“Why is the bear sad?”: preparing preservice educators to support children’s inferencing during storybook reading
Bibliographic record
Abstract
The study investigated the effects of an instructional unit for preservice educators aimed at developing their knowledge about children’s inferencing skills and strategies to support these skills during storybook reading. Participants were randomly assigned to either an experimental group that received instruction on supporting inferencing (n = 13) or a comparison group (n = 12) that received instruction on print referencing, another means of supporting emergent literacy. For both groups, instruction involved a videorecorded presentation; independent reading, observation, and reflection; and discussion and practice of the targeted strategies with peers in a virtual environment. Participants’ knowledge about emergent literacy and inferencing was evaluated via a questionnaire and a role-play. While both groups increased their knowledge about emergent literacy from pretest to posttest, only the experimental group improved significantly on knowledge about inferencing and asked a greater number and proportion of inferential questions during the role-play, as well as more diverse questions. The implications for education and professional development for preservice educators are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".