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Record W2947430033 · doi:10.1177/0741932519843998

Teaching Science Content and Practices to Students With Intellectual Disability and Autism

2019· article· en· W2947430033 on OpenAlex
Victoria Knight, Leah Wood, Bethany R. McKissick, Emily M. Kuntz

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRemedial and Special Education · 2019
Typearticle
Languageen
FieldPsychology
TopicBehavioral and Psychological Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIntellectual disabilityAutismPsychologySpecial educationContent analysisMedical educationPedagogyDevelopmental psychologySociologySocial scienceMedicinePsychiatry

Abstract

fetched live from OpenAlex

The purpose of this literature review was to synthesize recent research (2009–2018) for teaching science to students with intellectual disability and intellectual disability/autism. Authors identified a total of 15 studies; of these, 12 were determined to be methodologically sound studies using the Council for Exceptional Children quality indicators. Based on the methodologically sound studies, authors analyzed the evidence base of the instructional practices to teach science content and science practices to students with intellectual disability and intellectual disability/autism. Unlike previous literature reviews in which the focus has been on teaching science content, authors contribute to the literature on teaching science to this population by determining the evidence for teaching the science practices (e.g., asking questions, communicating findings). Resulting analysis was used to offer research-based recommendations for providing quality science instruction to students with intellectual disability and intellectual disability/autism. We conclude with limitations and possibilities for future research.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.266
Threshold uncertainty score0.227

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.175
GPT teacher head0.426
Teacher spread0.251 · 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