Feasibility of Building Bridges Between School and Homes in Developing ESL Literacy: The SPIRE Project
Bibliographic record
Abstract
This paper presents a feasible framework for building bridges between schools and homes to develop five year olds ESL literacy skills, using storybooks as a springboard. A reading program, i.e. Smart Partnership in Reading in English (SPIRE) was designed in response to the government’s aspiration to raise literacy rates to 100% by 2020 and the Minister of Education’s call for both parents and teachers to play a more active role for reading to be developed as part of the Malaysian culture. Evidence of the positive effects of storybook reading abounds in the literature and various successful reading programs that bridges schools and home to develop L1 literacy have been carried out, particularly in the UK and USA. However, a similar approach appears to be not adopted in Malaysia. Hence, the SPIRE project was conceptualised to make schools more “permeable” and to move L2 literacy from the classroom into the L2 naturalistic context at homes. 25 multiracial children, their parents and the class teacher participated in this project. Storybooks and other multimedia materials were frequently and repeatedly read/listened to in school, and were taken home for parents to scaffold their children’s ESL literacy development at home. The mixed method approach, using numerous instruments was employed to evaluate the effectiveness of the project. The study found that the children’s progress corresponded to the storybook reading experiences at home. The children, whose parents displayed higher levels of involvement made faster progress compared to the children whose parents were less involved. Consequently, 16 children made substantial improvements and were independent readers at the end of the six months project.
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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 | 0.017 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".