Identifying the Forms of Teacher-Student Dialogue That Are Productive for Student Learning

• In Event: Methodological Innovations for the Automated Analysis of Classroom Discourse

Abstract

Perspectives. Dialogic approaches involving building on others’ ideas, comparing and critiquing different perspectives have become increasingly of interest to researchers and educators after decades of research (Howe and Abedin, 2013; Resnick, Asterhan & Clarke, 2015; Song et al., 2019). Some studies investigated the impact of such approaches on student learning (Nystrand, 2006; Muhonen et al., 2018; O’Connor et al., 2015). Commonly, however, the forms of dialogue considered productive for learning are: confined to groupwork, variously emphasised by different researchers, rarely isolated from other interactional elements during dialogic interventions, or presumed rather than studied systematically, rigorously or at scale (AUTHOR, 2019).

Objectives. Practitioner professional development must be based on practices actually identified as effective. Our recent project related variation in classroom dialogue practices to learning outcomes for 1800 students aged 10-11 (ibid.). Our main objective in this follow-up study was to interrogate this unique, rich database to generate insights into specific classroom norms, teacher strategies and talk moves, and student responses and participation frameworks in classes that were more and less successful for learning. The work also addresses pertinent methodological issues; analyses span several granularity levels.

Methods originally included turn-level coding of teacher-student dialogue in 144 video-recorded lessons in 72 primary school classrooms, using an adapted version of the Scheme for Educational Dialogue Analysis developed by researchers in England and Mexico (AUTHOR, 2016). Lessons were also rated for levels of Student Participation: multiple students expressing ideas and actively engaging with others. Multilevel modeling – examining 27 potentially confounding influences – identified specific aspects of dialogue associated with literacy and mathematics attainment and positive attitudes to school.

Data sources for this subsequent study comprised 109 of the coded transcripts of English, mathematics and science lessons in state-funded schools across England, including some in socially deprived areas. Mixed methods analysis: To move beyond crude coding, we used concordance software alongside in-depth qualitative analysis to probe more deeply those characteristics of student-teacher interaction and participation associated with more and less successful outcomes.

Results. In the original study, three co-occurring aspects of dialogue strongly predicted learning outcomes (Fig. 1): 1) Inviting/providing Elaboration, building on/evaluating prior contributions; 2) Challenging/disagreeing with prior contributions – often underdeveloped; 3) Student Participation rating across the lesson. The subsequent analyses clarify how manifestation of these particular features in more successful classes goes beyond talk moves. Teachers create open tasks and open up space for students’ cognitive engagement and disagreement with others’ ideas, evaluating contrasting perspectives (Wegerif, 2007), drawing multiple students into collective knowledge building, and using objects of joint reference. They have a larger repertoire of constructive challenges.

Significance. Theoretical and practical contributions include increased understanding of relationships between forms of student participation that support curriculum learning, and how teachers can support these. Identifying and seeking to operationalize dialogue characteristics now demonstrably linked with student learning offers compelling implications for focusing automated coding and teacher development. We report briefly on recent trials in eight countries measuring impact on classroom practice and teacher thinking of a professional learning resource pack directly highlighting productive dialogue forms.

Authors

• Sara Hennessy, University of Cambridge

• Neil McKay Mercer, University of Cambridge

• Elisa Calcagni, University of Cambridge