Autonomous recommender system architecture for virtual learning environments
This article proposes an architecture of an intelligent and autonomous recommendation system to be applied to any virtual learning environment, with the objective of efficiently recommending digital resources. The paper presents the architectural details of the intelligent and autonomous dimensions...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Emerald Publishing
2024-01-01
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| Series: | Applied Computing and Informatics |
| Subjects: | |
| Online Access: | https://www.emerald.com/insight/content/doi/10.1016/j.aci.2020.03.001/full/pdf |
| _version_ | 1827391616475725824 |
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| author | Julián Monsalve-Pulido Jose Aguilar Edwin Montoya Camilo Salazar |
| author_facet | Julián Monsalve-Pulido Jose Aguilar Edwin Montoya Camilo Salazar |
| author_sort | Julián Monsalve-Pulido |
| collection | DOAJ |
| description | This article proposes an architecture of an intelligent and autonomous recommendation system to be applied to any virtual learning environment, with the objective of efficiently recommending digital resources. The paper presents the architectural details of the intelligent and autonomous dimensions of the recommendation system. The paper describes a hybrid recommendation model that orchestrates and manages the available information and the specific recommendation needs, in order to determine the recommendation algorithms to be used. The hybrid model allows the integration of the approaches based on collaborative filter, content or knowledge. In the architecture, information is extracted from four sources: the context, the students, the course and the digital resources, identifying variables, such as individual learning styles, socioeconomic information, connection characteristics, location, etc. Tests were carried out for the creation of an academic course, in order to analyse the intelligent and autonomous capabilities of the architecture. |
| first_indexed | 2024-03-08T17:14:41Z |
| format | Article |
| id | doaj.art-4103167a38f54b61a941f1a180b1692c |
| institution | Directory Open Access Journal |
| issn | 2634-1964 2210-8327 |
| language | English |
| last_indexed | 2024-03-08T17:14:41Z |
| publishDate | 2024-01-01 |
| publisher | Emerald Publishing |
| record_format | Article |
| series | Applied Computing and Informatics |
| spelling | doaj.art-4103167a38f54b61a941f1a180b1692c2024-01-03T15:21:48ZengEmerald PublishingApplied Computing and Informatics2634-19642210-83272024-01-01201/2698810.1016/j.aci.2020.03.001Autonomous recommender system architecture for virtual learning environmentsJulián Monsalve-Pulido0Jose Aguilar1Edwin Montoya2Camilo Salazar3GIDITIC, Universidad EAFIT, Medellín, ColombiaGIDITIC, Universidad EAFIT, Medellín, ColombiaGIDITIC, Universidad EAFIT, Medellín, ColombiaGIDITIC, Universidad EAFIT, Medellín, ColombiaThis article proposes an architecture of an intelligent and autonomous recommendation system to be applied to any virtual learning environment, with the objective of efficiently recommending digital resources. The paper presents the architectural details of the intelligent and autonomous dimensions of the recommendation system. The paper describes a hybrid recommendation model that orchestrates and manages the available information and the specific recommendation needs, in order to determine the recommendation algorithms to be used. The hybrid model allows the integration of the approaches based on collaborative filter, content or knowledge. In the architecture, information is extracted from four sources: the context, the students, the course and the digital resources, identifying variables, such as individual learning styles, socioeconomic information, connection characteristics, location, etc. Tests were carried out for the creation of an academic course, in order to analyse the intelligent and autonomous capabilities of the architecture.https://www.emerald.com/insight/content/doi/10.1016/j.aci.2020.03.001/full/pdfAutonomous computingContext-awareRecommendation systems |
| spellingShingle | Julián Monsalve-Pulido Jose Aguilar Edwin Montoya Camilo Salazar Autonomous recommender system architecture for virtual learning environments Applied Computing and Informatics Autonomous computing Context-aware Recommendation systems |
| title | Autonomous recommender system architecture for virtual learning environments |
| title_full | Autonomous recommender system architecture for virtual learning environments |
| title_fullStr | Autonomous recommender system architecture for virtual learning environments |
| title_full_unstemmed | Autonomous recommender system architecture for virtual learning environments |
| title_short | Autonomous recommender system architecture for virtual learning environments |
| title_sort | autonomous recommender system architecture for virtual learning environments |
| topic | Autonomous computing Context-aware Recommendation systems |
| url | https://www.emerald.com/insight/content/doi/10.1016/j.aci.2020.03.001/full/pdf |
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