EXPLORING THE INTEGRATION OF SPEECH RECOGNITION TECHNOLOGIES TO SUPPORT INCLUSIVE E-LEARNING FOR MULTILINGUAL NIGERIAN DISTANCE LEARNERS WITH DISABILITIES

Abstract

The rapid expansion of digital learning environments has transformed higher education by
enhancing instructional delivery, expanding educational access, and promoting learner
participation. In Nigeria, the increasing adoption of distance education has created opportunities
to extend higher education to geographically dispersed and underserved populations. Despite
these advancements, multilingual learners with disabilities continue to encounter significant
barriers related to communication, language diversity, accessibility, and equitable participation
in online learning environments. Speech recognition technologies have emerged as promising
assistive tools capable of supporting inclusive e-learning through speech-to-text transcription,
real-time captioning, and voice-enabled interaction.
This paper explores the integration of speech recognition technologies to support inclusive elearning for multilingual Nigerian distance learners with disabilities. The study adopts an
integrative literature review approach, drawing on contemporary scholarly literature, policy
documents, and empirical studies on speech recognition technologies, assistive technologies,
inclusive education, multilingual learning, and distance education. While speech recognition
technologies have considerable potential to improve accessibility, learner engagement,
communication, and participation, their successful implementation is influenced by several
interrelated factors, including recognition accuracy, multilingual capability, digital
infrastructure, institutional readiness, inclusive pedagogical practices, and supportive policy
frameworks.