Incorporating Mobile-based Artificial Intelligence to English Pronunciation Learning in Tertiary-level Students: Developing Autonomous Learning

Abstract

EFL pronunciation learning is known to be teacher-centered, in which students are reliant on the feedback given by their teachers. Fortunately, the presence of technology-based learning tools is believed to be able to reduce students' dependency on teachers. A built-in Automatic Speech Recognition technology (ASR): ELSA Speak is a mobile-based application that could help students with pronunciation learning by providing prompt feedback and detailed evaluation of its users' pronunciation accuracy. The objective of this study was to examine the use of the mobile-based application, ELSA, in pronunciation learning and whether it could stimulate learners to become more autonomous. A mix-method approach was employed in this study. The quantitative data, in the forms of pre-test and post-test, was gathered through students' pronunciation recordings available in ELSA. This data was analyzed using the paired sample t-test. In addition, a Google Form questionnaire, in five-point Likert Scale, was used to support the quantitative findings. Meanwhile, a semi-structured interview with selected participants served as the qualitative one. These data were analyzed thematically based on the participants' responses. The result shows that incorporating mobile-based technology into English pronunciation learning could provide an opportunity for students to improve their pronunciation. Moreover, students could also broaden their repertoire of available practice strategies that might be useful to improve their autonomous learning ability.

Technology and Language: Improving Speaking Skills through Cybergogy-Based Learning

“…Speaking and presenting skills are one of the focuses of this research because preliminary research shows that students' speaking skills are low, especially during online learning. This is in line with several studies that show that students' speaking skills in online learning are low due to several factors such as: lack of learning motivation [41], limited speaking practices [42], lack of social interaction [43], anxiety factors and lack of self-confidence [44], and less supportive learning environments [45]. Therefore, learning scenarios through blended learning packaged in cybergogybased learning models through cognitive, social, and emotional domains are expected to improve students' speaking skills both in online and offline learning.…”

Exploring the Use of Artificial Intelligence in Promoting English Language Pronunciation Skills

“…The results of these tests were an answer to the first research question. A questionnaire was structured by the researcher based on the previous studies (e.g., Miladiyenti, Rozi, Haslina, & Marzuki, 2022;Silaen & Rangkuti, 2022), and Cronbach`s alpha was utilized to measure its reliability, which was 0.82, indicating a high reliability of the test results. The researcher administered it with the assistance of other teachers to collect quantitative information on participants' preferences, perceived effectiveness when using AI-based pronunciation tools, and other pertinent factors.…”

The Use of Artificial Intelligence to Promote Autonomous Pronunciation Learning: Segmental and Suprasegmental Features Perspective

“…It is suitable with the current developed technologies in education. Some studies had discovered that it was found useful to use digital technology as tools for promoting pronunciation learning autonomously (Banafa, 2008;Carlet & De Souza, 2018;Kruk, 2012;Sariani et al, 2022). When Banafa (2008) looked into pronunciation practice, she found that using computers was extremely beneficial since they offered a secure environment for learning.…”