AN ICT-SUPPORTED PRONUNCIATION TRAINING COURSE FOR PRE-SERVICE ENGLISH TEACHERS IN JAPAN
, K. Oga2
1Waseda University (JAPAN)
2Hokkaido University of Education (JAPAN)
This study investigated the effectiveness of pronunciation software used in a phonetics and phonology course at a Japanese university, and we suggest that ICT-supported learning can improve the quality of teacher-training courses in pronunciation.
English teachers should develop the communication abilities of their students, which includes improving pronunciation skills. However, many teachers hesitate to teach pronunciation due to their own lack of skills and confidence in that area (Shibata et al., 2008; Orii, 2015).
In their survey, Kouchiyama et al. (2011) demonstrated that 56% of junior high school teachers reported not receiving enough pronunciation training as pre-service teachers. This is because typically phonology courses at Japanese universities are conducted in large classrooms, and focus on language theory rather than practice. Arimoto and Kouchiyama (2016) emphasize that teacher-training courses should be revised to improve the pronunciation skills of pre-service teachers.
ICT-supported learning has emerged as a way of administering teacher-training courses in pronunciation (Arimoto, 2016; Orii, 2015). In 2017, we designed and developed pronunciation training software (using Prontest©) to practice vowels, consonants, rhythm, and sound changes.
In the spring of 2018, we conducted a semester-long experimental class (15 sessions x 90 minutes) with 37 students. During the first half of the semester, students were given lectures on the basics of articulatory phonetics and how English consonants are produced. Students also viewed several online lectures on producing vowels. In the latter half of the semester, students used the software during six sessions. The students received feedback from the software, and the lecturer provided individual advice when the participants struggled.
A pronunciation assessment test (part of the software) was conducted before and after the training. A significant difference was observed between the word section (i.e., vowels and consonants) and the sentence section (i.e., rhythm and sound changes). Results show that software training contributed to the improvement of students’ pronunciation.
Furthermore, an end-of-semester student evaluation revealed a high satisfaction rate for using the software. For example, 36 students (99%) reported that they felt pronunciation training using software was effective. In addition, 31 students (86%) reported that comments from the software were effective for improving their pronunciation. After using the software for two months, 31 (86%) of the students showed continued interest in using it to further improve their pronunciation.
The results demonstrate that pronunciation training software is beneficial for pre-service teachers and can be an efficient and practical way of conducting teacher-training courses in pronunciation. To further evaluate the effectiveness of the software, we need to collect more data. We are currently collecting data from two groups (an experimental group with software use, and a control group conducted without using the software) and intend to compare results. We also need to include a delayed posttest to examine whether the improvement can be sustained.