A Learning Ecosystem for Linemen Training based on Big Data Components and Learning Analytics
Guillermo Santamaría-Bonfil (CONACYT-INEEL, México)
Guillermo Escobedo-Briones (CONACYT-INEEL, México)
Miguel Perez-Ramírez (CONACYT-INEEL, México)
Gustavo Arroyo-Figueroa (CONACYT-INEEL, México)
Abstract: Linemen training is mandatory, complex, and hazardous. Electronic technologies, such as virtual reality or learning management systems, have been used to improve such training, however these lack of interoperability, scalability, and do not exploit trace data generated by users in these systems. In this paper we present our ongoing work on developing a Learning Ecosystem for Training Linemen in Maintenance Maneuvers using the Experience API standard, Big Data components, and Learning Analytics. The paper describes the architecture of the ecosystem, elaborates on collecting learning experiences and emotional states, and applies analytics for the exploitation of both, legacy and new data. In the former, we exploit legacy e-Learning data for building a Domain model using Text Mining and unsupervised clustering algorithms. In the latter we explore self-reports capabilities for gathering educational support content, and assessing students emotional states. Results show that, a suitable domain model for personalizing maneuvers linemen training path can be built from legacy text data straightforwardly. Regarding self reports, promising results were obtained for tracking emotional states and collecting educational support material, nevertheless, more work around linemen training is required.
Keywords: Big Data, Experience API, Learning Analytics, Learning Ecosystems, Text Mining
Categories: L.1.0, L.2.5, L.3.0, L.3.5