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  • analítica del aprendizaje

Bibliografía: analítica del aprendizaje

Nº de publicaciones: 56
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Human-centred learning analytics and AI in education: A systematic literature review
Riordan Alfredo, Vanessa Echeverria, Yueqiao Jin (2024)
Computers & Education: Artificial Intelligence
Detalles Cerrar โœ•

Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial

Resumen:

Texto completo

The rapid expansion of Learning Analytics (LA) and Artificial Intelligence in Education (AIED) offers new scalable, data-intensive systems but raises concerns about data privacy and agency. Excluding stakeholders—like students and teachers—from the design process can potentially lead to mistrust and inadequately aligned tools. Despite a shift towards human-centred design in recent LA and AIED research, there remain gaps in our understanding of the importance of human control, safety, reliability, and trustworthiness in the design and implementation of these systems. We conducted a systematic literature review to explore these concerns and gaps. We analysed 108 papers to provide insights...

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Temporal pathways to learning: How learning emerges in an open-ended collaborative activity.
Jauwairia Nasir, Mortadha Abderrahim, Aditi Kothiyal (2022)
Computers & Education: Artificial Intelligence
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Texto completo

The learning process depends on the nature of the learning environment, particularly in the case of open-ended learning environments, where the learning process is considered to be non-linear. In this paper, we report on the findings of employing a multimodal Hidden Markov Model (HMM) based methodology to investigate the temporal learning processes of two types of learners that have learning gains and a type that does not have learning gains in an open-ended collaborative learning activity. Considering log data, speech behavior, affective states and gaze patterns, we find that all learners start from a similar state of non-productivity, but once out of it they are unlikely to fall back into...

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Transitions through lifelong learning: Implications for learning analytics
Oleksandra Poquet, Kirsty Kitto, Jelena Jovanovic (2021)
Computers & Education: Artificial Intelligence
Detalles Cerrar โœ•

Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial

Resumen:

Texto completo

The ability to develop new skills and competencies is a central concept of lifelong learning. Research to date has largely focused on the processes and support individuals require to engage in upskilling, re-learning or training. However, there has been limited attention examining the types of support that are necessary to assist a learner's transition from “old” workplace contexts to “new”. Professionals often undergo significant restructuring of their knowledge, skills, and identities as they transition between career roles, industries, and sectors. Domains such as learning analytics (LA) have the potential to support learners as they use the analysis of fine-grained data collected from...

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Mapping the evolution of AI in education: Toward a co-adaptive and human-centered paradigm
Shihui Feng, Huilin Zhang, Dragan Gaševiฤ‡ (2025)
Computers & Education: Artificial Intelligence
Detalles Cerrar โœ•

Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial

Resumen:

Texto completo

This study analyzes 2398 research articles published between 2020 and 2024 across eight core venues related to the field of Artificial Intelligence in Education (AIED). Using a three-level knowledge co-occurrence network analysis, this study analyzes the knowledge structure of the field, the evolving knowledge clusters, and the emerging frontiers. The findings reveal that AIED research is centered on developing AI-assisted systems and using AI to support educational analysis, with sustained themes such as intelligent tutoring systems, learning analytics, and natural language processing, alongside rising interest in large language models (LLMs) and generative artificial intelligence (GenAI...

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Assessing the proficiency of large language models in automatic feedback generation: An evaluation study
Wei Dai, Yi-Shan Tsai, Jionghao Lin (2024)
Computers & Education: Artificial Intelligence
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Texto completo

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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Effects of integrating an open learner model with AI-enabled visualization on students' self-regulation strategies usage and behavioral patterns in an online research ethics course
Jerry Chih-Yuan Sun, Hsueh-Er Tsai, Wai Ki Rebecca Cheng (2023)
Computers & Education: Artificial Intelligence
Detalles Cerrar โœ•

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Texto completo en HTML

This study seeks to understand the effects of a personalized learning platform, which applied an open learner model with self-regulation and AI-enabled data visualization features, on students' self-regulated learning strategies used and behavioral patterns during their self-directed online learning process. Results were based on a self-regulated learning scale and a prior knowledge test from 182 university students and supplemented with students' system logs to understand their behavioral patterns while interacting with the personalized learning platform. It showed that the combined self-regulation and data visualization features (dual features) improve student performance via self...

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