Recent advances in Predictive Learning Analytics: A decade systematic review (2012–2022)

N Sghir, A Adadi, M Lahmer - Education and information technologies, 2023 - Springer
The last few years have witnessed an upsurge in the number of studies using Machine and
Deep learning models to predict vital academic outcomes based on different kinds and …

The End is the Beginning is the End: The closed-loop learning analytics framework

M Sailer, M Ninaus, SE Huber, E Bauer… - Computers in Human …, 2024 - Elsevier
This article provides a comprehensive review of current practices and methodologies within
the field of learning analytics, structured around a dedicated closed-loop framework. This …

Predicting students' performance employing educational data mining techniques, machine learning, and learning analytics

A Alam, A Mohanty - International Conference on Communication …, 2022 - Springer
Student success is important in colleges and universities since it is often used as a measure
of the institution's effectiveness. Identifying at-risk students early on and implementing …

Improving Learning Outcomes through Predictive Analytics: Enhancing Teaching and Learning with Educational Data Mining

A Alam - 2023 7th International Conference on Intelligent …, 2023 - ieeexplore.ieee.org
Educational Data Mining (EDM) is a promising area of research that leverages
computational methods to improve educational outcomes by extracting valuable insights …

[HTML][HTML] Comparison of learning analytics and educational data mining: A topic modeling approach

DJ Lemay, C Baek, T Doleck - Computers and Education: Artificial …, 2021 - Elsevier
Educational data mining and learning analytics, although experiencing an upsurge in
exploration and use, continue to elude precise definition; the two terms are often …

[PDF][PDF] What is learning analytics

C Lang, AF Wise, A Merceron, D Gašević… - The handbook of …, 2022 - researchgate.net
Over the last ten years learning analytics (LA) has grown from a hypothetical future into a
concrete field of inquiry and a global community of researchers and practitioners. Although …

A data-driven approach to improve customer churn prediction based on telecom customer segmentation

T Zhang, S Moro, RF Ramos - Future Internet, 2022 - mdpi.com
Numerous valuable clients can be lost to competitors in the telecommunication industry,
leading to profit loss. Thus, understanding the reasons for client churn is vital for …

Dropout prediction in Moocs using deep learning and machine learning

RB Basnet, C Johnson, T Doleck - Education and Information …, 2022 - Springer
The nature of teaching and learning has evolved over the years, especially as technology
has evolved. Innovative application of educational analytics has gained momentum. Indeed …

The relationship between digital technologies and the circular economy: A systematic literature review and a research agenda

A Neri, E Cagno, E Susur, A Urueña, C Nuur… - R&D …, 2024 - Wiley Online Library
Digital technologies are widely recognised as crucial for promoting the circular economy in
industry. However, there still needs for clearer guidance for industrial practitioners on …

Educational data mining: A bibliometric analysis of an emerging field

C Baek, T Doleck - IEEE Access, 2022 - ieeexplore.ieee.org
We are now able to collect enormous amounts of information at the learner level. Mining
educational data to provide data-driven analytics has spurred great interest among …