A Solution to Manage the Full Life Cycle of Learning Analytics in a Learning Management System

• Fredys Alberto Simanca Herrera ^[1] ; Rubén González Crespo ^[2] ; Luis Rodriguez Baena ^[2] ; Daniel Burgos ^[2]
  1. [1] Universidad Cooperativa de Colombia

     Universidad Cooperativa de Colombia

     Colombia

     
  2. [2] Universidad Internacional de La Rioja

     Universidad Internacional de La Rioja

     Logroño, España

     
• Localización: Revista Iberoamericana de Tecnologías del Aprendizaje: IEEE-RITA, ISSN 1932-8540, Vol. 14, Nº. 4, 2019, págs. 127-134
• Idioma: inglés
• DOI: 10.1109/rita.2019.2950148
• Texto completo no disponible (Saber más ...)
• Dialnet Métricas: 1 Cita
• Resumen

  • Learning Analytics (LA) has a significant impact in learning and teaching processes. These processes can be improved using the available data retrieved from students' activity inside the virtual classrooms of a learning management system (LMS). This process requires the development of a tool that allows one to handle the retrieved information properly. This paper presents a solution to this need, in the form of a development model and actual implementation of an LA tool. Four phases (Explanation, Diagnosis, Prediction and Prescription) are implemented in the tool, allowing a teacher to track students' activity in a virtual classroom via the Sakai LMS. It also allows for the identification of users who face challenges in their academic process and the initiation of personalised mentoring by the teacher or tutor. The use of the tool was tested on groups of students in an algorithms course in the periods 2017-1, 2017-2, 2018-1 and 2018-2, with a total of 90 students - in parallel with the control groups in the same periods that totalled 95 students - obtaining superior averages in the test groups versus the control groups, which evidenced the functionality and utility of the software.

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