Title :
Enhancing Mobile Learning Using Speech Recognition Technologies: A Case Study
Author :
Motiwalla, L.F. ; Jialun Qin
Author_Institution :
Univ. of Massachusetts, Lowell
Abstract :
While many studies have demonstrated the value of mobile learning (m-learning) applications in educational environments, the limitations of mobile devices may impair the accessibility of such applications. In this study, we explore the integration of speech or voice recognition technologies into m- learning applications to reduce access barriers. Based on an m-learning framework proposed in our previous work, we built an educational online forum accessible through mobile devices. We then developed customized interactive voice response (IVR) and text-to-speech (TTS) technologies to allow users to interact with the forum through voice commands. This voice-enabled discussion forum application not only helps normal users avoid the cumbersome task of typing using small keypads, but also enables people with visual and mobility disabilities to engage in online educations. The prototype forum was tested in two different blind institutions in Massachusetts with 10 users. The results from this study provide insights into how to improve accessibility of m-learning and other related m- commerce applications.
Keywords :
computer aided instruction; distance learning; handicapped aids; speech recognition; speech synthesis; educational online forum; interactive voice response; mobile learning; mobility disability; online education; speech recognition; technology; text-to-speech; visual disability; voice recognition; Application software; Educational institutions; Educational technology; Electronic learning; Environmental management; Mobile computing; Prototypes; Speech recognition; Speech synthesis; Technology management;
Conference_Titel :
Management of eBusiness, 2007. WCMeB 2007. Eighth World Congress on the
Conference_Location :
Toronto, Ont.
Print_ISBN :
0-7695-2820-1
Electronic_ISBN :
0-7695-2820-1
DOI :
10.1109/WCMEB.2007.46