Being, Becoming, and Belonging: Exploring Students' Experiences of and Engagement within the International School in Hong Kong
Bibliographic record
Abstract
An engaging education attends to the subjective quality of students’ perceptions and experiences within learning and school life: It converges on whether, how, and why students meaning-make and belong within the school; and focuses on the conditions for their attachment, participation, and commitment within school programmes, practices, policies, and people. Three main questions guided this two-phase, mixed-methods study: 1) What makes international schools engaging places for students? 2) What meanings do students attach to key areas of their day-to-day experiences within the international school in Hong Kong? 3) How might re-imagining student engagement through a cosmopolitan lens lead to clearer understandings of students’ experiences within the international school?\n\tIn Phase 1, an achieved sample of 729 senior secondary students at 9 purposively selected schools were surveyed using a mainly Likert scale questionnaire: to describe their socio-demographics; to examine the relationships between their socio-demographics, attitudinal features, and schooling experiences, as measured by the researcher-designed Experience of International School – Revised (EIS-R) scale; and to cluster using their socio-demographics and attitudinal profiles. Building on the tripartite cluster solution, Phase 2 used observations and interviews with 30 purposively sampled teacher-leaders and 34 students, from across the three clusters, to investigate how the “institutional habitus” (Thomas, 2002) the students encountered at two international schools shaped their experiences of and engagement within the contexts of school culture, community, curriculum, and co-curriculum.\n\tA two-stage process of thematic content analysis revealed two super ordinate themes: 1) race/ethnic, linguistic, and nationality identities intersected to shape and challenge patterns of relationships amongst students (and between students/families) and the school to both include and exclude; and 2) the institutional contexts supported and constrained students’ sense of belonging therein. Overall, seen through a cosmopolitan lens the study implications are discussed as three lessons to achieve a better fit between students and the international school: 1) Attend to the school’s living and learning environment; 2) Take a cosmopolitan turn to school for cosmopolitan subjectivity; and 3) Adopt a student engagement-driven approach to improve and reform school policy, administration, and practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".