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Record W1984121043 · doi:10.5539/ass.v11n12p258

An Overview of Grounded Theory Design in Educational Research

2015· article· en· W1984121043 on OpenAlexvenueno aff
Chee-Huay Chong, Kee Jiar Yeo

Bibliographic record

VenueAsian Social Science · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsGrounded theoryKey (lock)Computer scienceRange (aeronautics)EpistemologyManagement scienceQualitative researchSociologySocial scienceEngineering

Abstract

fetched live from OpenAlex

Over past decades, grounded theory is increasingly popular in a broad range of research primarily in educationalresearch. The current paper aims to provide useful information for the new-comers and fit them well in groundedtheory research. This paper starts with definitions, origin and applications of grounded theory, followed by typesof grounded theory research designs and the key characteristics of grounded theory. Other aspects coveredinclude data collection and data analysis, general steps, and ethical issues in grounded theory. Discussions on thestrengths and limitations of grounded theory, as well as evaluation aspects, are found in the last part of thispaper.

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)0.084
metaresearch head score (Gemma)0.070
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.084
Threshold uncertainty score0.445

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0840.070
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0100.018
Science and technology studies0.0040.008
Scholarly communication0.0090.007
Open science0.0050.007
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0120.004

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 head0.741
GPT teacher head0.681
Teacher spread0.059 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations54
Published2015
Admission routes1
Has abstractyes

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