Publicación: Using LSTM to Identify Help Needs in Primary School Scratch Students
dc.contributor.author | Imbernón Cuadrado, Luis Eduardo | |
dc.contributor.author | Manjarrés Riesco, Ángeles | |
dc.contributor.author | Paz López, Félix de la | |
dc.date.accessioned | 2024-05-20T11:42:10Z | |
dc.date.available | 2024-05-20T11:42:10Z | |
dc.date.issued | 2023-11-30 | |
dc.description.abstract | first-in-class distance calculation method for block-based programming languages has been used in a Long Short-Term Memory (LSTM) model, with the aim of identifying when a primary school student needs help while he/she carries out Scratch exercises. This model has been trained twice: the first time taking into account the gender of the students, and the second time excluding it. The accuracy of the model that includes gender is 99.2%, while that of the model that excludes gender is 91.1%. We conclude that taking into account gender in training this model can lead to overfitting, due to the under-representation of girls among the students participating in the experiences, making the model less able to identify when a student needs help. We also conclude that avoiding gender bias is a major challenge in research on educational systems for learning computational thinking skills, and that it necessarily involves effective and motivating gender-sensitive instructional design. | en |
dc.description.version | versión publicada | |
dc.identifier.doi | http://doi.org/10.3390/app132312869 | |
dc.identifier.issn | 2076-3417 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14468/12440 | |
dc.journal.title | Applied Sciences | |
dc.journal.volume | 13 | |
dc.language.iso | en | |
dc.publisher | MDPI | |
dc.relation.center | E.T.S. de Ingeniería Informática | |
dc.relation.department | Inteligencia Artificial | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/deed.es | |
dc.subject.keywords | distance education | |
dc.subject.keywords | language models (LMs) | |
dc.subject.keywords | LSTM model | |
dc.subject.keywords | teaching with Scratch | |
dc.subject.keywords | ethics in AI | |
dc.title | Using LSTM to Identify Help Needs in Primary School Scratch Students | es |
dc.type | journal article | en |
dc.type | artículo | es |
dspace.entity.type | Publication | |
relation.isAuthorOfPublication | f1dc37a9-f950-4aa8-b83c-632da9961d8d | |
relation.isAuthorOfPublication | b3e97894-ffd4-4bda-b6d2-14ebd729e14a | |
relation.isAuthorOfPublication.latestForDiscovery | f1dc37a9-f950-4aa8-b83c-632da9961d8d |
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