Effectiveness of Intelligent Educational Technologies for Web Developer Retraining: Case Study of Khan Academy Platform and COSAR Program in Benin

Our study aimed to analyse the effectiveness of intelligent educational technologies, in this case Khan Academy, in the context of retraining for the profession of web developer, while examining the impact on learners' motivation, commitment and the development of their professional identity. In the specific context of adult continuing education and professional retraining, we conducted and analysed the experience of 17 learners who participated in COSAR's training and retraining program in Cotonou, Benin. Using a mixedmethods approach, we collected data first through questionnaires and then via semi-structured interviews. The results of this experience are quite satisfactory. They indicate that the Khan Academy technology studied facilitated learning, and that its use significantly influenced the construction of learners' professional identities, notably in terms of selfconfidence and perceived improvement in their technical skills or aptitudes. In addition to technical skills and the appropriation of professional identity, this study highlights the importance of cultural and linguistic adaptation of e-learning platforms in the French-speaking African context, which are essential areas to consider in the context of retraining. Our conclusions underline the real potential of intelligent educational technologies to facilitate and promote successful professional retraining. Finally, in our recommendations, we identify areas for improvement to adapt these technologies to the local context better.

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Published
2025-04-22
DOI
https://doi.org/10.1109/educon62633.2025.11016344
Primary Topic
Online Learning and Analytics
Type
article
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article

Effectiveness of Intelligent Educational Technologies for Web Developer Retraining: Case Study of Khan Academy Platform and COSAR Program in Benin

Pélagie Houngue, Gerlix Adankon
Online Learning and Analytics
article

Effectiveness of Intelligent Educational Technologies for Web Developer Retraining: Case Study of Khan Academy Platform and COSAR Program in Benin

Pélagie Houngue, Gerlix Adankon
article en

Abstract

Our study aimed to analyse the effectiveness of intelligent educational technologies, in this case Khan Academy, in the context of retraining for the profession of web developer, while examining the impact on learners' motivation, commitment and the development of their professional identity. In the specific context of adult continuing education and professional retraining, we conducted and analysed the experience of 17 learners who participated in COSAR's training and retraining program in Cotonou, Benin. Using a mixedmethods approach, we collected data first through questionnaires and then via semi-structured interviews. The results of this experience are quite satisfactory. They indicate that the Khan Academy technology studied facilitated learning, and that its use significantly influenced the construction of learners' professional identities, notably in terms of selfconfidence and perceived improvement in their technical skills or aptitudes. In addition to technical skills and the appropriation of professional identity, this study highlights the importance of cultural and linguistic adaptation of e-learning platforms in the French-speaking African context, which are essential areas to consider in the context of retraining. Our conclusions underline the real potential of intelligent educational technologies to facilitate and promote successful professional retraining. Finally, in our recommendations, we identify areas for improvement to adapt these technologies to the local context better.

Université d'Abomey-Calavi (BJ), Institute of Mathematics and Physics (BJ)
Openalex Percentile: Top 88%
Online Learning and Analytics
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Effectiveness of Intelligent Educational Technologies for Web Developer Retraining: Case Study of Khan Academy Platform and COSAR Program in Benin — Pélagie Houngue, Gerlix Adankon · (2025) | TGRS Research Map | TGRS