Crowdsourcing for Second Language Learning
Open Access
Article
Conference Proceedings
Authors: Abdelrahman Abounegm, Nursultan Askarbekuly, Magomed Magomedov, Manuel Mazzara
Abstract: This work implements language acquisition and crowdsourcing techniques in a unique combination to aid with second language learning. It allows users to contribute linguistic assets, while other users vote on the quality of the assets. The system’s goal is to provide a social platform for learning and contributing to underrepresented languages. The authors establish quality attributes for the system, namely: usability, scalability, security, and portability. The resulting system is tested against these quality attributes using quality scenarios and usability testing. The implemented system is shown to possess the quality of security, scalability, and portability. Usability testing highlights the importance of user interface for crowdsourcing systems and shows possible interface improvements.
Keywords: Empirical Software Engineering, Crowdsourcing, Language Learning
DOI: 10.54941/ahfe1003773
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