Epistemic network analysis of novice and expert chemistry teachers’ multimodal questioning and feedback behaviours

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This study aims to explore the multimodal behaviour characteristics and differences between expert and novice secondary school chemistry teachers during classroom questioning and feedback. Using epistemic network analysis, this study offers deeper insights into the interconnections among different communication modes, beyond traditional methods like frequency counts. By analysing secondary school chemistry teachers in China, this study reveals significant differences in the multimodal questioning and feedback behaviour networks of expert and novice teachers. Expert teachers exhibit a denser and more interconnected network of multimodal behaviours, ask more high-cognitive-level authentic questions, and flexibly use various types of feedback. They effectively combine multiple modalities, such as language, gestures, facial expressions, and eye contact, enhancing student understanding and engagement. Additionally, expert teachers demonstrate greater flexibility in managing interpersonal distance, creating a supportive and inclusive learning environment. In contrast, novice teachers’ multimodal behaviour networks show fewer connections and lower integration, predominantly using low-cognitive-level focused questions with limited feedback types. They are less flexible in using language, gestures, facial expressions, and eye contact. Novice teachers are also more conservative in managing interpersonal distance, resulting in more distant communication with students. These findings provide valuable insights for teacher training and instructional strategy improvement.