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Estudiante de Ingeniería Civil Matemática, FCFM, Universidad de Chile. Candidato a Magister en Ciencias, mención Computación,FCFM, Universidad de Chile. Co-fundador de Asociación de Ética en Datos e Inteligencia Artificial (AEDIA), Universidad de Chile. |
(Preprint) Vargas, F. I. U., & Araya, R. (2023). Automatic detection of incoherent written responses to open-ended mathematics questions of fourth graders. PDF: https://www.researchsquare.com/article/rs-2566472/latest.pdf.
(Preprint) Urrutia, F., & Araya, R. (2023). Who's the Best Detective? LLMs vs. MLs in Detecting Incoherent Fourth Grade Math Answers. Arxiv: https://arxiv.org/abs/2304.11257, PDF: https://arxiv.org/ftp/arxiv/papers/2304/2304.11257.pdf.
Urrutia, F.; Araya, R. Do Written Responses to Open-Ended Questions on Fourth-Grade Online Formative Assessments in Mathematics Help Predict Scores on End-of-Year Standardized Tests? J. Intell. 2022, 10, 82. DOI: https://doi.org/10.3390/jintelligence10040082.
Urrutia, F. The Role of Natural Language Processing in Advancing Competency-Based Education and Mathematics Learning in Fourth Graders. ReLeLa, 19/04/2023, https://relela.com/seminars/, PDF: slides.
Urrutia, F; & Abeliuk, A. Science of science in Artificial Intelligence. CENIA: Workshop anual "Enfocando la ruta". PDF: poster
Urrutia, F. Taller 3: Minería de Datos Educacionales con técnicas de Aprendizaje de Maquinas (ML) y Procesamiento del Lenguaje Natural (NLP). En IV Congreso Internacional de Tendencias de Innovación Educativa, XXIX Jornadas Internacionales de Ingeniería de Sistemas, 2022, Arequipa, Perú. URL: https://youtu.be/4pz473T5A4Q