IA y aprendizaje

Detalles Cerrar ✕

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial comprensión lectora alfabetización

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

Resumen:

This paper presents evidence on the impact of technology-aided instruction on literacy using an AI-based multi-sensory technology platform across a large cross-section of government schools in India. The study focused on reading and comprehension in the English language. The intervention enhances the instructional effectiveness of the teachers and the learning ability of the children within the existing instructional environment without any new instructional design or pedagogy or content. Besides, the intervention is implemented by existing teachers and not outside volunteers.A total of 1 million children and 15,000 teachers across 5000 government schools in the states of Maharashtra, West...

Evaluating adaptive and generative AI-based feedback and recommendations in a knowledge-graph-integrated programming learning system

Lalita Na Nongkhai, Jingyun Wang, Adam Wynn (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial pensamiento computacional feedback/retroalimentación

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

Resumen:

This paper introduces the design and development of a framework that integrates a large language model (LLM) with a retrieval-augmented generation (RAG) approach leveraging both a knowledge graph and user interaction history. The framework is incorporated into a previously developed adaptive learning support system to assess learners’ code, generate formative feedback, and recommend exercises. Moreover, this study examines learner preferences across three instructional modes: adaptive, Generative AI (GenAI), and hybrid GenAI–adaptive. An experimental study was conducted to compare the learning performance and perception of the learners, and the effectiveness of these three modes using four...

AI in informal digital English learning: A meta-analysis of its effectiveness on proficiency, motivation, and self-regulation

Lihang Guan, Shaofeng Li, Mingyue Michelle Gu (2024)

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Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial enseñanza/aprendizaje de lenguas aprendizaje informal

Temas IA: IA y enseñanza-aprendizaje de lenguas IA y aprendizaje revisión de bibliografía

Resumen:

This meta-analysis examines the efficacy of generative artificial intelligence (GenAI) in second language acquisition within self-directed, out-of-classroom informal contexts. A total of 15 studies meeting the inclusion criteria were identified that examined the impact of GenAI on second-language proficiency, motivation, and self-regulation. GenAI was shown to have significant effects on English proficiency and self-regulation, demonstrating its versatility in enhancing language learning outcomes. However, GenAI failed to show significant effects on learning motivation, and based on this finding we highlight the need to develop measures of motivation that are suitable for GenAI in education...

Does intrinsic motivation mediate perceived artificial intelligence (AI) learning and computational thinking of students during the COVID-19 pandemic?

José Luis Martín-Núñez, Anil Yasin Ar, Rodrigo Pérez Fernández (2023)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial pensamiento computacional motivación

Temas IA: IA y aprendizaje estudio empírico

Resumen:

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The concept of Artificial Intelligence (AI), born as the possibility of simulating the human brain's learning capabilities, quickly evolves into one of the educational technology concepts that provide tools for students to better themselves in a plethora of areas. Unlike the previous educational technology iterations, which are limited to instrumental use for providing platforms to build learning applications, AI has proposed a unique education laboratory by enabling students to explore an instrument that functions as a dynamic system of computational concepts. However, the extent of the implications of AI adaptation in modern education is yet to be explored. Motivated to fill the...

A design-based approach to analysing student engagement with a GenAI-Enabled brainstorming app

Joanne Chia, Angela Frattarola (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial expresión escrita aprendizaje autónomo

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

Resumen:

While there are several “writing buddy” Generative Artificial Intelligence (GenAI) apps that check grammar and language usage, not many focus exclusively on enhancing the brainstorming process for writing across disciplines. To fill this gap, a team of staff and student assistants with programming and User Interface (UI) and User Experience (UX) expertise designed and prototyped a web app named “Waai,” which rhymes with ‘why,’ that could assist students throughout the writing process for a first-year general writing module for all undergraduate students at a Singaporean university.Utilising surveys, focus group discussions, and app data that shows the nature and type of student engagement...

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)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial educación infantil chatbots

Temas IA: IA y aprendizaje chatbots estudio empírico

Resumen:

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...

From AI anxiety to strategic regulation: How university students transform generative AI into a strategic learning resource

Eunjeo Kim (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial escritura académica factores afectivos

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

Resumen:

This study examined how university students engaged with generative AI as a strategic learning resource in academic writing tasks, with particular attention to the role of AI anxiety. Using an explanatory sequential mixed-methods design, survey data and post-task written reflections were collected from 107 university students. The quantitative analysis examined the relationships among AI anxiety, evaluative capacity, ethical awareness, and regulatory engagement, while the qualitative analysis explored how students described verifying, revising, selectively adopting, or rejecting AI-generated content during actual academic writing tasks. The findings showed that AI anxiety was positively...

Learners’ web navigation behaviour beyond learning management systems: A way into addressing procrastination in online learning?

Eduard Pogorskiy, Jens F. Beckmann (2022)

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Tipo: artículo

Metodología: estudio empírico

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

Temas IA: IA y aprendizaje estudio empírico

Resumen:

The attractiveness of online games, social media, and mobile apps is frequently considered a challenge for online learners. Procrastinatory behaviour is often associated with a relative lack of self-regulatory skills that would otherwise help learners to resist distractions and to progress in learning. This paper reports a pilot study, conducted with 49 online learners, in which we describe the use of a virtual learning assistant as a tool for collecting online learners' web navigation behaviour. As this virtual learning assistant operates as an extension to the Chrome web browser, it is possible that data collection is achieved independently of, and beyond specific learning management...

Artificial intelligence agents in computer-supported collaborative learning: A systematic literature review

Shen Ba, Xuechun Shi, Shuang Wu (2026)

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Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial aprendizaje colaborativo chatbots

Temas IA: IA y aprendizaje chatbots revisión de bibliografía

Resumen:

Artificial intelligence (AI) agents are rapidly reshaping the landscape of computer-supported collaborative learning (CSCL), presenting both new opportunities and challenges for educators and learners. Despite their increasing prevalence, there remains a lack of comprehensive, theory-informed synthesis regarding the roles and impacts of AI agents within CSCL. This systematic literature review analyses 46 empirical studies published between 2014 and 2025, with the aim of clarifying the methodological and contextual characteristics of the field, the pedagogical and technological features of AI-mediated CSCL environments, the instructional and mediational functions of AI agents, and the...

Predicting student achievement through peer network analysis for timely personalization via generative AI

Ivica Pesovski, Petar Jolakoski, Vladimir Trajkovik (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial analítica del aprendizaje aprendizaje colaborativo

Temas IA: IA y creación de materiales IA y aprendizaje estudio empírico

Resumen:

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...