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Metodología: estudio empírico

Temas: inteligencia artificial

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Despite the growing body of research on developing K-12 teachers' generative AI (GenAI) knowledge and skills, its integration into daily teaching practices remains underexplored. Using a snowball sampling method, this study examined the preparedness, practices, and barriers encountered by 89 U.S. teachers in the state of Idaho. Participants were predominantly White, female teachers serving in rural schools. A mixed-methods analysis of survey responses revealed that teachers were generally underprepared for integrating GenAI, with fewer than half incorporating it into their educational practices. Unlike the widespread classroom integration patterns observed with general educational...

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Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial

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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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Metodología: revisión bibliográfica

Temas: inteligencia artificial

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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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Metodología: estudio empírico

Temas: inteligencia artificial

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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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Metodología: estudio empírico

Temas: inteligencia artificial

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In recent years, distance learning using learning management and e-book systems has been actively conducted in higher education institutions and various other organizations. It is possible to collect and analyze learning logs even in classes with many learners, including clickstreams and quiz scores in detail for each individual. This research proposes using Moodle's learning logs to classify learning patterns and outliers in order to identify struggling learners. The proposed method uses the descriptive statistics between the learner's teaching material clickstream and the final test score accumulated in Moodle, and students can be classified into four learning patterns. The frequency of...

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Metodología: revisión bibliográfica

Temas: inteligencia artificial

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This systematic review investigates learning task design for K-12 AI education, aiming to provide an overview of the status of AI education and identify trends, challenges, and opportunities. Through an analysis of 47 empirical studies, the review presents, synthesizes, and evaluates the educational theories underpinning the learning task design, the content, the pedagogies used for teaching, as well as the measurement and outcomes of the existing literature on AI education programs in K-12 settings. The principal findings reveal a diverse landscape of learning task design for teaching AI to K-12 students. Positive outcomes underscore the effectiveness of well-crafted hands-on tasks in...

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Metodología: estudio empírico

Temas: inteligencia artificial

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Predictive analytics in education holds promise for supporting student learning but poses risks of bias potentially disadvantaging certain groups based on demographic attributes such as gender. Prior work on fairness in educational prediction has largely focused on binary outcomes in higher education, leaving continuous predictions, such as standardized test scores, comparatively understudied, especially in early schooling where consequences can be long-lasting. Despite a few fairness metrics available for continuous outcomes, they often rely on mean differences, obscuring distributional disparities that may disadvantage specific students. Even fewer studies have attempted to address bias...

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Metodología: estudio empírico

Temas: inteligencia artificial

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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...

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Large language models have recently been proposed as tools for automated essay scoring, but their agreement with human grading remains unclear. In this work, we evaluate how LLM-generated scores compare with human grades and analyze the grading behavior of several models from the GPT and Llama families in an out-of-the-box setting, without task-specific training. Our results show that agreement between LLM and human scores remains relatively weak and varies with essay characteristics. In particular, compared to human raters, LLMs tend to assign higher scores to short or underdeveloped essays, while assigning lower scores to longer essays that contain minor grammatical or spelling errors. We...

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Metodología: estudio empírico

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Highlights:

• The analysis of gameplay data from the Blood Transfusion Serious Game (BTSG) revealed crucial insights into the engagement, performance, and competency levels of participating nurses.
• The study highlighted the efficiency of the adaptive assessment algorithm in determining competency indicators through gameplay activities.
• Notable discrepancies existed between the game-embedded result and the adaptive assessment result, suggesting potential biases in the game result, which tended to overestimate the demonstrated competence.

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