Informatics in Education

Teaching programming to elementary and high school students is important for developing problem-solving and logical reasoning skills. Block-based programming frameworks, such as Scratch and Kodular, have gained popularity for introducing programming concepts in an engaging and more didactic manner. However, these frameworks lack structured tools for analysing student learning processes, which makes it difficult to track progress, identify challenges, and understand student behaviour during application development. This manuscript presents EduPROV, a provenance-based approach that extracts, structures, and analyses student actions from log files generated by block-based programming frameworks. By storing this data in a queryable format, EduPROV supports the identification of learning bottlenecks, tracking programming trajectories, and can help refine teaching strategies. EduPROV was evaluated in a study with elementary and high school students from three schools in southern Brazil, using Kodular as the block-based programming framework. The results show that provenance analysis helps reveal student behaviour, contributing to more informed and effective programming education.

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.

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.

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.

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.

The introductory programming disciplines, which include the teaching of algorithms and computational logic, have high failure and dropout rates. Developing Computational Thinking in students can contribute to learning programming fundamentals by building algorithmic and problem-solving skills. However, keeping students engaged in training such skills is still a challenge. In this sense, this work proposes an intervention for teaching Computational Thinking in the initial semesters of the Technician in Informatics and Bachelor of Computer Science courses, using gamification as a motivational strategy and the Quizizz software as a gamified platform. To evaluate the results, a mixed-method case study was used to perform a quantitative and qualitative analysis of the data and, subsequently, integrate them. The results obtained were discussed based on the Theory of Self-Determination, indicating that students demonstrated a high level of oriented autonomy and motivation to learn, regardless of the performance obtained.

Integrating the understanding of digital threats into informatics education is crucial for preparing pupils to navigate the complexities of the digital world. This study provides foundational insights for embedding digital safety competencies within informatics curricula by prioritizing key threats faced by young people. Through data collected from 708 teachers and 278 parents in Austria, the study employs correspondence analysis to rank threats, including harmful content, data security, social risks, and online addiction. The findings highlight how these prioritized threats can inform the design of competence-based curricula, fostering computational thinking, data literacy, and ethical decision-making in pupils. This research bridges the gap between informatics education and digital safety, offering practical implications for educators and curriculum developers worldwide.