A Voice-Enabled Framework for Recommender and Adaptation Systems in E-Learning
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IGI-Global
Abstract
Description
With the proliferation of learning resources on the Web, finding suitable content (using telephone) has
become a rigorous task for voice-based online learners to achieve better performance. The problem
with Finding Content Suitability (FCS) with voice E-Learning applications is more complex when the
sight-impaired learner is involved. Existing voice-enabled applications in the domain of E-Learning
lack the attributes of adaptive and reusable learning objects to be able to address the FCS problem.
This study provides a Voice-enabled Framework for Recommender and Adaptation (VeFRA) Systems in
E-learning and an implementation of a system based on the framework with dual user interfaces – voice
and Web. A usability study was carried out in a visually impaired and non-visually impaired school
using the International Standard Organization’s (ISO) 9241-11 specification to determine the level
of effectiveness, efficiency and user satisfaction. The result of the usability evaluation reveals that the
prototype application developed for the school has “Good Usability” rating of 4.13 out of 5 scale. This
shows that the application will not only complement existing mobile and Web-based learning systems,
but will be of immense benefit to users, based on the system’s capacity for taking autonomous decisions
that are capable of adapting to the needs of both visually impaired and non-visually impaired learners.
Keywords
QA75 Electronic computers. Computer science