A taxonomy of factors affecting attitudes towards educational technologies for use with technology acceptance models

Abstract The aim of this theoretical review was to identify the important factors shown to affect attitudes towards use of educational technologies by students or educators in higher education institutions and organise them into broad, intermediate and narrow groupings. This was done to assist the construction of more objective measurement instruments used in the evaluation of educational technologies. A qualitative review of the influential factors that affect user attitudes, intentions and motivations to use educational technologies was conducted, first by interrogating the fundamental behavioural theories underpinning technology acceptance models, and then by exploring the findings of later and contemporary empirical research conducted in the educational context. Identified factors were grouped to produce an ordered taxonomy of measurement constructs. This taxonomy provides each construct’s lineage back through tertiary, secondary and primary taxonomic groups and provides a greater scope of measurement than commonly used models. Seven primary and twenty two secondary and tertiary taxonomic groups were defined, which collectively comprise sixty one measurement constructs. The taxonomy is designed to reduce measurement bias within studies and also acts as a basis for consistent and objective benchmarking within and across institutions. Practitioner Notes What is already known about this topic Technology acceptance models are derived from a number of foundational behavioural and motivational theories. The TAM and UTAUT are validated models that appraise attitude and/or behavioural intent to use an educational technology, which nonetheless do not cover the entire scope of what has been shown to be important in various studies. There is little consistency from study to study of measurement constructs used in technology acceptance models. What this paper adds Collection and organisation of the salient measurement constructs into a flexible taxonomy. Establishment of a consistent measurement scope that is specifically suited to educational technology research. Establishment of construct lineage that clearly shows similarities and differences between the various constructs. Implications for practice and/or policy The taxonomy supports robust instrument construction to improve both convergent and discriminant validity of measurement models. The taxonomy provides a recommended scope for higher education institutions to measure factors affecting use of various educational technologies. Consistent use of the taxonomy will provide an objective standard that can be used to compare across institutions or within institutions over time, which assist with benchmarking and management decisions. The taxonomy can be used as a framework for meta‐analyses or to collate ‘prior’ data to use in Bayesian‐type technology evaluation.