An Intervention in Reading Disabilities Using a Digital Tool During the COVID-19 Pandemic
Bibliographic record
Abstract
In the last decade, ICT-based interventions for developing reading skills in children with reading disabilities have become increasingly popular. This study had three goals: (a) to assess the existence of gains in word reading, oral reading fluency and listening comprehension after a Tier 2 intervention using the digital tool “I’m still learning,” which was delivered partially in a remote modality during the COVID-19 pandemic; (b) to investigate whether the gains depended on the students’ gender, the number of sessions attended and the interventionist; and (c) to investigate parents’ perceptions about the suitability and perceived effects of the intervention. A single group design with pre-test and post-test was used. The intervention was delivered to second graders ( N = 81) flagged as being at-risk for reading disabilities in a universal screening. The analyses showed significant gains in all three outcome variables after the intervention. The gains did not depend on students’ gender, number of intervention sessions attended or interventionist. Parents’ perceptions of the remote intervention were positive. The study findings highlight the potentialities of using technology-based interventions to foster reading skills and suggest that these may be especially useful during lockdowns.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".