Synchronous (Onsite) Technology / Online Learning / CALL / MALL Research Report/Paper (25 mins Onsite)
Exploring the Impact of AI-based Automated Pronunciation Evaluation Technology on Korean English Language Learners
MCALL Special Interest Group (SIG)
This study explored how automated pronunciation score feedback in a Computer-Assisted Pronunciation Training (CAPT) system impacted undergraduate L2 English learners’ pronunciation and motivation. The experiment involved the use of the CAPT system to provide multiple feedback (word-level, phoneme-level, and syllable-level) scores on the learner’s read-speech of English sentences, which contained phonemes Korean L2 English learners commonly make errors pronouncing. The learners practiced pronunciation with the CAPT system, and the effect of the score feedback was examined objectively and subjectively. In the objective analysis, pronunciation quality and motivation were measured using the score trend and the number of practices. In the subjective analysis, learners’ views on the system’s effectiveness for pronunciation and motivation were surveyed and analyzed. The results indicated that the CAPT system helped Korean L2 English learners improve their pronunciation and motivation.
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Reece Randall (M.Ed., TEFL) teaches at Gwangju Institute of Science and Technology (GIST) in South Korea. He has also served as a senior invited professor at Gangneung-Wonju National University and as a lecturer at Yonsei University. As an elected member of the Korea TESOL national council, he oversees KOTESOL Teacher Training (KTT), Special Interest Groups (SIGs), KOTESOL Job Board, and Gangwon chapter in his roles as second vice president, job board coordinator, and chapter president.
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I am a Team Leader of AI EduTech in MediaZen. My team has been developing AI-based automated evaluations of English learners’ speech and writings.