Mozamel M. Saeed^*

Intelligent Automation & Soft Computing, Vol.39, No.2, pp. 213-231, 2024, DOI:10.32604/iasc.2024.043020 - 21 May 2024

Abstract The study aims to recognize how efficiently Educational Data Mining (EDM) integrates into Artificial Intelligence (AI) to develop skills for predicting students’ performance. The study used a survey questionnaire and collected data from 300 undergraduate students of Al Neelain University. The first step’s initial population placements were created using Particle Swarm Optimization (PSO). Then, using adaptive feature space search, Educational Grey Wolf Optimization (EGWO) was employed to choose the optimal attribute combination. The second stage uses the SVM classifier to forecast classification accuracy. Different classifiers were utilized to evaluate the performance of students. According to… More >

Ierin Babu^1,*, R. MathuSoothana², S. Kumar²

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3621-3636, 2023, DOI:10.32604/iasc.2023.033791 - 15 March 2023

Abstract Educational Data Mining (EDM) is an emergent discipline that concentrates on the design of self-learning and adaptive approaches. Higher education institutions have started to utilize analytical tools to improve students’ grades and retention. Prediction of students’ performance is a difficult process owing to the massive quantity of educational data. Therefore, Artificial Intelligence (AI) techniques can be used for educational data mining in a big data environment. At the same time, in EDM, the feature selection process becomes necessary in creation of feature subsets. Since the feature selection performance affects the predictive performance of any model,… More >

Evren Hincal, Amna Hashim Alzadjali

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 393-411, 2022, DOI:10.32604/cmes.2022.019781 - 15 June 2022

Abstract Excellent student’s academic performance is the uppermost priority and goal of educators and facilitators. The dubious marginal rate between admission and graduation rates unveils the rates of dropout and withdrawal from school. To improve the academic performance of students, we optimize the performance indices to the dynamics describing the academic performance in the form of nonlinear system ODE. We established the uniform boundedness of the model and the existence and uniqueness result. The independence and interdependence equilibria were found to be locally and globally asymptotically stable. The optimal control analysis was carried out, and lastly, More >

Victoria Gonzáles-Gutierrez¹, Aldo Alvarez-Risco², Alfredo Estrada-Merino², María de las Mercedes Anderson-Seminario², Sabina Mlodzianowska², Shyla Del-Aguila-Arcentales³, Jaime A. Yáñez^4,5,*

International Journal of Mental Health Promotion, Vol.24, No.4, pp. 565-581, 2022, DOI:10.32604/ijmhp.2022.021176 - 27 May 2022

Abstract The current study measures the influence of multitasking behavior and self-efficacy for self-regulated learning (SESRL) on perceptions of academic performance and views in university students during the COVID-19 pandemic in Mexico. 264 university students fulfilled an online questionnaire. It was observed that multitasking behavior negatively influences SESRL (−0.203), while SESRL showed a positive influence of 0.537 on perceptions of academic performance, and multitasking behavior had an influence of −0.097 on the perception of academic performance. Cronbach’s alpha and Average Variance Extracted values were 0.809 and 0.577 (multitasking behavior), 0.819 and 0.626 (SESRL), 0.873 and 0.725 More >

Shaoying Liu^1,2,#, Qian Yu^3,#, Md Mahbub Hossain⁴, Scott Doig⁵, Ran Bao⁶, Yaping Zhao⁷, Jin Yan^8,*, Xun Luo³, Jiaxuan Yang³, Arthur F. Kramer^9,10, Liye Zou³

International Journal of Mental Health Promotion, Vol.24, No.1, pp. 13-24, 2022, DOI:10.32604/IJMHP.2021.017660 - 20 December 2021

Abstract This research is designed to investigate the relationship between the 24-h movement guidelines (24-HMG) and self-reported academic achievement (AA) using nationally representative data derived from the 2019 U.S. National Youth Risk Behaviour Survey. A multiple-stage cluster sampling procedure has been adopted to ensure a representative sample (N = 9127 adolescents; mean age = 15.7 years old; male% = 49.8%). Logistic regression has been adopted to obtain the odds ratio (OR) regarding the associations between adherence to 24-HMG and AA while controlling for ethnicity, body mass index, sex and age. The prevalence of meeting the 24-h… More >

Shagufta Zada^1,2, Yuefen Wang^1,*, Muhammad Zada^3,4, Fatima Gul¹

International Journal of Mental Health Promotion, Vol.23, No.3, pp. 395-408, 2021, DOI:10.32604/IJMHP.2021.015903 - 23 July 2021

Abstract Scientific interest in student’s mental health experiences has been increasing in the last years due to their influence on students’ learning processes, academic performance, and recently, the suicidal news of a student at a private university due to her mental health condition in Lahore Punjab, Pakistan, captured public attention. That incident also shifted researchers and scholars’ attention on the much underexplored and tabooed sphere of the broader public health domain. Hence, the current study aimed to explore the relationship between mental health problems and Pakistani university students’ academic performance. Participants were 540 senior semester students… More >