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Record W6990073699

Cross-National Information and Communication Technology Policies and Practices in Education (Revised Second Edition)

2010· book· en· W6990073699 on OpenAlexaboutno aff

Bibliographic record

VenueThe HKU Scholars Hub (University of Hong Kong) · 2010
Typebook
Languageen
FieldSocial Sciences
TopicEducation and Technology Integration
Canadian institutionsnot available
Fundersnot available
KeywordsCompendiumInformation and Communications TechnologyWork (physics)NorwegianChristian ministryInformation technologyAgency (philosophy)CharterResource (disambiguation)
DOInot available

Abstract

fetched live from OpenAlex

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.
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\nThis 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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.802
Threshold uncertainty score0.683

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.317
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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