Passport to Prosperity: Enhancing Student Advising and Support for International Students at an Ontario College
Bibliographic record
Abstract
International students are underserviced and increasingly unsupported in Ontario’s post-secondary education system. This dissertation-in-practice (DiP) explores the complex challenges confronting international students in Ontario, with a primary focus on Polytechnic College. Through an in-depth analysis of existing literature and institutional practices, the DiP uncovers gaps in current support systems and proposes strategic interventions, particularly within student advising services, to address these gaps. Embracing principles of inclusivity, cultural sensitivity, and collaborative partnership, the DiP employs a multifaceted approach to enhance the academic and personal success of international students. The Problem of Practice (PoP) centers on the disparities in support needed and support actualized for international students, exacerbated by shifting demographics, financial constraints, and governing policies. Through a thorough needs assessment, and analysis of the environment and context of Polytechnic College, the DiP identifies critical areas for intervention and support. The DiP delineates a series of strategic change initiatives, and communication, evaluation, and monitoring strategies anchored in a reimagined student advising intake for international students at Polytechnic College. By implementing evidence-based interventions, the DiP aims to elevate the academic and personal success and well-being of international students, creating connections and support, while contributing to broader realms of student life. Through collaboration with campus partners and the mobilization of knowledge, the change plan endeavours to effect enduring change that positively shapes the experiences of international students within and beyond Polytechnic College.
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 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".