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Record W2951982458 · doi:10.5539/jedp.v9n2p1

Self-Regulation of Middle School Students With Learning Disabilities During a Complex Project-Based Science Activity

2019· article· en· W2951982458 on OpenAlexvenueno aff
Sheri Berkeley, Anna Larsen, Amanda Colburn, Robert K. Yin

Bibliographic record

VenueJournal of Educational and Developmental Psychology · 2019
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsPsychologyAttributionMathematics educationLearning disabilityPerceptionSelf-regulated learningEnergy (signal processing)Developmental psychologySocial psychology

Abstract

fetched live from OpenAlex

Self-regulation is widely considered important for the academic success of students. Yet, there is limited research about how students self-regulate during complex, long-term learning tasks, such as the project-based learning activities that commonly occur as part of science classroom instruction. There is also less known about how atypical learners, including students with learning disabilities (LD), self-regulate academic tasks. The current multiple case study explores these gaps in the research base through an investigation of how middle school students with language-based LDs self-regulated their learning during a complex, science-based project—creation of computerized serious educational games (SEG) about renewable energy sources. Findings from the current study suggest that there is a relationship between attributions that students with LD make for their performance and their self-efficacy for learning, but only under specific conditions. The role of this relationship seems to diminish when a student poorly calibrates perception of ability relative to actual performance and when a student perceives the cost of effort to outweigh the benefit.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.419
Teacher spread0.354 · 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 designObservational
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

Citations3
Published2019
Admission routes1
Has abstractyes

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