The Adaptation and Implementation of ISTE Standards in the Integration of Technology-based Learning in the Classroom
Bibliographic record
Abstract
Children must be introduced to information technology in the school environment to be competitive in this new information society; however, teachers are not adequately prepared to provide technology-supported instruction to children in a meaningful way. This descriptive study documented the process of adapting and implementing existing information technology standards developed by the International Society for Technology in Education (ISTE) to address the local needs of the Toronto District School Board. The Toronto District School Board is a K-12 educational institution located in Toronto, Canada, with approximately 30,000 staff and a student population of over 300,000. The study process occurred in four phases: the establishment of a set of criteria to adapt and implement ISTE standards, the validation of the established criteria, the adaptation and implementation of the ISTE standards, and an evaluation of the adapted and implemented I STE standards. A Criteria Committee comprised of secondary school teachers established the criteria to adapt and implement the existing I STE standards. A group of education experts validated the established criteria. A Standards Committee worked with a Formative Committee of secondary school teachers to adapt the ISTE standards to address the needs of the local school district. The Standards Committee consisted of competency experts and experts from the field of education. Adaptation procedures addressed the criteria identified and validated. The adapted ISTE standards were implemented as a pi lot study to identify potential problem areas that were corrected prior to involving the entire school district. An Evaluation Committee evaluated the efficacy of the adapted and implemented ISTE standards and practices. The outcome of this descriptive study was a documented process for a local school district to adapt and implement ISTE standards to integrate technology based learning into the classroom.
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 | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".