Title page for ETD etd-07282006-195218

Type of Document

Master's Thesis

Author

Bhatkhande, Yogesh Dilip

Author's Email Address

yogeshdb@vt.edu

URN

etd-07282006-195218

Title

COMPARISON OF TRADITIONAL AND ACTIVITY THEORY BASED ANALYSIS METHODS FOR VERBAL PROTOCOL DATA

Degree

Master of Science

Department

Industrial and Systems Engineering

Advisory Committee

Advisor Name	Title
Dr. Tonya Smith-Jackson	Committee Chair
Dr. Brian Kleiner	Committee Member
Dr. Maury A Nussbaum	Committee Member

Keywords

Think Aloud Method
Critical Incidents
Activity Theory

Date of Defense

2006-05-22

Availability

unrestricted

Abstract

The think aloud method has been used in this research to generate data that
reveals the thoughts of participants of a study while they are performing tasks. The
pioneers of this method, Simon and Ericsson, have provided a method to analyze the
data so as to obtain meaningful results. However, this analysis method is complicated
and time consuming. Most researchers use some form of categorization to perform their
analysis. Critical incidents were used to categorize the data gathered in the tests
conducted as part of this research. This research proposed the use of tenets of Activity
Theory while performing data analysis so that the cultural and environmental aspects
that influence task performance are identified and addressed as part of the analysis. A
data analysis template was created that directs the analyst to follow activity theory while
performing the analysis. Sample data was gathered using the Think Aloud Method. The
results obtained after analyzing this data using the proposed Activity Theory Based
method were compared with those obtained when the same data was analyzed using a
representative traditional method of analysis. The research included positive critical
incidents, negative critical incidents and level of severity of negative critical incidents as
the dependent measures. No significant differences were found between the two
methods based on these dependent measures. Task type had a significant effect on the
number of positive and negative critical incidents identified.

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