Current state of Learning Management Systems’ log data-based learning analytics

Hernández García, Ángel; Acquila Natale, Emiliano y Chaparro Pelaez, Jose Julian (2017). Current state of Learning Management Systems’ log data-based learning analytics. En: "17th Biennial EARLI Conference for Research on Learning and Instruction", 27/08/2017-02-09.2017, Tampere (Finlandia). pp. 1-3.

Descripción

Título: Current state of Learning Management Systems’ log data-based learning analytics
Autor/es:
  • Hernández García, Ángel
  • Acquila Natale, Emiliano
  • Chaparro Pelaez, Jose Julian
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 17th Biennial EARLI Conference for Research on Learning and Instruction
Fechas del Evento: 27/08/2017-02-09.2017
Lugar del Evento: Tampere (Finlandia)
Título del Libro: Education in the Crossroads of Economy and Politics. Role of Research in the Advancement of Public Good
Fecha: 2 Septiembre 2017
Materias:
Palabras Clave Informales: Learning Analytics, Educational technology, Learning Technologies, E-learning/Online learning, Learning and Instructional Technology, Technology
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Ingeniería de Organización, Administración de Empresas y Estadística
Grupo Investigación UPM: Innovación, Propiedad industrial y Política tecnológica INNOPRO
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

The application of learning analytics techniques to log data from Learning Management Systems (LMS) has raised increasing interest in the past years. Advances in this field include the selection of adequate indicators and development of research frameworks. However, log data-based analysis of courses still poses some obstacles and challenges for researchers and practitioners in order to effectively improve and optimize learning processes. This paper highlights the challenges, and presents approaches that can help complement log data-based learning analytics. These approaches may be especially effective in collaborative settings, and include analysis of information flows, social interactions, and content analysis. This conceptual work aims to promote the debate surrounding the need for comprehensive and comparable studies and frameworks, and to foster advances in log data-based learning analytics.

Más información

ID de Registro: 47250
Identificador DC: http://oa.upm.es/47250/
Identificador OAI: oai:oa.upm.es:47250
Depositado por: Dr. Ángel Hernández García
Depositado el: 17 Jul 2017 10:04
Ultima Modificación: 17 Jul 2017 10:04
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