Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

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Cumulative experience is important for developing expertise through in-person learning, along with country setting and gender, but evidence is limited the role of these features in online learning. Yet, COVID-19 has catalysed the centrality of online learning, such that the efficacy of online learning is now highly relevant. Although the Pandemic triggered a surge of self-report and literature review research on stakeholder perceptions of online learning, less educational research has used big data to understand online learning. Therefore, the present research mined online learning data to identify features that are important for developing expertise in online learning. Data mining of 54,...

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Metodología: revisión bibliográfica

Temas: inteligencia artificial

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The application of Machine Learning (ML) and Deep Learning (DL) in Educational Data Mining (EDM) is revolutionizing the educational field. Researchers have been particularly interested in predicting student performance at an early stage. These early predictions can significantly benefit students’ learning experiences, allowing educators and other stakeholders to plan timely interventions. This review examines studies employing these technologies, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to ensure the approach is transparent and replicable. This systematic review begins with preselecting a total of 281 records that go through a...

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Metodología: revisión bibliográfica

Temas: inteligencia artificial

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We present a systematic literature review of data-driven self-regulated learning (SRL) that emphasises the methodological importance of temporality and sequence, as opposed to conventional statistical analysis. Researchers seem unanimous in their view of the importance of SRL in modern online and blended educational settings; this is borne out by number of reviews of literature on the subject. There has, as yet, been no systematic treatment of SRL in the context of its conceptualisation as a phenomenon that unfolds in sequences over time. To address this limitation, this review explores the corpus of work (n = 53) in which SRL and its related dimensions are analysed through the lenses of...

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Metodología: estudio empírico

Temas: inteligencia artificial

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This study developed an interactive test dashboard with diagnosis and feedback mechanisms (ITD-DFM) that can generate visualized, rich, and high-quality test feedback for each learner’s learning reflection and review based on simultaneously considering test response time and correctness to assist students’ learning. A quasi-experimental research was conducted with 50 Grade 8 students from two classes in a public junior high school in Taiwan to assess the learning performance of ITD-DFM. One class with 26 students was assigned to the experimental group using the ITD-DFM to support learning, whereas the other class with 24 students was assigned to the control group using the traditional test...

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Metodología: estudio empírico

Temas: inteligencia artificial

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The integration of Artificial Intelligence (AI) into higher education, particularly through Academic Performance Prediction (APP), promises enhanced educational outcomes. However, it simultaneously raises concerns regarding data privacy, potential biases, and broader socio-technical implications. Our study, focusing on Germany–a pivotal player in shaping the European Union's AI policies–seeks to understand prevailing perceptions of APP among students and the general public. Initial findings of a large standardized online survey suggest a divergence in perceptions: While students, in comparison to the general population, do not attribute a higher risk to APP in a general risk assessment,...

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Metodología: estudio empírico

Temas: inteligencia artificial

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Statement of problem: The students’ academic performance is influenced by a complex interplay among several factors. Traditional educational approaches often struggle to accommodate the diverse needs of students, leading to suboptimal learning outcomes. Purpose: This article aims to comprehensively understand the role of study strategies and learning disabilities in shaping academic performance. Through the integration of artificial intelligence (AI) tools, the purpose is to propose a decision support system (DSS) for recommendations to improve the educational approach. Method: To identify features with higher explanatory power based on empirical data, we employed an artificial neural...

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Temas: inteligencia artificial

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Massive Open Online Courses (MOOCs) are a type of Learning Management Systems (LMSs), but it seems that the influence of the instructor in these systems is minimal or simply lacking. These systems present the learning content and materials to all learners attending the course in the same way and fail to offer individualized instruction that recognizes the individual differences and needs of the learners. It is reported that such problems can be eliminated by making the new generation intelligent learning systems. However, there is still an ongoing search for making such systems intelligent and a conceptual discussion concerning them. Integrating an intelligent tutoring system (ITS) with...

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Metodología: estudio empírico

Temas: inteligencia artificial

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Background: Peer influence is a significant determinant in shaping students' academic performance, yet it is often overlooked in traditional educational strategies. The ability to analyze peer influence and collaboration is an important piece in personalizing student educational experiences. Objective: This study aims to investigate how peer interactions can be used to predict students' achievement levels and create clusters based on these predictions. Building on these clusters, a novel AI-driven approach is introduced to personalize the learning experiences for each group, providing content aligned with students' predicted achievement levels and ensuring that students receive the right...

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Metodología: revisión bibliográfica

Temas: inteligencia artificial

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This study aimed to categorize learning analytics (LA) models and identify their relevant components by analyzing LA-related articles published between 2011 and 2019 in international journals. A total of 101 articles discussing various LA models were selected. These models were characterized according to their goals and components. A qualitative content analysis approach was used to develop a coding scheme for analyzing the aforementioned models. The results reveal that the studied LA models belong to five categories, namely performance, meta-cognitive, interactivity, communication, and data models. The majority of the selected LA-related articles were data models, followed by performance...

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Metodología: estudio empírico

Temas: inteligencia artificial

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Online learning and teaching increased in 2020, driven by the COVID-19 pandemic. As many researchers attempted to understand the impact stress had on the emotional behaviours and academic performance of students, most studies explored these pre- and during-COVID behaviours in the context of brick and mortar institutions transitioning to online delivery. There is an opportunity to compare the experiences of students in the MOOC environment in this period, particularly in terms of the difference of engagement, semantics and sentiment/stress behaviours in 2019 and 2020. In this study, we use a dataset from AdelaideX between this time period to identify the most significant features...

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