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Record W1497063710

Computer technology integration: handbook for primary and elementary teachers

2005· dissertation· en· W1497063710 on OpenAlexaff
Marina Bishop Foley

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2005
Typedissertation
Languageen
FieldSocial Sciences
TopicEducation and Technology Integration
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsCurriculumTechnology integrationMathematics educationSchool teachersInformation and Communications TechnologyClass (philosophy)Sample (material)Information technologyElementary mathematicsComputer technologyPrimary educationPsychologyEducational technologyPedagogyComputer scienceMultimediaWorld Wide Web
DOInot available

Abstract

fetched live from OpenAlex

Computer technology has been in schools since the early 80s. Information Communication Technologies (ICTs) have been incorporated more at the junior high and senior high than at the primary and elementary level. Boards have often focused attention on the senior grades. Primary and elementary teachers have received little support with the integration of technology into classroom settings. Many primary and elementary teachers have not adopted technology as another tool in their classrooms. There are many reasons for this, one of which includes the lack of training for teachers in how to successfully integrate technology into teaching and learning. Professional development in the area has progressed through three stages with the most current being “just-in-time”. There is much research telling why we should use technology and how. This work, an electronic handbook, is a justification for the use of technology in the lower grades. It offers research that supports why teachers should use technology and its curriculum connections. It also includes sample lessons from K-6, ideas of how to use one computer in a class, and links to relevant web sites that are appropriate for both teachers and students.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.668
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0040.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.024
GPT teacher head0.308
Teacher spread0.284 · 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.

Study designNot applicable
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
Published2005
Admission routes1
Has abstractyes

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