Turning the Page for Spot: The Potential of Therapy Dogs to Support Reading Motivation Among Young Children
Bibliographic record
Abstract
This study investigated whether dogs might facilitate a context conducive to reading for children when they are faced with a challenging reading passage. A within-subjects design was used to assess children’s motivation to read in two conditions: with a therapy dog and without a therapy dog. Seventeen children (8 girls; 9 boys) in Grades 1 to 3 (aged 6–8 years) and their parents participated in this study. Results of a multivariate repeated-measures ANOVA with two levels suggested that the presence of a therapy dog positively impacted children’s reading motivation and persistence when they were faced with the task of reading a challenging passage. Specifically, children confirmed feeling significantly more interested and more competent when reading in the presence (versus absence) of a therapy dog. Additionally, participants spent significantly more time reading in the presence of the therapy dog than when they read without the therapy dog present. To the best of our knowledge, this study is the first to use a within-subjects design to explore children’s reading motivation and reading persistence during a canine-assisted reading task. Moreover, as canine-assisted reading interventions assume that the reading context is one that may present a challenge, this research is unique because the reading passages were carefully selected and assigned to each participant to ensure that each child was provided with a challenging reading task. This research holds implications for the development of a gold-standard canine-assisted intervention for young struggling readers.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".