A Systematic Literature Review: The Modalities, Pedagogies, Benefits, and Implications of Storytelling Approaches in Early Childhood Education Classroom
Bibliographic record
Abstract
Abstract\nThe purpose of this systematic literature review was to investigate and synthesize several aspects of storytelling in the reviewed scholarly research, providing a holistic summary and potential insights for early childhood educators. The study asked: (1) What are the various forms, modes and media, and involved pedagogies that storytelling in early childhood education can take? (2) What are the reported benefits of storytelling in early childhood education? (3) Based on the literature, what understandings and pedagogical implications are enriched for early childhood educators to utilize storytelling in their pedagogies? Using a theoretical framework based in multimodal literacy and sociocultural theory, data for the study were derived from 33 screened articles that had been published in the last 10 years. The findings showcase that educators use diverse storytelling approaches with multimodal ensembles in early childhood education, and storytelling was found to provide children a variety of different opportunities to make meaning of the world and express it. By being immersed in storytelling, children were documented in the literature as benefiting from considerable immediate and long-term effects. This study offers understandings of a diversity of forms of storytelling and instructional implications for engaging children through multimodal participation. Additionally, this study may provide baseline knowledge for teacher education to improve storytelling strategies and corresponding multimodal scaffolding feedback, which may provide insights into supporting young children’s storytelling experiences.
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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 | 0.025 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.022 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".