REHABILITEES WITH VISUAL IMPAIRMENTS’ CANE SKILLS AND THEIR INFLUENCE ON INDEPENDENT TRAVEL IN NAIROBI CITY COUNTY, KENYA
Bibliographic record
Abstract
The purpose of this study was to determine the influence of rehabilitees with visual impairment cane skills on their independent travel. The study was based on Bandura’s social cognitive learning theory. The researcher used a case study research design. The study was carried out at Kenya Institute for the Blind located in Nairobi County, Kenya. The target population was two orientation and mobility trainers and fifty rehabilitees with visual impairment who lost sight between the years 2011 and 2016 and who underwent rehabilitation at KIB. A purposive sampling technique was used to select KIB for the study. Snowball sampling technique was used to locate thirty-seven rehabilitees with visual impairment. Data was collected using questionnaires. The pilot study was conducted at Machakos Technical Institute for the Blind because of its similar characteristics in the admission of rehabilitees with visual impairment. The researcher ensured the content validity of the research instruments through discussion with supervisors and lecturers in the Department of early childhood and Special Needs Education. Quantitative data was gathered using questionnaires and processed using Statistical Package for Social Sciences (SPSS) program. Data was analysed using descriptive statistics and presented using tables. The findings revealed that mobility canes were the main device used at Kenya Institute for the Blind for orientation and mobility. Worldwide, canes were the most used device for orientation and mobility for individuals with visual impairment. In KIB, the device was limited in supply and not readily available. Cane skills were the most popular orientation and mobility techniques among rehabilitees in KIB. The study concluded that rehabilitees were not adequately trained since a substantial period of time has elapsed yet they have not indicated favourable independent travel to their places of work. Orientation and mobility training at KIB led to the acquisition of necessary skills relevant to independent travel of individuals with visual impairment. The study recommended that there is a need for Kenya Government to facilitate the production of cheap locally made long canes suitable for our Kenyan roads. Article visualizations:
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".