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  • Computers & Education: Artificial Intelligence

Revistas: Computers & Education: Artificial Intelligence

Nº de publicaciones: 569

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Bridging technology and pedagogy from a global lens: Teachers’ perspectives on integrating ChatGPT in English language teaching
Mohammad H. Al-khresheh (2024)
Computers & Education: Artificial Intelligence 6
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial ChatGPT creencias y actitudes de los profesores

Resumen:

Texto completo

The rise of Artificial Intelligence in educational contexts has sparked both excitement and trepidation, highlighting the urgent need to investigate its implications, especially in English Language Teaching. In light of this context, this study aimed to find out how English language teachers perceive the pedagogical benefits and challenges posed by ChatGPT when incorporated into ELT and identify potential avenues for such digital innovations. Adopting a qualitative research design, data were purposively collected by distributing an open-ended questionnaire to 46 English language teachers from multiple countries. This sample was solicited via the academic and research platform ResearchGate,...

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Assessing the quality of automatic-generated short answers using GPT-4
Luiz Rodrigues, Filipe Dwan Pereira, Luciano Cabral (2024)
Computers & Education: Artificial Intelligence 7
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial grandes modelos de lenguaje evaluación

Resumen:

Texto completo

Open-ended assessments play a pivotal role in enabling instructors to evaluate student knowledge acquisition and provide constructive feedback. Integrating large language models (LLMs) such as GPT-4 in educational settings presents a transformative opportunity for assessment methodologies. However, existing literature on LLMs addressing open-ended questions lacks breadth, relying on limited data or overlooking question difficulty levels. This study evaluates GPT-4's proficiency in responding to open-ended questions spanning diverse topics and cognitive complexities in comparison to human responses. To facilitate this assessment, we generated a dataset of 738 open-ended questions across...

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Examining teachers’ behavioural intention of using generative artificial intelligence tools for teaching and learning based on the extended technology acceptance model
Siu-Cheung Kong, Yin Yang, Chunyu Hou (2024)
Computers & Education: Artificial Intelligence 7
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial creencias y actitudes de los profesores profesorado

Resumen:

Texto completo

The rapid development of generative artificial intelligence (GenAI) tools has given rise to a growing discussion of the potential challenges and benefits that the use of these technologies may present in the field of education. This study examines the acceptance of the use of GenAI tools for teaching and learning among primary and secondary school teachers in Hong Kong. It uses an extension of the technology acceptance model (TAM) with a modified framework that incorporates two key factors: self-efficacy and subjective norm. Data were collected from a sample of 367 primary and secondary school teachers in Hong Kong using questionnaires containing items for six constructs: self-efficacy,...

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AI-assisted knowledge assessment techniques for adaptive learning environments
Sein Minn (2022)
Computers & Education: Artificial Intelligence 3
Detalles Cerrar βœ•

Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial evaluación tecnología educativa

Resumen:

Texto completo

The growth of online learning, enabled by the availability on the Internet of different forms of didactic materials such as MOOCs and Intelligent Tutoring Systems (ITS), in turn, increases the relevance of personalized instructions for students in an adaptive learning environment. There are increasing interests as well as many challenges in the application of Artificial Intelligence (AI) techniques in educational settings to provide adaptive learning content to learners. Knowledge assessment is necessary for providing an adaptive learning environment. A student model serves as a fundamental building block of knowledge assessment in an adaptive learning environment. This paper intends to...

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A cross-country analysis of self-determination and continuance use intention of AI tools in business education: Does instructor support matter?
Egena Ode, Rabake Nana, Irene O. Boro (2025)
Computers & Education: Artificial Intelligence 8
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial motivación educación superior

Resumen:

Texto completo

This study builds on the recent interest in AI adoption research in academic settings by highlighting the need for culturally sensitive AI educational tools. The study achieved this by demonstrating how cultural differences shape students' motivation and AI use. This study adopts a cross-country comparative analytical approach to explore postgraduate students’ motivation to continue using AI tools in the context of higher education. The study developed a theoretical model based on Self-Determination Theory (SDT) and Expectation Disconfirmation Theory (EDT) to explore how perceived competence, perceived relatedness and perceived autonomy influence the continuance use intention of AI tools in...

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English speaking practice with conversational AI: Lower secondary students' educational experiences over time
Elin Ericsson, Stefan Johansson (2023)
Computers & Education: Artificial Intelligence 5
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial expresión oral chatbots

Resumen:

Texto completo

Conversational artificial intelligence enables opportunities for practicing speaking the target language while giving individualized feedback in a low-anxiety environment offered in spoken dialogue systems with conversational agents. In this paper, we present results from a longitudinal study conducted on Swedish lower-secondary students who used a spoken dialogue system as an integrated part of their ordinary English lessons. They interacted orally with embodied conversational agents to solve given tasks in everyday-life scenarios and self-reported their experiences in questionnaires and systematic logbook reflections. Analytical methods were mainly non-parametric tests. Results revealed...

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Unpacking artificial intelligence in elementary education: A comprehensive thematic analysis systematic review
Taoufik Boulhrir, Mahmoud Hamash (2025)
Computers & Education: Artificial Intelligence 9
Detalles Cerrar βœ•

Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial educación primaria y secundaria tecnología educativa

Resumen:

Texto completo

Artificial Intelligence (AI) has gained much research interest recently and is rapidly transforming education around the world. However, there is still limited research with regards to its applications and effects on learning, in comparison to the available studies conducted at higher levels of education. This paper presents a systematic literature review conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. It explores the geographical distribution and frequency of research on AI in elementary education between 2013 and 2023. It provides an analysis of the various educational areas in which AI has been applied, and it synthesizes...

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Evaluating the academic outcome of AI-powered joint support for at-risk students
Ning Xu, Fengjun Wu, Zhiyuan Liu (2025)
Computers & Education: Artificial Intelligence 9
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial analítica del aprendizaje educación superior

Resumen:

Texto completo

Despite the growing global adoption of AI-powered academic advice, its impact remains underexplored. This study addresses this gap by evaluating the academic performance of at-risk students who receive AI-driven joint support. We proposed a practical framework for assessing academic outcomes by leveraging AI as a decision-making tool for advisors. Our study employs a quasi-experimental difference-in-differences (DID) methodology over three semesters. We compare the academic outcomes of at-risk students in pilot departments who received the intervention (treatment group, N = 516) with all other students in the analytic sample (control group, N = 12,004), supplemented with robustness checks....

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Taming the black box: Design principles for rule-integrated LLM tutoring systems in primary school mathematical problem solving
Chee-Kit Looi, Zhaolong Liu, Daner Sun (2026)
Computers & Education: Artificial Intelligence 10
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial grandes modelos de lenguaje andamiaje/scaffolding

Resumen:

Texto completo

The integration of large language models (LLMs) into intelligent tutoring systems promises personalized learning, yet procedural domains such as primary mathematics remain challenging due to inconsistency and pedagogical opacity. LLM tutors may give unsolicited answers or show unstable scaffolding when students vary arithmetic, units, or rounding. This design science research develops and evaluates a rule-guided tutoring system for mathematical word problems in primary schools. We formalize a distinction between rule-guided scaffolding, in which tutoring is governed by a three-layer architecture (diagnosis → intent selection → constrained response generation), and ad-hoc scaffolding, where...

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LLMs do not grade essays like humans
Jerin George Mathew, Sumayya Taher, Anindita Kundu (2026)
Computers & Education: Artificial Intelligence 11
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial expresión escrita evaluación

Resumen:

Texto completo

Large language models have recently been proposed as tools for automated essay scoring, but their agreement with human grading remains unclear. In this work, we evaluate how LLM-generated scores compare with human grades and analyze the grading behavior of several models from the GPT and Llama families in an out-of-the-box setting, without task-specific training. Our results show that agreement between LLM and human scores remains relatively weak and varies with essay characteristics. In particular, compared to human raters, LLMs tend to assign higher scores to short or underdeveloped essays, while assigning lower scores to longer essays that contain minor grammatical or spelling errors. We...

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