Microcoordination is an overarching term that we use to describe a program of research that focuses on describing phenomena and exploring designs associated with mediated human coordination in the small. As a program of research, microcoordination derives from interaction analysis with its rich historical roots in ethology, sociology, conversation analysis and so forth. But it is also influenced by experimental psycholinguistics (c.f. Herb Clark, David McNeil) and the kinds of interests and values that designers (should) bring to the design of computing technologies.

We argue that there are a number of important contexts of use that both important and really hard to study if we just confine ourselves to natural occurrences. Other qualitative researchers have also done this! David McNeill is one model (1992, 2005). Another is Rick Shweder (c.f. 1991).

We examine “use practices” in the context of solving interactional problems with and without technology. By “use practices” we mean the ways that people go about using the resources available to them to solve interactional problems, like whether to say anything, how much to say and when to say it.

Microcoordination investigations emerge from a set of concerns that are mentioned in summarized in the short piece “Reflecting our Better Nature” which appears in ACM Interactions in the May/June 2014 issue.

One concern is that our current computing systems too often put us in powerless, passive roles as actors in the world. They are not unique in this! But the more we work with them, the more dire the possible consequences become.

Another concern is that we are not noticing the effects of our designs because we rely on descriptive phenomenology of everyday life and experience while the technology changes their underpinnings.

This program of research is kind of complex because it takes unusual approaches to several different aspects of investigation: the constituents and nature of validity in investigating the relationship between people and machines, the value of particular kinds of outcomes for knowledge in Human-Computer Interaction, and the relationship between design and knowledge.

We make life difficult for ourselves through three important but controversial positions:

  1. We study situations that are naturally occurring in the world, but that do not arise with enough frequency to be a focus of investigation. This is an unusual technique, but not unheard of.
  2. We emphasize phenomenological capture rather than experimental control.
  3. We study process as well as outcomes. Indeed, we study process more than outcomes.

This material is based upon work supported by the National Science Foundation under Grant No. IIS-1018607.  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.


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