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  • Computers & Education: Artificial Intelligence

Revistas: Computers & Education: Artificial Intelligence

Nº de publicaciones: 569

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An investigation of barriers to Hong Kong K-12 schools incorporating Artificial Intelligence in education
Tianchong Wang, Eric Chi Keung Cheng (2021)
Computers & Education: Artificial Intelligence 2
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial educación primaria y secundaria innovación educativa

Resumen:

Texto completo

Artificial Intelligence in Education (AIED) has been the focus of significant attention in recent years because of its growing social importance and pedagogical value. In Hong Kong, an increasing number of K-12 schools are planning or piloting their grassroots AIED incorporation practices. However, progress is reportedly slow due to a number of barriers. Unfortunately, because of their limited scope, disputed interpretations and contextual irrelevance, current research literature seems to be of limited referencing value in aiding schools to address the issues and overcome the barriers. This paper highlights the necessity of embracing AIED as wide-ranging given the current understanding of...

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Optimising team dynamics: The role of AI in enhancing challenge-based learning participation experience and outcomes
Athina Georgara, Marc Santolini, Olga Kokshagina (2025)
Computers & Education: Artificial Intelligence 8
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial aprendizaje colaborativo educación superior

Resumen:

Texto completo

The approach of engaging students with real-world challenges to enhance collaboration and problem-solving has attracted significant interest from scholars and practitioners across diverse disciplines. Often called Challenge-Based Learning (CBL), this educational approach emphasises developing collaborative and problem-solving skills, with significant learning occurring within team settings. Prior studies highlight the influence of team composition on the efficacy of learning outcomes, pointing out that factors such as gender diversity, personality trait diversity, and a wide range of skills affect team dynamics and performance. Despite these insights, the practical organisation of these...

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Learnersourcing in the age of AI: Student, educator and machine partnerships for content creation
Hassan Khosravi, Paul Denny, Steven Moore (2023)
Computers & Education: Artificial Intelligence 5
Detalles Cerrar โœ•

Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial creación de materiales tecnología educativa

Resumen:

Texto completo

Engaging students in creating novel content, also referred to as learnersourcing, is increasingly recognised as an effective approach to promoting higher-order learning, deeply engaging students with course material and developing large repositories of content suitable for personalised learning. Despite these benefits, some common concerns and criticisms are associated with learnersourcing (e.g., the quality of resources created by students, challenges in incentivising engagement and lack of availability of reliable learnersourcing systems), which have limited its adoption. This paper presents a framework that considers the existing learnersourcing literature, the latest insights from the...

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Is GPT-4 fair? An empirical analysis in automatic short answer grading
Luiz Rodrigues, Cleon Xavier, Newarney Costa (2025)
Computers & Education: Artificial Intelligence 8
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial evaluación grandes modelos de lenguaje

Resumen:

Texto completo

Short open-ended questions represent a central resource in formative and summative assessments both face-to-face and online settings, ranging from elementary to higher education. However, grading these questions remains challenging for instructors, raising attention to the field of Automatic Short Answer Grading (ASAG). While ASAG has yielded valuable contributions to learning analytics, it often faces generalizability issues. Accordingly, the rapid advancement in Large Language Models (LLMs) has motivated their adoption to empower ASAG systems. Despite that, previous research has not investigated whether LLMs are fair graders in the context of ASAG. Therefore, this paper presents an...

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Evaluating the potential of ChatGPT-reformulated essays as written feedback in L2 writing
Yingzhao Chen (2025)
Computers & Education: Artificial Intelligence 9
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial ChatGPT expresión escrita

Resumen:

Texto completo

Reformulation is a form of written corrective feedback to help second language (L2) learners improve their writing. This study examined whether ChatGPT could produce reformulations that (1) retain the meanings of the original essays and (2) are linguistically more developed than learners’ original essays. In addition, three types of ChatGPT prompts were compared to see which type yielded better reformulations. One thousand two hundred argumentative essays written for the TOEFL iBT® independent writing task were submitted to ChatGPT. ROUGE-L scores, used as a proxy for meaning retention, showed that ChatGPT reformulations largely retained the meaning of the original essays. A qualitative...

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Scaffolding critical thinking with generative AI: Design principles for integrating large language models in higher education
Mireia Vendrell, Samantha-Kaye Johnston (2026)
Computers & Education: Artificial Intelligence 10
Detalles Cerrar โœ•

Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial pensamiento crítico andamiaje/scaffolding

Resumen:

Texto completo

The rapid adoption of Large Language Models (LLMs) such as GPT-4 and DeepSeek R1 is transforming learning in higher education, yet unstructured use can weaken critical thinking by encouraging cognitive offloading, metacognitive disengagement, and reduced epistemic agency. This paper presents a conceptual and normative analysis that synthesises research from cognitive psychology, educational theory, and AI ethics to develop a design-oriented pedagogical framework for integrating LLMs in ways that strengthen, rather than displace, higher-order thinking. Grounded in design-based research principles, the framework identifies six essential processes that underpin critical engagement: conceptual...

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From simulation to flight: Simulation-assisted drone learning with teacher-AI co-designed scaffolds for secondary students’ STEM knowledge and competencies
Richard Chung Yiu Yeung, Chi Ho Yeung, Daner Sun (2026)
Computers & Education: Artificial Intelligence 11
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial educación primaria y secundaria andamiaje/scaffolding

Resumen:

Texto completo

A persistent challenge in drone-based STEM education is the scarcity of teacher-verified, interactive simulations that support both conceptual learning and competency development. Generative AI can accelerate content creation, but its outputs frequently lack pedagogical validity and contextual alignment. This study examines whether simulation-assisted drone instruction, anchored by teacher-AI co-designed simulations, yields superior learning outcomes compared to the same hands-on curriculum delivered without simulations. Using a quasi-experimental pretest–posttest design with 30 secondary students (aged 13 to 17), both groups completed identical drone tasks with the same instructor; however...

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Immersive multi-modal pedagogical conversational artificial intelligence for early childhood education: An exploratory case study in the wild
Sinem Aslan, Lenitra M. Durham, Nese Alyuz (2024)
Computers & Education: Artificial Intelligence 6
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial educación infantil chatbots

Resumen:

Texto completo

Educational technology research has found that parents of young children widely share concerns about extended screen time, lack of physical activity, and lack of social interaction. Kid Space was developed to address these concerns by enabling multi-modal and immersive collaborative play-based learning. Kid Space utilizes multiple sensing technologies with an immersive physical space through a human-scale wall projection and incorporates a conversational AI agent to interact with children, understand individual progress, and personalize learning experiences in a blended physical and digital environment. To evaluate Kid Space in the wild, we conducted a multi-method user study involving a...

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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 7
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial analítica del aprendizaje ética

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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Four paradigms in learning analytics: Why paradigm convergence matters
Ryan S. Baker, Dragan Gaševiฤ‡, Shamya Karumbaiah (2021)
Computers & Education: Artificial Intelligence 2
Detalles Cerrar โœ•

Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial analítica del aprendizaje metodología de investigación

Resumen:

Texto completo

Learning analytics has matured significantly since its early days. The field has rapidly grown in terms of the reputation of its publication venues, established a vibrant community, and has demonstrated an increasing impact on policy and practice. However, the boundaries of the field are still being explored by many researchers in a bid to determine what differentiates a contribution in learning analytics from contributions in related fields, which also center around data in education. In this paper, we propose that instead of emphasizing the examination of differences, a healthy development of the field should focus on collaboration and be informed by the developments in related fields....

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