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  • Computers & Education: Artificial Intelligence

Revistas: Computers & Education: Artificial Intelligence

Nº de publicaciones: 569

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Fine-tuning AI models for enhanced consistency and precision in chemistry educational assessments
Sri Yamtinah, Antuni Wiyarsi, Hayuni Retno Widarti (2025)
Computers & Education: Artificial Intelligence 8
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial evaluación grandes modelos de lenguaje

Resumen:

Texto completo

Integrating artificial intelligence (AI) into educational assessments represents a paradigm shift, especially in STEM subjects such as chemistry, which require complex problem-solving and written feedback. This study focuses on the effects of fine-tuning on each of the four AI models—Gemini 1.5, Gemini 1.0, BERT, and XLNet—and their performance on chemistry tasks. The models were implemented using three evaluation methods: Seq2Seq for Sodium Reaction Grading, a Regression Task for Overall Grading, and Attention-Based Grading for Key Steps Grading. The fine-tuning process significantly improved the models' accuracy, precision, and stability. Gemini 1.5 outperformed the other models across...

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Evaluation of an artificial intelligence literacy course for university students with diverse study backgrounds
Siu-Cheung Kong, William Man-Yin Cheung, Guo Zhang (2021)
Computers & Education: Artificial Intelligence 2
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial alfabetización en IA educación superior

Resumen:

Texto completo

A few limited efforts have been made to promote artificial intelligence (AI) literacy for citizens. The objective of this study was to design, implement and evaluate an AI literacy course for university students. One of the study's research questions was whether university students from a variety of disciplines could develop a conceptual understanding of AI through a literacy course. We promoted this course to 4000 students and recruited 120 volunteer participants to attend and complete the 7-h course. The results of our pre-course and post-course surveys indicated that the participants made significant progress in understanding AI concepts, felt empowered to work with AI. These findings...

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AI-based multidisciplinary framework to assess the impact of gamified video-based learning through schema and emotion analysis
Anjana Junius Vidanaralage, Anuja Thimali Dharmaratne, Shamsul Haque (2022)
Computers & Education: Artificial Intelligence 3
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial gamificación materiales audiovisuales

Resumen:

Texto completo

Background: As a natural and continual process, the initial learning stages encompass mastering and recalling basic facts. The process proves effective with the integration of new information with pre-existing knowledge characterised as schema to facilitate memory encoding. Additionally, emotions also have the ability to modulate human cognition in terms of learning and memory. The recent advent of gamification in e-learning, which has garnered much scholarly and industrial interest, necessitates a thorough examination between video-based learning and its subsequent implications on schema, emotions, and gamification. Objectives: The current multidisciplinary research triangulated cognitive...

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Fostering responsible AI literacy: A systematic review of K-12 AI ethics education
Ming Ma, Davy Tsz Kit Ng, Zhichun Liu (2025)
Computers & Education: Artificial Intelligence 8
Detalles Cerrar βœ•

Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial ética alfabetización en IA

Resumen:

Texto completo

AI ethics education remains significantly underprioritized in classroom practice, despite the global push for AI literacy in K-12 curricula. This systematic review analyzes 68 peer-reviewed publications (from January 2014 to March 2025) to map the research landscape of K-12 AI ethics education. The results reveal global trends in the current research landscape, pedagogical designs addressing major responsible AI (RAI) principles, and various learning assessment methods, and students’ ethical learning outcomes manifested across cognitive, affective, and behavioral domains. By further synthesizing findings, we identify disparities of eastern and western contexts, gaps in addressing RAI...

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Measuring Acceptance of Age-Tiered AI Literacy Guidebooks: A Developmentally Informed Study of K-12 Students and Teachers
Li-Jen Wang, Tsung-Yen Chuang, Ying-Tien Wu (2026)
Computers & Education: Artificial Intelligence
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial alfabetización en IA educación primaria y secundaria

Resumen:

Texto completo

As generative artificial intelligence (AI) becomes increasingly integrated into K-12 education, there is a pressing need for AI literacy initiatives to incorporate learning resources that are both age-appropriate and ethically grounded. This study examined acceptance of the AI Learning Application Guidebook, developed in Elementary and Advanced editions for learners aged 9–12 and 13–18, respectively. The Elementary edition features scaffolded, platform-based, non-generative activities, whereas the Advanced edition includes authentic applications, ethical reasoning exercises, and supervised engagement with generative AI. The guidebooks were evaluated in Taiwanese classrooms by 831...

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Unmasking the impacts of self-evaluation in AI-supported writing instruction on EFL learners’ emotion regulation, self-competence, motivation, and writing achievement
Tahereh Heydarnejad (2025)
Computers & Education: Artificial Intelligence 9
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial autoevaluación expresión escrita

Resumen:

Texto completo

This study explores the impact of embedding self-evaluation within AI-supported writing instruction on learners’ cognitive emotion regulation, self-competence, motivation, and writing achievement. Conducted at a high school in Iran, the research utilized a quantitative quasi-experimental pretest-posttest design involving two intact pre-intermediate writing classes randomly assigned to an experimental group and a control group. The experimental group received instruction that combined AI tools with structured self-evaluation activities, whereas the control group followed a traditional teaching approach without AI integration or self-evaluation. Data were collected using the Cognitive Emotion...

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Decoding divides: The role of socioeconomic status and personality traits in AI divides and educational inequality
Zeyu Wang, Sanne van Wetten, Eliane Segers (2026)
Computers & Education: Artificial Intelligence 10
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial inclusión y equidad competencia digital

Resumen:

Texto completo

This study investigates whether the integration of AI in primary education relates to the digital divide and educational inequality, thereby examining the mediating roles of AI usage and digital literacy. Using survey and national registry data from 4497 Grade 6 students in the Netherlands (2022–2023), we examined relations between family socioeconomic status (SES) and personality traits (openness, extraversion, perseverance) via AI usage and digital literacy to academic performance. Our analyses revealed that digital literacy, not AI usage, positively mediated the relationship between all three personality traits and academic achievement. Family SES demonstrated a strong, direct...

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The effect of student acceptance on learning outcomes: AI-generated short videos versus paper materials
Yidi Zhang, Margarida Lucas, Pedro Bem-haja (2024)
Computers & Education: Artificial Intelligence 7
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial materiales audiovisuales materiales didácticos

Resumen:

Texto completo

The use of video and paper-based materials is commonly widespread in foreign language learning (FLL). It is well established that the level of acceptance of these materials influences learning outcomes, but there is lack of evidence regarding the use and related impact of videos generated by artificial intelligence (AI) on these aspects. This paper used linear mixed models and path analysis to investigate the influence of student acceptance of AI-generated short videos on learning outcomes compared to paper-based materials. Student acceptance was assessed based on perceived ease of use (PEU), perceived usefulness (PU), attitude (A), intentions (I), and concentration (C). The results...

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AI for education: The digital transformation of a liberal arts institution – implementation at Lingnan University
S. Joe Qin (2026)
Computers & Education: Artificial Intelligence 10
Detalles Cerrar βœ•

Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial educación superior innovación educativa

Resumen:

Texto completo

The global landscape of higher education is undergoing a profound transformation driven by Generative Artificial Intelligence (GenAI) and pervasive digital technologies, particularly posing fundamental challenges to the traditional liberal arts education model grounded in holistic human development, broad intellectual inquiry, and student engagement. This position paper examines Lingnan University (Lingnan), Hong Kong’s longest-established institution of higher education, as a critical case of how a liberal arts university can strategically transform itself in the digital era without relinquishing its humanistic foundations. It analyzes Lingnan’s institutional transformation towards a “...

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The power of Deep Learning techniques for predicting student performance in Virtual Learning Environments: A systematic literature review
Bayan Alnasyan, Mohammed Basheri, Madini Alassafi (2024)
Computers & Education: Artificial Intelligence 6
Detalles Cerrar βœ•

Tipo: artículo

Metodología: revisión bibliográfica

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

Resumen:

Texto completo

With the advances in Artificial Intelligence (AI) and the increasing volume of online educational data, Deep Learning techniques have played a critical role in predicting student performance. Recent developments have assisted instructors in determining the strengths and weaknesses of student achievement. This understanding will benefit from adopting the necessary interventions to assist students in improving their performance, helping at-risk of failure students, and preventing dropout rates. The review analyzed 46 studies between 2019 and 2023 that apply one or more Deep Learning (DL) techniques, either single or in combination with Machine Learning (ML) or Ensemble Learning techniques....

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