Informatics (computer science) education is the research field that studies how people learn and how educators teach computing – including core computing concepts (e.g., programming, algorithms, data, systems), practices (e.g., decomposition, abstraction, debugging, modeling), and perspectives (e.g., identity, ethics, societal impact) – across school, higher education, and informal learning contexts. INFEDU treats computational thinking and AI literacy as computing‑education constructs when they are investigated through rigorous educational research and produce transferable knowledge (theory, evidence, methods, instruments, or design knowledge). The field includes curriculum and pedagogy, assessment and measurement, teacher education and professional development, equity and ethics, and evidence‑based evaluation of computing learning environments and tools.
Paradigm and evidence pluralism
INFEDU does not define research quality by data volume or by one preferred methodology. The journal welcomes positivist and post-positivist studies, interpretive and qualitative inquiry, pragmatist design-based research and practitioner inquiry, critical and participatory work, and rigorous conceptual or theoretical contributions.
Methods should be selected because they are appropriate to the educational problem and the claim being made. A small, context-rich study may make a strong contribution when it produces an original interpretation, useful artefact, transferable design principle, boundary or failure insight, or socially consequential practice knowledge. Conversely, large datasets and sophisticated statistics do not compensate for weak synthesis or negligible educational meaning.
INFEDU distinguishes confirmatory evidence from interpretive, illustrative, formative, and design-informative evidence. Control groups and large samples are required only for claims that depend on causal or population inference. Local transfer should be argued through context, mechanism, adaptation conditions, and limits rather than through unsupported universality.
INFORMATICS IN EDUCATION publishes original peer-reviewed research articles reporting theoretical, empirical, and methodological studies in the fields of informatics* education and computing in informatics/CT education. The journal provides an interdisciplinary forum for researchers, educators, policymakers, and other professionals involved in informatics education. Its scope ranges from primary (and even from pre-primary) to tertiary education and includes various contexts of informatics education, such as individual and collaborative learning and classroom, organizational and system-level studies.
INFORMATICS IN EDUCATION publishes diverse kinds of informatics education research, including:
- educational engineering studies focusing on the design, development and evaluation of high-quality pedagogical and educational technology innovations for different informatics topics, such as the development of computational thinking and everyday computational reasoning as well as formal computing education;
- educational data mining and artificial intelligence studies based on big data related to informatics education, such as assessment, online learning of computing, and informatics competitions;
- evaluation of computer-supported tools or educational technologies for teaching and learning computing concepts, programming notations and tools, such as visual, block-based, and other text-based coding environments;
- empirical studies, encompassing pedagogies to teach informatics, learning of computing concepts, assessment and measurement of knowledge, skills and transfer, ethical issues related to the development and use of artificial intelligence in informatics education and exploring gender-related considerations.
- interpretive and qualitative studies that explain meanings, practices, professional judgement, learner or teacher experience, and context-dependent mechanisms in informatics education;
- pragmatist, design-based, action-oriented, research-through-design, and reflective practitioner studies that generate inspectable artefacts, design propositions, implementation knowledge, or community-relevant educational improvement;
- conceptual and theoretical studies that clarify constructs, values, mechanisms, educational purposes, or societal consequences and provide a transparent argumentative or synthesis procedure;
- local or community-based cases whose contextual analysis yields explicit transfer, adaptation, boundary, or failure knowledge for other informatics-education settings.
We welcome high-quality systematic reviews and meta-analyses that include clear research questions, analytical framework, results and discussion aligned with the scope and aims of the journal.
* We use “informatics” as a synonym of “computer science”.