The Relationship between English Language Arts Teachers’ Use of Instructional Strategies and Young Adolescents’ Reading Motivation, Engagement, and Preference
Bibliographic record
Abstract
Conducted at 10 schools in four communities, this study investigated relationships of young adolescents’ readingmotivation, reading preference, and reading engagement as influenced by their English Language Arts teachers’use of instructional strategies. Students in eight sixth grade (N=196) and nine seventh grade (N=218) classescompleted a post Reading Behavior Survey and the Motivation to Read Questionnaire (MRQ) and a ClassStrategies Checklist at the beginning and end of the academic year. The 17 teachers also completed a pre/postStrategies Checklist and a Survey. Mean MRQ difference scores were averaged by ELA class group. Scores innine MRQ dimensions revealed a decline except for Challenge with a slight positive increase for seventh graders.These results confirm prior research findings that as adolescents move along in grade level their readingmotivation decreases. However, 11 of the 17 class groups indicated some positive change in one or more MRQdimensions with five classes revealing positive reading motivation growth in four dimensions. Enjoyable readingactivities noted by all students involved receptive and expressive oral language. Such preference may have beendue to large class populations of Hispanic, subsidized lunch, and limited English proficient students who foundthat oral language interaction helped them understand and enjoy the readings. The most preferred readingactivity during out-of-school time was that of a social nature involving text messaging. Both this current andprior research suggest that successful teachers motivate their students through classroom interaction, challengingliteracy activities and discussion about what was read.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".