[Paper Review] Predicting Virtual Learning Environment adoption - A case study

Sonam Penjor, Pär‐Ola Zander|arXiv (Cornell University)|Mar 9, 2015

Online and Blended Learning20 references13 citations

TL;DR

This study applies Rogers' Diffusion of Innovations theory to predict Virtual Learning Environment (VLE) adoption at the Royal University of Bhutan using descriptive statistics and logistic regression. It finds that while the theory lacks cross-organizational stability, it yields reliable predictions within a single institutional context, challenging the generalizability of diffusion models in VLE research and highlighting the need for organization-specific validation in educational technology adoption.

ABSTRACT

Purpose - To qualify the significance of Rogers' Diffusion of Innovations theory with regard to Virtual Learning Environments. To apply an existing Diffusion of Innovations instrument on a case organisation, the Royal University of Bhutan (RUB), in order to compare its results with previous findings. Descriptive statistics and logistic regression analysis were deployed to analyze adopter group memberships and predictor significance in Virtual Learning Environment adoption and use. Findings - The Diffusion of Innovations theory is not stable across organizations when it comes to predicting different user categories or the distribution of users. However, it was possible to achieve reliable results for virtual learning environments within a particular organization. Research limitations ND implications - The study questions scholarly attempts to establish models of this type across organizations. Practical implications - Professionals should be aware that cross-organizational generalizations from Diffusion Of Innovation findings within the domain of virtual learning environments may be very unreliable. Originality and value - The study challenges the massively cited Diffusion of Innovation literature. It provides data from Bhutan, which is underrepresented in empirical investigations.

Motivation & Objective

• To assess the applicability of Rogers' Diffusion of Innovations theory to Virtual Learning Environment (VLE) adoption in higher education.
• To evaluate whether existing diffusion instruments reliably predict VLE adoption across different user categories within an organization.
• To compare findings from the Royal University of Bhutan (RUB) with prior studies to test the theory’s consistency across institutions.
• To challenge the assumption that diffusion models in VLE adoption are universally applicable across diverse educational organizations.

Proposed method

• Applied an existing Diffusion of Innovations instrument to collect data on user characteristics and adoption behaviors at the Royal University of Bhutan.
• Used descriptive statistics to summarize adopter group memberships and distribution across user categories.
• Employed logistic regression analysis to identify significant predictors of VLE adoption and usage.
• Analyzed data from a single case organization to assess model reliability within a specific institutional context.
• Compared results with previous studies to evaluate the stability of the diffusion model across different organizations.
• Focused on identifying which innovation attributes (e.g., relative advantage, compatibility) significantly predicted adoption.

Experimental results

Research questions

• RQ1 To what extent does Rogers' Diffusion of Innovations theory predict VLE adoption across different user categories within a single educational institution?
• RQ2 How do the predictor variables identified in prior diffusion studies perform when applied to a new organizational context like the Royal University of Bhutan?
• RQ3 Is the Diffusion of Innovations model stable and generalizable across different educational organizations when predicting VLE adoption?
• RQ4 What are the key factors influencing VLE adoption within a specific higher education institution in a developing country context?
• RQ5 Can reliable predictions of VLE adoption be made using diffusion theory when applied within a single organizational setting?

Key findings

• The Diffusion of Innovations theory demonstrated limited stability across organizations when predicting VLE adoption across different user categories.
• Despite cross-organizational inconsistencies, reliable predictions of VLE adoption were achieved within the specific context of the Royal University of Bhutan.
• The study found that generalizations from diffusion research in VLE adoption may be highly unreliable when applied beyond the original organizational setting.
• The results challenge the widespread assumption that diffusion models are universally applicable in educational technology adoption contexts.
• Empirical data from Bhutan—a region underrepresented in such research—adds value by providing a non-Western, developing country perspective on VLE adoption.
• The study underscores the importance of context-specific validation of diffusion models rather than relying on cross-organizational generalizations.