Bibliografía sobre IA y ELE

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Tipo: artículo

Metodología: estudio empírico

Resumen:

This study investigates how cognitive, affective, and behavioral variables related to artificial intelligence (AI) build AI self-efficacy among university students. Based on these variables, we identify three meaningful student groups, which can guide educational initiatives. We recruited 1465 undergraduate and graduate students from the United States, the United Kingdom, and Germany and measured their AI self-efficacy, AI literacy, interest in AI, attitudes towards AI, and AI use. Using a path model, we examine the correlations and paths among these variables. Results reveal that AI usage and positive AI attitudes significantly predict interest in AI, which in turn and together with AI...

Artificial intelligence and computer vision education: Codifying student learning gains and attitudes

Pramod Abichandani, Craig Iaboni, Deepan Lobo (2023)

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Tipo: artículo

Metodología: estudio empírico

Resumen:

Artificial Intelligence (AI) and Computer Vision (CV) have rapidly permeated various industries, increasing demand for professionals well-versed in these disciplines. In response to this need, this study evaluates the effectiveness of a novel undergraduate course that aims to equip students with foundational AI and CV knowledge and skills. Unlike existing software-centric courses, this class capitalizes on drones as a practical application area for AI and CV, fostering an active learning environment. The course was conducted over five semesters at a U.S. research institution, with 153 participating students. Data were collected using diverse methods, including formative and summative...

Deep learning and fuzzy algorithm in improving the effectiveness of college English translation teaching

Biao Kong, Che He (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas:
IA y enseñanza-aprendizaje de lenguas IA y evaluación estudio empírico

Resumen:

With the development of globalization, college English translation teaching is faced with the challenge of dealing with complex language structure and cross-cultural content. The traditional teaching methods are inadequate in evaluating translation quality and correcting translation errors, which is difficult to meet the actual needs of students. This study combines deep learning and fuzzy algorithm to improve the effect of translation teaching. Based on the data analysis of 387 students, the BiLSTM model is used to train translation tasks, and the fuzzy inference system is used to evaluate translation quality comprehensively. The results show that this method improves students’ translation...

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)

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Tipo: artículo

Metodología: estudio empírico

Temas:
IA y enseñanza-aprendizaje de lenguas IA y evaluación modelos de lenguaje (LLM) estudio empírico

Resumen:

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...

AI analysis reveals top predictors of first grade success: Insights from multifactorial screening students’ early days of school

Pedro Bem-haja, Paulo Nossa, Andreia J. Ferreira (2025)

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Tipo: artículo

Metodología: estudio empírico

Resumen:

Early prediction of students' primary school academic performance is crucial for planning timely interventions for those expected to struggle. Random Forest, Gradient Boosting, and Extra Trees AI techniques were used to study 2549 first graders to predict end-of-year academic performance and identify critical predictors for targeted interventions. The Extra Trees model used EPIS (Empresários pela Inclusão Social) screening to yield high F1 scores above 99.7 %, accurately identifying passing and failing students. Out of 142 variables, the top ten strongest predictors of academic success were categorized into three areas: 1) teacher perceptions of cognitive function, particularly attention (...

A Bayesian active learning approach to comparative judgement within education assessment

Andy Gray, Alma Rahat, Tom Crick (2024)

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Tipo: artículo

Metodología: estudio empírico

Temas:
IA y evaluación estudio empírico

Resumen:

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...

Enhancing language learning through generative AI feedback on picture-cued writing tasks

Yipeng Zhuang, Ruibin Zhao, ZhiWei Xie (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas:
IA y enseñanza-aprendizaje de lenguas IA y evaluación modelos de lenguaje (LLM) estudio empírico

Resumen:

Generative AI (GAI) is transforming education, despite its widespread use, its role in supporting student learning remains underexplored, and how to effectively leverage GAI for educational purposes is still unclear. This study focuses on enhancing language learning through GAI, specifically in picture-cued writing tasks, where students describe life scenarios depicted in pictures through text. A Generative AI-assisted language learning system was developed, powered by fine-tuned multimodal Large Language Models (LLMs), designed to evaluate students' textual descriptions in relation to corresponding images and provide adaptive feedback. A lot of middle school students participated in the...

Developing and validating measures for AI literacy tests: From self-reported to objective measures

Thomas K.F. Chiu, Yifan Chen, King Woon Yau (2024)

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Tipo: artículo

Metodología: estudio empírico

Resumen:

The majority of AI literacy studies have designed and developed self-reported questionnaires to assess AI learning and understanding. These studies assessed students' perceived AI capability rather than AI literacy because self-perceptions are seldom an accurate account of true measures. International assessment programs that use objective measures to assess science, mathematical, digital, and computational literacy back up this argument. Furthermore, because AI education research is still in its infancy, the current definition of AI literacy in the literature may not meet the needs of young students. Therefore, this study aims to develop and validate an AI literacy test for school students...

Are pre-service teachers ready to teach the Alpha generation? The impact of pre-service teachers' ChatGPT literacy levels on behavioral intentions toward ChatGPT-4.0

Eylem Kılıç, Firas Almasri, H. Eray Çelik (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas:
chatGPT estudio empírico

Resumen:

This study seeks to enhance our understanding of how pre-service teachers working with the Alpha Generation (PSTAG) interact with the Technology Acceptance Model (TAM) in the context of ChatGPT. It specifically examines their perceptions of ease of use (PEOU), perceived usefulness (PU), and behavioral intention (BI) toward ChatGPT-4o, utilizing an extended version of the TAM. The survey method was used, and 450 PSTAG participated in the current study. Data were collected through a survey including the ChatGPT literacy scale (ChatGPT-LS) and TAM to determine PSTAG's ChatGPT-4o literacy level and its relationship with PEOU, PU, and BI. Thirteen hypotheses are developed to test the proposed...

Learning-to-learn in the age of generative AI: A scoping review and conceptual framework

Isabel Schorr, Lisa Bardach, Babette Bühler (2026)

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Tipo: artículo

Metodología: revisión bibliográfica

Temas:
IA y aprendizaje revisión de bibliografía

Resumen:

With the rapid integration of generative AI (GenAI) into higher education, concerns over cognitive offloading, overreliance, and diminished critical thinking underscore an urgent need to prioritize learning-to-learn (L2L) competencies. However, the lack of a clear and detailed conceptualization of L2L, a key 21st-century skill for lifelong learning, hinders interdisciplinary research and limits the development of informed, pedagogically sound AI applications. This paper presents a scoping review of L2L definitions within pedagogical and psychological literature, based on sources retrieved from ERIC, Scopus, and Web of Science. The review follows the PRISMA-ScR framework and identifies 21...