Evaluating the Effectiveness of Blended Learning and Technology-Enhanced Pronunciation Pedagogy: A Comprehensive Review with Student Feedback

Research output: Book Chapters | Papers in Conference ProceedingsConference (Extended Abstracts)peer-review

Abstract

This presentation explores the efficacy of blended-learning and technology-enhanced pedagogy in improving pronunciation in a tertiary education setting, focusing on student feedback from a case study conducted at Lingnan University. The study incorporated a 7-day pronunciation improvement plan using the digital platform VirtualVoiceLab.com as part of the blended-learning component in an elective language course in 2024-25. A total of 202 undergraduate students participated, with 150 completing a post-course survey to provide feedback. Results overwhelmingly indicated positive responses, with students reporting significant improvements in their pronunciation, fluency, and overall confidence in spoken English. The use of VirtualVoiceLab.com allowed for a flexible, interactive, and self-paced learning experience, completing in-class activities and fostering independent practice outside traditional classroom settings. The survey also highlighted students’ appreciation for the visualized sound charts and audio-visual materials provided by the platform. This study underscores the potential of integrating innovative technology into language pedagogy to enhance learning outcomes and student engagement. The findings contribute to the growing body of research supporting blended-learning approaches in Higher Education and provide practical insights for educators seeking to adopt technology-enhanced teaching methods. This presentation will discuss the detailed survey findings, pedagogical implications, and recommendations for optimizing blended-learning strategies in language education.
Original languageEnglish
Title of host publicationProceeding of the 3rd Global Conference on Innovations in Education
PublisherProudpen
ISBN (Electronic)9781914266843
Publication statusPublished - 17 Jun 2025

Keywords

  • Aging population
  • large-language models
  • older adults
  • sustainable solutions
  • dementia

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