Unpacking Reading Comprehension by Text Type: An Examination of Reading Strategy Use and Cognitive Functioning in Poor and Typically-Achieving Comprehenders
Bibliographic record
Abstract
In the present study, I examined how students build comprehension with different types of text. Poor comprehenders and typically-achieving comprehenders, as determined by a standardized measure for general reading comprehension, were compared in their reading comprehension and reading strategy use across narrative, expository, and graphic text. I also examined the influence of cognitive functioning on reading comprehension, and to what extent cognitive functions can explain the difference in reading comprehension between poor and typically-achieving comprehenders. This research was partially exploratory, where I aimed to validate existing research on cognitive functions, reading strategies, and reading comprehension of text, as well as to contribute new research that distinguishes between text types. Past research has shown that cognitive functions predict reading comprehension and that poor comprehenders have poorer cognitive functioning and use fewer reading strategies than their peers. However, no research to date has made distinctions between different types of text, specifically graphic text, and how cognitive functioning and reading strategy use relate to comprehension. A group of poor comprehenders (n = 24) and typically-achieving comprehenders (n = 38) completed measures of cognitive functioning and read narrative, expository, and graphic texts aloud before answering comprehension questions. Participants were asked to ‘think-aloud’ during reading, which allowed me to make comparisons between the two groups on reading strategy use. Poor comprehenders used fewer cognitive strategies than their typically-achieving peers while reading narrative and expository text, and fewer evaluative strategies with graphic text. Typically-achieving comprehenders also outperformed poor comprehenders on comprehension of each style of text. Participants’ abilities to recognize abstract patterns predicted comprehension of each text type, while participants’ abilities to exercise inhibition also predicted expository text comprehension. The same variables accounted for a significant portion of the variance between poor and typically-achieving comprehenders, though graphic text had the most variance unaccounted for. The findings from the present study highlight the importance of distinguishing between text types in research on reading comprehension, and suggest that more attention should be paid to dynamic reading comprehension instruction and support.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".