THE 4P MODEL: A TYPOLOGY OF INDICATORS FOR PRIMARY EDUCATION EASSESSMENT DASHBOARDS / LE MODÈLE 4P : UNE TYPOLOGIE D'INDICATEURS POUR LES TABLEAUX DE BORD D'E-ÉVALUATION DANS L'ENSEIGNEMENT PRIMAIRE
Abstract
The growing integration of digital technology in Moroccan education generates massive data, raising questions about its effective use. This research examines the relevance of eAssessment dashboards for primary teachers, focusing on adoption factors and indicators that align with pedagogical decision-making. Using a mixed-methods approach with 61 teachers in Marrakech-Safi, the study combined quantitative acceptance measures with a lexicometric analysis of social representations. Results highlight a mixed adoption rate (44.3%) and reveal a "training paradox": trained teachers are more skeptical than their untrained colleagues, questioning the adequacy of current training programs. Qualitatively, teachers reject purely accounting-based views of eAssessment in favor of competence development. The article proposes the 4P model, structuring essential indicators into four dimensions: monitoring the Process (progress over time), validating the Profile (competence status), objectifying Performance (raw data), and Positioning (classroom context). It concludes that cognitive ergonomics and diachronic visualization are essential for transforming these tools into effective levers for pedagogical regulation.
L’intégration croissante du numérique dans le système éducatif marocain génère une massification des données scolaires, posant le défi de leur exploitation pédagogique. Cette recherche interroge la pertinence des tableaux de bord d’e-évaluation pour les enseignants du cycle primaire : au-delà de la disponibilité technique, quels sont les déterminants de leur adoption et quels indicateurs répondent aux besoins réels du métier ? Adoptant une approche méthodologique mixte, cette recherche a été menée auprès de 61 enseignants de l’AREF de Marrakech-Safi. Le protocole a combiné une mesure quantitative de l’adhésion avec une analyse lexicométrique (analyse de similitude) des représentations sociales des enseignants. Les résultats mettent en évidence un taux d’adhésion mitigé (44,3 %) et révèlent un « paradoxe de la formation » contre-intuitif : les enseignants formés à l’e-évaluation manifestent un scepticisme plus marqué que leurs collègues non-initiés, interrogeant ainsi l’adéquation des dispositifs de formation actuels. Sur le plan qualitatif, l’analyse montre que les enseignants rejettent une vision purement comptable de l’e-évaluation au profit d’une approche centrée sur le développement des compétences. Cette étude aboutit à la proposition d’une typologie fonctionnelle, le Modèle des 4P, structurant les indicateurs essentiels selon quatre dimensions : le suivi du Processus (progression temporelle), la validation du Profil (statut de la compétence), l’objectivation de la Performance (données brutes) et le Positionnement (dans le contexte de la classe). Elle conclut que l’ergonomie cognitive et la visualisation diachronique constituent des conditions indispensables pour transformer ces outils en véritables leviers de régulation pédagogique.
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Akkioui, K. (2022). Evaluation of the use of information systems in schools in Morocco: Contribution to the study of the key factors of adoption of the Massar information system. African Scientific Journal, 3(12). https://doi.org/10.5281/zenodo.6868091
Black, P., Harrison, C., Lee, C., Marshall, B., & Wiliam, D. (2004). Working inside the black box: Assessment for learning in the classroom. Phi Delta Kappan, 86(1), 8–21. https://doi.org/10.1177/003172170408600105
Black, P., & Wiliam, D. (2018). Classroom assessment and pedagogy. Assessment in Education: Principles, Policy & Practice, 25(6), 551–575. https://doi.org/10.1080/0969594X.2018.1441807
Cisel, M., & Baron, G. L. (2019). Utilisation de tableaux de bord numériques pour l’évaluation des compétences scolaires : Une étude de cas. Questions Vives, 31. http://journals.openedition.org/questionsvives/3883
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Duval, E. (2011). Attention please! Learning analytics for visualization and recommendation. In Proceedings of the 1st International Conference on Learning Analytics and Knowledge (pp. 9–17). Association for Computing Machinery. https://doi.org/10.1145/2090116.2090118
El Idrissi, F., & Larhrissi, N. (2025). Intégration des TIC dans l’enseignement/apprentissage au Maroc : Entre innovation et défis. L’Archétype, 3(1), 174–187. https://doi.org/10.34874/PRSM/archtype-54430
El Janous, Y., Laafou, M., El-Hassouny, E. H., & Madrane, M. (2022). Teachers’ perception of the Moroccan ICT portal of the Ministry of Education. European Scientific Journal, 18(12). https://doi.org/10.19044/esj.2022.v18n12p155
Elmadhi, A., Lakhmour, A., & Craita, M. (2024). L’évaluation en ligne et la taxonomie de Bloom. Revue Du LaRSLAME: Société, Langage, Art, Médias Et Education, 1(2). https://doi.org/10.34874/IMIST.PRSM/larslam-i2.46909
Ghassoub, A., & Merkazi, A. F. (2017). Analyse des facteurs déterminant de l'acceptation des élèves du collège marocain d'un dispositif mobile d'apprentissage hors classe. Revue EPI. https://epi.asso.fr/revue/articles/a1706c.htm
Jivet, I., Scheffel, M., Drachsler, H., & Specht, M. (2017). Awareness is not enough: Pitfalls of learning analytics dashboards in the educational practice. In É. Lavoué, H. Drachsler, K. Verbert, J. Broisin, & M. Pérez-Sanagustín (Eds.), Data-driven approaches in digital education (Vol. 10474). Springer. https://doi.org/10.1007/978-3-319-66610-5_7
Jivet, I., Scheffel, M., Specht, M., & Drachsler, H. (2018). License to evaluate: Preparing learning analytics dashboards for educational practice. In Proceedings of the 8th International Conference on Learning Analytics and Knowledge (pp. 31–40). Association for Computing Machinery. https://doi.org/10.1145/3170358.3170421
Kasepalu, R., Chejara, P., & Prieto, L. P. (2022). Do teachers find dashboards trustworthy, actionable and useful? A vignette study using a logs and audio dashboard. Technology, Knowledge and Learning, 27, 971–989. https://doi.org/10.1007/s10758-021-09522-5
OCDE. (2024). L'évaluation de la performance des établissements scolaires au Maroc. Éditions OCDE. https://doi.org/10.1787/4f59bfc1-fr
Ouatiq, A., Riyami, B., Mansouri, K., & Qbadou, M. (2022). The preferences and expectations of Moroccan teachers from learning analytics dashboards in a blended learning environment: Empirical study. In Y. Maleh, M. Alazab, N. Gherabi, L. Tawalbeh, & A. A. Abd El-Latif (Eds.), Advances in information, communication and cybersecurity (Vol. 357). Springer. https://doi.org/10.1007/978-3-030-91738-8_27
Scherer, R., Siddiq, F., & Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Computers & Education, 128, 13–35. https://doi.org/10.1016/j.compedu.2018.09.009
Schwendimann, B. A., Rodriguez-Triana, M. J., Vozniuk, A., Prieto, L. P., Boroujeni, M. S., Holzer, A., Gillet, D., & Dillenbourg, P. (2017). Perceiving learning at a glance: A systematic literature review of learning analytics dashboards. IEEE Transactions on Learning Technologies, 10(1), 30–41. https://doi.org/10.1109/TLT.2016.2599522
Sclater, N., Peasgood, A., & Mullan, J. (2016). Learning analytics in higher education. Jisc.
Van Barneveld, A., Arnold, K. E., & Campbell, J. P. (2012). Analytics in higher education: Establishing a common language (ELI Paper 1: 2012). EDUCAUSE Learning Initiative. https://library.educause.edu/resources/2012/1/analytics-in-higher-education-establishing-a-common-language
Van Leeuwen, A., Janssen, J., Erkens, G., & Brekelmans, M. (2013). Teacher interventions in a synchronous, co-located CSCL setting: Analyzing focus, means, and temporality. Computers in Human Behavior, 29(4), 1377–1386. https://doi.org/10.1016/j.chb.2013.01.028
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
Wang, H., Huang, T., Zhao, Y., & Hu, S. (2023). The impact of dashboard feedback type on learning effectiveness, focusing on learner differences. Sustainability, 15(5). https://doi.org/10.3390/su15054474
DOI: http://dx.doi.org/10.46827/ejes.v13i7.6825
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