iPad Versus Handwriting: Pilot Study Exploring the Writing Abilities of Students with Learning Disabilities
Bibliographic record
Abstract
Abstract Written expression is an essential skill to actively function in today's society. For many learners, especially those with a learning disability (LD), writing can be a source of frustration. Technology in its various forms, holds promise to assist students in this area. The current study examines the role that tablet technology, specifically, iPads, has on the writing skills of students who have an LD. Using a visual analysis approach and paired-sample t-tests, the current study examines how the writing of nine (female = 1, age = 12.5; male = 8; mean age = 11.5) grade six Caucasian students from Northern Ontario with an LD differs when they write by hand versus writing with an iPad. Specifically, the study examines whether there is a difference in (a) writing productivity; (b) spelling accuracy; (c) lexical diversity; (d) syntactical complexity; and, (e) ideas expressed. Results revealed that digital writing using an iPad was effective in significantly improving spelling accuracy, number of T-units and number of ideas expressed. There was also an insignificant improvement in the areas of writing productivity, number of sentences written, and grammatical errors. The results of the current study suggest that the use of iPads has a positive influence on' writing. Therefore, the use of iPads may have long-term effects that cannot be measured sufficiently in a short-term study.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".