estudio empírico

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial formación de profesores creencias y actitudes de los profesores

Temas IA: IA y educación estudio empírico

Resumen:

Artificial intelligence (AI) has provided numerous learning benefits due to and beyond its personalization capabilities. AI significantly alters the interaction dynamics among students, teachers, and technology, necessitating the collaborative integration of AI in education instead of mere mechanical use. This study investigates pre-service teachers' perceptions and capabilities within the framework of social cognitive theory, focusing on their attitudes, intentions, self-efficacy, and AI literacy for effective AI integration. We discuss how these perceptions and capabilities help pre-service teachers prepare for the changing identities of being a teacher in AI-integrated education....

Is GPT-4 fair? An empirical analysis in automatic short answer grading

Luiz Rodrigues, Cleon Xavier, Newarney Costa (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial evaluación grandes modelos de lenguaje

Temas IA: IA y evaluación modelos de lenguaje (LLM) ética de la IA

Resumen:

Short open-ended questions represent a central resource in formative and summative assessments both face-to-face and online settings, ranging from elementary to higher education. However, grading these questions remains challenging for instructors, raising attention to the field of Automatic Short Answer Grading (ASAG). While ASAG has yielded valuable contributions to learning analytics, it often faces generalizability issues. Accordingly, the rapid advancement in Large Language Models (LLMs) has motivated their adoption to empower ASAG systems. Despite that, previous research has not investigated whether LLMs are fair graders in the context of ASAG. Therefore, this paper presents an...

Digital equity and computational thinking privilege: The case of first-year engineering and computing students' attitudes towards artificial intelligence

Noemi V. Mendoza Diaz, So Yoon Yoon, Nancy Gertrudiz Salvador (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial pensamiento computacional inclusión y equidad

Temas IA: IA y educación estudio empírico

Resumen:

Attitudes can constitute barriers to engineering, computing, and artificial intelligence (AI) enculturation, contributing to and resulting from digital inequity. Building upon research on computational thinking privilege, we explored first-year students' (a) perceived future impact of AI on their career prospects and (b) backgrounds (e.g., gender, underrepresented minority (URM) status, and First-Generation status) associated with their attitudes toward AI, computational thinking, and course performance. Computational thinking was measured using our newly validated Engineering Computational Thinking Diagnostic (ECTD), while course performance was assessed based on final grades in an...

Needs and requirements for an additional AI qualification during dual vocational training: Results from studies of apprentices and teachers

Karin Julia Rott, Lena Lao, Efthymia Petridou (2022)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial alfabetización en IA diseño curricular

Temas IA: IA y educación estudio empírico

Resumen:

The integration of artificial intelligence (AI) in application-based contexts has created the need for skilled workers with AI knowledge and competencies. In order to meet this demand, it is necessary to integrate AI into vocational education and training (VET) in Germany, for example in the form of an additional AI qualification. Such an additional qualification in the field of AI in the VET system is innovative and comparatively new. Therefore, this article explores the views of both teachers and apprentices regarding the requirements for an additional AI qualification, - perspectives which have not been sufficiently researched, yet. Results from a mixed-methods needs analysis based on...

Designing large language model-based agents with 5E framework for ESL learners’ grammar acquisition

Xiaoxiao Yang, Xiaojing Weng, Mengyao Yang (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial enseñanza/aprendizaje de la gramática grandes modelos de lenguaje

Temas IA: IA y enseñanza-aprendizaje de lenguas modelos de lenguaje (LLM) chatbots

Resumen:

This study examines how large language models (LLMs) aid English as a Second Language (ESL) learners in acquiring grammar. Two artificial intelligence (AI) agents were designed: one as a conventional English teacher and another utilizing the 5E framework (engage, explore, explain, elaborate, evaluate) for inquiry-based learning (IBL). Thirty-seven ESL students were randomly divided into two groups: 17 in the AI-facilitated conventional English teacher group and 20 in the AI-facilitated 5E English teacher group. Pre- and post-tests, along with interviews, were used to investigate students’ intrinsic motivation, cognitive changes, and performance transformation with the designed AI agents....

Large language models and automated essay scoring of English language learner writing: Insights into validity and reliability

Austin Pack, Alex Barrett, Juan Escalante (2024)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial expresión escrita evaluación

Temas IA: IA y enseñanza-aprendizaje de lenguas IA y evaluación modelos de lenguaje (LLM)

Resumen:

Advancements in generative AI, such as large language models (LLMs), may serve as a potential solution to the burdensome task of essay grading often faced by language education teachers. Yet, the validity and reliability of leveraging LLMs for automatic essay scoring (AES) in language education is not well understood. To address this, we evaluated the cross-sectional and longitudinal validity and reliability of four prominent LLMs, Google's PaLM 2, Anthropic's Claude 2, and OpenAI's GPT-3.5 and GPT-4, for the AES of English language learners' writing. 119 essays taken from an English language placement test were assessed twice by each LLM, on two separate occasions, as well as by a pair of...

Assessing the proficiency of large language models in automatic feedback generation: An evaluation study

Wei Dai, Yi-Shan Tsai, Jionghao Lin (2024)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial feedback/retroalimentación grandes modelos de lenguaje

Temas IA: IA y evaluación modelos de lenguaje (LLM) análisis de producción de IA

Resumen:

Assessment feedback is important to student learning. Learning analytics (LA) powered by artificial intelligence exhibits profound potential in helping instructors with the laborious provision of feedback. Inspired by the recent advancements made by Generative Pre-trained Transformer (GPT) models, we conducted a study to examine the extent to which GPT models hold the potential to advance the existing knowledge of LA-supported feedback systems towards improving the efficiency of feedback provision. Therefore, our study explored the ability of two versions of GPT models – i.e., GPT-3.5 (ChatGPT) and GPT-4 – to generate assessment feedback on students' writing assessment tasks, common in...

The influence of AI literacy on complex problem-solving skills through systematic thinking skills and intuition thinking skills: An empirical study in Thai gen Z accounting students

Watcharawat Promma, Narinthon Imjai, Berto Usman (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial alfabetización en IA educación superior

Temas IA: IA y educación estudio empírico

Resumen:

The rapid integration of artificial intelligence (AI) into various sectors has heightened the need for understanding its impact on cognitive and problem-solving skills. This study investigates the influence of AI literacy (AIL) on complex problem-solving skills (CPS) by examining the mediating roles of systematic thinking skills (STS) and intuitive thinking skills (ITS) among Generation Z accounting students in Thailand. Utilizing structural equation modeling (SEM) to analyze the relationships between these constructs, the research draws on a sample of 420 final-year undergraduate accounting students from both public and private universities, selected through convenience sampling. The...

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)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial creencias y actitudes de los profesores profesorado

Temas IA: IA y educación estudio empírico

Resumen:

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...

AI analysis reveals top predictors of first grade success: Insights from multifactorial screening students’ early days of school

Pedro Bem-haja, Paulo Nossa, Andreia J. Ferreira (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial educación primaria y secundaria analítica del aprendizaje

Temas IA: IA y educación estudio empírico

Resumen:

Early prediction of students' primary school academic performance is crucial for planning timely interventions for those expected to struggle. Random Forest, Gradient Boosting, and Extra Trees AI techniques were used to study 2549 first graders to predict end-of-year academic performance and identify critical predictors for targeted interventions. The Extra Trees model used EPIS (Empresários pela Inclusão Social) screening to yield high F1 scores above 99.7 %, accurately identifying passing and failing students. Out of 142 variables, the top ten strongest predictors of academic success were categorized into three areas: 1) teacher perceptions of cognitive function, particularly attention (...