Investigating the educational value of social learning networks: a quantitative analysis

Abstract

Purpose

The emergence of Education 2.0 enabled technology-enhanced learning, necessitating new pedagogical approaches, while e-learning has evolved into an instrumental pedagogy of collaboration through affordances of social media. Social learning networks and ubiquitous learning enabled individual and group learning through social engagement and social distribution of knowledge. Nevertheless, these developments have not been supported with extensive studies focusing on quantifying the impact of technology-enhanced learning on students’ progress and achievement. The purpose of this paper is to investigate how a quantitative overview of Facebook’s influence on students’ progress can be incorporated in a proposed e-moderation model of teaching and learning.

Design/methodology/approach

The approach is based on extending Salmon’s (2003) e-moderation model, which provides an emphasis on the theoretical perspectives that support socially situated learning environments of social networks such as Facebook. The findings revealed that students’ grades were positively influenced by the complementary use of Facebook on their courses of study.

Findings

The use of a social learning network also triggered a significant increase in student participation in learning activities delivered over Facebook.

Research limitations/implications

The main research limitations were due to the fact that a single social network was chosen for conducting the experiments. Furthermore, the investigation was narrowed down to a selected range of sessions offered to college and university students as part of their course.

Originality/value

The paper’s contribution is twofold, as it offers an original set of guidelines for conducting social learning network experiments and provides valuable quantifiable findings on the educational value of such networks.

Citation

Dafoulas, G. and Shokri, A. (2016), "Investigating the educational value of social learning networks: a quantitative analysis", Interactive Technology and Smart Education, Vol. 13 No. 4, pp. 305-322. https://doi.org/10.1108/ITSE-09-2016-0034