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Record W4320029002 · doi:10.24059/olj.v26i4.3441

Teachers’ Self-Directed Online Learning Strategies and Experiences: A Longitudinal Study

2022· article· en· W4320029002 on OpenAlexaff
Pamela Beach, Alexandra Minuk, Elena Favret

Bibliographic record

VenueOnline Learning · 2022
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsQueen's University
Fundersnot available
KeywordsPsychologyThink aloud protocolThe InternetOnline learningMathematics educationLiteracyMedical educationPedagogyMultimediaComputer scienceWorld Wide WebHuman–computer interactionMedicineUsability

Abstract

fetched live from OpenAlex

This study examines the strategies used by teachers during a series of self-directed online learning (SDOL) experiences. Over a period of four months, the authors met with 12 practicing elementary teachers three separate times. During the meetings, the teacher participants informally used the Internet for their professional learning in literacy. Their online navigations were captured using screen-recording software. Immediately following their navigations, a virtual revisit think aloud was conducted where participants verbalized their thoughts aloud while viewing a screen-recording of their navigation. Semi-structured interviews with each participant were conducted following the three meetings. Data were analyzed both qualitatively and quantitatively. Findings relate to the cognitive and behavioral strategies in which participants engaged during their SDOL experiences and how these strategies changed over time.

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)0.005
metaresearch head score (Gemma)0.013
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0030.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.067
GPT teacher head0.409
Teacher spread0.342 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

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