Educational Online Technologies in Blended Tertiary Environments: Experts' Perspectives

Introduction

Educational online technologies (EOTs) have dynamically transformed the delivery of higher education, creating extraordinary opportunities for enhanced learning and teaching. In an era of great digital growth, their enhanced functionalities and affordances have revolutionised methods of knowledge access and engagement, generating phenomenal increases in the demand for web-based learning and support. Factors including affordability, scalability, ubiquity, and accessibility have bolstered levels of generational acceptance and encouraged growth. Traditional learning spaces have evolved into dynamic blended tertiary environments (BTEs), and channels of content dissemination have switched from didactically-styled “traditional, face-to-face courses to … online courses” (Picciano, 2015, p. 148).

This paper aimed to identify, and describe the application of a range of EOTs popularly used in blended tertiary environments (BTEs). Achieved using a qualitative design involving semi-structured interviews with 13 blended learning experts from New Zealand, Australia and Canada, and a 5-step analysis of data, it verified the use of 35 different EOTs in BTEs, including Adobe Connect, Blackboard, Facebook, Instagram, and YouTube. Their key characteristics were summarised using a multi-dimensional taxonomy, called the Pentexonomy, which synergised a range of perspectives into a robust, contextualised, and multi-dimensional framework for categorising EOTs. An outline of recommendations for the effective use of some of these EOTs was also provided. As EOTs advance and usage accelerates, the outcomes of this research will assist TEIs in their efforts to keep abreast of EOT developments, make informed choices about EOT use, and contribute to the delivery of relevant, meaningful EOT support.

Methodology

A qualitative system of methods was used to guide the collection and analysis of data (Marelli, 2016). Participants were selected using an expert sampling strategy to ensure that data came from those with specific expertise and experience in the field (Trochim, 2006). This method was similar to the approaches used by Chapleo and Simms (2010), who obtained data from ‘opinion-formers’, and Wagner et al. (2008) who used experts’ feedback. Criteria were set to establish a basis for their selection for interviews. Participants had to fit the criteria of a ‘blended learning expert’. An expert is defined as “one whose special knowledge or skill causes him to be regarded as an authority” (Oxford University Press, 2014). Experts could be selected on relatively simple criteria, such as through certain qualifications or experience (Changing Minds, 2013). Thus, the following criteria established a basis for their selection: 1) the individual must have occupied an academic role for not less than 10 yrs in a tertiary blended learning context, 2) hold a post-graduate qualification, and 3) have conducted published research in the area of blended learning. Candidates without blended learning experience or without post-graduate qualifications were excluded from this study.