Preparing Students At-Risk for Successful Transitions into Institutions of Higher Education
Bibliographic record
Abstract
For students from lower socioeconomic areas or who might be the first in their family to contemplate attending postsecondary, transition support programs can provide students with the opportunity to become more familiar with institutions of higher education. The purpose of this Master of Teaching Research Project is to examine how a small sample of secondary and postsecondary teachers working collaboratively within a credit-bearing transition support program preparing secondary school students deemed at-risk in Toronto’s priority neighborhoods for the transition from high school to university. Data was collected through a series of semi-structured interviews with three educators involved in a specific credit-bearing transition support program in Ontario. These interviews were first audio-recorded, and then subsequently transcribed, coded, and analyzed by the researcher. The results of this qualitative study determined that the financial cost of attending postsecondary, family expectations, and systemic and cultural oppression can be barriers for students’ access to institutions of higher education. It also found secondary teachers need to further develop the reading and writing comprehension of their students, as well as their critical inquiry skills. Furthermore, the research found that transition support programs promote a sense of belonging for students involved in the programs within institutions of higher education. Finally, the study was found that students need to foster self-confidence in their academic abilities as well as self-assuredness that students at-risk are capable of attending postsecondary.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".