Teachers’ Experiences with Literacy Instruction for Dual-Media Students who Use Print and Braille
Bibliographic record
Abstract
Introduction This study analyzed survey responses from 84 teachers of students with visual impairments who had provided literacy instruction to dual-media students who used both print and braille. Methods These teachers in the United States and Canada completed an online survey during spring 2015. Results The teachers reported that they introduced braille to their students at the mean age of 7.8 years. The three most common reasons reported for introducing a student to braille were the student's diagnosis, print reading speed, and print reading stamina. The amount of instructional time in braille literacy varied widely, and slightly more than 60% of the students were initially introduced to uncontracted braille. The teachers reported that approximately half of their students were at or above grade level with their print literacy skills, but only about 25% were at or above grade level with their braille literacy skills. Discussion Both contracted and uncontracted braille were used when beginning braille instruction for students reading both print and braille. The roles of student motivation and confidence appeared to be important considerations when designing and providing braille literacy instruction. Implications for practitioners There are many factors that should be considered when determining if a student should transition from print to braille as a primary literacy medium. Motivating students to want to learn and use braille is critical. A comprehensive curriculum is needed for use with established print readers at various reading levels who are making the transition to braille.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".