Maximising motivators for technology-enhanced learning for further education teachers: moving beyond the early adopters in a time of austerity

Armstrong, Emily J.

Abstract

Technology-enhanced learning (TEL) has become a prominent issue in further education (FE) since the publication of the Further Education Learning Technology Action Group (FELTAG) report in 2014, but many initiatives have concentrated on digital competence without investigating the role of staff attitudes and motivation in extending their use of new technologies. This research explored the views and experiences of FE staff using technology to support learning and the impact of these on their motivation to develop a technology-enhanced curriculum in their subject. The aim was to identify any common themes or factors linked to positive engagement with TEL which could inform institutional efforts to increase the extent and effectiveness of TEL use. This research used a mixed-methods approach to attempt to provide a broader and more reliable view of attitudes and also considered the similarities and differences between the experiences of further and higher education teachers through comparison with Bennett’s (2014) Digital Practitioner Framework and the particular barriers found in the resource-constrained environment of FE. It summarises the key factors identified as likely to influence staff engagement with TEL, and recommends how such motivating factors could be maximised and how potential barriers could be addressed.

Citation

Armstrong, E. J. (2019). Maximising motivators for technology-enhanced learning for further education teachers: moving beyond the early adopters in a time of austerity. Research in Learning Technology, 27, https://doi.org/10.25304/rlt.v27.2032

• Journal Article Type: Article
• Acceptance Date: Feb 28, 2019
• Online Publication Date: Feb 28, 2019
• Publication Date: 2019
• Deposit Date: Jun 11, 2019
• Publicly Available Date: Jun 11, 2019
• Journal: Research in Learning Technology
• Print ISSN: 2156-7069
• Electronic ISSN: 2156-7077
• Publisher: Taylor & Francis Open Access
• Peer Reviewed: Peer Reviewed
• Volume: 27
• DOI: https://doi.org/10.25304/rlt.v27.2032
• Keywords: Education; Computer Science Applications
• Public URL: https://hull-repository.worktribe.com/output/1970004