Best-practice model for technology enhanced learning in the creative arts

This paper presents a best-practice model for the redesign of virtual learning environments (VLEs) within creative arts to augment blended learning. In considering a blended learning best-practice model, three factors should be considered: the conscious and active human intervention, good learning design and pedagogical input, and the sensitive handling of the process by trained professionals. This study is based on a comprehensive VLE content analysis conducted across two academic schools within the creative arts at one Post-92 higher education (HE) institution. It was found that four main barriers affect the use of the VLE within creative arts: lack of flexibility in relation to navigation and interface, time in developing resources, competency level of tutors (confidence in developing online resources balanced against other flexible open resources) and factors affecting the engagement of ‘digital residents’. The experimental approach adopted in this study involved a partnership between the learning technology advisor and academic staff, which resulted in a VLE best-practice model that focused directly on improving aesthetics and navigation. The approach adopted in this study allowed a purposive sample of academic staff to engage as participants, stepping back cognitively from their routine practices in relation to their use of the VLE and questioning approaches to how they embed the VLE to support teaching and learning. The model presented in this paper identified a potential solution to overcome the challenges of integrating the VLE within creative arts. The findings of this study demonstrate positive impact on staff and student experience and provide a sustainable model of good practice for the redesign of the VLE within creative disciplines.

Shaping the future of learning using the student voice: we’re listening but are we hearing clearly?

Student voice data is a key factor as Manchester Metropolitan University strives to continually improve institutional technology enhanced learning (TEL) infrastructure. A bi-annual Institutional Student Survey enables students to communicate their experience of learning, teaching and assessment on programmes and specific units studied. Each cycle of the survey contains approximately 40–50,000 free text comments from students pertaining to what they appreciate and what they would like to see improved. A detailed thematic analysis of this data has identified 18 themes, arranged into six categories relating to the ‘Best’ aspects of courses, and 25 themes, arranged in seven categories in relation to aspects of courses considered to be ‘in need of improvement’. This student data was then used as a basis for semi-structured interviews with staff. Anecdotally, evidence suggested that student expectations and staff expectations around TEL and the virtual learning environment (VLE) differed. On-going evaluation of this work has highlighted a disconnect. In significant instances, academic colleagues seemingly misinterpret the student voice analysis and consequently struggle to respond effectively. In response to the analysis, the learning technologist's role has been to re-interpret the analysis and redevelop TEL staff development and training activities. The changes implemented have focused on: contextualising resources in VLE; making lectures more interactive; enriching the curriculum with audio–visual resources; and setting expectations around communications.