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  • Computers & Education: Artificial Intelligence

Revistas: Computers & Education: Artificial Intelligence

Nº de publicaciones: 569

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Transitions through lifelong learning: Implications for learning analytics
Oleksandra Poquet, Kirsty Kitto, Jelena Jovanovic (2021)
Computers & Education: Artificial Intelligence 2
Detalles Cerrar βœ•

Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial analítica del aprendizaje teorías de aprendizaje

Resumen:

Texto completo

The ability to develop new skills and competencies is a central concept of lifelong learning. Research to date has largely focused on the processes and support individuals require to engage in upskilling, re-learning or training. However, there has been limited attention examining the types of support that are necessary to assist a learner's transition from “old” workplace contexts to “new”. Professionals often undergo significant restructuring of their knowledge, skills, and identities as they transition between career roles, industries, and sectors. Domains such as learning analytics (LA) have the potential to support learners as they use the analysis of fine-grained data collected from...

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Generative AI in higher education: Seeing ChatGPT through universities' policies, resources, and guidelines
Hui Wang, Anh Dang, Zihao Wu (2024)
Computers & Education: Artificial Intelligence 7
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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial educación superior integridad académica

Resumen:

Texto completo

The advancements in Generative Artificial Intelligence (GenAI) can provide opportunities for enriching educational experiences, but at the same time raise concerns regarding academic integrity. Many educators have expressed anxiety and hesitation when it comes to integrating GenAI in their teaching practices. Thus, recommendations and guidance from institutions are needed to support instructors in this new and emerging GenAI era. In response to this need, this study explores different U.S. universities' academic policies and guidelines regarding the use of GenAI tools (e.g., ChatGPT) for teaching and learning, and from there, gains understanding of how these universities respond and adapt...

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Exploring generative artificial intelligence preparedness among university language instructors: A case study
Lucas Kohnke, Benjamin Luke Moorhouse, Di Zou (2023)
Computers & Education: Artificial Intelligence 5
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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial creencias y actitudes de los profesores profesorado

Resumen:

Texto completo

The integration of generative artificial intelligence (AI) in English language teaching presents opportunities and challenges for instructors. This study explores the attitudes of higher education English language instructors towards generative AI tools, their intentions to use them and the institutional support and professional development necessary to teach and learn with them. As the field continues to evolve rapidly, it is essential to comprehend the readiness of front-line language instructors. This qualitative interpretive study seeks to identify the digital competencies and pedagogical knowledge required to implement generative AI in education and provide guidance for the design of...

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AI4Design: A generative AI-based system to improve creativity in design–A field evaluation
Luca Abrusci, Karma Dabaghi, Stefano D'Urso (2025)
Computers & Education: Artificial Intelligence 8
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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial educación superior tecnología educativa

Resumen:

Texto completo

Chatbots serve as valuable instruments for enhancing students' educational experience and aiding them in their day-to-day academic tasks. Advances in Generative AI (GAI) have ushered in increasingly sophisticated and adaptive chatbots, with ChatGPT and DALL⋅E being prime examples. ChatGPT excels at generating text-based answers across diverse areas of knowledge, while DALL⋅E is adept at converting text-based concepts into visual imagery. These technologies are increasingly used by students across various levels of education. In this study, we introduce AI4Design, a web-based system designed to assist design students with their course projects by acting as an intelligent chatbot. The field...

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Predicting student achievement through peer network analysis for timely personalization via generative AI
Ivica Pesovski, Petar Jolakoski, Vladimir Trajkovik (2025)
Computers & Education: Artificial Intelligence 8
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial analítica del aprendizaje aprendizaje colaborativo

Resumen:

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Background: Peer influence is a significant determinant in shaping students' academic performance, yet it is often overlooked in traditional educational strategies. The ability to analyze peer influence and collaboration is an important piece in personalizing student educational experiences. Objective: This study aims to investigate how peer interactions can be used to predict students' achievement levels and create clusters based on these predictions. Building on these clusters, a novel AI-driven approach is introduced to personalize the learning experiences for each group, providing content aligned with students' predicted achievement levels and ensuring that students receive the right...

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An exploration of the role of generative AI in fostering creativity in architectural learning environments
Carlos Medel-Vera, Sandy Britton, William Francis Gates (2025)
Computers & Education: Artificial Intelligence 9
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Tipo: artículo

Metodología: estudio empírico

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

Resumen:

Texto completo

This paper explores the role of generative AI (GenAI) in supporting creativity within architectural education through the lens of a student-led AI drawing competition. The research addresses two questions: (1) how creative are students' text prompts and the resulting AI-generated images, and is there a relationship between them? and (2) to what extent do students perceive GenAI as a supportive tool in their creative process? Drawing on a mixed-methods approach, the study combines semantic analysis of text prompts, aesthetic evaluation of AI-generated images, and a Creativity Support Index (CSI) survey, complemented by sentiment analysis of student feedback. The semantic analysis reveals...

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Learning with machines: Toward a theory of epistemic co-agency
Anita Samuel (2026)
Computers & Education: Artificial Intelligence 10
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Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial teorías de aprendizaje cognición y procesamiento

Resumen:

Texto completo

The rapid integration of generative AI (GenAI) systems into educational settings necessitates a reevaluation of how learners reason, construct, and assume responsibility for knowledge. Existing learning theories like constructivism, sociocultural theory, and connectivism presume human-centered epistemic agency and fail to account for the ways GenAI simulates reasoning, reframes arguments, and co-constructs meaning. This paper introduces the Epistemic Entanglement Framework, a theory-informed model that captures how learners engage with AI systems. Drawing on distributed cognition, sociomaterialism, and posthumanist theory, the framework proposes epistemic co-agency as a reflexive stance...

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Beyond “painting in pink”: A critical case study of all-girls generative AI workshops in a European makerspace and implications for gender equity in computing
Qian Liu, Louise Archer, Meghna Nag Chowdhuri (2026)
Computers & Education: Artificial Intelligence 10
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial estudios de género inclusión y equidad

Resumen:

Texto completo

Equity-oriented uses of generative artificial intelligence (GenAI) remain largely underexplored. To address the persistent gender inequities in girls’ representation and participation in computing, we present a case study of an all-girls initiative incorporating two GenAI tools in a European makerspace. We analysed qualitative, multimodal data, including 15 interviews with girls, parents, and practitioners, four reflective sessions, two observation fieldnotes, and 44 GenAI-generated images. Harding’s (1986) multi-level framework and feminist pedagogy provide critical lenses through which to examine and discuss the practice and practitioners’ reflections. Stakeholders generally expressed...

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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)
Computers & Education: Artificial Intelligence 6
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial ortografía alfabetización

Resumen:

Texto completo

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...

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The IDEA framework for metacognitively regulated GenAI use in higher education: Development and exploratory pilot evidence
Xiangpeng Wang, Ziwei Zheng, Jincheng Zhang (2026)
Computers & Education: Artificial Intelligence 11
Detalles Cerrar βœ•

Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial metacognición aprendizaje autónomo

Resumen:

Texto completo

Generative artificial intelligence (GenAI) can enhance students’ efficiency and the apparent quality of academic work, yet its fluent outputs may encourage learners to outsource cognitive activities central to learning. This creates the risk of “performance without learning”, whereby successful task completion does not necessarily reflect meaningful understanding or learner regulation. To address this concern, this article develops the Intent, Deconstruction, Expression, and Adaptation (IDEA) framework, a theory-informed metacognitive scaffold for GenAI-supported academic work. IDEA guides learners to articulate goals and constraints, decompose tasks into essential processes, communicate...

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