estudio empírico

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial alfabetización en IA educación superior

Temas IA: IA y educación 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...

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: inteligencia artificial feedback/retroalimentación grandes modelos de lenguaje

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

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...

Unmasking the impacts of self-evaluation in AI-supported writing instruction on EFL learners’ emotion regulation, self-competence, motivation, and writing achievement

Tahereh Heydarnejad (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial autoevaluación expresión escrita

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

Resumen:

This study explores the impact of embedding self-evaluation within AI-supported writing instruction on learners’ cognitive emotion regulation, self-competence, motivation, and writing achievement. Conducted at a high school in Iran, the research utilized a quantitative quasi-experimental pretest-posttest design involving two intact pre-intermediate writing classes randomly assigned to an experimental group and a control group. The experimental group received instruction that combined AI tools with structured self-evaluation activities, whereas the control group followed a traditional teaching approach without AI integration or self-evaluation. Data were collected using the Cognitive Emotion...

Teachers’ readiness and intention to teach artificial intelligence in schools

Musa Adekunle Ayanwale, Ismaila Temitayo Sanusi, Owolabi Paul Adelana (2022)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial alfabetización en IA creencias y actitudes de los profesores

Temas IA: IA y educación estudio empírico

Resumen:

The emergence of artificial intelligence (AI) as a subject to be incorporated into K-12 educational levels places new demand on relevant stakeholders, especially teachers that drive the teaching and learning process. It is therefore important to understand how ready teachers are to teach the emerging subject as the success of AI education would probably be closely dependent on the readiness of teachers. As a result, this study presents an insight into factors influencing the behavioural intention and readiness of Nigerian in-service teachers to teach artificial intelligence. A total of 368 teachers, from elementary to high school participated in the study. We utilised quantitative...

AI-assisted writing and the impact of ChatGPT on Greek-speaking students with and without learning disabilities. Outcomes from a repeated measures design

Elena C. Papanastasiou, Evdokia Pittas, Marina Rodosthenous-Balafa (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial escritura académica expresión escrita

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

Resumen:

This study examines the impact of structured instruction on artificial intelligence (AI) use for improving academic writing in a non-English context. Participants included first-year students enrolled in a teacher education program, including some with disabilities. Three writing tasks were designed: typed essay, AI-based essay, and a critical AI use essay. The repeated measures analyses revealed that targeted AI integration supported overall writing quality, as indicated by improvements in language use, structure, and content. Additionally, students felt more confident when familiarizing themselves with effective prompt strategies. Students with learning difficulties exhibited the most...

Machine learning for spelling acquisition: How accurate is the prediction of specific spelling errors in German primary school students?

Richard Boehme, Stefan Coors, Patrick Oster (2024)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial ortografía alfabetización

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

Resumen:

In Germany (similar to other countries), 30 % of students demonstrate insufficient spelling skills at the end of primary school – partly owing to the challenge for teachers to manage a variety of students' learning needs. Digital tools using Machine Learning can enable teachers to individualise students' learning. However, there are still no suitable approaches for demographics of students who are not yet proficient in spelling.With an aim to adapt Machine Learning for students of all proficiencies, we investigate how accurately specific spelling errors can be predicted across different skill levels, and what the content-related reasons for incorrect predictions are.To that end, we...

Analysis of LLMs for educational question classification and generation

Said Al Faraby, Ade Romadhony, Adiwijaya (2024)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial grandes modelos de lenguaje ChatGPT

Temas IA: IA y creación de materiales modelos de lenguaje (LLM) análisis de producción de IA

Resumen:

Large language models (LLMs) like ChatGPT have shown promise in generating educational content, including questions. This study evaluates the effectiveness of LLMs in classifying and generating educational-type questions. We assessed ChatGPT's performance using a dataset of 4,959 user-generated questions labeled into ten categories, employing various prompting techniques and aggregating results with a voting method to enhance robustness. Additionally, we evaluated ChatGPT's accuracy in generating type-specific questions from 100 reading sections sourced from five online textbooks, which were manually reviewed by human evaluators. We also generated questions based on learning objectives and...

The mediating role of academic stress, critical thinking and performance expectations in the influence of academic self-efficacy on AI dependence: Case study in college students

Benicio Gonzalo Acosta-Enriquez, Marco Agustín Arbulú Ballesteros, Maria de los Angeles Guzman Valle (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial educación superior pensamiento crítico

Temas IA: IA y educación estudio empírico

Resumen:

This study investigated the mediating roles of academic stress, critical thinking, and performance expectations in the relationship between academic self-efficacy and AI dependency among university students. Data were collected via validated instruments and analyzed via structural equation modeling (PLS-SEM) in a cross-sectional study that included 676 students from six universities in northern Peru. The findings indicated that the relationship between academic self-efficacy and AI dependency was substantially mediated by academic stress (β = 0.398, p < 0.001). Furthermore, this relationship is serially mediated by academic stress and performance expectations (β = 0.325, p < 0.001)....

How do LLMs perform in the context of MCQs across different levels of thinking skills in a business education course at higher education? A comparison of ChatGPT, Gemini, and Copilot

Laurens Goorts, Ryan Hollevoet, Vanessa Xia (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial grandes modelos de lenguaje ChatGPT

Temas IA: análisis de producción de IA modelos de lenguaje (LLM) chatGPT

Resumen:

This exploratory study investigates the performance of three widely-used and freely available large language models (LLMs)— ChatGPT (GPT-3.5 Turbo), Gemini, and Copilot—in answering multiple-choice questions (MCQs) categorized by cognitive complexity based on the revised Bloom's Taxonomy. Although MCQs offer a structured, efficient, and scalable method for evaluation, a gap exists in the literature on how LLMs handle varying cognitive levels, particularly in a business course at higher education. Understanding LLM performance in this context is crucial, as students increasingly use LLMs for searching answers but also to receive tailored and scaffolded responses for an interactive and...

Enhancing knowledge integration from multiple experts to guiding personalized learning paths for testing and diagnostic systems

Dechawut Wanichsan, Patcharin Panjaburee, Sasithorn Chookaew (2021)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial tecnología educativa evaluación

Temas IA: IA y evaluación IA y aprendizaje estudio empírico

Resumen:

The testing and diagnostic systems have been considered to be useful for students because they can point to their learning problems to provide helpful suggestions for improving the knowledge. The previous approach shows that using the knowledge from multiple experts can develop a testing and diagnostic system that provides more accurate suggestions for learners comparing to the system using a single expert. Nevertheless, the low-quality knowledge integration method of the multi-expert approach can provide some inaccurate learning suggestions. This work proposes a practical method for enhancing knowledge integration from multiple experts to provide more effective learning suggestions. An...