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Record W2902109698 · doi:10.24059/olj.v22i4.1518

Quiet Participation: Investigating non-posting activities in online learning

2018· article· en· W2902109698 on OpenAlexaff
Lesley Wilton

Bibliographic record

VenueOnline Learning · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsReading (process)Online learningValue (mathematics)PerceptionPsychologyKey (lock)Mathematics educationComputer scienceWorld Wide WebLinguistics

Abstract

fetched live from OpenAlex

Despite the growth in online learning offerings in K-12 and higher education, limited research has been undertaken to better understand less visible online learning activities. Reading and rereading are not typically valued as important indicators of learning since number or frequency of entries, words or key phrases are usually visible and easily tracked. This paper addresses reading, writing and revisiting behaviours by cluster groups in eight online courses, and looks for patterns related to rereading. Participant perceptions of the value of rereading entries in online learning are discussed. The findings highlight the importance of a more nuanced understanding of the different roles reading and rereading play in online learning discussions. This research informs our understanding of the importance of non-posting behaviors to student learning. Instructionally, these results may encourage valuing of different “paths” to online learning success beyond the criterion of written entries.Despite the growth in online learning offerings in K-12 and higher education, limited research has been undertaken to better understand less visible online learning activities. Reading and rereading are not typically valued as important indicators of learning since number or frequency of entries, words or key phrases are usually visible and easily tracked. This paper addresses reading, writing and revisiting behaviours by cluster groups in eight online courses, and looks for patterns related to rereading. Participant perceptions of the value of rereading entries in online learning are discussed. The findings highlight the importance of a more nuanced understanding of the different roles reading and rereading play in online learning discussions. This research informs our understanding of the importance of non-posting behaviors to student learning. Instructionally, these results may encourage valuing of different “paths” to online learning success beyond the criterion of written entries.

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)0.007
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.047
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.039
GPT teacher head0.371
Teacher spread0.332 · 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 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

Citations12
Published2018
Admission routes1
Has abstractyes

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