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Degree and Higher Level Apprenticeships: an empirical investigation of stakeholder perceptions of challenges and opportunities.

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Title: Degree and Higher Level Apprenticeships: an empirical investigation of stakeholder perceptions of challenges and opportunities.
Authors: Mulkeen, James, Abdou, Hussein A., Leigh, Jacqueline, Ward, Paul
Source: Studies in Higher Education. Feb2019, Vol. 44 Issue 2, p333-346. 14p. 2 Charts.
Subjects: Sensory perception, Stakeholders, Employers, Universities & colleges, Program design (Education), Higher education
Abstract: The aim of this paper is to explore the challenges and opportunities of designing and delivering Degree and Higher Level Apprenticeships (D&HLAs) at levels 4-7 from a multi-stakeholder perspective namely employers, Universities, independent training organisations and professional bodies. Twenty-seven face-to-face interviews were undertaken and thematic content analysis was used to analyse the data. The following three themes emerged from the data analysis: programme design; programme delivery; and graduate attributes. We conclude that whilst there are increasing numbers of trailblazer groups developing higher level standards, the uptake of apprenticeships at these levels remains relatively low. Although stakeholders support the principle of D&HLAs, we identify a number of challenges and opportunities facing those who seek to successful introduction of these programmes. Our policy recommendations include the need for all stakeholders to work collaboratively to co-create a flexible system to support the validity and relevance of D&HLAs. This will include streamlining and mapping the variety of qualifications currently available in order to promote a platform for parity of both esteem and opportunity for those achieving degree qualifications through the apprenticeship route. [ABSTRACT FROM AUTHOR]
Copyright of Studies in Higher Education is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: The aim of this paper is to explore the challenges and opportunities of designing and delivering Degree and Higher Level Apprenticeships (D&HLAs) at levels 4-7 from a multi-stakeholder perspective namely employers, Universities, independent training organisations and professional bodies. Twenty-seven face-to-face interviews were undertaken and thematic content analysis was used to analyse the data. The following three themes emerged from the data analysis: programme design; programme delivery; and graduate attributes. We conclude that whilst there are increasing numbers of trailblazer groups developing higher level standards, the uptake of apprenticeships at these levels remains relatively low. Although stakeholders support the principle of D&HLAs, we identify a number of challenges and opportunities facing those who seek to successful introduction of these programmes. Our policy recommendations include the need for all stakeholders to work collaboratively to co-create a flexible system to support the validity and relevance of D&HLAs. This will include streamlining and mapping the variety of qualifications currently available in order to promote a platform for parity of both esteem and opportunity for those achieving degree qualifications through the apprenticeship route. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Studies in Higher Education is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/03075079.2017.1365357
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        Text: English
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        PageCount: 14
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        Type: general
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              Text: Feb2019
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