Bibliografía sobre IA y ELE

El objetivo de esta investigación es analizar las estrategias de actitud crítica de los maestros en formación inicial en el uso de dos herramientas de Inteligencia Artificial Generativa (IAG), ChatGPT y Perplexity, en el proceso de construcción de un texto expositivo académico. Esta investigación deriva de una propuesta didáctica implementada en la Facultad de Educación (Universitat de Barcelona), en la que participaron 26 maestros en formación inicial en el Grado de Educación Infantil. El corpus de datos está constituido por 26 textos expositivos, 74 borradores de proceso y 26 reflexiones sobre su proceso de escritura. El análisis de contenido muestra tres tendencias en la forma en la que...

Modeling the structural relationship among primary students’ motivation to learn artificial intelligence

Pei-Yi Lin, Ching Sing Chai, Morris Siu-Yung Jong (2021)

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Tipo: artículo

Metodología: estudio empírico

Temas:
IA y educación estudio empírico

Resumen:

The recent advances in artificial intelligence (AI) present both challenges and opportunities for educational practitioners. A new AI curriculum has been developed and piloted in many primary schools in Beijing, China. The present study had two aims: (1) to test the factor structure of students’ motivation to learn AI and (2) to examine possible gender differences in students’ motivation to learn AI. This online questionnaire–based research recruited 420 primary students from the piloting schools. Structural equation modeling was employed to test a hypothesized model comprising six motivational factors and strategies: (1) intrinsic motivation, (2) career motivation, (3) attention, (4)...

Artificial intelligence in early childhood education: A scoping review

Jiahong Su, Weipeng Yang (2022)

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Tipo: artículo

Metodología: revisión bibliográfica

Temas:
IA y educación revisión de bibliografía

Resumen:

Artificial intelligence (AI) tools are increasingly being used in the field of early childhood education (ECE) to enhance learning and development among young children. Previous proof-of-concept studies have demonstrated that AI can effectively improve teaching and learning in ECE; however, there is a scarcity of knowledge about how these studies are conducted and how AI is used across these studies. We conducted this scoping review to evaluate, synthesize and display the latest literature on AI in ECE. This review analyzed 17 eligible studies conducted in different countries from 1995 to 2021. Although few studies on this critical issue have been found, the existing references provide up-...

Evaluating the capability of large language models in characterising relational feedback: A comparative analysis of prompting strategies

Wei Dai, Yixin Cheng, Ahmad Ari Aldino (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas:
modelos de lenguaje (LLM) prompts IA y evaluación estudio empírico

Resumen:

Relational feedback is increasingly recognised for its crucial role in enhancing student-instructor relationships and promoting the assimilation of feedback. Despite its significance, no studies have tried to develop automated methods to analyse written feedback for properties of relational feedback to promote its use at scale and assist feedback providers with their relational feedback practices. This automated analysis of relational feedback can be performed as a classification task. However, traditional machine and deep learning methods for text classification typically require extensive human labelling and pose a significant challenge for educators and researchers lacking machine...

Factors influencing educators' AI adoption: A grounded meta-analysis review

Rana Taheri, Neda Nazemi, Sarah E. Pennington (2025)

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Tipo: artículo

Metodología: revisión bibliográfica

Temas:
IA y educación revisión de bibliografía

Resumen:

Artificial Intelligence (AI) is rapidly reshaping educational practices, yet educators' adoption of AI varies. This paper utilized a grounded meta-analysis framework of 45 peer-reviewed articles published between 2020 and 2024, including qualitative, quantitative, mixed-method, and social media (X) studies, to examine factors influencing educators' AI adoption. Four primary categories emerged from coding the papers: Individual Factors (demographics, AI literacy, beliefs, and self-efficacy), Infrastructure (institutional support, resource availability, social influence, and media narratives), Tools (perceived usefulness, ease of use, compatibility, transparency, bias, and reliability), and...

Modeling the sustainability perspectives on personalized digital games for digital citizenship education: A PLS-SEM approach

Patcharin Panjaburee, Gwo-Jen Hwang, Ungsinun Intarakamhang (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas:
IA y aprendizaje estudio empírico

Resumen:

As digital citizenship becomes an essential educational priority in the digital age, there is a growing need for sustainable and engaging instructional designs that foster students' ethical and responsible use of technology. Addressing this gap, this study modeled the sustainability perspectives underlying personalized digital game-based learning through a partial least squares structural equation modeling (PLS-SEM) approach. A longitudinal repeated-measures design was conducted with 372 lower secondary students in Thailand, using fuzzy logic and decision tree algorithms to personalize ethical digital scenarios. The proposed model examined how pedagogical design, content quality, usability...

Towards responsible AI in education: A Delphi-AHP-based framework for evaluating educational large language models

Pingrong Lin, Qin Deng, Yanbian Zhou (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas:
modelos de lenguaje (LLM) ética de la IA estudio empírico

Resumen:

As large language models (LLMs) become deeply integrated into the educational landscape, evaluation criteria focusing solely on performance are insufficient to mitigate the risks of value misalignment and socioethical concerns. To steer educational LLMs towards responsible and beneficial development, this study aims to construct a multidimensional evaluation framework grounded in educational theory. Initially, a preliminary pool of evaluation indicators was established on the basis of a review of the literature and pedagogical theories. The Delphi method was subsequently employed to refine the indicator structure by integrating opinions from 21 cross-disciplinary experts. The analytic...

A systematic review of the impact of GenAI on learning performance, AI hallucinations, and problem-solving in computer science education

Adedeji Adefisoye Adejumo, Solomon Sunday Oyelere, Ismaila Temitayo Sanusi (2026)

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Tipo: artículo

Metodología: revisión bibliográfica

Temas:
IA y educación IA y aprendizaje revisión de bibliografía

Resumen:

This systematic review synthesizes 64 empirical studies to examine how Generative AI (GenAI) shapes learning in Computer Science Education (CSE), particularly in programming, debugging, algorithmic reasoning, and computational problem-solving contexts. Grounded in Constructivist, Sociocultural, Cognitive Load, Adaptive Learning, and Metacognitive Learning theories, the review adopts an integrative perspective to analyze how GenAI-driven adaptivity, AI output qualities, hallucination dynamics, and cognitive–affective regulation influence learners’ interpretation, cognitive processing, and learning outcomes. Findings reveal a dual impact of GenAI in CSE. On the negative side, hallucinated or...

Generative AI-enhanced learning experiences for computational thinking: A systematic scoping review and design guidelines

Abdessalam Ouaazki, Antonette Shibani, Simon Knight (2026)

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Tipo: artículo

Metodología: revisión bibliográfica

Temas:
IA y aprendizaje IA y educación revisión de bibliografía

Resumen:

Computational thinking (CT) skills are crucial to teach. The rise of Generative AI could potentially revolutionize the teaching of these skills by changing learning experiences and outcomes. Educators are rapidly integrating these tools into their educational activities; however, the best practices for doing so remain unclear. Existing reviews on GenAI are either too broad in regards to studying specific tools such as ChatGPT for learning, or too limited in terms of studying computational thinking with a focus on programming. As such, this paper aims to summarize existing knowledge and extract best practices and avenues for future research and practice around GenAI and computational...

Moeketsi Mosia, Fadip Audu Nannim, Felix Egara (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas:
IA y educación estudio empírico

Resumen:

In this factor-informed exploratory CFA/SEM study, AI-literacy-related domains were treated as theoretically informed and empirically tested predictors of AI-TPACK readiness rather than as fully validated independent latent variables. Artificial intelligence (AI) is increasingly entering mathematics education, making it important to understand how preservice teachers become ready to integrate AI-supported tools pedagogically. This study examined AI-TPACK readiness among 130 preservice mathematics teachers at a South African public university. Exploratory factor analysis using polychoric correlations indicated that the AI-TPACK readiness items were essentially unidimensional; one weak design...