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  • Computers & Education: Artificial Intelligence

Revistas: Computers & Education: Artificial Intelligence

Nº de publicaciones: 569

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EvalYaks: Instruction tuning datasets and LoRA fine-tuned models for automated scoring of CEFR B2 speaking assessment transcripts
Nicy Scaria, Silvester John Joseph Kennedy, Thomas Latinovich (2026)
Computers & Education: Artificial Intelligence 10
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial expresión oral evaluación

Resumen:

Texto completo

Relying on human experts to evaluate the Common European Framework of Reference for Languages (CEFR) speaking assessments in an e-learning environment creates scalability challenges, as it limits how quickly and widely assessments can be conducted. We aim to automate the evaluation of CEFR B2 English speaking assessments in e-learning environments from conversation transcripts. First, we evaluate the capability of leading open source and commercial Large Language Models (LLMs) to score a candidate’s performance across various criteria in the CEFR B2 speaking exam in both global and India-specific contexts. Next, we create a new expert-validated, CEFR-aligned synthetic conversational dataset...

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Can AI provide useful holistic essay scoring?
Tamara P. Tate, Jacob Steiss, Drew Bailey (2024)
Computers & Education: Artificial Intelligence 7
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial expresión escrita evaluación

Resumen:

Texto completo

Researchers have sought for decades to automate holistic essay scoring. Over the years, these programs have improved significantly. However, accuracy requires significant amounts of training on human-scored texts—reducing the expediency and usefulness of such programs for routine uses by teachers across the nation on non-standardized prompts. This study analyzes the output of multiple versions of ChatGPT scoring of secondary student essays from three extant corpora and compares it to quality human ratings. We find that the current iteration of ChatGPT scoring is not statistically significantly different from human scoring; substantial agreement with humans is achievable and may be...

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AI-mediated research agency formation in higher education: Autonomy, self-efficacy and innovation in early-career scientific training
Shanshan Han, Pingqing Liu (2026)
Computers & Education: Artificial Intelligence 11
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial educación superior aprendizaje autónomo

Resumen:

Texto completo

Generative AI is becoming part of the infrastructure of higher education research training, yet little is known about how AI-mediated environments shape early-career researchers’ agency. This study examines AI dependence, defined as reliance on intelligent tools as a primary source of cognitive support in judgement-intensive research tasks, and interprets its educational risk as epistemic delegation: the transfer of problem framing, methodological choice and interpretive authority from the researcher to the intelligent system. Drawing on an AI-mediated research agency formation framework, we examined whether research autonomy and research self-efficacy mediate the association between AI...

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Verifying student identity in oral assessments with deep speaker
Jake Renzella, Andrew Cain, Jean-Guy Schneider (2022)
Computers & Education: Artificial Intelligence 3
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial integridad académica evaluación

Resumen:

Texto completo

Contract cheating, a form of academic misconduct in which students outsource assessment activities to third parties, is a topic of concern among educators. As similarity-detection systems are ineffective at detecting contract cheating, some institutions have turned to intensely criticised proctoring systems, however student and educator bodies report high costs and privacy concerns. Oral assessment is an alternative assessment approach that provides valuable interpersonal and communication skills in graduates and can naturally help detect and deter cheating. However, oral assessment is typically time-consuming, and in larger courses, it is challenging to validate respondents' identity....

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Navigating the future: Exploring in-service teachers' preparedness for artificial intelligence integration into South African schools
Musa Adekunle Ayanwale, Sibusiso D. Ntshangase, Owolabi Paul Adelana (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

This study contributes to existing research on how to integrate Artificial intelligence (AI) into school systems globally. This research explores in-service teachers' preparedness for integrating artificial intelligence into schools. We conducted this research within the context of the South African school system with teachers of various specializations, including sciences, social Sciences, mathematics, and languages. Drawing on the extended Unified Theory of Acceptance and Use of Technology (UTAUT2), we gathered teachers' perspectives through eight variables of technology integration, social influence, AI ethics, attitudes, TPACK, perceived self-efficacy, AI professional development, and...

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Artificial intelligence and computer vision education: Codifying student learning gains and attitudes
Pramod Abichandani, Craig Iaboni, Deepan Lobo (2023)
Computers & Education: Artificial Intelligence 5
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial alfabetización en IA educación superior

Resumen:

Texto completo

Artificial Intelligence (AI) and Computer Vision (CV) have rapidly permeated various industries, increasing demand for professionals well-versed in these disciplines. In response to this need, this study evaluates the effectiveness of a novel undergraduate course that aims to equip students with foundational AI and CV knowledge and skills. Unlike existing software-centric courses, this class capitalizes on drones as a practical application area for AI and CV, fostering an active learning environment. The course was conducted over five semesters at a U.S. research institution, with 153 participating students. Data were collected using diverse methods, including formative and summative...

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Leveraging generative AI for course learning outcome categorization using Bloom's taxonomy
Omaima Almatrafi, Aditya Johri (2025)
Computers & Education: Artificial Intelligence 8
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial grandes modelos de lenguaje diseño curricular

Resumen:

Texto completo

Learning outcomes are clear and concise statements that describe what students should be able to do or know at the end of a particular course. These statements are crucial in instructional planning, curriculum development, and assessment of student progress and learning. Although there is no universal guidance on how to develop learning outcomes, Bloom's taxonomy is one widely used framework that helps instructors develop outcomes that reflect different levels of thinking, from basic remembering to creative problem-solving. This study investigates the potential of generative AI, specifically GPT-4, in classifying course learning outcomes according to their respective cognitive levels within...

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Enhancing traditional ITS architectures with large language models for generating motivational feedback
Angelo Gaeta, Francesco Orciuoli, Antonella Pascuzzo (2025)
Computers & Education: Artificial Intelligence 9
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial grandes modelos de lenguaje feedback/retroalimentación

Resumen:

Texto completo

Large Language Models (LLMs) have emerged as powerful computational tools with significant potential across various fields, particularly education. Previous research demonstrated that LLMs can be effectively integrated into the Tutoring Model of Intelligent Tutoring Systems (ITS) to generate motivational feedback within learning environments. To further explore this area, the authors define an ITS architecture that integrates an LLM (referred to as the ITS-LLM architecture) and validates this architecture by implementing a prototype using Llama 3.2 model. Moreover, the prototype aims to evaluate the impact of LLM-generated motivational feedback on student motivation and their learning...

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How does students' perception of ChatGPT shape online learning engagement and performance?
Mahboobeh Mehrvarz, Ghasem Salimi, Samaneh Abdoli (2025)
Computers & Education: Artificial Intelligence 9
Detalles Cerrar βœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial ChatGPT enseñanza en línea e híbrida

Resumen:

Texto completo

Artiicial intelligence technologies, such as ChatGPT, Bert, LaMDA, and T5 have become deeply integrated into universities, influencing numerous functions within higher education and various aspects of students' lives. This article examined how students' perceptions of ChatGPT influence their engagement and performance in online learning, focusing on the mediating role of engagement. The perception of ChatGPT involves a student's understanding of, willingness to utilize, and concerns regarding the technology. These interconnected factors can influence students' online learning engagement with the software and, consequently, affect their academic performance. The study used self-reported data...

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Large language models in education: a systematic review of empirical applications, benefits, and challenges
Yuhong Shi, Kun Yu, Yifei Dong (2026)
Computers & Education: Artificial Intelligence 10
Detalles Cerrar βœ•

Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial grandes modelos de lenguaje tecnología educativa

Resumen:

Texto completo

The rapid advancement of Large Language Models (LLMs), particularly following the release of ChatGPT in November 2022, has significantly transformed educational methodologies. This systematic review aims to synthesize empirical studies published between November 2022 and March 2025, examining the implementation and effectiveness of LLMs in educational settings. 88 empirical studies identified key applications, benefits, and challenges associated with LLM integration in education. Our findings reveal that LLMs are utilized across various educational contexts in six primary applications, with Intelligent Tutoring Systems being particularly prominent. The benefits include improved academic...

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