Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

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This study investigates the application of machine learning and BERT models to identify topic categories in helpful online course reviews and uncover factors that influence the overall satisfaction of learners in massive open online courses (MOOCs). The research has three main objectives: (1) to assess the effectiveness of machine learning models in classifying review helpfulness, (2) to evaluate the performance of fine-tuned BERT models in identifying review topics, and (3) to explore the factors that influence learner satisfaction across various disciplines. The study uses a MOOC corpus containing 102,184 course reviews from 401 courses across 13 disciplines. The methodology involves...

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Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial

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Large language models (LLMs) are being integrated into nursing education at a pace that outstrips the field's capacity to evaluate their consequences. Existing syntheses have mapped what LLMs can do in nursing contexts. Among those identified in this review, none has examined how their integration affects the professional development processes through which nursing expertise is formed. This critical integrative review addresses that gap.Following Whittemore and Knafl’s (2005) five-stage framework, we systematically searched four databases (PubMed/MEDLINE, Web of Science, Scopus, CINAHL) for studies published between January 2017 and December 2025, yielding 489 included studies from 47...

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

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Online learning and teaching increased in 2020, driven by the COVID-19 pandemic. As many researchers attempted to understand the impact stress had on the emotional behaviours and academic performance of students, most studies explored these pre- and during-COVID behaviours in the context of brick and mortar institutions transitioning to online delivery. There is an opportunity to compare the experiences of students in the MOOC environment in this period, particularly in terms of the difference of engagement, semantics and sentiment/stress behaviours in 2019 and 2020. In this study, we use a dataset from AdelaideX between this time period to identify the most significant features...

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