Concurrent and Predictive Links Between Children's Classroom Experiences, Academic Engagement, and Anxious Solitude in Elementary School
Bibliographic record
Abstract
The primary goal of this dissertation was to examine the predictors and outcomes associated with behavioural academic engagement in childhood. Behavioural academic engagement can be described as attention, participation, and on-task behaviour in the classroom (Fredricks, Blumenfeld, & Paris, 2004). Many factors have been found to predict behavioural engagement, such as classroom factors (e.g., teacher-child relationships, peer relationships, class climate), socio-demographic factors, and child factors (e.g., gender, anxious solitude). Although many educational outcomes are strongly inter-associated, the current dissertation examined the mediating role of academic engagement on the relation between classroom experiences and academic achievement. In addition, the moderating role of child factors was examined on the relations between classroom experiences and academic engagement. For the current study, data on N = 779 children were drawn from the National Institute of Child and Human Development (NICHD) Study of Early Child Care and Youth Development (SECCYD) data set. A series of moderated-mediation models were examined at both grade 1 and grade 3. Finally, predictors of change in engagement over time were examined. Among the results, support for the differential susceptibility hypothesis (Belsky, 1997) was found, indicating that anxious solitary children may be more reactive (both positively and negatively) to elements of the classroom environment. In addition, some gender effects were found, suggesting that anxious solitary boys may be at a particularly elevated risk for academic problems. Results are discussed in terms of their implications for future research and educational policies concerning the structure of the classroom environment.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".