Abstract:  A significant amount of study has been done to determine the impact of digital distraction on students from an international viewpoint, according to the evaluated literature that is accessible from the perspective of the research issue. The research on the proposed issue has been minimal in the Indian setting. Moreover, considering the information of the unavoidable prevalence of distraction among today's pupils, it is necessary to develop specific ways for transforming these distractions into manageable factors. Based on the existing research, it is evident that the current generation of students is easily diverted by several variables, both internal and external to the classroom environment. However, attempting to take into account and analyse all of these elements would result in a research scope that is too broad. The current study will specifically examine distractions experienced by students in classroom situations. Considering the extensive impact of the widespread availability of the internet and digital devices, it is important to evaluate the level of distraction experienced by students in the digital realm and its influence on their academic performance. In terms of a wider viewpoint, the current research project will focus on consolidating the existing literature on how digital distractions affect students' academic performance and highlighting the consequent consequences for both students and instructors. Machine learning techniques have been used in the domain of intelligent diagnostics to address these problems, particularly in detecting anomalous data and structural deterioration....

Cite:
Kamala S, Dr. A. Jayanthiladevi,"Machine Learning-Based Analysis on Digital Distractions and Academic Performance of Online Engagement", IARJSET International Advanced Research Journal in Science, Engineering and Technology, vol. 10, no. 12, pp. 202-208, 2023, Crossref https://doi.org/10.17148/IARJSET.2023.101226

| DOI: 10.17148/IARJSET.2023.101226