A review of the meta‐analysis by Tingir and colleagues (2017) on the effects of mobile devices on learning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Tingir et al. (2017) concluded from their meta‐analysis that the subject areas taught through mobile devices had significantly higher achievement scores ( d = 0.48) than the ones taught with traditional teaching methods. Given the relatively high positive effect of mobile devices on student achievement, we carefully analysed the selected research in this meta‐analysis. We reviewed Tingir et al.’s (2017) meta‐analysis based on analysis of the methodology of the selected research, while drawing on the work of Slavin (2003), Cheung and Slavin (2016), and Sung et al. (2019). Twelve of the 14 (86%) studies included in the meta‐analysis done by Tingir and his team (2017) present such major methodological flaws that they should not have been included. Our analysis leads us to believe that the conclusion of Tingir et al. (2017) is not justified. It is recognized that duration of experiment is negatively correlated with effect size: the shorter the duration, the higher the effect (Burston, 2015; Slavin & Lake, 2009). Although demanding more effort, the field of education must raise the bar if it is to have knowledge of acceptable value.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it