Macshapa: Software Support for Exploratory Sequential Data Analysis

Abstract

This paper outlines the need for better conceptual and methodological tools for performing observational data analysis in support of cognitive engineering research and practice and presents a tool, MacSHAPA, that has been designed to support such work. MacSHAPA is particularly suited for cognitive engineering studies of complex real-world decisionmaking. MacSHAPA lets users (1) enter or import data into a spreadsheet-like viewing medium, (2) annotate, manipulate, and visualize data in various ways, (3) carry out statistical analyses of various kinds, and (4) export data and results to other applications. MacSHAPA controls video devices, capturing timecode and inserting it into the database, and using timestamps in the database to locate events of interest on videotape. MacSHAPA's statistical routines include content and duration analysis, transition analysis (with some Markov statistics), lag sequential analysis, cycles reports, and some kinds of sequential pattern matching. The paper concludes with several examples of how MacSHAPA has been used to obtain useful results from observational data collected in laboratory and field settings.

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