Many first-year university students preparing for TOEIC report they "know the words but cannot hear them," suggesting a gap between lexical knowledge and spoken-word recognition (Field, 2008). This presentation describes how technology can be used in the classroom to help learners connect pronunciation features to listening performance.

Each week, three classes of students (n = 90) follow a short cycle (10 minutes): (1) identify segments of TOEIC audio they find hard to hear, (2) label the likely phonological source (e.g., reduction, linking, flap /t/, weak forms), (3) practise shadowing with that feature, and (4) submit recordings of themselves reading sentences with these forms using the LMS. This approach builds upon previous uses of shadowing (Hamada, 2016) by leveraging ASR-based pronunciation tools integrated into LMSs, such as Microsoft Teams Reading Progress (Molenda & Grabarczyk, 2022).

Analytics tracked include submission frequency, feature tags selected, and pre/post listening checks. Preliminary findings suggest (a) listening breakdowns can often be attributed to specific sound changes, (b) micro-shadowing routines strengthen both confidence and anticipation of connected speech patterns, and (c) the cycle is feasible without reducing core TOEIC practice time. The session will also discuss how teachers can integrate these cycles into their own classes.