Informatics in Education

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.

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.

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.