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Record W7112568975

Learning methods for students with learning disabilities : A comparison study between teachers in Sweden and the English-speaking world

2018· article· sv· W7112568975 on OpenAlexaboutno aff

Bibliographic record

VenueDigitala vetenskapliga arkivet (Diva) (Karlstad University) · 2018
Typearticle
Languagesv
FieldSocial Sciences
TopicSocial and Educational Sciences
Canadian institutionsnot available
Fundersnot available
KeywordsInclusion (mineral)Learning disabilityCurriculumWork (physics)Focus groupLearning disabledTeaching methodSpecial education
DOInot available

Abstract

fetched live from OpenAlex

This is a research study about children who develop learning difficulties during the early years of schooling, and how teachers can help them best learn. The focus will be on learning methods, which help students with learning disabilities, learn to read. I decided to make this an international study, by comparing a Swedish teachers observation, to teachers from five different English-speaking countries (USA; England; Canada; Australia; New Zealand). I made a lot of international contacts through my work as a volunteer for Karlstad University international office, host program. Through these contacts, I got in contact with different international participants for my research study. I conducted interviews with my participants on Skype. The end result of what I learned from these interviews was very interesting and educational, especially how the different school systems function and how the teachers work with children with learning disabilities in their elementary schools. For example, most of the teachers work a lot, with sounding out letters and personalized schedules. A few of the teachers work a lot with inclusion and specialized curriculums for the students with learning disabilities, which their department of education pressed a lot on, while other teachers department of education did not.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0030.004
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.065
GPT teacher head0.394
Teacher spread0.329 · 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; both teacher heads agree on what is shown here.

Study designQualitative
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
Published2018
Admission routes1
Has abstractyes

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