Issues & Trends in Educational Technology

L2 Pronunciation Tools: The Unrealized Potential of Prominent Computer-assisted Language Learning Software (Bajorek, 2017)

The Unrealized Potential of Rosetta Stone, Duolingo, Babbel, and Mango Languages

(L2 = Second Language Learning) Publication has been Downloaded over 2k times. Cited over 13 times

Abstract

Hundreds of millions of language learners worldwide use and purchase language software that may not fully support their language development. This review of Rosetta Stone (Swad, 1992), Duolingo (Hacker, 2011), Babbel (Witte & Holl, 2016), and Mango Languages (Teshuba, 2016) examines the current state of second language (L2) pronunciation technology through the review of the pronunciation features of prominent computer-assisted language learning (CALL) software (Lotherington, 2016; McMeekin, 2014; Teixeira, 2014).

The objective of the review is:

1) to consider which L2 pronunciation tools are evidence-based and effective for student development (Celce-Murcia, Brinton, & Goodwin, 2010);

2) to make recommendations for which of the tools analyzed in this review is the best for L2 learners and instructors today; and

3) to conceptualize features of the ideal L2 pronunciation software.

This research is valuable to language learners, instructors, and institutions that are invested in effective contemporary software for L2 pronunciation development. This article considers the importance of L2 pronunciation, the evolution of the L2 pronunciation field in relation to the language classroom, contrasting viewpoints of theory and empirical evidence, the power of CALL software for language learners, and how targeted feedback of spoken production can support language learners.

Findings indicate that the software reviewed provide insufficient feedback to learners about their speech and, thus, have unrealized potential. Specific recommendations are provided for design elements in future software, including targeted feedback, explicit instructions, sophisticated integration of automatic speech recognition, and better scaffolding of language content.