), while recent studies show a more even distribution of citations, reflecting a shift from basic to applied research. This analysis highlights the important role of AI in enhancing CT development through learning strategies, educational technology, and cross-disciplines. The impact of AI implementation is seen in various aspects of education, such as learning strategies, educational media, and the relationship between CT and other skills. These findings demonstrate the importance of leveraging AI to support the development of CT in education, which can improve the quality of learning and enrich educational experiences globally.

Modern software companies prioritize high-quality products for competitiveness, and Software Process Improvement (SPI) models help achieve this. In Brazil, the Brazilian Software Process Improvement Model (MPS-SW model) is widely used, but its complexity and extensive documentation make it challenging to teach in undergraduate courses. To address the lack of students engagement to learn SPI, we developed the MPS Manager, a serious game that incorporates gamification to facilitate learning about the MPS-SW model. The game was evaluated in four Software Engineering courses across three universities with 83 students. Using the Model for the Evaluation of Educational GAmes (MEEGA+) method, students assessed the game across dimensions such as usability, confidence, and learning, with 55% overall agreement. Further analysis explored correlations between satisfaction and factors like gender, gaming experience, and course format (i.e., virtual or in-person). Feedback from students highlighted the need for improved engagement, social interaction, and reduced gameplay monotony, which will guide future game enhancements.

This paper presents survey results involving students from three fields of study (computer science, business, and pedagogy), positing that computer science students exhibit distinct patterns in the spectrum of multiple intelligences compared to students in social sciences disciplines. The study involved over 300 students, revealing statistically significant differences, especially in logical-mathematical intelligence, one of the crucial intelligences according to Howard Gardner's theory and is traditionally measured by IQ indices. Statistical analysis confirms the dominance of computer science students in this intelligence. The data on student preferences were collected through self-assessment in an online questionnaire.

Transcripts play a crucial role in qualitative research in computing education, with significant implications for the credibility and reproducibility of findings. However, unreflective and inconsistent transcription standards may unintentionally introduce biases, potentially undermining the validity of research outcomes and the collective progress of the field. In this article, we introduce transcription as a theoretically guided process rather than a mere preparatory step, illustrating its role using a case example. Additionally, through a systematic review of 107 qualitative research articles in computing education, we identify widespread shortcomings in the reporting and implementation of transcription practices, revealing a need for greater intentionality and transparency. To address these challenges, we propose a three-step framework for selecting, applying, and documenting transcription standards that align with the specific context and goals of a study. Rather than advocating for overly complex, one-size-fits-all transcription strategies, we emphasize the importance of a context-appropriate approach that is clearly communicated to foster trust and reproducibility. By advancing a more robust transcription culture, this work aims to support computing education researchers in adopting standards that enhance the quality and reliability of qualitative research in the field.