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The aim of this study was to explore the learning experiences of visually impaired physiotherapy students in the UK, specifically focusing on barriers and enablers faced within university and classroom based education. A qualitative multiple case study design was used due to the unique and small group of participants under exploration. Course Leaders of all universities in the UK that offered Physiotherapy education at undergraduate or pre-registration level were approached as gatekeepers to access participants. Four visually impaired physiotherapy students consented to take part in the study, each from a different institution. Semi-structured interviews were used at a time and setting chosen by each participant. Data were recorded and transcribed verbatim, and analysed thematically using NVivo 10. Both barriers and enablers were identified, with sub-themes within the data; the barriers were: environmental factors, unsupportive behaviours and time and effort. The enablers were: supportive relationships, student attributes, and strategies and adaptations. All participants experienced barriers to learning within their university setting, despite having disclosed a disability and having access to and provision of reasonable adjustments. However, despite facing barriers, there were many positive experiences that enabled learning, particularly when staff and students worked together in an open, supportive, and proactive environment.
This article was published in the following journal.
Name: Nurse education in practice
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Teaching strategy of shared learning based cross-discipline experiences and placements.
Process in which individuals take the initiative, in diagnosing their learning needs, formulating learning goals, identifying resources for learning, choosing and implementing learning strategies and evaluating learning outcomes (Knowles, 1975)
Persons with loss of vision such that there is an impact on activities of daily living.
Professionals responsible for teaching in an institution or place of learning such as a school, college, vocational institute, or university.
A MACHINE LEARNING paradigm used to make predictions about future instances based on a given set of unlabeled paired input-output training (sample) data.