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Record W4389223190 · doi:10.15273/jue.v13i2.11798

New Norm, Old Obstacles: The Impact of Distance Learning on Student Agency during the Covid-19 Pandemic

2023· article· en· W4389223190 on OpenAlexvenueno aff
Tyler Cardenas

Bibliographic record

VenueJournal for Undergraduate Ethnography · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Environments and Student Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsAttendancePandemicCoronavirus disease 2019 (COVID-19)Norm (philosophy)Mathematics educationDistance educationAgency (philosophy)PerceptionPedagogyClass (philosophy)PsychologySociologyPolitical scienceMedicineSocial scienceComputer science

Abstract

fetched live from OpenAlex

Mandatory distance learning implemented during the COVID-19 pandemic has produced a new educational landscape for elementary students. Working- and middle-class students have had to meet new expectations around class attendance, homework, and time management, and some are now responsible for overseeing their own education. This study examines students’ agentive expressions and perceptions of time to explore the effects of these expectations, and to contribute to a discussion about the implications of distance learning. Through participant observation and interviews with elementary school students across four Southern California school districts, this study offers insights into how students conceptualize their new role in their education and it provides concrete examples of how this manifests day-to-day. Students from ages five to thirteen learning from home, especially those with limited assistancefrom guardians throughout the school day, have new responsibilities and a greater sense of “their time,” through which they simultaneously discover and establish their position as agents in their 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.089
GPT teacher head0.438
Teacher spread0.349 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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