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Bibliografía: inglés

Nº de publicaciones: 1921
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How well can LLMs grade essays in Arabic?
Rayed Ghazawi, Edwin Simpson (2025)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Texto completo

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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Smart MOOC integrated with intelligent tutoring: A system architecture and framework model proposal
Ramazan Yilmaz, Halil Yurdugül, Fatma Gizem Karaoglan Yilmaz (2022)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Temas: inteligencia artificial

Resumen:

Texto completo

Massive Open Online Courses (MOOCs) are a type of Learning Management Systems (LMSs), but it seems that the influence of the instructor in these systems is minimal or simply lacking. These systems present the learning content and materials to all learners attending the course in the same way and fail to offer individualized instruction that recognizes the individual differences and needs of the learners. It is reported that such problems can be eliminated by making the new generation intelligent learning systems. However, there is still an ongoing search for making such systems intelligent and a conceptual discussion concerning them. Integrating an intelligent tutoring system (ITS) with...

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Investigating the affordances of OpenAI's large language model in developing listening assessments
Vahid Aryadoust, Azrifah Zakaria, Yichen Jia (2024)
Computers & Education: Artificial Intelligence
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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Texto completo

To address the complexity and high costs of developing listening tests for test-takers of varying proficiency levels, this study investigates the capabilities of an OpenAI's large language model, ChatGPT 4, in developing listening assessments. Employing prompt engineering and fine-tuning of prompts, the study specifically focuses on creating listening scripts and test items using ChatGPT 4 for test-takers across a spectrum of proficiency levels (academic, low, intermediate, and advanced). For comparability, the 24 topics of these scripts were selected from topics found in academic listening tests. We conducted two types of analyses to evaluate the quality of the output. First, we performed...

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Scaffolding critical thinking with generative AI: Design principles for integrating large language models in higher education
Mireia Vendrell, Samantha-Kaye Johnston (2026)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial

Resumen:

Texto completo

The rapid adoption of Large Language Models (LLMs) such as GPT-4 and DeepSeek R1 is transforming learning in higher education, yet unstructured use can weaken critical thinking by encouraging cognitive offloading, metacognitive disengagement, and reduced epistemic agency. This paper presents a conceptual and normative analysis that synthesises research from cognitive psychology, educational theory, and AI ethics to develop a design-oriented pedagogical framework for integrating LLMs in ways that strengthen, rather than displace, higher-order thinking. Grounded in design-based research principles, the framework identifies six essential processes that underpin critical engagement: conceptual...

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The effect of student acceptance on learning outcomes: AI-generated short videos versus paper materials
Yidi Zhang, Margarida Lucas, Pedro Bem-haja (2024)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Texto completo

The use of video and paper-based materials is commonly widespread in foreign language learning (FLL). It is well established that the level of acceptance of these materials influences learning outcomes, but there is lack of evidence regarding the use and related impact of videos generated by artificial intelligence (AI) on these aspects. This paper used linear mixed models and path analysis to investigate the influence of student acceptance of AI-generated short videos on learning outcomes compared to paper-based materials. Student acceptance was assessed based on perceived ease of use (PEU), perceived usefulness (PU), attitude (A), intentions (I), and concentration (C). The results...

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Artificial intelligence ethical awareness of university students in Ghana: A network and latent profile analyses
Bernard Yaw Sekyi Acquah, Iddrisu Salifu, Francis Arthur (2026)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Texto completo

Artificial intelligence is becoming increasingly integrated into students’ academic lives in Ghana, making it crucial to examine their perspectives on ethical dimensions. Against this backdrop, this study assesses the artificial intelligence ethical awareness (AIEA) among 509 Ghanaian university students across the dimensions of human autonomy, beneficence, and fairness, based on AIEA scale originally developed and validated in Hong Kong. The confirmatory factor analysis supported the scale’s three-factor structure within this setting. The network analysis also demonstrated meaningful interconnection among the dimensions, with select items serving as conceptual links, most prominently tying...

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RICE AlgebraBot: Lessons learned from designing and developing responsible conversational AI using induction, concretization, and exemplification to support algebra learning
Chenglu Li, Wanli Xing, Yukyeong Song (2025)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Texto completo

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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Unidades temáticas y aspectos del conocimiento léxico en los manuales de ELE
Claudia H. Sánchez Gutiérrez, Pablo Robles García, Diego Alins Breda (2021)
Revista Nebrija de Lingüística Aplicada a la Enseñanza de Lenguas
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: vocabulario

Resumen:

Texto completo

Learning vocabulary entails the development of several aspects of lexical knowledge. Concretely, Nation (2001) proposed nine aspects of particular relevance. This study aims at analyzing their treatment in four L2 Spanish textbooks. Seven vocabulary themes that were present in all textbooks, were selected for analysis since certain aspects of lexical knowledge are more likely to appear in specific themes. For example, greetings would promote the introduction of constraints of use since Spanish greetings depend on the formality of the situation and the relationship between interlocutors; whereas introducing the parts of a house would not implicate contextual constraints. Results show that...

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Opportunities of natural language processing for comparative judgment assessment of essays
Michiel De Vrindt, Anaïs Tack, Wim Van den Noortgate (2025)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial

Resumen:

Texto completo

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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Explainable Artificial Intelligence in education
Hassan Khosravi, Simon Buckingham Shum, Guanliang Chen (2022)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial

Resumen:

Texto completo

There are emerging concerns about the Fairness, Accountability, Transparency, and Ethics (FATE) of educational interventions supported by the use of Artificial Intelligence (AI) algorithms. One of the emerging methods for increasing trust in AI systems is to use eXplainable AI (XAI), which promotes the use of methods that produce transparent explanations and reasons for decisions AI systems make. Considering the existing literature on XAI, this paper argues that XAI in education has commonalities with the broader use of AI but also has distinctive needs. Accordingly, we first present a framework, referred to as XAI-ED, that considers six key aspects in relation to explainability for...

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