Date
Publisher
arXiv
As classroom cohorts expand, team teaching is increasingly used to integrate the expertise and pedagogical perspectives of multiple teachers. Yet, there is limited empirical understanding of how team teaching unfolds in practice, particularly regarding differences in teachers' contributions across experience levels, student cohorts, and learning task design. Prior research on team teaching has largely relied on retrospective self-reports or small-scale observations, offering limited insight into the micro-level processes through which team teaching is enacted. Teacher talk offers a scalable lens on these processes. While research in individual teaching contexts shows that acoustic features of speech (e.g., voice quality, intonation, and loudness) can shape student learning, evidence from team-teaching settings remains scarce. Moreover, capturing such features through manual observation or transcription is especially challenging in team-teaching classrooms, where multiple teachers speak across extended sessions and spatial locations, limiting scalability without automation. Grounded in spatial pedagogy theory and team-teaching research, this paper presents an AI-based speech processing approach to analyse classroom talk in team-teaching settings. We analysed 36 recorded undergraduate and postgraduate sessions involving 12 teachers. Spatial pedagogy behaviours were coded and acoustic features extracted to examine variation across teachers' experience, student cohorts, and the learning task design. The results reveal systematic differences, most notably in loudness dynamics: high-experience teachers, undergraduate classes and collaborative learning tasks exhibited greater loudness variation, suggesting more frequent modulation of volume to foreground key information and support classroom interaction and engagement.
Study at a glance
- Question: How do teachers' acoustic speech patterns vary by experience level, student cohort, and learning task design in team teaching?
- Setting and data: Undergraduate and postgraduate database course at Monash University, 12 teachers across 34 recorded two-hour team-taught sessions over four weeks.
- Method: Principal component analysis and non-parametric group comparisons (Mann–Whitney U-test with false discovery rate correction) of speech acoustic features across coded classroom behaviors.
Why it matters
Team teaching is expanding, but empirical understanding of how it unfolds in practice is limited. Prior research relied heavily on self-reports, leaving acoustic speech patterns across teacher experience, cohorts, and tasks largely unexplored.
Key findings
- High-experience teachers exhibited greater loudness dynamics and steeper loudness rising slopes, whereas low-experience teachers showed greater overall loudness and spectral variability.
- Teaching undergraduate students was associated with stronger loudness dynamics and greater loudness variability compared to teaching postgraduate students, who received more restrained vocal delivery.
- Collaborative learning tasks involved significantly higher loudness dynamics and spectral modulation from teachers than individual learning tasks across classroom behavioral categories.
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