Do Teacher Reports of Executive Functions Predict Reading Development? Evidence from a Nationally Representative Sample
Bibliographic record
Abstract
Abstract This study explores whether teacher reports of executive functions predict change in reading performance (i.e., reading development) for elementary‐aged students when controlling for direct assessments of executive functions and for teacher reports of students' literacy skills. Prior research has raised problems with the construct validity of teacher reports of executive functions but has yet to consider that these teacher reports might be related to teachers' perceptions of their students' literacy skills. The current study used Grades 3 through 5 data from nationally representative data ( N = 6945) of students collected between 2014 and 2016 to examine the contributions of teacher reports of executive functions to change in reading performance over the course of a year with autoregressive structural equation models. Measures of executive functions tapped attentional focusing (in Grades 3 and 4), working memory (in Grade 3), and inhibitory control (in Grade 4). When controlling for a direct assessment of the same facet of executive function as the teacher report, the teacher report of executive function predicted next year's reading. However, controlling for a teacher report of students' literacy skills reduced the effect of teacher reports of executive functions to nearly 0 across models while not reducing the effect of direct assessments of executive functions. This finding held across student race and home language subgroups in multigroup analyses. Based on these findings, teacher reports of executive functions do not capture information about executive functions that predicts of reading development beyond the teachers' perceptions of their students' literacy skills. Further research is needed to determine how teacher reports of EF could be designed to capture EFs as applied to reading.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".