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Record W2888974989 · doi:10.22168/2237-6321-21129

Intervention on reading comprehension: an approach designed for students with Asperger’s Syndrome (AS)

2018· article· pt· W2888974989 on OpenAlexaff
Lidia Correia, Wilson Júnior de Araújo Carvalho, Becky Chen

Bibliographic record

VenueEntrepalavras · 2018
Typearticle
Languagept
FieldSocial Sciences
TopicEducation and Digital Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyReading (process)Developmental psychologyPhilosophyLinguistics

Abstract

fetched live from OpenAlex

This paper reports the results of a study which examined reading comprehension in adolescents and young adults with Asperger’s Syndrome (AS). The study was conducted in the city of Fortaleza, Northwest region of Brazil, with 6 students from grade 6 and above. More specifically, the study focused on improving reading comprehension of teenagers and young adults with AS through an intervention program based on metacognitive reading strategies, having as a theoretical base the conciliatory approach of reading. We adopted the reading model proposed by Kintsch and Van Dijk (1983), which presents reading comprehension as a dynamic, online and strategic process. In addition, we relied on the theoretical framework of Solé (1998) to address basic reading strategies. The results presented in this paper are part of the mentioned research, they suggest that teaching activities that focus on explicit instruction are effective for reducing reading comprehension difficulties in students with AS. These activities encourage students to reflect on their knowledge, facilitating the comprehension process andself-monitoring.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.073
GPT teacher head0.401
Teacher spread0.328 · 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 designNon-randomized trial
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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