Proposal for an Adaptive Recommender System to Support Teaching Practices

The shift to online learning, which has grown by 70% in recent years, has brought unprecedented challenges to the educational landscape. This emphasizes the urgent need for innovative solutions that address the evolving needs of both educators and students. This study introduces a novel adaptive recommender system for educators, which has demonstrated significant improvements in teaching effectiveness through personalized strategy recommendations. Preliminary findings reveal a notable increase in student engagement and comprehension, underscoring the system’s potential to revolutionize educational practices.

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Publication Details

Journal
International Journal of Interactive Mobile Technologies (iJIM)
Published
2025-03-13
DOI
https://doi.org/10.3991/ijim.v19i05.52431
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

Proposal for an Adaptive Recommender System to Support Teaching Practices

Elías Ruiz, Jose Angel Gonzalez, H. Alemán, German Cuaya-Simbro et al.
International Journal of Interactive Mobile Technologies (iJIM)
Intelligent Tutoring Systems and Adaptive Learning
article

Proposal for an Adaptive Recommender System to Support Teaching Practices

Elías Ruiz, Jose Angel Gonzalez, H. Alemán, German Cuaya-Simbro, Alexander Barinas
article en

Abstract

The shift to online learning, which has grown by 70% in recent years, has brought unprecedented challenges to the educational landscape. This emphasizes the urgent need for innovative solutions that address the evolving needs of both educators and students. This study introduces a novel adaptive recommender system for educators, which has demonstrated significant improvements in teaching effectiveness through personalized strategy recommendations. Preliminary findings reveal a notable increase in student engagement and comprehension, underscoring the system’s potential to revolutionize educational practices.

International Journal of Interactive Mobile Technologies (iJIM)Vol. 19(05)
Universidad Autónoma del Estado de Hidalgo (MX), Fundación Universitaria Juan de Castellanos (CO), Centro Universitario del Oriente de Hidalgo (MX)
Openalex Percentile: Top 98%
Intelligent Tutoring Systems and Adaptive Learning
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Proposal for an Adaptive Recommender System to Support Teaching Practices — Elías Ruiz, Jose Angel Gonzalez, et al. · International Journal of Interactive Mobile Technologies (iJIM) (2025) | TGRS Research Map | TGRS