Predicción del compromiso estudiantil mediante analítica del aprendizaje y análisis del discurso en foros Moodle

• Hendy Maier Pérez Barrera https://orcid.org/0000-0003-1989-2136
• Raúl López Fernández https://orcid.org/0000-0001-5091-5522
• Ennio Jesús Mérida Córdova https://orcid.org/0000-0001-5091-5522
• María José Orellana Tolozano https://orcid.org/0009-0002-8716-2864

DOI: https://doi.org/10.31876/rcs.v32i.45756

Palabras clave: Analítica del aprendizaje, procesamiento de lenguaje natural, foros virtuales, análisis discursivo, compromiso estudiantil

Resumen

Este artículo de tecnologías para la educación describe un estudio que desarrolla un modelo analítico basado en técnicas de procesamiento de lenguaje natural y análisis automático del discurso para identificar patrones comunicativos en mensajes estudiantiles publicados en foros virtuales de Moodle. Bajo un enfoque cuantitativo de alcance exploratorio-descriptivo, se analizaron 212 mensajes de 56 estudiantes de un programa de maestría, identificando la longitud, riqueza léxica y tono comunicativo de las intervenciones. Los resultados muestran un predominio de mensajes con tono cortés y neutro, reflejando un ambiente de respeto y formalidad en el foro. Además, se evidencia que los mensajes inseguros tienden a ser más extensos y con alta densidad de palabras clave; mientras que los tonos agresivos y agradecidos son marginales. Las visualizaciones generadas permitieron identificar diferencias en la calidad discursiva y patrones de participación, ofreciendo información valiosa para comprender las dinámicas de interacción en entornos virtuales. En conclusión, este análisis aporta evidencias que pueden ser utilizadas para diseñar estrategias pedagógicas que fomenten la participación significativa, el compromiso estudiantil y la precisión discursiva en contextos de aprendizaje digital, contribuyendo al desarrollo de modelos educativos más adaptativos y centrados en las necesidades del estudiante.

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