Natural-Descriptive and Causal-Mechanistic Theories: A Complex Relationship Across Disciplines

• In Event: Integrating Issues of Knowledge and Interaction in Analyses of Cognition and Learning

Abstract

This paper analyzes cultural and methodological differences across research practices present in both, knowledge and interaction analysis. As opposed to the more traditional distinction between individual and sociocultural approaches, we foreground divergences in scientific orientations and theoretical visions whose poles are: 1) natural-descriptive, and 2) causal-mechanistic; we will refer to these two poles as "naturalism" and "hidden machineries". The paper will characterize these two orientations and their pervasive presence in the natural and social sciences. We will argue that: 1) naturalism and hidden machineries are both legitimate enterprises with their own traditions, methods, and diverse professional communities; 2) rather than a hierarchical (i.e. one being the "better" one) or developmental relationship (i.e. description comes first, explanation later), they are parallel strands of work that benefit from dialogue and cross-over insights; and 3) in order to enable dialogue it is crucial to acknowledge and grasp the cultural and historical roots of naturalism and hidden machineries perspectives.

Hidden machineries approaches postulate a domain underlying the phenomena of interest, such as social relations of production in Marxist history, mental structures in cognitive psychology, or generative rules in Chomskian linguistics. Their main goal is the identification of structures and processes in these underlying domains (i.e. the theory) with predictive and causal powers over the phenomena of interest. Naturalistic approaches, on the other hand, focus on the close examination of the phenomena of interest, noticing unexpected relationships and documenting previously unnoticed cases and circumstances. Naturalistic theories are instruments for focusing on phenomena that had previously remained unnoticed or without broad significance. The paper will examine the complex dynamics that unfolds between naturalism and hidden machineries in different disciplines, and, in particular, their presence in the research practices of knowledge and interaction analysis. The issue that we will highlight is not whether practitioners attend to either "knowledge" or "interaction", but the ways in which they examine both with naturalistic or hidden machinery orientations.

The paper will describe our work and our ongoing collaboration to study the role of the body in mathematical activity and learning (Hall & Nemirovsky, in press). Hall’s group focuses on conceptual change at different levels of analysis—multi-party talk, biography of the individual, social history of work groups—and how these are articulated (e.g., Hall, Wieckert & Wright, 2010). Nemirovsky’s group focuses on the nature of mathematical experience and how this can be extended with tool use (e.g., Nemirovsky, 2011). Because we characterize our research orientation as naturalistic, the paper will outline relationships with other strands of naturalism in the social sciences. Finally, we will describe conjectures about ways in which naturalistic work in the social sciences in general, and in interaction and knowledge analysis in particular, might sustain productive dialogues and crossover insights with researchers developing hidden machineries theories.

Authors

• Rogers P. Hall, Vanderbilt University

• Ricardo Nemirovsky, San Diego State University

• Jasmine Y. Ma, New York University

• Molly Kelton, San Diego State University