MétaCan
Menu
Back to cohort
Record W4303488374 · doi:10.1177/01626434221131775

Speed and Accuracy Measures of School-Age Readers With Visual Impairments Using a Refreshable Braille Display

2022· article· en· W4303488374 on OpenAlexaff
Tessa McCarthy, Cay Holbrook, Cheryl Kamei-Hannan, Frances Mary D’Andrea

Bibliographic record

VenueJournal of Special Education Technology · 2022
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsUniversity of British Columbia
FundersOffice of Special Education Programs, Office of Special Education and Rehabilitative Services
KeywordsBrailleReading (process)Words per minuteReading ratePsychologyAudiologyComputer scienceReading comprehensionMedicine

Abstract

fetched live from OpenAlex

This study provides information on the use of a refreshable braille display in relation to reading speeds and accuracy for students with visual impairments. The characteristics and variables which were statistically significant predictors of reading speed were explored. Forty-nine students in grades 1–9 participated with their teachers of students with visual impairments. In this 16-week study participants used the Reading Adventure Time! app to complete a pretest, intervention, and eight progress monitoring checks. Using descriptive statistics, correlation, and multiple regression analyses the researchers found silent reading speeds averaged 16.80 WPM at grades 1–2, 46.43 WPM at grades 3–4, 46.12 WPM at grades 5–6, and 50.51 WPM at grades 7–9. Oral reading speeds averaged 18.37 WPM at grades 1–2, 49.05 WPM at grades 3–4, 45.62 WPM at grades 5–6, and 45.82 WPM at grades 7–9. On average, there were few miscues for participants at all grade levels. Statistically significant predictors of reading speed included the number of braille cells on the refreshable braille display, the proportion of students receiving free and reduced lunch recipients, time spent in literacy instruction with the general education teacher, and whether the student was a dual braille and print reader. Reading speeds were comparable to those found in studies which examined reading paper-based formats. The most common statistically significant predictor of reading speed was the number of cells on the refreshable braille display. Wise decisions about the types of refreshable displays used can potentially make a difference in students’ reading speeds.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.251
Threshold uncertainty score0.394

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.054
GPT teacher head0.348
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Special Education TechnologySame topicTactile and Sensory InteractionsFrench-language works237,207