6 articles for “Academic Performance Prediction Academic Performance of Students”

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Review ArticleOpen accessIn the keywordsA Systematic Review Regarding the Prediction of Academic PerformancePercy De-La-Cruz, Rommel Rojas-Coaquira, Hugo Vega-Huerta et al.The prediction of students' academic performance is an area of great concern for universities and educational institutions since academic performance is one of the most important aspects of the learning process. To analyze this behavior, this study makes a critical analysis of the topic of interest and aims to review, analyze and summarize the latest research advances related to the … …Journal of Computer Science, Vol. 18, Issue 12 · 23 Dec 2022 · 8,602 accessesView PDF Cite

Research ArticleOpen accessIn the abstractHybrid Soft Voting Ensemble of XGBoost and DNN for At-Risk Student Performance PredictionEugene Wan, Po Chan Chiu, Mohammad bin Hossin et al.Early identification of at-risk students in higher education is important for timely academic intervention, yet conventional prediction methods often struggle with data imbalance and limited model precision. This study proposes a hybrid soft voting ensemble model that integrates Extreme Gradient Boosting (XGBoost) and Deep Neural Network (DNN) to enhance multi-class student grade prediction (A-F classification) and at-risk student identification. This … …Journal of Computer Science, Vol. 22, Issue 5 · 28 May 2026 · 1,390 accessesView PDF Cite

Research ArticleOpen accessIn the abstractEvaluation of Machine Learning Models to Predict Student Academic Performance Using Structured Educational DataHardik Ishwarbhai Patel, Dharmendra PatelThis study analyses the use of machine learning for predicting the academic performance of students using their academic information from the institution, combined with socio-economic information that comes from outside sources. The collection of information is done using structured questionnaires as well as through data extraction from the Student Information System (SIS). To increase the reliability of models built, a … …Journal of Computer Science, Vol. 22, Issue 5 · 26 May 2026 · 1,419 accessesView PDF Cite

Research ArticleOpen accessIn the abstractClassifying and Predicting Students’ Performance using Improved Decision Tree C4.5 in Higher Education InstitutesMohammed Hikmat Sadiq, Nawzat Sadiq AhmedStudents’ information in higher education institutions increases yearly. It is hard for them to extract meaningful information from the huge amount of data manually. Such information can support academic staff to stop students from dropping out at the end of courses. This can be done by evaluating the students’ performance for the course and also by predicting their performance in … …Journal of Computer Science, Vol. 15, Issue 9 · 12 Sep 2019 · 9,168 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordSupervised Machine Learning Model-Based Approach for Performance Prediction of StudentsAbdul Razaque, Abrar M. AlajlanPredicting students’ performance is one of the crucial issue for learning contexts, since it helps to develop alternative recommendation systems for academically weak students. Thus, several methods and practices have been applied for educational improvement. However, most of the existing methods do not determine the performance of the students. In this study, we have studied the execution of six machine … …Journal of Computer Science, Vol. 16, Issue 8 · 28 Aug 2020 · 7,082 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordPredicting Students’ Academic Performance in the University Using Meta Decision Tree ClassifiersShanthini A., G. Vinodhini, R.M. ChandrasekaranStudent performance prediction is an area of concern for educational institutions. At the University level learning system, the method or rule adopted to identify the candidates who pass or fail differs depending on various factors such as the course, the department of study and so on. Predicting the result of a student in a course is an issue that has … …Journal of Computer Science, Vol. 14, Issue 5 · 28 Feb 2018 · 9,194 accessesView PDF Cite