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Record W4321439408 · doi:10.19173/irrodl.v24i1.6664

“Someone in Their Corner”: Parental Support in Online Secondary Education

2023· article· en· W4321439408 on OpenAlexvenueno aff
Courtney Hanny, Charles R. Graham, Richard E. West, Jered Borup

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyAttritionStudent engagementOnline communityOnline discussionComputer-mediated communicationCommunity of inquiryCognitionPedagogyThe InternetWorld Wide WebComputer science

Abstract

fetched live from OpenAlex

Despite increased interest in K–12 online education, student engagement deficits and the resulting student attrition remain widespread issues. The Academic Communities of Engagement (ACE) framework theorizes that two groups support online student engagement: the personal community of support and the course community of support. However, more evidence is needed to understand how members of these communities, especially parents, support students in various contexts. Using insights gleaned from 14 semi-structured interviews of parents with students enrolled in online secondary school, this study adds support to the roles identified in the ACE framework by presenting real examples of parents supporting their online students’ affective, behavioral, and cognitive engagement. Findings also confirm patterns found in previous research that are not explained using the ACE framework, such as parental advocacy, communication with teachers, and self-teaching. We discuss how a systems approach to conceptualizing the ACE communities allows the framework to more accurately capture parents' perceived experiences within the personal community of support. We also discuss implications for both practitioners and members of students’ support structures.

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)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.173
GPT teacher head0.514
Teacher spread0.340 · 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 designObservational
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

Citations7
Published2023
Admission routes1
Has abstractyes

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