Publication Cover
Educational Psychology
An International Journal of Experimental Educational Psychology
Volume 35, 2015 - Issue 7
2,168
Views
12
CrossRef citations to date
0
Altmetric
Articles

Are students really connected? Predicting college adjustment from social network usage

&
Pages 819-834 | Received 04 Sep 2012, Accepted 23 May 2013, Published online: 30 Jul 2013
 

Abstract

The rapid growth in popularity of social networking sites has spurred research exploring the impact of usage in a variety of areas. The current study furthered this line of research by examining the relationships between social network usage and adjustment to college in the academic, social, personal-emotional and university affiliation domains. Realising the number of students with social networking accounts, some universities have developed strategic plans for social media. Thus, this study also compared two universities, one with a social media strategic plan and one without, to determine if the planning process had an influence on students. Results indicated that social network usage was related to college adjustment. Specifically, those students who reported higher rates of social media use reported lower levels of adjustment to college in all domains. However, there were no differences between the two universities, indicating that having a social media strategic plan does not influence students in the area of college adjustment. These results are discussed in light of retention rates and changing practices within higher education.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 759.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.