Shouting in space: promoting oral reading fluency with Spaceteam ESL
Bibliographic record
Abstract
This study examined whether the pedagogical use of Spaceteam ESL (English as a Second Language), a digital shouting game, could contribute to the development of Oral Reading Fluency (ORF) among 71 English students in secondary schools in Mombasa, Kenya. Following a mixed-methods approach for data collection and analysis, we pre- and post-tested the participants on their ability to read aloud efficiently (speed) and accurately (accuracy) in three tasks: (1) phrases extracted from the game; (2) phrases not related to the game; and (3) an anecdote. Our findings indicate that participants who played Spaceteam ESL improved their ORF on all measures of speed, but no significant differences were observed in terms of accuracy. Overall, these findings corroborate our hypothesis that some of the affordances of Spaceteam ESL (e.g. speed reading) would contribute to the development of some aspects of ORF.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".