Evaluación de un Modelo de Madurez para la adopción de Learning Analytics en instituciones de educación superior

Palabras clave: Educación Superior, Learning Analytics, Políticas Educativas, Cuestionarios, Modelos

Resumen

Learning Analytics (LA) tiene como objetivo analizar los datos generados por estudiantes y profesores en entornos online con el fin de promover acciones que conduzcan a una mejor enseñanza y aprendizaje. Los resultados de estos análisis pueden ayudar a los docentes a conocer los procesos de estudio empleados por sus alumnos, además de poder ayudar en la verificación y corrección de las actividades y prácticas educativas. Para los estudiantes, LA puede ayudar con la reflexión y la autorregulación del aprendizaje. Sin embargo, a pesar de sus beneficios, las instituciones han tenido dificultades para adoptar. En este contexto, un instrumento que puede apoyar el empleo de AL es el Modelo de Madurez (MM), que se ha utilizado en diferentes áreas del conocimiento con el fin de indicar una hoja de ruta de mejora para las organizaciones. En vista de lo anterior, este artículo tiene como objetivo presentar los resultados de la evaluación de un MM propuesto para apoyar la adopción de AL en Instituciones de Educación Superior, denominado MMALA. La evaluación, centrada en la composición del modelo, se llevó a cabo mediante un cuestionario dirigido a investigadores y profesionales del área de AL. Luego de la realización de análisis, tanto cualitativos como cuantitativos, se identificaron sugerencias de mejora para el modelo propuesto y se validó, apoyando la continuación de su desarrollo.

Biografía del autor/a

Elyda Laisa Soares Xavier Freitas, Universidad Federal de Pernambuco (UFPE) / Centro de Computación

Graduated in Information Systems from the University of Pernambuco (UPE) and Master in Computer Science from the Federal University of Pernambuco (UFPE). Has experience in Oracle Database Management, SQL, PL / SQL, Data Warehouse and Business Intelligence development, Cloud Database and programming. She is currently an assistant professor at the University of Pernambuco at the Caruaru campus and a doctoral student at the UFPE Computer Center, conducting research in the areas of Learning Analytics and Non-Relational Databases.

Fernando da Fonseca de Souza, Universidad Federal de Pernambuco (UFPE) / Centro de Computación

He holds a Bachelor's degree in Civil Engineering from the Federal University of Pernambuco (1976), master's degree in computer science from the Federal University of Pernambuco (1982) and a Ph.D. in Computer Sscience from the University Of Kent At Canterbury (1990). He is currently an Associate Professor in the Informatics Center of the Federal University of Pernambuco. He has experience in the area of computer science with an emphasis in databases, working mainly on the following themes: Strategic Information Management, Cloud Databases, Virtual Learning Environments and Accessibility.

Vinicius Cardoso Garcia, Universidad Federal de Pernambuco (UFPE) / Centro de Computación

Dr. Vinicius Garcia is an adjunct professor in the Software Engineering area at Federal University of Pernambuco, Brazil, where he is member of the LABES (Software Engineering Lab), is a senior member of the RiSE (Reuse in Software Engineering) Group and actually is the leader of the ASSERT (Advanced System and Software Engineering Research Technologies) Lab.

Taciana Pontual da Rocha Falcão, Departamento de Computação. Universidade Federal Rural de Pernambuco (UFRPE)

is a professor and researcher at the Federal Rural University of Pernambuco (UFRPE) in the area of ​​Human-Computer Interaction (IHC) and a member of the Graduate Programs in: Technology and Management in Distance Education (PPGTEG-UFRPE) and Applied Informatics (PPGIA) -UFRPE) PhD from the Institute of Education (IoE) - University of London, UK, her doctoral research dealt with how tangible interfaces can contribute to the learning of children with intellectual difficulties. Graduated (2004) and master's (2007) in Computer Science from the Federal University of Pernambuco. He was an interaction designer at CESAR Recife from 2010 to 2013, and a researcher at the London Knowledge Lab (University of London) in the area of ​​tangible interfaces for education, from 2008 to 2010. He has also worked at NAAH / S-Recife, activities center for children with high skills. He did post-doctoral studies at McGill University - Canada, working with the development of technologies to support the communication of the elderly. His interests include: tangible interfaces for education, technologies for education, teaching programming, computational thinking, digital games in educational contexts, usability, user experience and accessibility.

Elaine Cristina Moreira Marques, Departamento de Computação. Universidade Federal Rural de Pernambuco (UFRPE)
    PhD student in Biometrics and Applied Statistics at the Federal Rural University of Pernambuco (UFRPE) - Recife (2019). Master in Biometrics and Applied Statistics from the Federal Rural University of Pernambuco (UFRPE) - Recife (2018). Graduated in Statistics (Bachelor) from the Federal University of Paraíba - João Pessoa (2015). She is currently a Distance Tutor at the Federal Institute of Education, Science and Technology of Pernambuco - (IFPE) - Recife (2019). She was substitute professor at the Federal Rural University of Pernambuco (UFRPE) - Recife (2018). She was an intern at the Brazilian Micro and Small Business Support Service Company - SEBRAE / PB, at the Strategic Management and Monitoring Unit (UGEM) - João Pessoa (2015). Works in the area of ​​Probability and Statistics, Biological Testing and Bioequivalence, Experiment Planning and in the area of ​​Artificial Intelligence (AI) with an emphasis on Text Mining (MT), with a focus on information retrieval (IR) and text classification (TC) ).
Rafael Ferreira Mello, Departamento de Computação. Universidade Federal Rural de Pernambuco (UFRPE)

Rafael Ferreira Mello is a doctor in computer science with research interests that include natural language processing, learning analytics and educational technology. He is a professor at the Federal Rural University of Pernambuco, Brazil, where he is one of the coordinators of the Artificial Intelligence Laboratory (https://aiboxlab.org/), develops several initiatives related to learning analytics (LA) and supervises undergraduate students and postgraduate studies. Dr. Mello held a postdoc at the University of Edinburgh School of Informatics in 2018, where he continues to have collaborations. He has worked on several multinational research projects, involving academic partners and companies in Europe, Australia, the United States and Latin America. Dr. Mello's previous experience also includes a research project funded by Hewlett-Packard, where he served as a technical leader. A key theme of his recent research has been the use of natural language processing applied as education and themes more focused on text analysis such as summarization and classification.

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Publicado
2020-12-13
Cómo citar
Freitas, E., Souza, F., Garcia, V., Falcão, T., Marques, E., & Mello, R. (2020). Evaluación de un Modelo de Madurez para la adopción de Learning Analytics en instituciones de educación superior. Revista Latinoamericana De Tecnología Educativa - RELATEC, 19(2), 101-113. https://doi.org/10.17398/1695-288X.19.2.101
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Artículos / Articles