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Record W2223465503

Rural schools and technology: Connecting for innovation

2013· article· en· W2223465503 on OpenAlexaboutno aff
Barbara Barter

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumBarterContext (archaeology)SociologyPedagogyClass (philosophy)Presentation (obstetrics)Distance educationVideoconferencingMathematics educationComputer sciencePsychologyMultimediaMedicine
DOInot available

Abstract

fetched live from OpenAlex

Placed within the context of rural teaching and learning and the use of new technologies, this paper presents a comparative study of three technological approaches to the presentation of curriculum in schools. Supported by three different research projects in one Canadian province, it highlights three areas of e-learning: the use of video conferencing to deliver curriculum to children in five rural schools (Barter, 2004), web-based distance education implemented by the Ministry of Education to deliver academic courses to students in rural and remote areas (Barter, 2011), and a lap top computer-based project with a class of intermediate students (Barter, Murphy, Hardy, Norman and Pack, 2004). Including a literature review, the paper provides a brief background of each project, outlines the results, and then discusses the impact such projects can have on education. Two projects (video conferencing and Ministry of Education delivered distance education) are described and then discussed through the responses of practicing teachers, while the third (lap tops for learning) is explored through the reflections of participating teachers as well as those from consenting junior high students. Accepting that the three projects represent a largely localized instance of curriculum research, they are used as a 'stepping off point' that serves to highlight the challenges and successes in implementing curriculum through multiple forms of technology that can be expanded to a wider audience. The paper does not delve into the effects of different technology applications. Rather, it focuses on the effects of implementation in general. The intent is to present the successes and challenges of the three projects as examples that may help educators to identify and define theoretical aspects of technology leadership and lead to further understandings about how users may experience its implementation and use. The three projects and an extant literature indicate that innovations involving technology are process driven. They bring opportunity as well as challenges that stretch the limits of teaching and learning. As a result, the effective use of distance education, in any form, requires consistent, extensive support for both students and teachers.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.015
Scholarly communication0.0100.009
Open science0.0010.010
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.040
GPT teacher head0.378
Teacher spread0.339 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations6
Published2013
Admission routes1
Has abstractyes

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