IA y educación

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial alfabetización en IA aprendizaje basado en proyectos

Temas IA: IA y educación estudio empírico

Resumen:

In the artificial intelligence (AI) era, secondary and university students should be able to apply AI for problem-solving. This study designed and evaluated an AI literacy programme to enhance understanding of machine learning concepts. It also examined how the conceptual understanding from two foundational courses (Courses 1 and 2) affected students' application of these concepts in the subsequent two project-based learning courses (Courses 3 and 4). The regression analysis of data from 566, 566, 470, and 196 student participants enrolled on Courses 1, 2, 3, and 4, respectively, revealed that the post-course concept tests for Courses 1 and 2 accounted for 19.9 % of the variance in the...

University teachers' perceptions of responsibility and artificial intelligence in higher education - An experimental philosophical study

Cormac McGrath, Teresa Cerratto Pargman, Niklas Juth (2023)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial creencias y actitudes de los profesores profesorado

Temas IA: IA y educación ética de la IA

Resumen:

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This study investigates university teachers’ relationships with emerging technologies by focusing on the uptake of artificial intelligence in higher education practices. We utilise an experimental philosophy approach to i) determine university teachers’ intuitions around universities’ responsibilities to adopt new artificial intelligence technologies, ii) understand the conditions under which university teachers consider artificial intelligence defensible and, hence, would be willing to introduce such tools and services into their daily practice and iii) specify teachers’ self-reported knowledge of artificial intelligence. An online survey, where participants were sent one of three...

Rewriting the curriculum: A systematic review of generative AI-driven pedagogical change and emerging systems of learning in higher education

Alvedi Sabani, Mohamed H. Farah, Putra Endi Catyanadika (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial educación superior diseño curricular

Temas IA: IA y educación estudio empírico revisión de bibliografía

Resumen:

The rapid rise of generative artificial intelligence (GenAI) tools such as ChatGPT is transforming the landscape of higher education. Beyond their immediate use in writing support and tutoring, these tools are driving a more profound transformation in pedagogy, curriculum design, and the foundational structures of learning itself. Drawing on a triangulated mixed-methods design, this study integrates a scoping review, bibliometric mapping (VOSviewer, n=209 records), a systematic literature review of 36 peer-reviewed articles (2023–2025), and ten semi-structured interviews with academic leaders and educators across five institutions in Australia and Indonesia. The central aim of the study is...

To GPT or not GPT? Empowering our students to learn with AI

Jennifer L. Steele (2023)

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Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial ChatGPT pensamiento crítico

Temas IA: chatGPT IA y educación

Resumen:

I argue that ChatGPT and other generative artificial intelligence tools pose three main threats to our current education systems, creating problems of measurement, information accuracy, and skill devaluation. But when we place these threats into historical context, we see that AI tools can also empower students and level the educational playing field. In classrooms from primary to tertiary and spanning all content areas, we can help our students become critical thinkers by using ChatGPT to comprehend texts, aggregate knowledge, and understand genre conventions in prose as well as programming. The aim is to help students leverage AI as a tool that they question and critique, advancing their...

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)....

The power of Deep Learning techniques for predicting student performance in Virtual Learning Environments: A systematic literature review

Bayan Alnasyan, Mohammed Basheri, Madini Alassafi (2024)

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Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial analítica del aprendizaje enseñanza en línea e híbrida

Temas IA: IA y educación revisión de bibliografía

Resumen:

With the advances in Artificial Intelligence (AI) and the increasing volume of online educational data, Deep Learning techniques have played a critical role in predicting student performance. Recent developments have assisted instructors in determining the strengths and weaknesses of student achievement. This understanding will benefit from adopting the necessary interventions to assist students in improving their performance, helping at-risk of failure students, and preventing dropout rates. The review analyzed 46 studies between 2019 and 2023 that apply one or more Deep Learning (DL) techniques, either single or in combination with Machine Learning (ML) or Ensemble Learning techniques....

Artificial intelligence in classroom management: A systematic review on educational purposes, technical implementations, and ethical considerations

Tim Fütterer, Patricia Goldberg, Babette Bühler (2025)

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Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial práctica docente ética

Temas IA: IA y educación ética de la IA revisión de bibliografía

Resumen:

Artificial intelligence (AI) is increasingly shaping education, including classroom management. This systematic review analyzes 104 studies (2000–2022) on the use of AI in classroom management, focusing on educational purposes, technical implementations, and ethical considerations. Our findings show a growing use of AI technologies—particularly machine learning and deep learning—for tasks such as attendance tracking, behavior monitoring, and engagement assessment. These tools can streamline classroom management and offer detailed insights into student behavior. However, only a minority of studies leveraged AI's full potential, such as real-time feedback or multimodal data. Ethical issues,...

Delphi study for the development and preliminary validation of an item set for the assessment of non-experts' AI literacy

Matthias Carl Laupichler, Alexandra Aster, Tobias Raupach (2023)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial alfabetización en IA evaluación

Temas IA: IA y educación conceptos básicos

Resumen:

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Artificial intelligence literacy is a concept that has been the focus of exhaustive research recently. However, there are very few psychometrically sound and thoroughly evaluated instruments that attempt to assess AI literacy in a valid way. Therefore, this study presents an item set to assess the AI literacy of non-experts. In the context of a Delphi expert study, 53 subject matter experts participated in three iterative questionnaire rounds to generate potential AI literacy items and assess their content validity. In addition, the experts made suggestions on how the items’ wording accuracy could be improved and evaluated the wording suggestions of the other experts. Of 47...

GenAI as a runaway object in higher education: A socio-cultural view on AI-influenced academic practice in mathematics

Dionysia Bakogianni, Yvonne Liljekvist, Phuong Bui (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial educación superior creencias y actitudes de los profesores

Temas IA: IA y educación estudio empírico

Resumen:

This study explores how generative AI (GenAI) technologies are reshaping research and teaching practices at the university level. Drawing on Cultural-Historical Activity Theory (CHAT) (Engeström, 1987), we examine the interrelated activity systems of teaching and research through the lens of GenAI as a “runaway object”, a concept describing technologies that evolve unpredictably, disrupt boundaries, and reconfigure roles, tools, and epistemic norms. Based on qualitative data from ten academics in a mathematics department at a Swedish university, the analysis identifies five dominant themes that characterize emerging changes across both activity systems: boundary fluidity, shifting objects,...

Predictive learning analytics in online education: A deeper understanding through explaining algorithmic errors

Martin Hlosta, Christothea Herodotou, Tina Papathoma (2022)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial analítica del aprendizaje enseñanza en línea e híbrida

Temas IA: IA y educación estudio empírico

Resumen:

Existing Predictive Learning Analytics (PLA) systems utilising machine learning models show they can improve teacher practice and, at the same time, student outcomes. The accuracy, and related errors, of these systems can negatively influence their adoption. However, little effort has been made to investigate the errors made by the underlying models. This study focused on errors of models predicting students at risk of not submitting their assignments. We analysed two groups of error when the model was confident about the prediction: (a) students predicted to submit their assignment, yet they did not (False Negative; FN), and (b) students predicted not to submit their assignment yet they...