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  • Computers & Education: Artificial Intelligence

Revistas: Computers & Education: Artificial Intelligence

Nº de publicaciones: 569

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Educational data journeys: Where are we going, what are we taking and making for AI?
Sarah K. Howard, Teresa Swist, Dragan Gaševiฤ‡ (2022)
Computers & Education: Artificial Intelligence 3
Detalles Cerrar โœ•

Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial analítica del aprendizaje ética

Resumen:

Texto completo

Educational systems generate huge quantities of digital data. Digital educational data is captured and used at all points -- from classrooms and schools, to the level of educational departments. As growing trends in ‘data-driven instruction’ suggest, all these data have great potential to support student, teacher and leadership practices, help guide work and learning decisions, and inform policy development. Moreover, an increasing focus is being placed on the development of artificial intelligence to automate and improve how data are used. Yet, stakeholder data practices remain invisible and little understood, which complicates how artificial intelligence can be embedded in this context....

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Leveraging an LLM-enhanced bilingual conversational agent for EFL children’s dialogic reading: Insights from children, parents, and educators
Feiwen Xiao, Zhaohui Li, Jiaju Lin (2025)
Computers & Education: Artificial Intelligence 9
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial chatbots grandes modelos de lenguaje

Resumen:

Texto completo

Dialogic reading, a technique in which adults and children engage in interactive discussions around a story, has been shown to improve children’s language and literacy development. Despite its evidence-based benefits, its adoption amongfamilies with English as a Foreign Language (EFL) backgrounds has been particularly challenging due to limited English proficiency, restricted conversational skills, and a low inclination to read in English. This paper presents “Storio'', an e-book integrated with a bilingual large language model (LLM)-based conversational agent named “Mia'', used as a design probe to investigate interactions between EFL children (N=17) and the agent, and to gather insights...

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Towards the development of complex thinking in university students: Mixed methods with ideathon and artificial intelligence
Isolda Margarita Castillo-Martínez, Amadeo José Argüelles-Cruz, Octavio Elías Piñal-Ramírez (2023)
Computers & Education: Artificial Intelligence 5
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial pensamiento crítico evaluación

Resumen:

Texto completo

This article examines the capacity of an artificial intelligence (AI) platform to assess university students' mastery of complex thinking. Central questions addressed include the identification of essential technical elements that contribute to the platform's effectiveness, and how the AI platform can boost student motivation and cultivate complex thinking. The research employed a mixed-methods approach, anchored by an Ideathon centered on the Sharing Economy. Qualitative insights were drawn from semi-structured interviews with nine university students. The results indicate that the platform effectively evaluates complex thinking proficiency, differentiating between systemic, scientific,...

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Exploring the relationship between empowerment in using artificial intelligence for problem-solving and artificial intelligence ethical awareness: Multi-group structural equation modelling
Siu-Cheung Kong, Jinyu Zhu (2026)
Computers & Education: Artificial Intelligence 10
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial alfabetización en IA ética

Resumen:

Texto completo

While increasing attention has been given to cultivating students' artificial intelligence (AI) ethical awareness, the factors that contribute to its development remain underexplored. Psychological empowerment is a crucial motivational factor influencing students' intentions to incorporate ethical norms in developing AI-based solutions. Hence, this study filled this up by exploring the relationship between empowerment in using AI for problem-solving and AI ethical awareness. Empowerment in using AI for problem-solving in this study comprised three components: impact, self-efficacy and meaningfulness. Data was collected from 681 students from secondary schools and a university in Hong Kong....

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Using convolutional neural networks to automatically score eight TIMSS 2019 graphical response items
Lillian Tyack, Lale Khorramdel, Matthias von Davier (2024)
Computers & Education: Artificial Intelligence 6
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial evaluación educación primaria y secundaria

Resumen:

Texto completo

International large-scale assessments (ILSAs) have used graphical response-based items to measure student ability for decades, but they have yet to implement automated scoring of these responses and instead rely on human scoring alone. To investigate how scores provided by machine algorithms compare to those provided by human raters, we applied convolutional neural networks (CNNs) to classify image-based responses from eight Timss 2019 items. Our results show that the most accurate CNN models classified over 99% of the image responses into the appropriate scoring category for dichotomous items and almost 98% for one trichotomous item. Additionally, during the modeling process, the CNNs...

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Coauthorship integrity: Reconceptualising assessment validity for the age of generative artificial intelligence
Mohsen Ebrahimzadeh, Antonette Shibani, Simon Buckingham Shum (2026)
Computers & Education: Artificial Intelligence 10
Detalles Cerrar โœ•

Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial integridad académica evaluación

Resumen:

Texto completo

We consider how a future of pervasive human/AI coauthorship challenges current notions of validity and academic integrity. Specifically, we address widespread concerns that in non-proctored contexts, students are using generative artificial intelligence (GenAI) to submit texts they do not understand. Adopting an assessment validity lens, we show how GenAI undermines the integrity of multiple forms of validity evidence, leading us to propose Coauthorship Integrity as a new conceptual source of validity evidence for addressing these threats. Coauthorship Integrity is violated when students submit AI-generated content that they do not understand. To hold students accountable in this regard, a...

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AI in informal digital English learning: A meta-analysis of its effectiveness on proficiency, motivation, and self-regulation
Lihang Guan, Shaofeng Li, Mingyue Michelle Gu (2024)
Computers & Education: Artificial Intelligence 7
Detalles Cerrar โœ•

Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial enseñanza/aprendizaje de lenguas aprendizaje informal

Resumen:

Texto completo

This meta-analysis examines the efficacy of generative artificial intelligence (GenAI) in second language acquisition within self-directed, out-of-classroom informal contexts. A total of 15 studies meeting the inclusion criteria were identified that examined the impact of GenAI on second-language proficiency, motivation, and self-regulation. GenAI was shown to have significant effects on English proficiency and self-regulation, demonstrating its versatility in enhancing language learning outcomes. However, GenAI failed to show significant effects on learning motivation, and based on this finding we highlight the need to develop measures of motivation that are suitable for GenAI in education...

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Preparing future educators for AI-enhanced classrooms: Insights into AI literacy and integration
Lucas Kohnke, Di Zou, Amy Wanyu Ou (2025)
Computers & Education: Artificial Intelligence 8
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial formación de profesores alfabetización en IA

Resumen:

Texto completo

The rapid transformation of educational practice by artificial intelligence (AI) requires that teacher-education programmes prepare pre-service teachers to integrate AI into their teaching. This qualitative study explores pre-service teachers' perceptions of AI integration in education and identifies the support they need to develop AI literacy. We conducted semi-structured interviews with 15 pre-service teachers and used thematic analysis to interpret the data. Our findings revealed that these future educators recognised AI's potential to enhance personalised learning and increase classroom efficiency but worried about relying on AI too much and losing the human element in teaching. The...

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A gamified web based system for computer programming learning
Giuseppina Polito, Marco Temperini (2021)
Computers & Education: Artificial Intelligence 2
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial gamificación pensamiento computacional

Resumen:

Texto completo

The availability of Automated Assessment tools for computer programming tasks can be a significant asset in Computer Science education. Systems providing such kind of service are built around an interface, allowing to administer the tasks (exercises to train programming skills), and show the results, accompanied by meaningful feedback. To produce such results, they apply techniques ranging from static analysis of program correctness, to testing-based evaluation. These systems can also support Competitive Programming, which is known to have educational meaning too. We developed the 2TSW system, supporting the automated correction of computer programming tasks, in a gamified web-based...

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AI-based teaching evaluations: How well do they reflect student perceptions?
Yossi Ben Zion, Shir Yakov, Einat Abramovitch (2025)
Computers & Education: Artificial Intelligence 9
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial procesamiento del lenguaje natural educación superior

Resumen:

Texto completo

This study presents an innovative solution for evaluating university-level teaching quality using artificial intelligence (AI), focusing on key aspects such as clarity of explanation and lecture structure. Traditional student surveys, while valuable, are often subject to biases and lack the necessary granularity, creating a need for objective, scalable solutions that provide consistent results. We propose an automated framework utilizing advanced natural language processing (NLP) models to assess teaching quality based on lecture transcripts. The methodology combines AI-driven transcription, machine learning-based assessments, and correlation with institutional student evaluations to...

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