Beyond the Scoreboard: A Machine Learning Investigation of Online Games’ Influence on Jordanian University Students’ Grades

Autor: Mohammad Alshraideh, Abeer Abdel-Jabbar Abu-Zayed, Martin Leiner, Iyad Muhsen AlDajani
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Applied Computational Intelligence and Soft Computing, Vol 2024 (2024)
Druh dokumentu: article
ISSN: 1687-9732
DOI: 10.1155/2024/1337725
Popis: In the latter part of the 21st century, the prevalence of online games has significantly increased, encompassing titles connected to the Internet via smart devices, enabling multiplayer interaction. Recent media attention has shed light on the adverse effects associated with online gaming. This research paper explores the viewpoints of 4,700 university students in Jordan regarding the physical, psychological, and behavioural impacts of Internet games. Additionally, it predicts how these impacts may affect the academic performance of 1,410 students. To analyze student trends and forecast outcomes based on sustained game engagement, a convolutional neural network (CNN) was specifically developed for the neural network. The findings revealed student consensus with recommended university measures to limit online game usage, emphasizing a prevalent belief in the negative influence of games on the body, behaviour, and mental health. In terms of the prediction process, the training data encompassed 60%, 70%, and 80% of the dataset. The results revealed that the highest accuracy, 96.69%, was achieved at the 70% threshold for predicting students’ grade point average (GPA). The analysis suggested that projecting a decrease in the percentage of hours dedicated to playing online games could act as a mitigating factor to prevent GPA decline. Consequently, the system advises a range from 99.9% to 4.1%. This implies that a student with a maximum of 99.9% is encouraged to significantly reduce playing hours to preserve their GPA, while a student with a minimum of 4.1% is recommended to decrease playing hours by 4.1%. On average, for the 1,090 students, the system proposes a 48.36% reduction in playing hours to safeguard their GPAs and mitigate potential risks. This high level of accuracy played a crucial role in forecasting students’ GPA outcomes following a year of sustained daily engagement with online games. Notably, the results unveiled a concerning revelation that 80% of students would face a detrimental impact on their academic performance after one year of such consistent online game involvement.
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