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IA: Bibliografía

Nº de publicaciones: 850

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The impact of generative AI on higher education learning and teaching: A study of educators’ perspectives
Daniel Lee, Matthew Arnold, Amit Srivastava (2024)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas:
IA y educación estudio empírico

Resumen:

Texto completo

In recent months, Artificial Intelligence (AI) has had, and will continue to have, a dramatic impact on Higher Education (HE). A study conducted by researchers at a leading university in Australia surveyed 30 of their teaching staff, drawn predominantly from their teaching academy, and interviewed eight of them regarding the impact of AI on HE. Data were analyzed using the procedures of Inductive Thematic Analysis and revealed a lack of any homogenous sentiment around AI in HE and much ambiguity regarding best practice regarding recent technological developments. The results indicate concerns exist around concepts relating to academic integrity, however, these concerns may be exaggerated....

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How to responsibly deploy a predictive modelling dashboard for study advisors? A use case illustrating various stakeholder perspectives
Anouschka van Leeuwen, Marije Goudriaan, Ünal Aksu (2024)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas:
ética de la IA IA y educación estudio empírico

Resumen:

Texto completo

Most higher education institutions employ study advisors to support their students. To adequately perform their task, study advisors have access to study information about their students. Using AI techniques to analyze that information and to predict if a student might be at risk of study delay could be a valuable tool in study advisors' practice. In this paper, we present a use case of how such a tool was developed (in the form of a dashboard) and which steps and considerations played a role in the responsible deployment of the tool. Three aspects are described: first, we present the timeline of the case study and zoom in on how the macro-level of the institution (where the groundwork is...

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Perceived impact of generative AI on assessments: Comparing educator and student perspectives in Australia, Cyprus, and the United States
René F. Kizilcec, Elaine Huber, Elena C. Papanastasiou (2024)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas:
IA y evaluación estudio empírico

Resumen:

Texto completo

The growing use of generative AI tools built on large language models (LLMs) calls the sustainability of traditional assessment practices into question. Tools like OpenAI's ChatGPT can generate eloquent essays on any topic and in any language, write code in various programming languages, and ace most standardized tests, all within seconds. We conducted an international survey of educators and students in higher education to understand and compare their perspectives on the impact of generative AI across various assessment scenarios, building on an established framework for examining the quality of online assessments along six dimensions. Across three universities, 680 students and 87...

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AI advocates and cautious critics: How AI attitudes, AI interest, use of AI, and AI literacy build university students' AI self-efficacy
Arne Bewersdorff, Marie Hornberger, Claudia Nerdel (2025)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas:
IA y educación estudio empírico

Resumen:

Texto completo

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...

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Deep learning and fuzzy algorithm in improving the effectiveness of college English translation teaching
Biao Kong, Che He (2025)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

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

Resumen:

Texto completo

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...

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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)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas:
IA y educación estudio empírico

Resumen:

Texto completo

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 (...

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Enhancing language learning through generative AI feedback on picture-cued writing tasks
Yipeng Zhuang, Ruibin Zhao, ZhiWei Xie (2025)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

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

Resumen:

Texto completo

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...

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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 KΔ±lΔ±ç, Firas Almasri, H. Eray Çelik (2025)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas:
chatGPT estudio empírico

Resumen:

Texto completo

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...

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From knowledge gaps to learning opportunities: Leveraging student questions and dual use of generative AI to support student learning at scale
Stanislav Pozdniakov, Jonathan Brazil, Oleksandra Poquet (2026)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas:
modelos de lenguaje (LLM) IA y creación de materiales IA y aprendizaje estudio empírico

Resumen:

Texto completo

University courses with hundreds of students have become common, particularly during early years of university studies. The sheer scale of these courses limits traditional instruction, shifting it towards a one-to-many mode of delivery. This shift reduces student–instructor interaction and tailored instructor feedback which are crucial for student success. Automated feedback systems allow scaling feedback, but they often reduce instructor contributions to student learning. This paper investigates how emerging technologies can support, rather than replace, instructors in tailoring their teaching and feedback to identify and correct student knowledge gaps at scale. To address this challenge,...

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Optimizing automated scoring in ILSAs with prompt compression
Ji Yoon Jung, Ummugul Bezirhan, Matthias von Davier (2026)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

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

Resumen:

Texto completo

Automated scoring (AS) has become increasingly prevalent in educational measurement. However, applying it to international reading assessments remains challenging, particularly due to the length and complexity of the required prompting, driven by the need to include lengthy reading passages and detailed scoring guides. Processing these lengthy inputs results in high computational costs and may impede the performance of large language models (LLMs). This study explored the potential of optimizing AS with prompt compression using OpenAI's LLM, GPT-4o. Our results show that prompt compression significantly reduces the length of reading passages and scoring guides while maintaining their...

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Etiquetas

  • análisis de producción de IA (54)
  • catálogo de herramientas (15)
  • chatbots (68)
  • chatGPT (156)
  • conceptos básicos (39)
  • estudio empírico (490)
  • ética de la IA (123)
  • guía (29)
  • IA y aprendizaje (163)
  • IA y creación de materiales (64)
  • IA y educación (363)
  • IA y ELE (31)
  • IA y enseñanza-aprendizaje de lenguas (210)
  • IA y evaluación (143)
  • IA y variedades del español (1)
  • modelos de lenguaje (LLM) (87)
  • prompts (65)
  • revisión de bibliografía (136)
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