IA y aprendizaje

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial pensamiento computacional andamiaje/scaffolding

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

Resumen:

Introduction: Generative AI is reshaping programming education, yet its effects on conceptual learning, intrinsic motivation, and cognitive load remain unclear. This study tests whether assistance deepens understanding or primarily boosts task completion, and how scaffolded versus answer-giving designs matter. Objectives: This study compares performance, learning, cognitive load, frustration, and motivation across three AI support types, and examines students’ perceptions. Methods: A three-arm randomized controlled trial was conducted in an introductory programming (CS1) course at TUM (N=275). Participants completed a 90-minute exercise on concurrency, implementing a parallel sum with...

Enhancing data analysis and programming skills through structured prompt training: The impact of generative AI in engineering education

Ashish Garg, K. Nisumba Soodhani, Ramkumar Rajendran (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial pensamiento computacional educación superior

Temas IA: prompts IA y aprendizaje modelos de lenguaje (LLM)

Resumen:

The advent of Generative Artificial Intelligence (GenAI) and large language models like LLama, Palm2, GPT, Gemini, and Claude has revolutionized education by generating human-like text and contextually relevant responses. Our research investigates the impact of structured prompt training on students' learning in data analysis and programming. We experimented with 157 first-year engineering students divided into three groups: a control group (internet access, no GenAI), an experimental group 1 (internet and GenAI without prompt training), and an experimental group 2 (internet and GenAI with prompt training). The prompt training session included techniques like few-shot prompting, chain...

Generative AI-assisted workflows in architectural conceptual design: Performance, creative self-efficacy, and cognitive load

Yao Xiao, Han Jiang, Rachel Hurley (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial educación superior cognición y procesamiento

Temas IA: IA y aprendizaje estudio empírico

Resumen:

Generative AI (GenAI) is increasingly adopted in design education, yet evaluating its educational value through final outcomes provides an incomplete picture. This study compares two ecologically plausible workflows in an architectural conceptual design task: GenAI-assisted image generation and ArchDaily-based precedent search. The comparison concerns complete workflows rather than the isolated contributions. Thirty-six students completed a two-phase design task, first designing independently and then revising with their assigned workflow. Screen-recording demonstrated active engagement in both conditions. Eight judges rated design performance, while participants reported task-specific and...

Is ChatGPT a good study companion? The role of AI-generated summaries and reflective prompts in learning from educational videos

Ayşe Candan Şimşek, Gerrit Anders, Jonathan Göth (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial ChatGPT materiales audiovisuales

Temas IA: chatGPT IA y aprendizaje estudio empírico

Resumen:

Online videos have become a central tool in modern education. Alongside this shift, Artificial Intelligence (AI) is reshaping personalized learning experiences, with generative large language models like ChatGPT offering new ways to tailor information to individual learners. Based on the Cognitive Theory of Multimedia Learning (CTML), which proposes two principles that relate to the interaction with the learning material (segmenting and generative activity), we conducted two experiments in which participants were asked to pause an educational video at times of comprehension difficulty. In Experiment 1 (N = 101), we examined whether GPT-generated summaries -introduced at self-paced pause...

LLaVA-docent: Instruction tuning with multimodal large language model to support art appreciation education

Unggi Lee, Minji Jeon, Yunseo Lee (2024)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial grandes modelos de lenguaje chatbots

Temas IA: modelos de lenguaje (LLM) chatbots IA y aprendizaje

Resumen:

Despite the development of various AI systems to support learning in various domains, AI assistance for art appreciation education has not been extensively explored. Art appreciation, often perceived as an unfamiliar and challenging endeavor for most students, can be more accessible with a generative AI enabled conversation partner that provides tailored questions and encourages the audience to deeply appreciate artwork. This study explores the application of multimodal large language models (MLLMs) in art appreciation education, with a focus on developing LLaVA-Docent, a model designed to serve as a personal tutor for art appreciation. Our approach involved design and development research...

Conversational AI as a catalyst for informal learning: An empirical large-scale study on LLM use in everyday learning

Nađa Terzimehić, Babette Bühler, Enkelejda Kasneci (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial aprendizaje informal grandes modelos de lenguaje

Temas IA: chatbots IA y aprendizaje estudio empírico

Resumen:

Large language models have not only captivated the public imagination but have also sparked a profound rethinking of how we learn. In the third year following the breakthrough launch of ChatGPT, everyday informal learning has been transformed as these novel tools become easily and widely available. Who is embracing LLMs for self-directed learning, and who remains hesitant? What are their reasons for adoption or avoidance? What learning patterns emerge with this novel technological landscape? We present an in-depth analysis from a large-scale survey of 776 German participants, showcasing that 88% of our respondents already incorporate LLMs into their everyday learning routines for a wide...

Modelling and exploiting taxonomic knowledge for developing mobile learning systems to enhance children’s structural and functional categorization

MuhammadAzeem Abbas, Gwo-Jen Hwang, Saheed Ajayi (2021)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial tecnología educativa educación infantil

Temas IA: IA y aprendizaje estudio empírico

Resumen:

The recent decade has seen increased attention focused on understanding category formation–a cognition ability of preschool aged children. Children organize their knowledge about real-world objects by categorizing them under some common properties or functions. The advancement and popularity of mobile devices with touch screens provide a good opportunity for young children to learn and practice. In this study, an approach that models structural and functional categorization knowledge for developing mobile learning systems with dynamic categorization exemplars is proposed. A mobile application was implemented based on the proposed model for pre-schoolers (aged 3–6 years). Moreover, the quasi...

Exploring the role of intrinsic motivation in ChatGPT adoption to support active learning: An extension of the technology acceptance model

Chung Yee Lai, Kwok Yip Cheung, Chee Seng Chan (2023)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial ChatGPT motivación

Temas IA: chatGPT IA y aprendizaje estudio empírico

Resumen:

Background: ChatGPT, a powerful artificial intelligence chatbot, has great potential for active learning because of its ability to generate instant responses to academic inquiries and foster spontaneous interactions. Purpose: This exploratory study investigated the roles of intrinsic motivation and factors of the technology acceptance model that influence ChatGPT acceptance for active learning among undergraduates in Hong Kong. Method: Using a structural equation modeling approach, we examined the extended technology acceptance model in the context of higher education. Using self-report questionnaires, we obtained useful responses from 473 undergraduate students in Hong Kong in July 2023....

Generative AI-enhanced learning experiences for computational thinking: A systematic scoping review and design guidelines

Abdessalam Ouaazki, Antonette Shibani, Simon Knight (2026)

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Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial pensamiento computacional

Temas IA: IA y aprendizaje IA y educación revisión de bibliografía

Resumen:

Computational thinking (CT) skills are crucial to teach. The rise of Generative AI could potentially revolutionize the teaching of these skills by changing learning experiences and outcomes. Educators are rapidly integrating these tools into their educational activities; however, the best practices for doing so remain unclear. Existing reviews on GenAI are either too broad in regards to studying specific tools such as ChatGPT for learning, or too limited in terms of studying computational thinking with a focus on programming. As such, this paper aims to summarize existing knowledge and extract best practices and avenues for future research and practice around GenAI and computational...

AI-based learning content generation and learning pathway augmentation to increase learner engagement

Chaitali Diwan, Srinath Srinivasa, Gandharv Suri (2023)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial tecnología educativa creación de materiales

Temas IA: IA y creación de materiales IA y aprendizaje modelos de lenguaje (LLM)

Resumen:

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Retaining learner engagement is a major challenge in online learning environments, which is even more intensified with learning spaces increasingly built by combining resources from multiple independent sources. Narrative-centric learning experience has been found to improve learner engagement by several researchers. Towards this end, we propose an AI-based approach that generates auxiliary learning content called narrative fragments which are interspersed into the learning pathways to create interactive learning narratives. The proposed approach consists of the automatic generation of two types of narrative fragments– overviews of the learning pathway segments and reflection...