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Data from an early stage of development of conversational agent based support for collaborative learning provides an ideal resource for demonstrating the value of sociolinguistic style analysis paired with time series visualizations as part of an iterative design process. The methodology illustrated in this chapter was introduced in earlier publications focusing separately on the sociolinguistic style analysis (Howley and Rose, Modeling the rhetoric of human-computer interaction. In: HCII’11 Proceedings of the 14th international conference on Human-computer interaction: interaction techniques and environments, pp 341–350, Springer-Verlag, Berlin, Heidelberg, 2011; Howley et al., A multivocal process analysis of social positioning in study groups. In: Suthers et al. (eds). Productive multivocality in the analysis of group interactions, Springer, 2013) and the time series visualization using the Tatiana tool (Dyke et al., Challenging assumptions: using sliding window visualizations to reveal time-based irregularities in CSCL processes. In: Proceedings of the international conference of the learning sciences. Sydney, Australia, 2012). However this chapter is unique in its application to data that is at such an early stage in a development process. The data is admittedly raw, and contains many examples of interaction gone awry. Nevertheless, the value in this analysis is in a demonstration of what insights can be gained through detailed stylistic analysis of conversational behavior that informs the next steps of intervention development.

Our analyses illustrate nine instances of what we call multimodal and multimedial reformulations of content beginning either with drawings of physics experiments and going to the manipulation of the physics experiments themselves or beginning with the experiments and going to the drawings. We postulated that each time one of these reformulations occurred, it was a potential (yet rare) pivotal moment for conceptual change because content was being transformed across modes and media. Within the nine instances of reformulation, we found two types of pivotal moments (three instances in all). The first type was changing one’s conception from an intuitive everyday view on physics to a canonical view of physics. The second was maintaining a canonical view of physics but while also integrating more complexity in terms of experiments constructed, drawings made, or concepts talked about. In addition, the notion of the semantic bundle enabled us to show how the ongoing interaction supplied building blocks that illustrated either sustained conceptual change coherent with canonical physics or difficulties that students faced.

This chapter describes and reflects upon the analytic representations used in the analyses presented in this book, and the roles they played in multivocal analysis. As shown in other chapters, multivocality across analyses based on shared datasets can be productive in a variety of ways and for a variety of reasons. From a pragmatic perspective this productivity is also dependent on the ability of analysts to share datasets, perform analyses, inscribe new analytic knowledge into representations and use these representations as a basis for discussion. In this chapter, we examine how representations are used and given meaning in analysis. We catalogue the types of entities and attributes inscribed in representations, the notational systems by which they are encoded, and the kinds of moves that result in the creation of new representations. We then discuss the opportunities for multivocality afforded by the representations present in the different data sections, and discuss the properties desirable in a framework for coordinating analytic representations. We describe instances of representation-based productive multivocality found in this volume, presenting nine strategies for researchers seeking to engage in productive multivocality. This chapter will be of interest to tool designers, but also provide guidance to researchers in reflectively choosing representations (and their affordances for interpretation and manipulation) so as to maximize their ability to engage in productive multivocality.