Bibliografía: analítica del aprendizaje
Nº de publicaciones: 56Detalles Cerrar ✕
Tipo: artículo
Metodología: estudio empírico
Temas: inteligencia artificial
Resumen:
The attractiveness of online games, social media, and mobile apps is frequently considered a challenge for online learners. Procrastinatory behaviour is often associated with a relative lack of self-regulatory skills that would otherwise help learners to resist distractions and to progress in learning. This paper reports a pilot study, conducted with 49 online learners, in which we describe the use of a virtual learning assistant as a tool for collecting online learners' web navigation behaviour. As this virtual learning assistant operates as an extension to the Chrome web browser, it is possible that data collection is achieved independently of, and beyond specific learning management...
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Tipo: artículo
Metodología: estudio empírico
Temas: inteligencia artificial
Resumen:
The growth and uptake of educational technology has significantly reshaped the delivery of distance and online learning. With an unprecedented number of learners engaging with online modes of education, there is a growing need to understand the underlying student enrolment motivations, goals and learning behaviours evolving from a highly diverse student population. Research in learning analytics has advanced the use of digital data to understand student learning processes. However, there remains a limited understanding of how non-traditional learner characteristics, needs and motivational factors influence their learning behaviour and engagement strategies. Survey data from 232 students...
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Tipo: artículo
Metodología: estudio empírico
Temas: inteligencia artificial
Resumen:
Despite the growing global adoption of AI-powered academic advice, its impact remains underexplored. This study addresses this gap by evaluating the academic performance of at-risk students who receive AI-driven joint support. We proposed a practical framework for assessing academic outcomes by leveraging AI as a decision-making tool for advisors. Our study employs a quasi-experimental difference-in-differences (DID) methodology over three semesters. We compare the academic outcomes of at-risk students in pilot departments who received the intervention (treatment group, N = 516) with all other students in the analytic sample (control group, N = 12,004), supplemented with robustness checks....
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Tipo: artículo
Metodología: estudio empírico
Temas: inteligencia artificial
Resumen:
The use of computational tools to predict academic success has become increasingly popular. Machine learning algorithms, trained on past study histories, have been shown to provide valid predictions. However, knowing about biases and unfairness in algorithms, one should take a closer look at these predictions. This paper explores the extent to which the predictive accuracy of academic success varies between specific groups of students, focusing on traditional and non-traditional students (NTS), who have not acquired a higher education entrance qualification at school. In a case study the study compares several popular algorithms and their prediction quality, and investigates whether...
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Tipo: artículo
Metodología: revisión bibliográfica
Temas: inteligencia artificial
Resumen:
Understanding and improving education are critical goals of learning analytics. However, learning is not always mediated or aided by a digital system that can capture digital traces. Learning in such environments can be studied by recording, processing, and analyzing different signals, including video and audio, so that traces of actors’ actions and interactions are captured. Multimodal Learning Analytics refers to analyzing these signals through the use and integration of these multiple modes. However, a need exists to evaluate how research is conducted in the emerging field of multimodal learning analytics to aid and evaluate how these systems work. With the growth of multimodal...
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Tipo: artículo
Metodología: estudio empírico
Temas: inteligencia artificial
Resumen:
Reflection and goal-setting are interrelated processes in well-established educational theories to promote in-depth self-reflection and self-regulated learning. Prior studies have considered reflection to be an important antecedent for meaningful goal-setting. Yet, there lacks empirical evidence to shed light on how students' abilities to reflect inform their abilities to set goals. Hence, in the present study, we aimed to quantify the connection between students' retrospective reflection and their subsequent goal-setting, and derive more in-depth insights to benefit educators in their teaching to promote deeper reflection, more specific goal-setting and better self-regulation. To this end...
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Tipo: artículo
Metodología: trabajo teórico
Temas: inteligencia artificial
Resumen:
There are emerging concerns about the Fairness, Accountability, Transparency, and Ethics (FATE) of educational interventions supported by the use of Artificial Intelligence (AI) algorithms. One of the emerging methods for increasing trust in AI systems is to use eXplainable AI (XAI), which promotes the use of methods that produce transparent explanations and reasons for decisions AI systems make. Considering the existing literature on XAI, this paper argues that XAI in education has commonalities with the broader use of AI but also has distinctive needs. Accordingly, we first present a framework, referred to as XAI-ED, that considers six key aspects in relation to explainability for...
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Tipo: artículo
Metodología: estudio empírico
Temas: inteligencia artificial
Resumen:
Automating the process of qualitatively coding text data from learners has been a long-standing ambition of learning analytics researchers since it represents an essential step toward delivering timely and scalable feedback. Automating this process is especially challenging in the case of ordered coding schemes —necessary for temporal analytical methods— where one text utterance can be assigned more than one qualitative code and the assignment order matters. This problem goes beyond multi-class and multi-label classification and, therefore, cannot be easily tackled using classic language models such as BERT. Recent advances in generative artificial intelligence, especially with the advent...
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Tipo: artículo
Metodología: estudio empírico
Temas: inteligencia artificial
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 (...
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Tipo: artículo
Metodología: trabajo teórico
Temas: inteligencia artificial
Resumen:
Learning analytics has matured significantly since its early days. The field has rapidly grown in terms of the reputation of its publication venues, established a vibrant community, and has demonstrated an increasing impact on policy and practice. However, the boundaries of the field are still being explored by many researchers in a bid to determine what differentiates a contribution in learning analytics from contributions in related fields, which also center around data in education. In this paper, we propose that instead of emphasizing the examination of differences, a healthy development of the field should focus on collaboration and be informed by the developments in related fields....
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