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Record W2110380459

What Are They Doing and How Are They Doing It? Rural Student Experiences in Virtual Schooling

2008· article· en· W2110380459 on OpenAlexaboutno aff
Michael K. Barbour

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsAsynchronous communicationClass (philosophy)Mathematics educationPsychologyQualitative researchWork (physics)PedagogyComputer scienceEngineeringSociology
DOInot available

Abstract

fetched live from OpenAlex

This study examined the nature of virtual schooling in Newfoundland and Labrador secondary education. The primary goals of this research were to investigate the virtual school learning experience for students in the Centre for Distance Learning and Innovation (CDLI) including the kinds of support and assistance most frequently used and most valued by students learning in a virtual environment. Data were collected related to what students did during their asynchronous class and synchronous class time, along with where they sought help when they needed content-based assistance. Students were interviewed and observed during their virtual school class time. In-school teachers were interviewed and e-teachers were also observed. Data were analyzed using the constant comparative method utilizing Microsoft Word ® as a tool for qualitative data analysis. Findings indicated that during their asynchronous class time students were often assigned seat work or provided time to work on assignments, however, students rarely used this time to complete CDLI work. When the students required assistance they usually relied upon their local classmates. If peer support was not successful, they turned to their e-teacher if it was during synchronous class time or if they had the time to wait for a response. If it was during asynchronous class time or if they needed more immediate feedback, they would seek out their in-school teachers. Students rarely used most of the support resources provided by the CDLI. Further research is needed to improve asynchronous teaching strategies exhibited, to better understand the virtual school experience of lower performing students, to improve upon the identification of students who will be successful in and provide remediation for students who are weak in certain characteristics, and finally to investigate how e-teachers and in-school teachers encourage greater interaction and sense of community to allow students to learn in the social process from their more capable peers. As the goals of this future research are to impact the practice of virtual schooling, design/development research may be a suitable methodology for these future studies.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.401
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.317
Teacher spread0.293 · 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 designQualitative
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

Citations25
Published2008
Admission routes1
Has abstractyes

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