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Policy Processes for Technological Change

2006· book-chapter· en· W4212793950 on OpenAlexaffabout
Richard Smith, Brian Lewis, Christine Massey

Bibliographic record

VenueCases on information technology series · 2006
Typebook-chapter
Languageen
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsHigher educationGovernment (linguistics)Political sciencePublic relationsTechnological changePublic administrationKnowledge managementComputer science

Abstract

fetched live from OpenAlex

This chapter examines policy processes for the introduction of technology-mediated learning at universities and colleges. It is based on the results of a two-year research project to investigate policy issues that arise with the implementation of telelearning technology in universities and colleges. The focus was on Canadian institutions of higher learning, but the issues raised are common to higher educational institutions in other countries. The study scanned a large number of institutions, reviewed documents, and interviewed key actors including government and institutional administrators, faculty, and students, to discover the range of issues raised by the implementation of telelearning technologies. This chapter discusses these issues and findings. •What policies or processes are in place to guide change in colleges and universities? Who knows about these policies and participates in them? •What are the forces behind technological change in higher education organizations? Are they external or internal? •Can technology be used as a tool for achieving meaningful and positive change or is it an end to itself? •In what ways can technology be used to increase access to education?

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)0.000
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: Other · Consensus signal: Other
Teacher disagreement score0.844
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.031
GPT teacher head0.304
Teacher spread0.273 · 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
GenreOther

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
Published2006
Admission routes2
Has abstractyes

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