Student media usage patterns and non-traditional learning in higher education

Authors

  • Olaf Zawacki-Richter Carl von Ossietzky University of Oldenburg
  • Wolfgang Müskens Carl von Ossietzky University of Oldenburg
  • Ulrike Krause Carl von Ossietzky University of Oldenburg
  • Uthman Alturki King Saud University, Department of Educational Technology, College of Education
  • Ahmed Aldraiweesh King Saud University, Department of Educational Technology, College of Education

DOI:

https://doi.org/10.19173/irrodl.v16i2.1979

Keywords:

Media usage patterns, media usage typology, non-traditional students, instructional design, media selection

Abstract

A total of 2,338 students at German universities participated in a survey, which investigated media usage patterns of so-called traditional and non-traditional students (Schuetze & Wolter, 2003). The students provided information on the digital devices that they own or have access to, and on their usage of media and e-learning tools and services for their learning. A distinction was made between external, formal and internal, informal tools and services.

Based on the students’ responses, a typology of media usage patterns was established by means of a latent class analysis (LCA). Four types or profiles of media usage patterns were identified. These types were labeled entertainment users, peripheral users, advanced users and instrumental users. Among non-traditional students, the proportion of instrumental users was rather high. Based on the usage patterns of traditional and non-traditional students, implications for media selection in the instructional design process are outlined in the paper.

Author Biography

Olaf Zawacki-Richter, Carl von Ossietzky University of Oldenburg

Professor of Educational Technology

Published

2015-04-15

How to Cite

Zawacki-Richter, O., Müskens, W., Krause, U., Alturki, U., & Aldraiweesh, A. (2015). Student media usage patterns and non-traditional learning in higher education. The International Review of Research in Open and Distributed Learning, 16(2). https://doi.org/10.19173/irrodl.v16i2.1979

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