An xAPI Application Profile to Monitor Self-Regulated Learning Strategies
Self-regulated learning (SRL) is being promoted and adopted increasingly due to the needs of current education, student centered and focused on competence development. One of the main components of SRL is learners' self-monitoring, which eventually contributes to a better performance. Monitorin...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2018-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8423185/ |
| _version_ | 1818618325850128384 |
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| author | Mario Manso-Vazquez Manuel Caeiro-Rodriguez Martin Llamas-Nistal |
| author_facet | Mario Manso-Vazquez Manuel Caeiro-Rodriguez Martin Llamas-Nistal |
| author_sort | Mario Manso-Vazquez |
| collection | DOAJ |
| description | Self-regulated learning (SRL) is being promoted and adopted increasingly due to the needs of current education, student centered and focused on competence development. One of the main components of SRL is learners' self-monitoring, which eventually contributes to a better performance. Monitoring is also important for teachers, as it enables them to know to what extent their learners are doing well and progressing properly. At the same time, the use of technology for learning is now common and facilitates monitoring. Nevertheless, the available software still offers poor support from the SRL point of view, especially, for SRL monitoring. This clashes with the growth of learning analytics and educational data mining. The main issue is the wide variety of SRL actions that need to be captured, commonly performed in different tools, and the need to integrate them to support the development of analytics and data mining developments, making imperative the search of interoperable solutions. This paper focuses on the standardization of SRL traces to enable data collection from multiple sources and data analysis with the goal of easing the monitoring process for teachers and learners. First, the paper analyzes current monitoring software and its limitations for SRL. Then, after a brief analysis of available standards on this area, an application profile for the eXperience API specification is proposed to enable the interoperable recording of the SRL traces. The paper describes the process followed to create the profile, from the analysis to the final implementation, including the selection of the interactions that represent relevant SRL actions, the selection of vocabularies to record them and a case study. |
| first_indexed | 2024-12-16T17:19:48Z |
| format | Article |
| id | doaj.art-599d374290ab4bb792ba452900ff2b0f |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T17:19:48Z |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-599d374290ab4bb792ba452900ff2b0f2022-12-21T22:23:12ZengIEEEIEEE Access2169-35362018-01-016424674248110.1109/ACCESS.2018.28605198423185An xAPI Application Profile to Monitor Self-Regulated Learning StrategiesMario Manso-Vazquez0https://orcid.org/0000-0001-8785-2406Manuel Caeiro-Rodriguez1Martin Llamas-Nistal2Department of Telematic Engineering, University of Vigo, Vigo, SpainDepartment of Telematic Engineering, University of Vigo, Vigo, SpainDepartment of Telematic Engineering, University of Vigo, Vigo, SpainSelf-regulated learning (SRL) is being promoted and adopted increasingly due to the needs of current education, student centered and focused on competence development. One of the main components of SRL is learners' self-monitoring, which eventually contributes to a better performance. Monitoring is also important for teachers, as it enables them to know to what extent their learners are doing well and progressing properly. At the same time, the use of technology for learning is now common and facilitates monitoring. Nevertheless, the available software still offers poor support from the SRL point of view, especially, for SRL monitoring. This clashes with the growth of learning analytics and educational data mining. The main issue is the wide variety of SRL actions that need to be captured, commonly performed in different tools, and the need to integrate them to support the development of analytics and data mining developments, making imperative the search of interoperable solutions. This paper focuses on the standardization of SRL traces to enable data collection from multiple sources and data analysis with the goal of easing the monitoring process for teachers and learners. First, the paper analyzes current monitoring software and its limitations for SRL. Then, after a brief analysis of available standards on this area, an application profile for the eXperience API specification is proposed to enable the interoperable recording of the SRL traces. The paper describes the process followed to create the profile, from the analysis to the final implementation, including the selection of the interactions that represent relevant SRL actions, the selection of vocabularies to record them and a case study.https://ieeexplore.ieee.org/document/8423185/Educational technologylearning analyticsself-regulated learningstandardization |
| spellingShingle | Mario Manso-Vazquez Manuel Caeiro-Rodriguez Martin Llamas-Nistal An xAPI Application Profile to Monitor Self-Regulated Learning Strategies IEEE Access Educational technology learning analytics self-regulated learning standardization |
| title | An xAPI Application Profile to Monitor Self-Regulated Learning Strategies |
| title_full | An xAPI Application Profile to Monitor Self-Regulated Learning Strategies |
| title_fullStr | An xAPI Application Profile to Monitor Self-Regulated Learning Strategies |
| title_full_unstemmed | An xAPI Application Profile to Monitor Self-Regulated Learning Strategies |
| title_short | An xAPI Application Profile to Monitor Self-Regulated Learning Strategies |
| title_sort | xapi application profile to monitor self regulated learning strategies |
| topic | Educational technology learning analytics self-regulated learning standardization |
| url | https://ieeexplore.ieee.org/document/8423185/ |
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