Effectiveness of technology for braille literacy education for children: a systematic review
Bibliographic record
Abstract
PURPOSE: Despite the well-documented importance of braille for people who are blind or visually impaired, few studies explore technology for facilitating braille literacy education. Evaluations of the impact of using assistive devices on academics for children and youth who are blind or visually impaired are needed. This systematic review aimed to evaluate the effectiveness of technology used to support braille literacy education for children and youth. MATERIALS AND METHODS: The population of interest was defined as children and youth aged 0-21 years who were blind or visually impaired, learning literacy through braille as their primary medium, and had not previously learned to read through sighted methods. Sixteen academic education, health sciences, multidisciplinary, rehabilitation, and engineering databases were searched. RESULTS: Twelve peer-reviewed, English-language articles were included in the review evaluating a total of 176 participants. In general, the quality of research was low with little evidence to support the use of current technology for braille literacy education. CONCLUSIONS: Standards of technology evaluation for braille literacy must be developed. Furthermore, assistive technologies for braille literacy education for children and youth should provide real-time auditory and tactile feedback, enable independent study/practice and editing of work, and be easy to use, motivational, and engaging. IMPLICATIONS FOR REHABILITATIONStandards must be developed to ensure technology evaluation is consistent among researchers and clinicians to achieve the best outcomes.Technologies for braille literacy education for children and youth should provide real-time auditory and tactile feedback, enable independent study/practice and editing of work, and be easy to use, motivational, and engaging.
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 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 | 0.011 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".