Informatics in Education

This narrative literature review examines constructionist approaches to AI literacy education for school-aged children, synthesizing research from 2009–2024 to develop a pedagogical framework grounded in hands-on learning principles. Through systematic analysis of studies retrieved from Web of Science, Scopus, IEEE Xplore, and ACM Digital Library, five interconnected themes emerged: active hands-on learning, project-based inquiry, ethics integration, age-appropriate scaffolding, and teacher support with accessible tools. The findings demonstrate that constructionist methodologies – emphasizing learning through creating AI-powered artifacts – effectively foster conceptual understanding, ethical reasoning, and critical agency among young learners. The review reveals that AI literacy develops most effectively when students actively manipulate and experiment with AI systems rather than passively consuming theoretical content. Age-differentiated strategies are essential, with primary students benefiting from embodied analogies and narrative contexts, while secondary students engage with collaborative design projects addressing real-world challenges. Teacher preparation and accessible tools emerge as critical implementation factors. This framework provides educators and policymakers with evidence-based guidance for integrating meaningful AI literacy experiences into K-12 curricula through constructionist pedagogies.

This study aims to explore how gamification elements influence the development of the Community of Inquiry (CoI) in an online project-based programming course conducted on Facebook. We formed student groups by using a quasi-experimental design from students studying in the computer science department. While both courses were project-based, the experimental group's project development process was enriched with gamification elements. We collected data from the CoI survey, transcript analysis of online discussions, and interviews with students. The results indicated that the use of gamification elements contributed significantly to students' social, cognitive, and teaching presence development. Besides, while a high level of CoI perception was created in both groups in the online project-based learning environment, the design and organization role of the instructor came to the fore in the gamified environment more.

Preparing students for the workforce is a balancing act that involves theory, practice, and assessment. As students navigate an educational experience that is, however, often distant from real-world needs, it is imperative that academia finds a novel way to bridge the gap. As many organizations utilize open challenges to attract ideas and talent, academia can easily create such bridge, leading to greater engagement, greater student preparation, and a potential employment pipeline. This paper describes the experience of our students and faculty advisors who participated to the NASA SUITS (Spacesuit User Interface Technologies for Students) Design Challenge. In particular, we review the pedagogical value of the solution that they created and the changes that were implemented in the curriculum of an undergraduate degree program in Information Technology. This open-source, multi-year project is also a flexible platform that can be utilized for engagement in K-12 education as well as graduate research projects.

The aim of the present study was to investigate the properties of paper-and-pencil data collection instruments developed to measure Computational Thinking (CT) based on several variables. Thus, keywords were identified and used in searches conducted in various databases. The outcomes of the search were analyzed based on the inclusion/exclusion criteria and 64 studies that focused on CT measurement were identified. Content analysis findings were classified under several themes. Based the present study findings, it was determined that the number of tools developed to measure CT demonstrated an increasing trend over time. Furthermore, it was found that the above-mentioned studies included mainly tests. Moreover, it was observed that the processes of ensuring validity and reliability were not clearly specified for more than half of the paper-and-pencil data collection instruments designed to measure CT. Based on the findings, several recommendations were presented for future studies and implementations in the related field.

Nondeterminism (ND) is a fundamental concept in computer science, and comes in two main flavors. One is the kind of ND that appears in automata theory and formal languages, and is the one that students are usually introduced to. It is known to be hard to teach. We present here a study, in which we introduced students to the second kind of ND, which we term operative. This kind of ND is quite different from the first one. It appears in nondeterministic programming languages and in the context of concurrent and distributed programming. We study how high-school students understand operative ND after learning the nondeterministic programming language of live sequence charts (LSC). To assess students' learning, we used a two-dimensional taxonomy that is based upon the SOLO and the Bloom taxonomies. Our findings show that after a semestrial course on LSC, high-school students with no previous experience with ND of either type, understood operative ND on a level that allowed them to create and execute programs that included nondeterminism on various levels and in various degrees of complexity. We believe that it is important to expose students to the two types of ND, especially as ND has become a very prominent characteristic of computerized systems. Our findings suggest that students can reach a significant understanding of operative ND when the concept is introduced in the context of a programming course.