Cross-National Information and Communication Technology Policies and Practices in Education
Bibliographic record
Abstract
This compendium of papers documents educational ICT policies and practices in 37 countries, making it a valuable resource for understanding and comparing ICT-related national policy developments in education. We believe that this work offers a unique in-depth examination of the trends within major education systems and how they have adapted to and taken advantage of the challenges and opportunities posed by the new information and communication technologies. A special feature of this edition is that it allows for interesting comparative analyses of sub-groups of countries, as many Asian, European Union, and former eastern-European countries, as well as the United States and Canada (among others), are included in the book. But it allows also for other than regional comparisons given that a number of newly industrialized countries (such as Brazil, Chile, Malaysia, and South Africa) are represented in this book, together with many OECD countries.This book is the result of the effort and hard work of the contributing authors, many of whom are the NRCs for IEA SITES in their respective countries. Special thanks must go to the Norwegian Royal Ministry of Education and Research and the Netherlands Kennisnet ICT OP School Foundation, both of which provided generous support for the preparation and dissemination of the book, to the Center for Information Technology in Education (CITE) of the University of Hong Kong, which assisted in the technical preparation of the manuscript, and to the IEA Secretariat, which facilitated the copyediting of the chapters. We want to acknowledge especially the professional contribution of Paula Wagemaker, who has copyedited the entire volume. This copyediting work is especially critical and challenging, as many of the chapters were written by authors for whom English is a foreign language. We also want to express our appreciation to David Robitaille, chair of the IEA Publications and Editorial Committee, and his committee for the critical and constructive review of the manuscript.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".