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Predicting students' academic performance is one of the key tasks of educational data mining (EDM). Traditionally, the high forecasting quality of such models was deemed critical. More recently, the issues of fairness and discrimination…

Machine Learning · Computer Science 2023-01-31 Tai Le Quy , Thi Huyen Nguyen , Gunnar Friege , Eirini Ntoutsi

The ability to recognize weakness of students and solving any problem may confront them in timely fashion is always a target of all educational institutions. This study was designed to explore how can predictive and statistical analysis…

Other Computer Science · Computer Science 2016-01-19 Mohammed Al-Sarem

This research aims to develop machine learning models for students academic performance and study strategies prediction which could be generalized to all courses in higher education. Key learning attributes (intrinsic, extrinsic, autonomy,…

Machine Learning · Computer Science 2022-10-18 Fidelia A. Orji , Julita Vassileva

As online auto-grading systems appear, information obtained from those systems can potentially enable researchers to create predictive models to predict student behaviour and performances. In the University of Waterloo, the ECE 150…

Machine Learning · Computer Science 2021-02-03 Huanyi Chen , Paul A. S. Ward

This research investigates the use of machine learning methods to forecast students' academic performance in a school setting. Students' data with behavioral, academic, and demographic details were used in implementations with standard…

Computers and Society · Computer Science 2025-06-11 A. G. R. Sandeepa , Sanka Mohottala

One of the important measures of quality of education is the performance of students in the academic settings. Nowadays, abundant data is stored in educational institutions about students which can help to discover insight on how students…

Computers and Society · Computer Science 2019-09-18 Ephrem Admasu Yekun , Abrahaley Teklay

Most of the organizations put information on the web because they want it to be seen by the world. Their goal is to have visitors come to the site, feel comfortable and stay a while and try to know completely about the running organization.…

Databases · Computer Science 2010-09-03 Sandeep Singh Rawat , Lakshmi Rajamani

Normalization is an important database design method, in the course of the teaching of data modeling the understanding and applying of this method cause problems for students the most. For improving the efficiency of learning normalization…

Databases · Computer Science 2014-05-09 Márta Czenky

In this paper we applied data fusion approaches for predicting the final academic performance of university students using multiple-source, multimodal data from blended learning environments. We collected and preprocessed data about…

Computers and Society · Computer Science 2024-03-12 W. Chango , R. Cerezo , C. Romero

Studying materials informatics from a data mining perspective can be beneficial for manufacturing and other industrial engineering applications. Predictive data mining technique and machine learning algorithm are combined to design a…

Databases · Computer Science 2012-09-20 Doreswamy , Hemanth K. S

Academic performance prediction aims to leverage student-related information to predict their future academic outcomes, which is beneficial to numerous educational applications, such as personalized teaching and academic early warning. In…

Machine Learning · Computer Science 2021-07-23 Chaoran Cui , Jian Zong , Yuling Ma , Xinhua Wang , Lei Guo , Meng Chen , Yilong Yin

The growing popularity of data mining catalyses the researchers to explore various exciting aspects of education. Early prediction of student performance is an emerging area among them. The researchers have used various predictors in…

Computers and Society · Computer Science 2021-07-30 Anupam Khan , Sourav Ghosh , Soumya K. Ghosh

In this study, we examine how event data from campus management systems can be used to analyze the study paths of higher education students. The main goal is to offer valuable guidance for their study planning. We employ process and data…

In this study, we examine a set of primary data collected from 484 students enrolled in a large public university in the Mid-Atlantic United States region during the early stages of the COVID-19 pandemic. The data, called Ties data,…

Machine Learning · Statistics 2022-09-13 Anthony Frazier , Joethi Silva , Rachel Meilak , Indranil Sahoo , David Chan , Michael Broda

Methods based on machine learning become increasingly popular in many areas as they allow models to be fitted in a highly-data driven fashion, and often show comparable or even increased performance in comparison to classical methods.…

Applications · Statistics 2022-10-24 Annette Möller , Ann Cathrice George , Jürgen Groß

Student performance modelling (SPM) is a critical step to assessing and improving students performances in their learning discourse. However, most existing SPM are based on statistical approaches, which on one hand are based on probability,…

Improving the precision of heart diseases detection has been investigated by many researchers in the literature. Such improvement induced by the overwhelming health care expenditures and erroneous diagnosis. As a result, various…

Computers and Society · Computer Science 2018-03-29 Israa Ahmed Zriqat , Ahmad Mousa Altamimi , Mohammad Azzeh

The performance in higher secondary school education in India is a turning point in the academic lives of all students. As this academic performance is influenced by many factors, it is essential to develop predictive data mining model for…

Machine Learning · Computer Science 2010-02-08 M. Ramaswami , R. Bhaskaran

Machine teaching often involves the creation of an optimal (typically minimal) dataset to help a model (referred to as the `student') achieve specific goals given by a teacher. While abundant in the continuous domain, the studies on the…

Machine Learning · Computer Science 2024-02-01 Xiaodong Wu , Yufei Han , Hayssam Dahrouj , Jianbing Ni , Zhenwen Liang , Xiangliang Zhang

In recent years, machine learning has been proposed as a promising strategy to build accurate scoring functions for computational docking finalized to numerically empowered drug discovery. However, the latest studies have suggested that…

Quantitative Methods · Quantitative Biology 2023-02-17 F. Pellicani , D. Dal Ben , A. Perali , S. Pilati