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  • Computers & Education: Artificial Intelligence

Revistas: Computers & Education: Artificial Intelligence

Nº de publicaciones: 569

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Automatic proficiency scoring for early-stage writing
Michael Riis Andersen, Kristine Kabel, Jesper Bremholm (2023)
Computers & Education: Artificial Intelligence 5
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial expresión escrita evaluación

Resumen:

Texto completo

In this work, we study the feasibility of using machine learning and natural language processing methods for assessing writing proficiency in Danish with respect to text construction, sentence construction, and use of modifiers. Our work is based on the analytical framework for scoring early writing proposed by Kabel et al. (2022), where each text is first annotated by a human expert according to a predefined coding scheme and subsequently scored using statistical Rasch modeling (Rasch, 1960). We investigate two different strategies for estimating these scores automatically: 1) we propose a system for identifying the central linguistic features automatically mimicking the role of the human...

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Building AI companions that prioritise learning over performance
Hassan Khosravi, Dragan Gaševiฤ‡, Shazia Sadiq (2026)
Computers & Education: Artificial Intelligence 11
Detalles Cerrar โœ•

Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial grandes modelos de lenguaje metacognición

Resumen:

Texto completo

Generative AI, currently most visible in education through large language models (LLMs), is increasingly embedded in students’ everyday learning practices, supporting tasks such as writing, coding, reasoning, and analysis. Yet its educational value remains uncertain because systems designed to improve immediate task performance may also weaken the cognitive and metacognitive processes that support durable learning. This paper addresses this learning–performance paradox by asking how AI systems can be designed to support learning rather than merely produce better outputs. To address this, in this paper, we make three contributions. First, we synthesise current LLM-based study support with...

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How well can LLMs grade essays in Arabic?
Rayed Ghazawi, Edwin Simpson (2025)
Computers & Education: Artificial Intelligence 9
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial expresión escrita evaluación

Resumen:

Texto completo

This research assesses the effectiveness of state-of-the-art large language models (LLMs), including ChatGPT, Llama, Aya, Jais, and ACEGPT, in the task of Arabic automated essay scoring (AES) using the AR-AES dataset. It explores various evaluation methodologies, including zero-shot, few-shot in context learning, and fine-tuning, and examines the influence of instruction-following capabilities through the inclusion of marking guidelines within the prompts. A mixed-language prompting strategy, integrating English prompts with Arabic content, was implemented to improve model comprehension and performance. Among the models tested, ACEGPT demonstrated the strongest performance across the...

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Exploring student and teacher perceptions of ChatGPT use in higher education: A Q-Methodology study
Alma S. Espartinez (2024)
Computers & Education: Artificial Intelligence 7
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial ChatGPT educación superior

Resumen:

Texto completo

This study examined and categorized the views of students and teachers in Philippine Higher Education Institutions (HEIs) and correlated those with similar patterns of views regarding ChatGPT usage. While previous studies explored ChatGPT's risks and benefits, a significant gap remains in understanding how college students and educators perceive this technology for its culturally relevant and equitable integration into teaching and learning. Using Q-Methodology, 27 participants (15 students and 12 professors) were surveyed, interviewed, and invited to rank-order 36 statements about using ChatGPT. Three factors emerged from using factor analysis: Ethical Tech Guardians, Balanced Pedagogy...

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The formation of AI Capital in higher education: Enhancing students’ academic performance and employment rates
Nick Drydakis (2025)
Computers & Education: Artificial Intelligence 9
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial alfabetización en IA educación superior

Resumen:

Texto completo

The study evaluates the effectiveness of a 12-week AI module delivered to non-STEM university students in England, aimed at building students' AI Capital, encompassing AI-related knowledge, skills, and capabilities. An integral part of the process involved the development and validation of the AI Capital of Students scale, used to measure AI Capital before and after the educational intervention. The module was delivered on four occasions to final-year students between 2023 and 2024, with follow-up data collected on students' employment status. The findings indicate that AI learning enhances students' AI Capital across all three dimensions. Moreover, AI Capital is positively associated with...

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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
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial feedback/retroalimentación grandes modelos de lenguaje

Resumen:

Texto completo

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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Large language models for education: An open-source paradigm for automated Q&A in the graduate classroom
Ryann M. Perez, Marie Shimogawa, Yanan Chang (2026)
Computers & Education: Artificial Intelligence 10
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial grandes modelos de lenguaje andamiaje/scaffolding

Resumen:

Texto completo

Large Language Models (LLMs) offer scalable educational support, but face barriers regarding accuracy, cost, and learning depth. To interrogate these limitations, we developed the Teaching Assistant for Specialized Knowledge (TAsk), a retrieval-augmented generation enabled and educator curated pipeline. In this nine-week pilot study (N = 33 participants), we deployed TAsk in a graduate-level biological chemistry course. We compared TAsk against human expert teaching assistants (TAs) using blinded review process and analyzed inquiry depth. We observed three major findings related to potential pedagogical decisions and educational theory. First, TAsk delivered effective feedback that was...

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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
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial ChatGPT chatbots

Resumen:

Texto completo

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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Children as creators, thinkers and citizens in an AI-driven future
Safinah Ali, Daniella DiPaola, Irene Lee (2021)
Computers & Education: Artificial Intelligence 2
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial alfabetización en IA competencia digital

Resumen:

Texto completo

Generative Artificial Intelligence (AI) approaches open up new avenues of digital creation, and are simultaneously accompanied by societal and ethical implications such as the creation of Deepfakes and spread of misinformation, renewing our understanding of technical AI systems as socio-technical systems. Applications of, and media generated by generative AI techniques are abundantly present on social media platforms frequented by children, who are not yet aware of the existence of AI-manipulated media. Previous work has highlighted the importance of digital media literacy and AI literacy for children. In this work, we introduce middle school students to generative AI techniques as a tool...

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Are deeper reflectors better goal-setters? AI-empowered analytics of reflective writing in pharmaceutical education
Yuheng Li, Mladen Rakoviฤ‡, Wei Dai (2023)
Computers & Education: Artificial Intelligence 5
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial aprendizaje autónomo expresión escrita

Resumen:

Texto completo

Reflection and goal-setting are interrelated processes in well-established educational theories to promote in-depth self-reflection and self-regulated learning. Prior studies have considered reflection to be an important antecedent for meaningful goal-setting. Yet, there lacks empirical evidence to shed light on how students' abilities to reflect inform their abilities to set goals. Hence, in the present study, we aimed to quantify the connection between students' retrospective reflection and their subsequent goal-setting, and derive more in-depth insights to benefit educators in their teaching to promote deeper reflection, more specific goal-setting and better self-regulation. To this end...

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