Student retention using educational data mining and predictive analytics: a systematic literature review

DA Shafiq, M Marjani, RAA Habeeb… - IEEE Access, 2022 - ieeexplore.ieee.org
Student retention is an essential measurement metric in education, indicated by retention
rates, which are accumulated as students re-enroll from one academic year to the next. High …

[HTML][HTML] Student course grade prediction using the random forest algorithm: Analysis of predictors' importance

M Nachouki, EA Mohamed, R Mehdi… - Trends in Neuroscience …, 2023 - Elsevier
Background Universities need to find strategies for improving student retention rates.
Predicting student academic performance enables institutions to identify underachievers …

[HTML][HTML] Emerging advances of blockchain technology in finance: a content analysis

R Weerawarna, SJ Miah, X Shao - Personal and Ubiquitous Computing, 2023 - Springer
Blockchain has become a widely used information system technology recently because of its
effectiveness as an intermediary-free platform. While the use of blockchain in various fields …

[HTML][HTML] Predicting student performance to improve academic advising using the random forest algorithm

M Nachouki, M Abou Naaj - International Journal of Distance …, 2022 - igi-global.com
The Covid-19 pandemic constrained higher education institutions to switch to online
teaching, which led to major changes in students' learning behavior, affecting their overall …

[HTML][HTML] A design concept of big data analytics model for managers in hospitality industries

S Mousavian, SJ Miah, Y Zhong - Personal and Ubiquitous Computing, 2023 - Springer
The hospitality and tourism sector has long played a significant role in Australia's economy,
especially in regional areas. Due to the onslaught of COVID-19, numerous businesses have …

[HTML][HTML] Effectiveness of data augmentation to predict students at risk using deep learning algorithms

K Fahd, SJ Miah - Social Network Analysis and Mining, 2023 - Springer
The academic intervention to predict at-risk higher education (HE) students requires
effective data model development. Such data modelling projects in the HE context may have …

Academic performance prediction using machine learning: A comprehensive & systematic review

P Chakrapani, D Chitradevi - 2022 International Conference on …, 2022 - ieeexplore.ieee.org
Educational Institutions face numerous challenges today in providing quality and student-
centric education to students. Despite the huge volume of data available with educational …

[HTML][HTML] Integrating Business Analytics in Educational Decision-Making: A Multifaceted Approach to Enhance Learning Outcomes in EFL Contexts

M Cho, J Kim, J Kim, K Park - Mathematics, 2024 - mdpi.com
This study introduces a framework that integrates business analytics into educational
decision-making to improve learner engagement and performance in Massive Open Online …

[HTML][HTML] Towards AI-governance in psychosocial care: A systematic literature review analysis

X Wang, M Oussalah, M Niemilä, T Ristikari… - Journal of Open …, 2023 - Elsevier
With increased digitalization and e-government services, Artificial Intelligence (AI) gained
momentum. This paper focuses on AI-governance in Child Social Care field, exploring how …

Designing an AI-Driven talent intelligence solution: exploring big data to extend the TOE Framework

A Faqihi, SJ Miah - International Conference on Big Data Intelligence and …, 2022 - Springer
AI has the potential to improve approaches to talent management enabling dynamic
provisions through implementing advanced automation. This study aims to identify the new …