Transmedia Education 4.0: Effects of Artificial Intelligence on Student Engagement and Didactic Innovation.
In the context of digital educational transformation, Transmedia Education 4.0 hasemerged as an innovative pedagogical approach that integrates artificial intelligence(AI), transmedia narratives, and active student engagement. This study aimed toanalyse the effects of AI on student participation and didactic innovation in highereducation institutions in Ecuador and Peru. A mixed-methods approach was adopted,with a non-experimental, comparative design and an exploratory-descriptive scope.Data were collected through structured surveys administered to 420 students (210 percountry) and semi-structured interviews with 28 university lecturers (14 per country),complemented by document analysis. The instruments were validated through expertjudgement, yielding high reliability (Cronbach’s α = 0.87). Quantitative data wereanalysed using SPSS v.27, while qualitative data were examined using Atlas.ti v.23.Findings revealed medium-to-high levels of AI use, student engagement, and perceiveddidactic innovation, with slightly more favourable perceptions among Peruvianparticipants. The interviews indicated that AI is widely valued as a pedagogical supporttool; however, institutional barriers such as insufficient teacher training and limitedinfrastructure persist. The most frequently cited category was the need for continuousprofessional development. The study concludes that AI holds transformative potential inhigher education, provided its implementation is guided by context -sensitivepedagogical principles, digital ethics, and inclusive institutional policies. This researchprovides comparative empirical evidence on the challenges and opportunities ofTransmedia Education 4.0 in the Latin American context.
Institutions
- Universidad de las Fuerzas Armadas ESPE (EC)
- Universidad Privada de Tacna (PE)
- Universidad Peruana Unión (PE)
- Universidad Nacional de Huancavelica (PE)
- Universidad Nacional de Chimborazo (EC)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-08-29
- DOI
- https://doi.org/10.5281/zenodo.16994184
- Primary Topic
- Geochemistry and Geologic Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.00