In this paper we use ML algorithms in order to predict the performance of students, taking into account both past semester grades and socioeconomic factors.

Apr 30, 2024 · The study uses advanced machine learning algorithms to predict student performance, enhancing accuracy and enabling early intervention. It also allows for personalized interventions based on individual needs, optimizing resource allocation.

Jul 20, 2023 · The goal of this paper is to present a systematic literature review on predicting student performance using machine learning techniques and how the prediction algorithm can be used to...

By analyzing historical academic data, attendance, and engagement patterns, machine learning models accurately forecast student success and identify those at risk of underperformance. This enables educators to implement timely, targeted interventions, fostering …

Apr 30, 2024 · In this research work, K-means, a clustering data mining technique using Davies’ Bouldin method, obtains clusters to find important features affecting students’ performance. The study found...

Jan 28, 2025 · Predicting students’ success is crucial in educational settings to improve academic performance and prevent dropouts. This study aimed to improve student performance prediction by combining advanced machine learning (ML) approaches.

The literature on student performance prediction using machine learning (ML) is vast and evolving. Key trends include the application of various ML algorithms such as supervised learning, classification, and artificial intelligence (AI) to forecast academic outcomes.

In our report, we are giving the detailed view of the proposed algorithm for student’s features classification with the combination of two Mapping function and different base classifiers. System shows that which is best for the student data set.

Large amounts of online and offline learning data that students have left behind make it possible to anticipate their performance and to pre-intervene with at-risk kids, using data mining, machine learning, and deep learning to predict student achievement. [1]

Mar 26, 2020 · The goal of Pojon [15] research is to determine the best effective comparison-based prediction algorithm for predicting students' performance by using Grade Point Average (GPA) and final...