NAVIGATING NEW HORIZONS: EXAMINING THE TRANSITION EXPERIENCES AND SUPPORT SYSTEMS FOR AFRICAN INTERNATIONAL STUDENTS AT THE UNIVERSITY OF SASKATCHEWAN
Bibliographic record
Abstract
In recent years, Canadian post-secondary institutions have witnessed a significant increase in the enrolment of African International Students (AIS), particularly at the graduate level. While considerable discourse has focused on their cultural adaptation and academic transition, there remains a gap in the literature regarding the specific support systems that underpin these experiences, especially in the context of advancing national objectives tied to the internationalization of higher education. This study explores the lived experiences of African international students and the institutional support mechanisms that facilitate their academic and social integration. Employing a case study methodology within a constructivist framework, data were collected through in-depth interviews, a focus group discussion, and document analysis with a purposefully selected cohort of participants. A focus of this research was to identify the types of support that can effectively meet the academic, social, and cultural challenges of African International Students in their graduate programs. Findings reveal that while international students bring rich cultural perspectives and academic contributions to their host institutions, they often encounter barriers such as adjusting to independent learning styles, financial constraints, limited employment opportunities, racial discrimination, social isolation, and difficulty adapting to individualistic Canadian norms. These challenges emphasize the importance of Canadian institutions to rethink their approaches to international student support. As a result, this research highlights strategies for Canadian higher institutions to develop more targeted and effective support systems to facilitate a smoother academic and social transition for Africans and other international students on its campuses. It emphasizes the importance of collaborative learning environments, inclusive policies, and targeted services that truly align with institutional commitments to social inclusion, while contributing to the broader goals of equity, diversity, and inclusion (EDI). Ultimately, this study contributes to the evolving body of literature on the experiences of African International Students in Canadian post-secondary contexts. It further adds to the fields of International and Comparative Education, and the ongoing discourse on the internationalization of higher education.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".