Developing, Testing and Interpreting a Cross Age Peer Tutoring Intervention for Mathematics: Social Interdependence,Systematic Reviews and an Empirical Study.
Bibliographic record
Abstract
Abstract \n \nCross-age peer tutoring is a peer learning strategy which has been shown to improve both socio and academic process of learning factors as well improve attainment in various subjects. There is, however, still room for the intervention to be developed: which was the aim of this work. This was done by applying important socio interdependent aspects such as resource, interpersonal and goal interdependence to a cross-age-peer tutoring intervention in mathematics. Prior to developing the method, the researcher engaged with the theoretical literature as well as provides two forms of systematic reviews. The newly informed cross-age peer tutoring method was then tested on three schools, two of which adopted a pre-post-test quasi-experimental design and one took a single group pre-post-test design. All the schools applied an Interdependent Cross-Age Tutoring (ICAT) format for a period of 6 weeks, on the basis of a 30 minute session once a week. Mathematics head-teachers, facilitators, teachers and students were all trained in various aspects of ICAT. To capture and interpret the impact of the intervention, performance instruments were innovated for each school, together with various previously established attitude sub-scales. In order to measure implementation fidelity ICAT lesson materials were collected for most of the topics and each school received general as well as structured pair observations from the researcher. Also, in order to explore how different groups learned under ICAT the lesson materials of the higher performing tutees were compared to those of the lower performing tutees on various aspects. The findings were mixed, with one of the quasi-experimental design schools showing a highest effect size of 0.81 favoring the ICAT group. The impact of ICAT on important and broader processes of learning attitude variables, social as well as academic, are also discussed. Comparisons of lesson materials between higher performing tutees and lower performing tutees revealed that the highest performing tutees showed better implementation of an essential socio-interdependent aspect: setting a shared academic goal. \n
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".