Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

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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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Temas: inteligencia artificial

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The learning process depends on the nature of the learning environment, particularly in the case of open-ended learning environments, where the learning process is considered to be non-linear. In this paper, we report on the findings of employing a multimodal Hidden Markov Model (HMM) based methodology to investigate the temporal learning processes of two types of learners that have learning gains and a type that does not have learning gains in an open-ended collaborative learning activity. Considering log data, speech behavior, affective states and gaze patterns, we find that all learners start from a similar state of non-productivity, but once out of it they are unlikely to fall back into...

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Metodología: estudio empírico

Temas: inteligencia artificial

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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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Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial

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Text-based open-ended questions in academic formative and summative assessments help students become deep learners and prepare them to understand concepts for a subsequent conceptual assessment. However, grading text-based questions, especially in large (>50 enrolled students) courses, is tedious and time-consuming for instructors. Text processing models continue progressing with the rapid development of Artificial Intelligence (AI) tools and Natural Language Processing (NLP) algorithms. Especially after breakthroughs in Large Language Models (LLM), there is immense potential to automate rapid assessment and feedback of text-based responses in education. This systematic review adopts a...

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Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial

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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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Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial

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Generative AI-powered agentic systems are increasingly proposed for educational applications. However, the research landscape remains fragmented, and the relationship between technical capabilities and pedagogical design remains poorly understood. To address this gap, this scoping review systematically mapped 474 studies published between January 2020 and May 2026. Guided by three research questions, we analysed publication characteristics, study designs, agent roles, AI models and architectures, six dimensions of agentic capability, and the extent to which educational theory was incorporated. The results show that the field has expanded rapidly, particularly since 2025. At the same time,...

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Metodología: estudio empírico

Temas: inteligencia artificial

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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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Metodología: estudio empírico

Temas: inteligencia artificial

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Generative Large Language Models (LLMs) demonstrate impressive results in different writing tasks and have already attracted much attention from researchers and practitioners. However, there is limited research to investigate the capability of generative LLMs for reflective writing. To this end, in the present study, we have extensively reviewed the existing literature and selected 9 representative prompting strategies for ChatGPT – the chatbot based on state-of-art generative LLMs to generate a diverse set of reflective responses, which are combined with student-written reflections. Next, those responses were evaluated by experienced teaching staff following a theory-aligned...

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Metodología: estudio empírico

Temas: inteligencia artificial

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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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Metodología: estudio empírico

Temas: inteligencia artificial

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The growth and uptake of educational technology has significantly reshaped the delivery of distance and online learning. With an unprecedented number of learners engaging with online modes of education, there is a growing need to understand the underlying student enrolment motivations, goals and learning behaviours evolving from a highly diverse student population. Research in learning analytics has advanced the use of digital data to understand student learning processes. However, there remains a limited understanding of how non-traditional learner characteristics, needs and motivational factors influence their learning behaviour and engagement strategies. Survey data from 232 students...

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