Pan-Canadian abracadabra follow-up: What do we know four years later about students' and teachers' responsiveness to being part of an intervention study?
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,024 | 0,064 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,003 | 0,006 |
| Études des sciences et des technologies | 0,010 | 0,002 |
| Communication savante | 0,005 | 0,003 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».