[HTML][HTML] The application of AI technologies in STEM education: a systematic review from 2011 to 2021
W Xu, F Ouyang - International Journal of STEM Education, 2022 - Springer
Background The application of artificial intelligence (AI) in STEM education (AI-STEM), as an
emerging field, is confronted with a challenge of integrating diverse AI techniques and …
emerging field, is confronted with a challenge of integrating diverse AI techniques and …
[HTML][HTML] A systematic literature review of student'performance prediction using machine learning techniques
Educational Data Mining plays a critical role in advancing the learning environment by
contributing state-of-the-art methods, techniques, and applications. The recent development …
contributing state-of-the-art methods, techniques, and applications. The recent development …
Prediction of students' academic performance based on courses' grades using deep neural networks
A Nabil, M Seyam, A Abou-Elfetouh - IEEE Access, 2021 - ieeexplore.ieee.org
Predicting students' academic performance at an early stage of a semester is one of the
most crucial research topics in the field of Educational Data Mining (EDM). Students are …
most crucial research topics in the field of Educational Data Mining (EDM). Students are …
Multiclass prediction model for student grade prediction using machine learning
Today, predictive analytics applications became an urgent desire in higher educational
institutions. Predictive analytics used advanced analytics that encompasses machine …
institutions. Predictive analytics used advanced analytics that encompasses machine …
Educational data mining to predict students' academic performance: A survey study
Educational data mining is an emerging interdisciplinary research area involving both
education and informatics. It has become an imperative research area due to many …
education and informatics. It has become an imperative research area due to many …
Big data analytics for data-driven industry: a review of data sources, tools, challenges, solutions, and research directions
The study of big data analytics (BDA) methods for the data-driven industries is gaining
research attention and implementation in today's industrial activities, business intelligence …
research attention and implementation in today's industrial activities, business intelligence …
A survey on educational data mining methods used for predicting students' performance
W Xiao, P Ji, J Hu - Engineering Reports, 2022 - Wiley Online Library
Predicting students' performance is one of the most important issues in educational data
mining (EDM), which has received more and more attention. By predicting students' …
mining (EDM), which has received more and more attention. By predicting students' …
Application of machine learning in higher education to assess student academic performance, at-risk, and attrition: A meta-analysis of literature
Recently, machine learning (ML) has evolved and finds its application in higher education
(HE) for various data analysis. Studies have shown that such an emerging field in …
(HE) for various data analysis. Studies have shown that such an emerging field in …
[HTML][HTML] Predicting student performance from online engagement activities using novel statistical features
GB Brahim - Arabian Journal for Science and Engineering, 2022 - Springer
Predicting students' performance during their years of academic study has been investigated
tremendously. It offers important insights that can help and guide institutions to make timely …
tremendously. It offers important insights that can help and guide institutions to make timely …
[HTML][HTML] Increased digital resource consumption in higher educational institutions and the artificial intelligence role in informing decisions related to student …
As education is an essential enabler in achieving Sustainable Development Goals (SDGs), it
should “ensure inclusive, equitable quality education, and promote lifelong learning …
should “ensure inclusive, equitable quality education, and promote lifelong learning …