A Learning Ecosystem for Linemen Training based on Big Data Components and Learning Analytics
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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Graz University of Technology
2019-05-01
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| Series: | Journal of Universal Computer Science |
| Subjects: | |
| Online Access: | https://lib.jucs.org/article/22611/download/pdf/ |
| _version_ | 1818668537287278592 |
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| author | Guillermo Santamaría-Bonfil Guillermo Escobedo-Briones Miguel Perez-Ramírez Gustavo Arroyo-Figueroa |
| author_facet | Guillermo Santamaría-Bonfil Guillermo Escobedo-Briones Miguel Perez-Ramírez Gustavo Arroyo-Figueroa |
| author_sort | Guillermo Santamaría-Bonfil |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-17T06:37:54Z |
| format | Article |
| id | doaj.art-f2e4855b3ea14907bd95c9f24e30f715 |
| institution | Directory Open Access Journal |
| issn | 0948-6968 |
| language | English |
| last_indexed | 2024-12-17T06:37:54Z |
| publishDate | 2019-05-01 |
| publisher | Graz University of Technology |
| record_format | Article |
| series | Journal of Universal Computer Science |
| spelling | doaj.art-f2e4855b3ea14907bd95c9f24e30f7152022-12-21T21:59:57ZengGraz University of TechnologyJournal of Universal Computer Science0948-69682019-05-0125554156810.3217/jucs-025-05-054122611A Learning Ecosystem for Linemen Training based on Big Data Components and Learning AnalyticsGuillermo Santamaría-Bonfil0Guillermo Escobedo-Briones1Miguel Perez-Ramírez2Gustavo Arroyo-Figueroa3CONACYT-INEELCONACYT-INEELCONACYT-INEELCONACYT-INEELLinemen 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.https://lib.jucs.org/article/22611/download/pdf/Big DataExperience APILearning AnalyticsLear |
| spellingShingle | Guillermo Santamaría-Bonfil Guillermo Escobedo-Briones Miguel Perez-Ramírez Gustavo Arroyo-Figueroa A Learning Ecosystem for Linemen Training based on Big Data Components and Learning Analytics Journal of Universal Computer Science Big Data Experience API Learning Analytics Lear |
| title | A Learning Ecosystem for Linemen Training based on Big Data Components and Learning Analytics |
| title_full | A Learning Ecosystem for Linemen Training based on Big Data Components and Learning Analytics |
| title_fullStr | A Learning Ecosystem for Linemen Training based on Big Data Components and Learning Analytics |
| title_full_unstemmed | A Learning Ecosystem for Linemen Training based on Big Data Components and Learning Analytics |
| title_short | A Learning Ecosystem for Linemen Training based on Big Data Components and Learning Analytics |
| title_sort | learning ecosystem for linemen training based on big data components and learning analytics |
| topic | Big Data Experience API Learning Analytics Lear |
| url | https://lib.jucs.org/article/22611/download/pdf/ |
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