A systematic review of instructional interventions to improve school completion: mapping the evidence
Bibliographic record
Abstract
This review of research on dropout prevention programs in Canada between 1990 and 2006 was conducted with the goal of increasing awareness and knowledge of (a) current research on high school dropout prevention and intervention in Canada; (b) instructional design and implementation of successful programs; (c) context-related factors that moderate program effectiveness and (d) selecting and/or designing programs that take into consideration current research evidence. The identification of studies to be used in this review was conducted through a comprehensive search of publicly available literature (i.e., research databases, contacting researchers and program administrators, contacting local and provincial education agencies, etc.). Of the 240 documents retrieved 38 met all of the inclusion criteria. An additional 30 studies from outside of Canada were also analyzed. Underreporting and missing data presented significant challenges in terms of analyzing instructional practices and impacts. Results showed that the most frequent type of dropout prevention programs were pull-out support, specialized courses and workshops or alternative schools. Most programs incorporated multiple forms of support (i.e., combinations of health services, life-skills, career preparation, academic support, cultural/spiritual enrichment, etc.). Instructional strategies varied across findings with the most common being tutoring, work-based learning and mentoring. Almost three quarters of the findings presented evidence of positive program outcomes with another 13% reporting strong positive program impacts. Future research might focus on linking outcome impacts (e.g., enrolment status/dropout rates) with the program performance context to look beyond ''the learner" as the site of dropout prevention. Application for stakeholders and practitioners includes, among others, recommendations for revisiting existing practices and policies to determine if mainstream classroom practices support the school/work connection and redefining instruction using best-practices in teaching to accommodate self-direction, flexibility in course delivery and responsiveness to the needs of at-risk learners.
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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 | 0.021 | 0.104 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.019 | 0.025 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".