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Reading comprehension in university students: relevance of PASS theory of intelligence

2012· article· en· W2153845225 on OpenAlex

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

VenueJournal of Research in Reading · 2012
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFluencyReading comprehensionPsychologyReading (process)ComprehensionCognitionCognitive psychologyRelevance (law)LinguisticsMathematics education

Abstract

fetched live from OpenAlex

We examined how Planning, Attention, Simultaneous and Successive (PASS) processes predict reading comprehension in a sample of university students (Study 1) and what PASS processes distinguish adults with and without reading difficulties (Study 2). In Study 1, 128 university students were tested on Das‐Naglieri Cognitive Assessment System, reading fluency and reading comprehension. The results of path analysis indicated that successive processing predicted reading comprehension only through the effects of text‐ and word‐reading fluency, whereas simultaneous processing predicted reading comprehension both directly and through the effects of text‐reading fluency. In Study 2, university students with (n = 20) and without (n = 23) reading difficulties were assessed on the same measures as in Study 1. The results of group comparisons indicated that the university students with reading difficulties were experiencing cognitive weaknesses primarily in successive processing. The implications of these findings for PASS theory and comprehension are discussed.

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)0.011
metaresearch head score (Gemma)0.001
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 score0.035
Threshold uncertainty score0.364

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.117
GPT teacher head0.449
Teacher spread0.332 · 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