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  • Computers & Education: Artificial Intelligence

Revistas: Computers & Education: Artificial Intelligence

Nº de publicaciones: 569

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Large language models meet user interfaces: The case of provisioning feedback
Stanislav Pozdniakov, Jonathan Brazil, Solmaz Abdi (2024)
Computers & Education: Artificial Intelligence 7
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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial feedback/retroalimentación grandes modelos de lenguaje

Resumen:

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Incorporating Generative Artificial Intelligence (GenAI), especially Large Language Models (LLMs), into educational settings presents valuable opportunities to boost the efficiency of educators and enrich the learning experiences of students. A significant portion of the current use of LLMs by educators has involved using conversational user interfaces (CUIs), such as chat windows, for functions like generating educational materials or offering feedback to learners. The ability to engage in real-time conversations with LLMs, which can enhance educators' domain knowledge across various subjects, has been of high value. However, it also presents challenges to LLMs' widespread, ethical, and...

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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)
Computers & Education: Artificial Intelligence 2
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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial tecnología educativa educación infantil

Resumen:

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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...

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A cross-national assessment of artificial intelligence (AI) Chatbot user perceptions in collegiate physics education
Benjamin Agyare, Joseph Asare, Amani Kraishan (2025)
Computers & Education: Artificial Intelligence 8
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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial ChatGPT chatbots

Resumen:

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This study explores the perception of artificial intelligence (AI)-based Chatbots, specifically Open AI's ChatGPT use, among physics students in four universities in Ghana, Jordan, and the United States. We utilized a survey instrument adapted from the Technology Acceptance Model (TAM) to elicit responses from 804 students. TAM constructs: Perceived Usefulness (PU), Perceived Ease of Use (PEU), Subjective Norms (SN), Attitude Towards Technology Use (ATU), Behavioral Intention (BI), and User Behavior (UB) were assessed. We also assessed perceptions of ethical use (EU) and student learning outcomes (SLO) using a Structural Equation Model (SEM) approach. A measurement model had good fit...

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Smart MOOC integrated with intelligent tutoring: A system architecture and framework model proposal
Ramazan Yilmaz, Halil Yurdugül, Fatma Gizem Karaoglan Yilmaz (2022)
Computers & Education: Artificial Intelligence 3
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Tipo: artículo

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

Resumen:

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Massive Open Online Courses (MOOCs) are a type of Learning Management Systems (LMSs), but it seems that the influence of the instructor in these systems is minimal or simply lacking. These systems present the learning content and materials to all learners attending the course in the same way and fail to offer individualized instruction that recognizes the individual differences and needs of the learners. It is reported that such problems can be eliminated by making the new generation intelligent learning systems. However, there is still an ongoing search for making such systems intelligent and a conceptual discussion concerning them. Integrating an intelligent tutoring system (ITS) with...

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Investigating the affordances of OpenAI's large language model in developing listening assessments
Vahid Aryadoust, Azrifah Zakaria, Yichen Jia (2024)
Computers & Education: Artificial Intelligence 6
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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial comprensión oral evaluación

Resumen:

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To address the complexity and high costs of developing listening tests for test-takers of varying proficiency levels, this study investigates the capabilities of an OpenAI's large language model, ChatGPT 4, in developing listening assessments. Employing prompt engineering and fine-tuning of prompts, the study specifically focuses on creating listening scripts and test items using ChatGPT 4 for test-takers across a spectrum of proficiency levels (academic, low, intermediate, and advanced). For comparability, the 24 topics of these scripts were selected from topics found in academic listening tests. We conducted two types of analyses to evaluate the quality of the output. First, we performed...

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Promoting inclusive AI and technology in K-12 education: A review of context, instructional strategies, and learning outcomes
Hyejeong Lee, Hyojung Kim, Wei Yan (2025)
Computers & Education: Artificial Intelligence 9
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Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial alfabetización en IA inclusión y equidad

Resumen:

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As artificial intelligence (AI) becomes increasingly integrated into K–12 education, concerns about equity and access have grown. This scoping review explores how inclusive AI curricula are designed, implemented, and evaluated in educational settings. Guided by three research questions, we analyzed 17 empirical studies published between 2013 and 2024, focusing on (1) the contexts and characteristics of inclusive AI curricula, (2) instructional strategies that promote broader participation, and (3) learning outcomes associated with these approaches. The findings reveal five key instructional principles (identity, technology, design, content development, and sense of belonging) alongside...

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Conversational AI in children's home literacy learning: effectiveness, advantages, challenges, and family perception
Shuang Quan, Xintian Tu-Shea, Yi Ding (2026)
Computers & Education: Artificial Intelligence 10
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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial chatbots grandes modelos de lenguaje

Resumen:

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This study investigates the effectiveness, affordances, limitations, and family perceptions of conversational AI for home literacy learning vs. human. We developed a large language model (LLM)-powered conversational AI system, named Vovo, to teach children vocabulary and co-construct stories using structured literacy pedagogy. The system was tested in home environments over six weeks with 10 families and their children aged 3–7 (M = 5.4). Across 150 learning sessions, Vovo delivered structured literacy instruction as effectively as parents, though children achieved higher learning outcomes when learning with parents. Video analysis revealed Vovo's advantages in pedagogical consistency,...

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Same AI, different pathways: Unpacking mechanisms of AI-mediated learning across discipline-institution contexts
Qinjie Shen (2026)
Computers & Education: Artificial Intelligence 11
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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial alfabetización en IA educación superior

Resumen:

Texto completo

Large language models (LLMs) are transforming higher education, yet their learning benefits likely depend on students’ AI literacy and how they prompt and verify AI outputs. This mixed-methods study investigates how AI literacy relates to prompting proficiency and verification behavior, and how these behaviors operate through two mechanisms, trust calibration and extraneous cognitive load, to predict coursework performance across two discipline–institution contexts in Thailand. The author surveyed Design students (n = 221) and Business students (n = 222) and analyzed the data using multigroup structural equation modeling, complemented by thematic analysis of semi-structured interviews....

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Instructional design and learning outcomes of intelligent computer assisted language learning: Systematic review in the field
Xiaojing Weng, Thomas K.F. Chiu (2023)
Computers & Education: Artificial Intelligence 4
Detalles Cerrar βœ•

Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial CALL/ELAO diseño curricular

Resumen:

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Research on Artificial Intelligence (AI) in language education becomes more popular. This revolutionary technology is regarded as a promising tool to assist language learning environments by empowering automatic feedback, intelligent tutoring, and personalization. While designing Intelligent Computer Assisted Language Learning (ICALL) environments, educators have followed the First Principles of Instruction (FPI), including problem-centered, activation, demonstration, application,...

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