Pedagogical Quality of MagicSchool AI-Generated Multimodal Educational Resources and Their Impact on Learning Personalization in Higher Education
DOI:
https://doi.org/10.47230/ra.v9i1.153Keywords:
MagicSchool AI, pedagogical quality, learning personalization, higher education, instructional design, generative artificial intelligenceAbstract
The study evaluated the pedagogical quality of multimodal resources generated through the MagicSchool AI platform and their impact on learning personalization in higher education. A systematic literature review guided by the PRISMA 2020 statement was employed, analyzing research published between 2022 and 2026 across various scientific databases.
Findings evidenced that the tool stood out for its high efficiency in methodological structuring, logical sequencing, and taxonomic alignment of content, which significantly optimized instructional design tasks. Regarding personalization, it facilitated processes of cognitive and linguistic differentiation through text leveling and adapted scaffolding. However, limitations were identified in conceptual depth for postgraduate levels and a flat native multimodality that required external software integrations.
The research determined a Weighted Pedagogical Quality Index of 4.02/5, placing the resources at an “Acceptable-High” level. It was concluded that while the platform functioned as an effective engine for the initial phase of instructional design, final pedagogical quality strictly depended on the teacher's critical mediation, editorial curation, and ethical supervision.
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Copyright (c) 2026 Julissa Eufemia Marcillo Valverde, Geanfrank Isaías Cruz Lucas, Selena María Parrales Villacreses, Helen Yamileth Parrales Castro
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