Barriers to Systemic, Effective, and Sustainable Technology Use in High School Classrooms / Obstacles a l’utilisation systemique, efficace et durable de la technologie dans les salles de classe des ecoles secondaires
Bibliographic record
Abstract
The purpose of the Technology and High School Success (THSS) initiative was to encourage innovative strategies focused on improving provincial high school completion rates, using technology and student-centered learning to engage student interest. The primary purpose of this paper is to report on barriers that impede systemic, effective and sustainable technology integration within schools. Even with teacher and administrative support and commitment for THSS, evaluative research indicated minimal change in system capacity as a result of the initiative. Three primary barriers to program sustainability were: 1) schools and school districts did not leverage the opportunity to revisit their existing vision(s), 2) schools and school districts did not use data to make changes, and 3) limited access to technology. Le but de l’initiative « Technology and High School Success (THSS) » était d'encourager des stratégies novatrices visant à améliorer le taux d’achèvement des études secondaires dans la province de l’Alberta en utilisant la technologie et un apprentissage centré sur l'élève afin de susciter l'intérêt des élèves. L'objectif principal de cet article est de rendre compte des obstacles entravant l'intégration systémique, efficace et durable de la technologie dans les écoles. La recherche évaluative a révélé des changements minimes dans la capacité systémique à la suite de l'initiative, et ce, malgré l’appui et l’engagement des enseignants et des administrateurs envers le THSS. Les trois obstacles principaux à la viabilité du programme sont les suivants: 1) les écoles et les districts scolaires n'ont pas profité de l’occasion pour revoir leur(s) vision(s), 2) les écoles et les districts scolaires n'ont pas utilisé les données pour effectuer des changements, et 3) l'accès limité à la technologie.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.008 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".