Is learning analytics applicable and applied to education of students with intellectual/developmental disabilities? A systematic literature review

Conde, Miguel Á.; Rodríguez-Sedano, Francisco J.

doi:10.1016/j.chb.2024.108184

Cited by 3 publications

(1 citation statement)

References 38 publications

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“…Research has shown that, compared to reading materials, videos have a positive impact on student performance, although this effect is less significant for undergraduate students. Therefore, it is important for videos to promote student engagement rather than just passive viewing [7]. To enhance interactivity, tests and quizzes can be incorporated into online materials to make them more meaningful and beneficial for students…”

Section: Introductionmentioning

confidence: 99%

Sequence Modeling with Recurrent Neural Networks (RNNs) for Student Learning Behavior Pattern Recognition in a Flipped Classroom

Tang

2024

jes

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The flipped classroom model has become increasingly popular in education, altering the traditional methods of teaching. It is important to understand and acknowledge how students learn within this framework in order to optimize instructional strategies and promote personalized learning. This study investigates the use of Sequence Modeling with Recurrent Neural Networks (RNNs) to identify patterns in student learning behavior within a flipped classroom setting. The proposed deep learning architecture utilizes RNNs to analyze sequential patterns in students' interactions with the flipped classroom materials, while also incorporating attention mechanisms to better detect important patterns and temporal dynamics in the learning process. Multimodal learning techniques are also employed, combining data from various sources to gain a comprehensive understanding of student behavior. Additionally, clustering techniques using autoencoders are explored to group students with similar learning behaviors. Predictive models, such as RNN or LSTM networks, are developed to forecast future learning behaviors and provide insights into potential challenges or successes for individual students. The effectiveness of this framework is evaluated using real-world data from flipped classroom implementations, with performance metrics like recall, precision, and accuracy used to assess the success of the sequence modeling approach in recognizing and predicting student behavior patterns. Overall, the application of deep learning methods, specifically sequence modeling with RNNs, demonstrates potential for improving personalized learning experiences and facilitating proactive interventions to support diverse student needs.

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Section: Introductionmentioning

confidence: 99%

Sequence Modeling with Recurrent Neural Networks (RNNs) for Student Learning Behavior Pattern Recognition in a Flipped Classroom

Tang

2024

jes

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Decoding a decade. Trends and evolution in learning analytics: A comprehensive synthesis

Stanciu,

Hernández-García,

Conde

et al. 2025

Computers in Human Behavior

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Recycling of Silicon-Based Photovoltaic Modules: Mediterranean Region Insight

Diez-Suarez,

Martínez-Benavides,

Manteca Donado

et al. 2024

Energies

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The rapid expansion of photovoltaic (PV) installations across Mediterranean Europe since 2007 has resulted in a substantial increase in the need for end-of-life (EoL) management strategies for monocrystalline PV modules. This paper reviews the technical challenges and opportunities associated with the recycling of PV modules, focusing on the physical, chemical, and thermal processes currently employed. Despite advancements in recycling technology, significant gaps remain in infrastructure and regulatory enforcement, particularly in Mediterranean countries. The recovery of valuable materials such as silicon, silver, and glass presents both economic and environmental benefits, although the costs of recycling remain a key barrier to widespread adoption. Our analysis suggests that optimizing these recycling processes could improve their profitability and scalability, enabling more effective resource recovery. The paper concludes with recommendations for policy and infrastructure development to support the sustainable management of PV waste across the Mediterranean region.

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Is learning analytics applicable and applied to education of students with intellectual/developmental disabilities? A systematic literature review

Cited by 3 publications

References 38 publications

Sequence Modeling with Recurrent Neural Networks (RNNs) for Student Learning Behavior Pattern Recognition in a Flipped Classroom

Sequence Modeling with Recurrent Neural Networks (RNNs) for Student Learning Behavior Pattern Recognition in a Flipped Classroom

Decoding a decade. Trends and evolution in learning analytics: A comprehensive synthesis

Recycling of Silicon-Based Photovoltaic Modules: Mediterranean Region Insight

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