Informatics in Education

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 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.

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 builds on a recent systematic mapping of computing education literature by conducting an in-depth qualitative analysis of selected studies on group work in Project-Based Learning (PjBL), published between 2010 and 2021. We examined how prominent theoretical frameworks are used in this context. We found that frameworks were often applied either as teaching tools or to inform course design, and when used in these ways, authors frequently reported positive pedagogical outcomes. While frameworks like Tuckman’s model were often referenced only superficially, Social Loafing was more commonly explored in depth. Inductive analysis was particularly effective in distinguishing between background mentions and more substantial integration of theory.We recommend a more intentional, theory-driven approach to research and pedagogy to strengthen conceptual clarity and practical impact. Shared community resources and clearer reporting practices could further support deeper theoretical engagement in the field.

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.

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.

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.