Pan-Canadian abracadabra follow-up: What do we know four years later about students' and teachers' responsiveness to being part of an intervention study?
Bibliographic record
Abstract
This dissertation is a Canadian-based 4-year follow-up study that examines the long-term effectiveness of the ABRACADABRA (ABRA) web-based literacy intervention on students' (n = 467) reading progress and teachers' (n = 22) long-term use of a new intervention. This mixed-methods study is a quantitative study with a nested qualitative component at the teacher level of data analysis. This dissertation identifies factors influencing both students' and teachers' responses to being part of a randomized control trial (RCT) intervention study that examined the effectiveness of teacher-implemented ABRA lessons during classroom-level instruction. Framed within a response to an intervention (RtI) context, this study broadens the scope of the RtI literature from primarily focusing on pupil-level RtI variations to also considering the RtI effects on teachers. At the pupil level, this study examines the enduring effectiveness of the ABRA intervention and investigates if the short-term reading gains obtained by students at immediate posttesting (T2), who received the ABRA intervention, were maintained up to 4 years later at follow-up (T3). The added contribution of demographic variables in predicting students' short- and long-term likelihood of being at risk of reading difficulties is also examined. A series of binary stepwise logistic regressions were run to examine the interaction and main effects of ABRA and the demographic variables on the variance of students' reading. An Ethnicity effect evident at T2 found students of Asian background having a raised risk of not responding to the intervention and remaining in the at risk of reading difficulties group in comparison to their White peers. A Sex effect in favour of female students was evident at T3. While a SES effect at both T2 and T3 showed that the odds of having stronger reading skills increased for students with mothers with some post-secondary education. When examining the students' long-term reading intervention response, no support was found for the inoculation hypothesis model, as the positive short-term reading gains made at T2 by the students identified at risk were not maintained at T3. No interaction effects between the ABRA intervention condition and the demographic variables of interest were found at T2 or at T3. At the teacher level, a deductive thematic analysis (TA) approach is employed to examine factors influencing teachers' response to being part of an intervention study (RtI) and their subsequent long-term integration of a new resource into their teaching practice. At T3, over 70% of the teacher respondents reported that the ABRA program continued to be part of their literacy practice repertoire. A significant relationship was found between teachers' level of implementation (IFM) during the intervention phase and teachers' continued use of the ABRA tool. The findings from this study may have implications for how teachers are trained and supported during a classroom based intervention study, and how teachers can be included in the process to facilitate greater buy-in and improve their quality of implementation fidelity of new technology-based resources.Keywords: reading intervention, follow-up study, longitudinal effects, randomized control trial, response-to-intervention, demographic variables, teacher change, technology integration, ABRACADABRA, implementation fidelity, mixed methods
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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 | 0.024 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".