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Bibliografía: inglés

Nº de publicaciones: 1921
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From teachers to chatbots: Scaffolded corrective feedback and student trust in online L2 English classrooms
Ali Soyoof, Barry Lee Reynolds, Ehsan Rassaei (2026)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Texto completo

Teacher corrective feedback (TCF) plays a vital role in second language (L2) learning. Recent studies have examined feedback provided by both human teachers and large language models (LLMs). However, little is known about how students' trust differs toward scaffolded corrective feedback (SCF)—that is, feedback that incrementally progresses from indirect to direct during interaction—when it is provided by an LLM such as ChatGPT versus a language teacher. To address this gap, this study compared the effects of SCF, delivered by language teachers and ChatGPT, on L2 learning outcomes and student trust. Using a mixed-methods design, 40 lower-intermediate Iranian learners of English as a foreign...

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A Bayesian active learning approach to comparative judgement within education assessment
Andy Gray, Alma Rahat, Tom Crick (2024)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Texto completo

Assessment is a crucial part of education. Traditional marking is a source of inconsistencies and unconscious bias, placing a high cognitive load on the assessors. One approach to address these issues is comparative judgement (CJ). In CJ, the assessor is presented with a pair of items of work, and asked to select the better one. Following a series of comparisons, a rank for any item may be derived using a ranking model, for example, the Bradley-Terry model, based on the pairwise comparisons. While CJ is considered to be a reliable method for conducting marking, there are concerns surrounding its transparency, and the ideal number of pairwise comparisons to generate a reliable estimation of...

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Students’ engagement with generative AI in academic learning: A self-determination theory and epistemic network analysis study
Razia Isaeva, H. Nuran Caner, Mustafa Caner (2026)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Texto completo

This qualitative case study examines undergraduate students’ engagement with generative artificial intelligence (GenAI) in academic learning in an English-medium university setting. This study employs self-determination theory (SDT) as the primary interpretive framework, treating technology acceptance perceptions (e.g., usefulness and ease of use) as descriptive cues rather than explanatory constructs. Data from 23 semi-structured interviews were analyzed using reflexive thematic analysis, complemented by epistemic network analysis (ENA) to examine the structural relationships among themes in students’ discourse, with automated coding validated against a manually coded subset. Students...

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A critical review of teaching and learning artificial intelligence (AI) literacy: Developing an intelligence-based AI literacy framework for primary school education
Iris Heung Yue Yim (2024)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial

Resumen:

Texto completo

Artificial intelligence (AI) literacy education mainly targets secondary and university students, often overlooking the unique needs of younger students. This gap in AI literacy primary school education presents theoretical and pedagogical challenges. Despite the pervasive influence of AI, which can exacerbate inequalities and raise ethical challenges, primary students often lack an understanding of AI principles and mechanisms. Recent developments in age-appropriate AI learning tools have extended AI literacy to primary schools, but AI literacy frameworks for this age group remain underdeveloped. This study aims to conceptualize AI literacy by analyzing existing theoretical frameworks and...

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Effects of integrating an open learner model with AI-enabled visualization on students' self-regulation strategies usage and behavioral patterns in an online research ethics course
Jerry Chih-Yuan Sun, Hsueh-Er Tsai, Wai Ki Rebecca Cheng (2023)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Texto completo en HTML

This study seeks to understand the effects of a personalized learning platform, which applied an open learner model with self-regulation and AI-enabled data visualization features, on students' self-regulated learning strategies used and behavioral patterns during their self-directed online learning process. Results were based on a self-regulated learning scale and a prior knowledge test from 182 university students and supplemented with students' system logs to understand their behavioral patterns while interacting with the personalized learning platform. It showed that the combined self-regulation and data visualization features (dual features) improve student performance via self...

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Safer interaction with IVAs: The impact of privacy literacy training on competent use of intelligent voice assistants
André Markus, Maximilian Baumann, Jan Pfister (2025)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Texto completo

Intelligent voice assistants (IVAs) are widely used in households but can compromise privacy by inadvertently recording or encouraging personal disclosures through social cues. Against this backdrop, interventions that promote privacy literacy, sensitize users to privacy risks, and empower them to self-determine IVA interactions are becoming increasingly important. This work aims to develop and evaluate two online training modules that promote privacy literacy in the context of IVAs by providing knowledge about the institutional practices of IVA providers and clarifying users' privacy rights when using IVAs. Results show that the training modules have distinct strengths. For example,...

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Evaluation of an artificial intelligence literacy course for university students with diverse study backgrounds
Siu-Cheung Kong, William Man-Yin Cheung, Guo Zhang (2021)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Texto completo

A few limited efforts have been made to promote artificial intelligence (AI) literacy for citizens. The objective of this study was to design, implement and evaluate an AI literacy course for university students. One of the study's research questions was whether university students from a variety of disciplines could develop a conceptual understanding of AI through a literacy course. We promoted this course to 4000 students and recruited 120 volunteer participants to attend and complete the 7-h course. The results of our pre-course and post-course surveys indicated that the participants made significant progress in understanding AI concepts, felt empowered to work with AI. These findings...

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Two years of innovation: A systematic review of empirical generative AI research in language learning and teaching
Belle Li, Yaling Lily Tan, Chaoran Wang (2025)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial

Resumen:

Texto completo

This systematic review examines the evolution of empirical research on generative AI in language learning and teaching from 2023 to 2024. Following PRISMA guidelines, we analyzed 144 peer-reviewed articles from Web of Science, Scopus, and ERIC databases to explore the field's progression, including identifying new developments, shifts in research priorities, and emerging themes that have arisen compared to the first year. The findings reveal an exponential growth in publications, with a significant shift from primarily exploratory inquiries to more systematic and empirically driven investigations. The analysis identified six main research foci: Perceptions and attitudes, psychological and...

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A case study of using Alexa for out-of-class, self-directed Japanese language learning
Gilbert Dizon, Daniel Tang, Yumi Yamamoto (2022)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Texto completo

Intelligent personal assistants, otherwise known as virtual assistants, are artificial intelligence-powered conversational agents that utilize machine learning to understand and appropriately respond to user requests. In recent years, research interest on the use of this emerging technology for foreign language learning has increased. Several studies have examined the use of intelligent personal assistants for English as a foreign language learning. However, no study has studied intelligent personal assistants in the context of a non-English foreign language. Thus, this case study addressed this gap in the research by investigating the out-of-class, self-directed use of the intelligent...

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Using LLMs to bring evidence-based feedback into the classroom: AI-generated feedback increases secondary students’ text revision, motivation, and positive emotions
Jennifer Meyer, Thorben Jansen, Ronja Schiller (2024)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Texto completo

Writing proficiency is an essential skill for upper secondary students that can be enhanced through effective feedback. Creating feedback on writing tasks, however, is time-intensive and presents a challenge for educators, often resulting in students receiving insufficient or no feedback. The advent of text-generating large language models (LLMs) offers a promising solution, namely, automated evidence-based feedback generation. Yet, empirical evidence from randomized controlled studies about the effectiveness of LLM-generated feedback is missing. To address this issue, the current study compared the effectiveness of LLM-generated feedback to no feedback. A sample of N = 459 upper secondary...

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