Modern Multivariate Statistical Methods for Evaluating the Impact of WhatsApp on Academic Performance: Methodology and Case Study in India

Prayas Sharma, Ashish Kumar Singh, Víctor Leiva, Carlos Martin-Barreiro, Xavier Cabezas

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Despite the increasing amount of research on social media, there are few studies on the use of WhatsApp to assess academic performance. Surprisingly, students use social media during lectures, causing a problem. According to the literature, students utilize WhatsApp throughout academic activities where it is prohibited. Researchers and policymakers must pay attention to this problem to understand its impact on academic achievement. In this paper, by using multivariate statistical methods, we investigate the impact of WhatsApp use on academic performance. We construct a questionnaire for this investigation and apply it to a case study based on a sample of 258 students of management from India. We determine the prevalence of WhatsApp employment among these students and note that many of them utilize the app for academic purposes. We found a positive association between time spent on WhatsApp and students’ grade point average (GPA) based on factor, principal component, correlation, and chi-square analyses. Answering questions on the app in class is related to the program’s ability to help students learn. More use of the app in class leads to a lower GPA. However, sometimes, using the app might help students learn and perform better. We identify that many students disseminate materials through the app for academic purposes, contributing to their academic performance. Furthermore, this app is utilized for communicating with their teachers. Computations were carried out with the R and SPSS software.

Original languageEnglish
Article number6141
JournalApplied Sciences (Switzerland)
Volume12
Issue number12
DOIs
StatePublished - 1 Jun 2022

Keywords

  • disjoint principal components
  • education data
  • grade point average
  • information and communication technologies
  • multivariate statistics
  • operationalization of variables
  • social media

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