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Record W595437259 · doi:10.82308/33187

A metacognitive tool to support reading comprehension of historical narratives

2010· article· en· W595437259 on OpenAlexafffund
Eric Poitras

Bibliographic record

VenueeScholarship@McGill (McGill) · 2010
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsMcGill University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsNarrativeComprehensionMetacognitionReading (process)Reading comprehensionLinguisticsPsychologyComputer scienceCognitive psychologyCognitionPhilosophy

Abstract

fetched live from OpenAlex

Learners frequently have difficulty understanding incoherent historical narrative texts; therefore, this thesis project introduces a bottom-up approach to design metacognitive tools to assist learners reading comprehension. Metacognitive tools are defined as computer-based learning environments designed to assist learners to achieve an instructional goal through prompting, supporting, and modeling metacognitive and self-regulatory learning processes (Azevedo, 2005a, 2005b). The study follows a 2*2 design with experimental condition (reading with the benefit of the metacognitive tool vs. without the benefit of the tool) and process data (silent reading vs. think aloud). Pretest measures include reading comprehension skill and free recall measures. Posttest measures include amount of material recalled and accuracy of answers to open-ended questions. Learners who used the metacognitive tool outperformed the control group in their recall of information mentioned in the text because they monitored their comprehension and generated explanatory inferences more frequently. Keywords: metacognitive tools, reading comprehension, historical narratives

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), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
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
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.049
GPT teacher head0.340
Teacher spread0.290 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations2
Published2010
Admission routes2
Has abstractyes

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