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  • Computers & Education: Artificial Intelligence

Revistas: Computers & Education: Artificial Intelligence

Nº de publicaciones: 569

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Teacher feedback and ChatGPT feedback on Chinese university EFL learners’ English essay revision: A mixed-methods study
Feifei Han, Zehua Wang (2026)
Computers & Education: Artificial Intelligence 10
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial feedback/retroalimentación ChatGPT

Resumen:

Texto completo

Adopting mixed methods, the study compared teacher feedback and ChatGPT feedback on 35 Chinese university EFL learners’ essay revision, their Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) and their perceived benefits and drawbacks of the feedback. Students wrote two English essays and received writing feedback from their English teacher and ChatGPT respectively. They revised one essay using teacher feedback and another using ChatGPT feedback. Upon revision, students responded to a 5-point Likert-scale questionnaire regarding PU and PEOU of the two types of feedback. The results showed that students obtained significantly higher scores on the revised essays using ChatGPT...

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Synergizing collaborative writing and AI feedback: An investigation into enhancing L2 writing proficiency in wiki-based environments
Watcharapol Wiboolyasarin, Kanokpan Wiboolyasarin, Kanpabhat Suwanwihok (2024)
Computers & Education: Artificial Intelligence 6
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial expresión escrita aprendizaje colaborativo

Resumen:

Texto completo

Collaborative writing, paired with AI feedback, represents an innovative and effective pedagogical approach with the potential to revolutionize language learning practices. This study explores the influence of a three-step collaborative writing intervention, where AI feedback specially enhances the revision and editing stages of the L2 writing process for Thai-major undergraduate exchange students. Employing a quasi-experimental design, the study included 39 junior exchange students, with 18 in the experimental group and 21 in the control group. The approach employed a wiki-based collaborative writing strategy, integrating ChatGPT for written corrective feedback. The 10-week intervention...

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Overview and confirmatory and exploratory factor analysis of AI literacy scale
Martin J. Koch, Carolin Wienrich, Samantha Straka (2024)
Computers & Education: Artificial Intelligence 7
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial alfabetización en IA evaluación

Resumen:

Texto completo

Comprehensive concepts of AI literacy (AIL) and valid measures are essential for research (e.g., intervention studies) and practice (e.g., personnel selection/development) alike. To date, several scales have been published, sharing standard features but differing in some aspects. We first aim to briefly overview instruments identified from unsystematic literature research in February 2023. We identified four scales and one collection of items. We describe the instruments and compare them. We identified common themes and overlaps in the instruments and developmental procedure. We also found differences regarding scale development procedures and latent dimensions. Following this literature...

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Generative AI in computing education: A systematic review and a framework for responsible integration
Arun Kumar, Thakerng Wongsirichot, Aziz Nanthaamornphong (2026)
Computers & Education: Artificial Intelligence 11
Detalles Cerrar βœ•

Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial pensamiento computacional integridad académica

Resumen:

Texto completo

Context. Since late 2022, the rapid uptake of generative AI (GenAI) tools such as GitHub Copilot and ChatGPT has outpaced computing educators' evidence base for responding to it. Objective. This systematic literature review synthesises empirical evidence on four interconnected dimensions of GenAI in computing and programming education: effects on learning outcomes, student over-reliance, assessment integrity, and pedagogical adaptation. Method. Following Kitchenham and Charters (2007) guidelines and Wohlin's (2014) snowballing from seven curated seed papers, screening yielded 72 primary studies (2022–2026) from 33 venues, each was quality-assessed on a 10-item checklist (mean 8.32/10)....

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Investigating the tripartite interaction among teachers, students, and generative AI in EFL education: A mixed-methods study
Lihang Guan, John Chi-Kin Lee, Yue Zhang (2025)
Computers & Education: Artificial Intelligence 8
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial enseñanza/aprendizaje de lenguas interacción

Resumen:

Texto completo

This study explores the holistic integration of artificial intelligence (AI) in English as a Foreign Language (EFL) education, addressing significant gaps in empirical research on AI and EFL. Drawing on existing literature on the ecological views of AI in education, the study conceptualizes holistic integration as a balanced interaction among teachers, students, and AI technologies, enhancing rather than replacing traditional human interactions in pedagogy through mediating teacher-student interactions. The research utilized a mixed-method approach to investigate AI's impact on EFL students' proficiency and perceptions in teacher-led classrooms. 66 Participants from an eastern Chinese city...

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AI-enabled adaptive learning systems: A systematic mapping of the literature
Tumaini Kabudi, Ilias Pappas, Dag Håkon Olsen (2021)
Computers & Education: Artificial Intelligence 2
Detalles Cerrar βœ•

Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial tecnología educativa

Resumen:

Texto completo

Mobile internet, cloud computing, big data technologies, and significant breakthroughs in Artificial Intelligence (AI) have all transformed education. In recent years, there has been an emergence of more advanced AI-enabled learning systems, which are gaining traction due to their ability to deliver learning content and adapt to the individual needs of students. Yet, even though these contemporary learning systems are useful educational platforms that meet students’ needs, there is still a low number of implemented systems designed to address the concerns and problems faced by many students. Based on this perspective, a systematic mapping of the literature on AI-enabled adaptive learning...

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A scoping literature review of generative artificial intelligence for supporting neurodivergent school students
Michelle Ronksley-Pavia, Lan Nguyen, Elizabeth Wheeley (2025)
Computers & Education: Artificial Intelligence 9
Detalles Cerrar βœ•

Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial estudiantes con discapacidad educación primaria y secundaria

Resumen:

Texto completo

While Generative Artificial Intelligence (GenAI) platforms like ChatGPT have gained significant traction in education, their specific applications for neurodivergent learners remain largely unmapped. Through systematic searching of academic databases and grey literature between 2020 and 2024, this scoping literature review examined the emerging landscape of GenAI applications in supporting neurodivergent students (e.g., those with ADHD, autism, dyslexia, gifted, twice-exceptional) within K-12 educational contexts. Twenty-one relevant sources were identified, discussing GenAI usage with neurodivergent students, the analysis revealed discussion of several predominant applications, including...

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Teachers’ readiness and intention to teach artificial intelligence in schools
Musa Adekunle Ayanwale, Ismaila Temitayo Sanusi, Owolabi Paul Adelana (2022)
Computers & Education: Artificial Intelligence 3
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial alfabetización en IA creencias y actitudes de los profesores

Resumen:

Texto completo

The emergence of artificial intelligence (AI) as a subject to be incorporated into K-12 educational levels places new demand on relevant stakeholders, especially teachers that drive the teaching and learning process. It is therefore important to understand how ready teachers are to teach the emerging subject as the success of AI education would probably be closely dependent on the readiness of teachers. As a result, this study presents an insight into factors influencing the behavioural intention and readiness of Nigerian in-service teachers to teach artificial intelligence. A total of 368 teachers, from elementary to high school participated in the study. We utilised quantitative...

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Style, sentiment, and quality of undergraduate writing in the AI era: A cross-sectional and longitudinal analysis of 4,820 authentic empirical reports
Matthew H.C. Mak, Lukasz Walasek (2025)
Computers & Education: Artificial Intelligence 9
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial escritura académica educación superior

Resumen:

Texto completo

As generative artificial intelligence (GenAI) becomes widespread in education, its influence on students' academic practice raises concern. We conducted pre-registered analyses of 4820 empirical reports authored by 2000 psychology undergraduates (2016–2025) to examine how ChatGPT's launch in November 2022 may influence the style, sentiment, and quality of students' writing. Following ChatGPT's release, prevalence of ChatGPT-associated lexical markers (e.g., delve, intricate) surged until 2024, then declined in 2025, possibly due to some students actively masking GenAI traces. Writing style (indexed by lexical diversity/density/sophistication, nominalisation, readability) became increasingly...

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Applying large language models and chain-of-thought for automatic scoring
Gyeong-Geon Lee, Ehsan Latif, Xuansheng Wu (2024)
Computers & Education: Artificial Intelligence 6
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial evaluación grandes modelos de lenguaje

Resumen:

Texto completo

This study investigates the application of large language models (LLMs), specifically GPT-3.5 and GPT-4, with Chain-of-Though (CoT) in the automatic scoring of student-written responses to science assessments. We focused on overcoming the challenges of accessibility, technical complexity, and lack of explainability that have previously limited the use of artificial intelligence-based automatic scoring tools among researchers and educators. With a testing dataset comprising six assessment tasks (three binomial and three trinomial) with 1,650 student responses, we employed six prompt engineering strategies to automatically score student responses. The six strategies combined zero-shot or few-...

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