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Developing More Accurate Competence Models for Improved E-learning for the Blind

Rakesh Babu


Motivation for this research is the belief that blind and visually impaired
(BVI) employees cannot develop job-related competencies due to
accessibility and usability problems in e-learning. A knowledge gap on the
nature of these problems impedes the development of accurate competence
models for BVI e-learners. This paper presents a novel CUT (cognitive, usercentered,
task-oriented) approach to accurately understand the nature of
accessibility and usability problems of the BVI in e-learning. It demonstrates
the utility of the CUT approach through an exploratory field study. Verbal
protocol analysis (VPA) provides in-depth examination of BVI participants’
thoughts and perceptions in completing e-learning activities. Qualitative
analysis of verbal reports reveals their mental models. Results explain
where, how and why problems arise in completing e-learning activities. It
generates cognitive models for effective completion of these e-learning
activities. Such cognitive models will inform future research to develop more
accurate competence models and lead to more accessible and usable elearning
applications for the BVI. Organizations can use these competence
models to develop e-learning strategies to harness the unique skills and
capabilities of their BVI employees as part of multi-faceted development of a
diverse human resource.

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