Bibliografía: 2025
Nº de publicaciones: 636Detalles Cerrar β
Tipo: artículo
Metodología: estudio empírico
Temas: inteligencia artificial
Resumen:
This study investigates the effects of adaptive feedback generated by large language models (LLMs), specifically ChatGPT, on performance in a written diagnostic reasoning task among German pre-service teachers (n = 269). Additionally, the study analyzed user evaluations of the feedback and feedback processing time. Diagnostic reasoning, a critical skill for making informed pedagogical decisions, was assessed through a writing task integrated into a teacher preparation course. Participants were randomly assigned to receive either adaptive feedback generated by ChatGPT or static feedback prepared in advance by a human expert, which was identical for all participants in that condition, before...
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Tipo: artículo
Metodología: estudio empírico
Temas: inteligencia artificial
Resumen:
As generative artificial intelligence (GenAI) tools become increasingly integrated into educational environments, concerns have emerged about their potential to facilitate academic dishonesty. Drawing on the modified theory of planned behavior, this study aimed to understand undergraduate students’ academic cheating behaviors using GenAI. The study conducted a mixed-method approach, utilizing focus groups and polls to gather insights from 25 undergraduate students enrolled in a course that incorporated GenAI into its pedagogical design in the United States. The results revealed that the integration of GenAI into higher education is perceived as inevitable. While students clearly recognized...
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Tipo: artículo
Metodología: estudio empírico
Temas: inteligencia artificial
Resumen:
With the rapid penetration of generative artificial intelligence (AI) in higher education, university teachers' AI competency has become a critical determinant of effective technology integration in teaching. However, systematic and empirically validated intervention frameworks to support the development of this competency remain scarce. To address this gap, this study implemented a six-month professional development (PD) programme grounded in the Intelligent-TPACK framework and evaluated its effectiveness using a quasi-experimental pre-test-post-test design. A total of 64 teachers participated in the PD programme (experimental group), while pre- and post-test data were also collected from...
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Tipo: artículo
Metodología: estudio empírico
Temas: inteligencia artificial
Resumen:
The importance and challenge of Algebra learning is widely recognized, with students across the U.S. facing difficulties due to the subject's complexity. While extensive research has focused on enhancing Algebra learning in K-12 education, the reusability, scalability, and effectiveness of the strategies employed (e.g., manual interventions and digital tutoring platforms) remain limited. Conversational AI (ConvAI), enabled by the advancement of large language models (LLMs), emerges as a potential tool for automatic, personalized, and effective student support. However, ethical concerns surrounding diversity, safety, sentiment, and stereotype associated with ConvAI are prominent, and...
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Tipo: artículo
Metodología: trabajo teórico
Temas: inteligencia artificial
Resumen:
Comparative judgment (CJ) is an assessment method commonly used for assessing essay quality, where assessors compare pairs of essays and judge which essays are superior in quality. A psychometric model is used to convert judgments into quality scores. Although CJ yields reliable and valid scores, its widespread implementation in educational practice is hindered by its inefficiency and limited feedback capabilities. This conceptual study explores how Natural Language Processing (NLP) can address these limitations, drawing upon existing NLP techniques and the very limited research on their integration within CJ. More specifically, we argue that, at the start of the assessment, initial essay...
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Tipo: artículo
Metodología: estudio empírico
Temas: inteligencia artificial
Resumen:
This multi-informant mixed-methods study uses a concurrent parallel sampling approach to investigate undergraduate students' and faculty's perceptions of utilizing AI in teaching and learning at U.S. universities. A survey developed based on the Technology Acceptance Model, Social Influence Theory, and existing literature was implemented to collect undergraduate students' data regarding students' perceived AI learning environment, perceived others' attitudes toward AI, and personal attitudes toward AI. Faculty's opinions were collected through semi-structured interviews in accordance with the survey variables. Quantitative findings indicated that the effect of the AI learning environment on...
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Tipo: artículo
Metodología: estudio empírico
Temas: inteligencia artificial
Resumen:
This study investigates the factors influencing teachers within the Israeli education system toward the adaptations of artificial intelligence (AI) in teaching by examining the roles of technological self-efficacy (TSE) and a sense of coherence (SOC). Drawing on the Technology Acceptance Model (TAM), a sample of 200 Arab and Jewish teachers in Israel completed online questionnaires. The findings indicated a positive attitude towards AI among teachers. We found a significant positive correlation between perceived usefulness, perceived ease of use, and positive attitude towards AI. TSE fully mediated the relationship between attitude towards AI and adoption intentions AI, while a SOC...
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Tipo: artículo
Metodología: estudio empírico
Temas: inteligencia artificial
Resumen:
This research assesses the effectiveness of state-of-the-art large language models (LLMs), including ChatGPT, Llama, Aya, Jais, and ACEGPT, in the task of Arabic automated essay scoring (AES) using the AR-AES dataset. It explores various evaluation methodologies, including zero-shot, few-shot in context learning, and fine-tuning, and examines the influence of instruction-following capabilities through the inclusion of marking guidelines within the prompts. A mixed-language prompting strategy, integrating English prompts with Arabic content, was implemented to improve model comprehension and performance. Among the models tested, ACEGPT demonstrated the strongest performance across the...
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Tipo: artículo
Metodología: estudio empírico
Temas: inteligencia artificial
Resumen:
Generative artificial intelligence (GenAI) in higher education has introduced a spectrum of ethical challenges, significantly impacting learning outcomes, pedagogies, and assessments. Based on the experiences and perspectives of students and teachers at a research-intensive university in Hong Kong, the study draws on qualitative interview data with 58 undergraduate and graduate students and 12 teachers conducted in early 2025. Through the concept of policy trajectories (Ball, 1993; Ball et al., 2012), the research analyses the interconnections between material contexts and discursive constructions in how AI policies (and their absence) are framed, interpreted, enacted, and resisted. The...
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Tipo: artículo
Metodología: estudio empírico
Temas: inteligencia artificial
Resumen:
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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