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        <datestamp>2026-07-22T11:06:00Z</datestamp>
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          <dc:title>5W2H as a Flexible Analytical Framework for Investigating Programming Teaching and Learning Across Different Methodological Designs</dc:title>
          <dc:creator>Rodrigues, Gabryella</dc:creator>
          <dc:creator>Morais, Ceres</dc:creator>
          <dc:creator>Osório, António</dc:creator>
          <dc:subject>5W2H</dc:subject>
          <dc:subject>programming education</dc:subject>
          <dc:subject>programming learning</dc:subject>
          <dc:subject>analytical framework</dc:subject>
          <dc:subject>Higher Education</dc:subject>
          <dc:description>Teaching and learning programming in Higher Education is a complex process involving cognitive, pedagogical, contextual, and metacognitive dimensions. Traditional analyses focused only on final learning outcomes, such as code correctness, performance, or pass/fail rates, may not fully capture how students construct knowledge, face difficulties, mobilize strategies, and interact with different learning contexts. This article discusses the use of the 5W2H framework as a flexible analytical tool in two doctoral studies on programming teaching and learning. The first study used 5W2H to organize and triangulate data from a mixed-methods single case study on the teaching and learning of programming in a Higher Education course. The second study articulated 5W2H with the spiral model and Bloom’s revised taxonomy to analyze a qualitative multiple case study focused on students' algorithm construction process. Through a comparative analysis, the article shows that 5W2H can operate at different analytical scales: as a broad structure for mapping subjects, contexts, methodologies, difficulties, and learning factors, and as a process-oriented framework for interpreting students' actions during algorithmic problem solving. The findings suggest that 5W2H supports the organization, categorization, triangulation, and interpretation of complex educational data. Therefore, the framework offers a useful methodological lens for research in programming education, helping researchers understand the relationships between subjects, contexts, strategies, difficulties, and cognitive processes involved in teaching and learning programming.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Gabryella Rodrigues and Ceres Morais and António Osório</dc:contributor>
          <dc:date>2026</dc:date>
          <dc:relation>Is Part Of OASIcs, Volume 145, 7th International Computer Programming Education Conference (ICPEC 2026)</dc:relation>
          <dc:type>InProceedings</dc:type>
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          <dc:identifier>doi:10.4230/OASIcs.ICPEC.2026.14</dc:identifier>
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          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICPEC.2026.14</dc:identifier>
          <dc:language>eng</dc:language>
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