Integrative Analysis of Trajectories of Literate Activity and Literate Becoming in Four Data Sets

• In Event: 34.093 - Moving Data Across Methods of Analysis: Collaborative Research on the Complexities of Literacy Activity

Abstract

When undertaking longitudinal and mobile research on literate activity and becoming, data can quickly become complex (cf. Compton-Lilly, 2017; Nordquist, 2017). Tracing a single writer's text might involve multiple drafts, written responses captured on drafts (or as separate documents), audio- or video-recordings of conversations or activities related to the text (often across multiple settings), other texts by other writers that display some salient similarity, uptakes by readers, elicited research artifacts (e.g., process drawings, network representations), and multiple interviews. Reducing or coding the data is a common methodological strategy to deal with complexity, to generate and test interpretations, and to present tellable stories of findings (e.g., Miles, Huberman, & Saldana, 2014). In this paper, I argue for an alternative: integrative analysis, which involves laying out the data in some common frame, manipulating and marking it up to enhance visibility and connectivity, and deploying it as documented narratives in reports.

Theoretically, integrative analysis is informed by cultural-historical activity theory's focus on tracing the genesis of practices, people, and tools (e.g., Fleer, Gonzalez Rey, & Veresov, 2017; Lave & Wenger, 1991; Vygotsky, 1987; Wertsch, 1991); by actor-network theory's focus on following the actors and tracing associations (e.g., Latour 1998, 2005); and by dialogic semiotics's focus on the heterochronicity and heterogeneity of communicative practices (e.g., Agha, 2007; Irvine, 1996; Voloshinov, 1973).

Methodologically, integrative analysis involves methods of data visualization, juxtaposition, accumulation, and tracing/mapping connections (Stornaiuolo, Smith, & Phillips, 2017). It aims to bring data together to trace historical trajectories of activity and becoming rather than to code data for synchronic categories. Its goal is a documented (evidence-grounded) narrative of the multi-stranded trajectories of distributed action (del Rio & Alvarez, 2008; Hutchins, 1995).

The dataset that I bring to this symposium is a lifespan study of my daughter becoming a biologist. Like other within-family research on literacy, language and semiotic development (e.g., Bissex, 1985; Kress, 1997; Miller & Hengst, 1998; Scollon & Scollon, 1981), the sustained, everyday character of family life affords collection of data across expansive temporal and spatial scales. Based on life-history, semi-structured, and text-based interviews; participant observation; a collection of texts that reach back to her elementary school years; and memory, the dataset traces trajectories across her lifespan. For example, I will present an Integrative analysis that follows a process network drawing that features a conversation in the car to a history of conversations in cars reaching back 27 years, to an investigation of neighborhood cardinals in a childhood animal club, and to publication of the article represented in the drawing. After illustrating integrative analysis of this tracing, I will briefly illustrate similar analyses of the other three symposium datasets and note how the other presenters have identified different dimensions of my data.

I conclude by considering how integrative analysis addresses the challenges of longitudinal and mobile datasets on literate activity and how this experiment in collaborative analysis (with theoretical, methodological, and researcher triangulation) offers potential resources to enrich both the complexity and grounding of such analyses.

Author

• Paul A. Prior, University of Illinois