How students develop a sense of belonging to their academic community: a qualitative study of students’ experiences in a for-profit entertainment arts college
Bibliographic record
Abstract
How Students Develop a Sense of Belonging explores the experiences of non-traditional students during their first year of study at Entertainment Arts College, a broad-access for-profit private institution in a major city in British Columbia, Canada.The purpose of my study was to grapple with a practice-based problem: the unheard voices of nontraditional students in the for-profit private sector.Due to the paucity of research on students' sense of belonging in the Canadian post-secondary system, where few public and virtually no private-sector studies have occurred, I purposefully explored a broad range of factors in relation to the student participants' sense of belonging in this specific context.At the post-secondary level most of the research studies that have focused upon the fit between the student and the institution have done so from an institutional perspective.To better acknowledge the agency and contexts of students, some researchers have turned to more dynamic fit concepts including students' sense of belonging.Building upon these examples, I utilized the concepts of belonging, structure and agency to explore how student participants negotiated their sense of belonging within The College's academic community.Qualitative methods included a quasi-ethnographic form of educational criticism.To co-construct student participants' cultural experiences, I conducted several phases of in-depth interviews and collaborated closely with entertainment arts students, faculty, and administrators throughout the student participants' first year of study.The participants were also encouraged to represent their perceptions about belonging in non-verbal ways by submitting creative artifacts such as artwork, poetry, and images to complement the primary data set.Eight major themes emerged from the data including: a) Corporate Culture; b) Economic Capital, c) Academic and Artistic Capital, d) Self-Concepts, e) Support from Academic Staff, f) Student Participants' Representations of Self-Concepts, g) Support from Service-Based Departments, and h) Peer-Support.Multiple data-sets and the contributions of faculty and administrators' provided for a more holistic interpretation of student participants' sense of belonging.The findings revealed that their sense of vi belonging is a multi-dimensional process that is more complicated than traditional research on the student-institution fit suggests.The implications for theory and practice at The College are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.019 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".