Class Research Seminar in Informatics Didactics

The course unit Research Seminar in Didactics of Informatics is part of the Master's in Teaching Informatics, taught in the 1st semester of the 2nd year, concurrently with Internship I. It aims to enable future teachers to understand and critically analyse educational research in Computer Science and digital technologies, recognising teaching practice as a space for inquiry. It focuses on building research conceptual frameworks, defining questions, objectives, participants and data-collection instruments, and on research into Artificial Intelligence in Education, in articulation with ReLeCo. Being concurrent with Internship I, the course plays a structuring and supporting role in formulating students' research projects, anchored in the educational situations experienced during school immersion.

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CP1 - Researching in education: paradigms and approaches to research in Computer Science and digital technologies; teaching practice as a research activity. CP2 - Research problems and design: ontological and ethical commitments; topics, questions and objectives; empirical field and sources of information; data-collection methods; qualitative, quantitative and mixed analysis. CP3 - Building the research project: structure (title, theoretical framework, objectives, methodology, timetable); literature review; coherence between subject, methodology and analysis; planning empirical work; scientific quality criteria. CP4 - Communication and reflection on research: academic writing; dissemination (articles, reports, posters); communities of practice; researcher reflexivity; evaluation of the research path.

ME1 - Interactive thematic sessions, using audiovisual materials and digital platforms, for critical discussion of texts and case studies chosen with students, fostering autonomy and critical analysis (LO1, LO2). ME2 - Simulated research activity in small groups, with hands-on reflective practices, real open-access data and links to the professional practicum, including mentoring and feedback, applied to formulating problems, defining objectives and designing data-collection instruments (LO3, LO4, LO5). ME3 - Scientific writing and academic communication workshops, drafting projects, reports and articles, preparing presentations and posters, peer review and reflection on research ethics and scientific quality (LO4, LO5).

Amado (2014). Manual de investigação qualitativa em educação. Imprensa da Universidade de Coimbra. Belmar et al. (2023). Teaching computer programming: impact of Brown and Wilson's principles. Frontiers in Computer Science, 5. Cohen, Manion & Morrison (2000). Research Methods in Education. Routledge. Creswell (2002). Research design: qualitative, quantitative and mixed-method approach. Sage. Dowling & Brown (2010). Doing Research/Reading Research. Routledge. Harding (1986). Whose Science? Whose Knowledge? Cornell University Press. Muijs (2004). Quantitative research in education with SPSS. Sage. Hazzan, Lapidot & Ragonis (2020). Guide to Teaching Computer Science. Springer. Rosa (2020). A research model in didactics of programming. CLEI Electronic Journal, 23(1). Silva & Pinto (1986). Metodologia das ciências sociais. Afrontamento. Silverman (2000). Doing Qualitative Research. Sage.