Development of a digital educational library integrating conversational and generative artificial intelligence to Foster learning enjoyment en pre-reading education
Authors
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Rosales Espinoza
Universidad Técnica de Machala, Carrera de Tecnologías de la Información, Machala, Ecuador
https://orcid.org/0009-0000-6069-6159
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Leonidas Antonio Inca Portilla
Universidad Técnica de Machala, Facultad de Ingeniería Civil, Carrera de Tecnologías de la Información, Machala, El Oro, Ecuador.
https://orcid.org/0000-0001-5391-2503
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Fausto Fabián Redrován Castillo
Universidad Técnica de Machala, Docente de la Carrera de Tecnologías de la Información, Machala, Ecuador
https://orcid.org/0000-0001-9255-9810
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Elmina Matilde Rivadeneira Rodríguez
Universidad Técnica de Machala, Docente de la Carrera de Educación Inicial, Machala, Ecuador
https://orcid.org/0000-0002-8310-5574
DOI:
https://doi.org/10.33936/isrtic.v10i2.8474Keywords:
Pre-reading, digital educational library, technologies, artificial intelligence, pedagogyAbstract
Pre-reading in early childhood opens a path toward language, imagination, and symbolic thinking; yet digital resources rarely bring together interaction, imagery, and conversation in a coherent way for children aged 3 to 5. This work grew out of a previous experience by the [research group omitted for blind review] research group at the [institution omitted for blind review], and from there a digital educational library took shape, one designed so that children in the province of El Oro could find something to genuinely enjoy in pre-reading, not just another task. To build it, the team worked with Extreme Programming as an agile methodology and incorporated a user-centered design approach, because it was clear from the start that a platform for three-to-five-year-olds has to respond to how they actually think and move, not the other way around. On the technical side, the system relied on laravel, php, postgreSQL, and javaScript; two artificial intelligence modules were also integrated: an educational chatbot running on the openai/gpt-3.5-turbo model through openRouter, and an image generator built on FLUX.1-schnell via the hugging face API. When internal testing was carried out, with early childhood teachers observing the process, the chatbot responded coherently within the children's context in 85% of cases and the image module reached a 92% success rate. Children spent an average of 12 minutes on the platform and returned to activities on their own, a sign of sustained interest. Putting real-time image generation together with a conversational assistant built around how young children actually communicate made the experience feel different from what standard digital libraries offer, and that opens up a real conversation about where AI can meaningfully fit in early childhood education.
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Copyright (c) 2026 Ronaldo Steven Rosales Espinoza, Leonidas Antonio Inca Portilla, Fausto Fabián Redrován Castillo, Elmina Matilde Rivadeneira Rodríguez
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