Students’ Sense of Course, University and Industry Belonging: The Influence of Diverse Representation in the Curricula

Dataset

Description

A qualitative approach comprising semi-structured interviews was used to investigate the relationship between representation in the curricula and sport management student's sense of course, university and industry belonging. Participants were recruited through a purposive sampling technique (Bryman 2004) via the Sport Management programme and module virtual learning environment at the chosen post-1992 institution. Recognising the various classifications of social class (Bettencourt 2021) and the influence of intersectional identities on belonging (Bettencourt 2021; Kluch et al., 2023; Rodriguez and Blaney 2021), this study operationalised the following inclusion criteria for undergraduate sport management students: 1. Students who identified as first-generation (neither parent holds a higher education qualification). 2. Students who identified as working class. 3. BAME. Potential participants contacted the named researcher and an online semi-structured interview was organised according to their availability. Interviews were conducted via Microsoft teams to reflect the institution’s hybrid teaching format. Data collection occurred between January and February 2024. All interviews were audio recorded and transcribed verbatim. Participant were anonymised and pseudonyms were allocated to protect the identity of the interviewees. Recruitment of interviewees stopped when data saturation, the moment at which no new themes emerged (Fugard and Potts 2015), was reached. Braun and Clarke’s (2006) six phases of thematic analyses were used to analyse the data. NVivo was used during the qualitative coding process.

The interview transcripts cannot be shared publicly as the transcripts contain information that may allow identification of the institute and / or specific lecturers which the researcher does not have consent to share.
Date made available30 Sept 2024
PublisherUniversity of Northampton
Date of data productionJan 2024 - Feb 2024

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