Includes bibliographical references and index.

This dataset offers a tool and guidelines for systematically analysing 'dialogue' in classrooms across a wide range of educational settings. A team of researchers from the University of Cambridge, UK and UNAM (National Autonomous University), Mexico has developed a coding scheme that distils out -- from key literature in the field -- and embeds the common qualities of educational dialogue that are considered productive for learning. These qualities focus on exploring difference in perspectives (e.g. Bakhtin, 1981). They include teachers and students tuning in to others' perspectives, making reasoning explicit, and building knowledge together through sharing, critiquing and coordinating contrasting ideas. The openly licensed Cam-UNAM Scheme for Educational Dialogue Analysis (SEDA) contains 33 categories for analysing contributions to dialogue in depth. The dataset is provided by Dr Sara Hennessy from the University of Cambridge and illustrates how the framework can be applied using video recordings and transcripts. It highlights some issues arising -- including reliability (consistency between different coders' judgements) and moving beyond turn-by-turn coding to interpret whole dialogic sequences. It offers practical pointers for those wanting to use or adapt the scheme to address research questions around how 'dialogic' interaction in a particular setting seems to be, i.e. how much dialogue is of the productive kind described above. The dataset will be of most interest to those using video or audio recordings in their research and wanting to analyse 'natural' dialogue.

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