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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| Online-Zugang: | https://arxiv.org/abs/2512.12105 |
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| _version_ | 1866911323177091072 |
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| author | Sachete, Andreia dos Santos Loiola, Alba Valeria de SantAnna de Freitas Rossi, Fabio Diniz de Lima, Jose Valdeni Gomes, Raquel Salcedo |
| author_facet | Sachete, Andreia dos Santos Loiola, Alba Valeria de SantAnna de Freitas Rossi, Fabio Diniz de Lima, Jose Valdeni Gomes, Raquel Salcedo |
| contents | Student learning development must involve more than just correcting or incorrect questions. However, most adaptive learning methods in Virtual Learning Environments are based on whether the student's response is incorrect or correct. This perspective is limited in assessing the student's learning level, as it does not consider other elements that can be crucial in this process. The objective of this work is to conduct a Systematic Literature Review (SLR) to elucidate which learning indicators influence student learning and which can be implemented in a VLE to assist in adaptive learning. The works selected and filtered by qualitative assessment reveal a comprehensive approach to assessing different aspects of the learning in virtual environments, such as motivation, emotions, physiological responses, brain imaging, and the students' prior knowledge. The discussion of these new indicators allows adaptive technology developers to implement more appropriate solutions to students' realities, resulting in more complete training. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_12105 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Beyond right or wrong: towards redefining adaptive learning indicators in virtual learning environments Sachete, Andreia dos Santos Loiola, Alba Valeria de SantAnna de Freitas Rossi, Fabio Diniz de Lima, Jose Valdeni Gomes, Raquel Salcedo Computers and Society Distributed, Parallel, and Cluster Computing Student learning development must involve more than just correcting or incorrect questions. However, most adaptive learning methods in Virtual Learning Environments are based on whether the student's response is incorrect or correct. This perspective is limited in assessing the student's learning level, as it does not consider other elements that can be crucial in this process. The objective of this work is to conduct a Systematic Literature Review (SLR) to elucidate which learning indicators influence student learning and which can be implemented in a VLE to assist in adaptive learning. The works selected and filtered by qualitative assessment reveal a comprehensive approach to assessing different aspects of the learning in virtual environments, such as motivation, emotions, physiological responses, brain imaging, and the students' prior knowledge. The discussion of these new indicators allows adaptive technology developers to implement more appropriate solutions to students' realities, resulting in more complete training. |
| title | Beyond right or wrong: towards redefining adaptive learning indicators in virtual learning environments |
| topic | Computers and Society Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2512.12105 |