Fostering Self-Regulated Learning with H5P Technology: The Pedagogical Experiences of Educational Professionals
Bibliographic record
Abstract
This qualitative study examined the perspectives of educational professionals on integrating H5P technology to foster self-regulated learning (SRL) in blended learning environments at a post-secondary institution in Ontario, Canada. Using a phenomenological approach, data were collected through semi-structured interviews with five educators, five instructional designers, and five educational technologists, and analyzed thematically through the lens of Zimmerman’s SRL framework. The findings highlight key challenges in fostering learners' motivational processes (e.g., self-efficacy and autonomy), metacognitive processes (e.g., monitoring and planning), and behavioural processes (e.g., strategy execution) within blended contexts. The study evaluated the pedagogical applications, limitations, and potential of various H5P tools, such as interactive books, branching scenarios, and drag-and-drop activities, in supporting SRL. While advancements in H5P functionalities were noted, significant gaps were identified in aligning the technology with SRL best practices. These insights contribute to bridging gaps in literature and practice by offering actionable recommendations for optimizing H5P to enhance learners' SRL strategies. This research provides valuable implications for educators, instructional designers, and policymakers, laying the groundwork for future studies on leveraging educational technologies to support SRL in blended learning environments. Keywords: self-regulated learning; H5P technology; motivational; metacognitive; behavioural; pedagogy; blended learning Favoriser l’apprentissage autorégulé avec la technologie H5P : Les expériences pédagogiques des professionnels de l’éducation Résumé : Cette étude qualitative a examiné les perspectives des professionnels de l’éducation concernant l’intégration de la technologie H5P pour favoriser l’apprentissage autorégulé (AAR) dans des environnements d’apprentissage hybride au sein d’un établissement postsecondaire en Ontario, Canada. En adoptant une approche phénoménologique, des données ont été recueillies à travers des entretiens semi-structurés auprès de cinq enseignants, cinq concepteurs pédagogiques et cinq technologues éducatifs, puis analysées thématiquement à travers le cadre de l’AAR de Zimmerman. Les résultats mettent en lumière des défis clés pour encourager les processus motivationnels des apprenants (par exemple, l’auto-efficacité et l’autonomie), les processus métacognitifs (par exemple, la planification et l’auto-observation) et les processus comportementaux (par exemple, l’exécution de stratégies) dans des contextes hybrides. L’étude a évalué les applications pédagogiques, les limites et le potentiel de divers outils H5P, tels que les livres interactifs, les scénarios à embranchements et les activités de glisser-déposer, pour soutenir l’AAR. Bien que des progrès aient été observés dans les fonctionnalités de H5P, des lacunes importantes ont été identifiées quant à l’alignement de la technologie avec les meilleures pratiques de l’AAR. Ces résultats contribuent à combler les lacunes dans la littérature et la pratique en offrant des recommandations concrètes pour optimiser H5P afin d’améliorer les stratégies d’AAR des apprenants. Cette recherche fournit des implications précieuses pour les enseignants, les concepteurs pédagogiques et les décideurs, en jetant les bases d’études futures sur l’utilisation des technologies éducatives pour soutenir l’AAR dans des environnements d’apprentissage hybride. Mots-clés : Apprentissage autorégulé ; technologie H5P ; motivationnel ; métacognitif ; comportemental ; pédagogie ; apprentissage hybride
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".