The medium is the measure of itself: Using tracking data for deductive and inductive analysis of the users of an interactive experience and their behavior

Date of Award


Degree Type


Degree Name

Doctor of Philosophy (PhD)


Mass Communications


Joan Deppa


Tracking data, Users, Interactive experience

Subject Categories

Communication | Mass Communication | Social and Behavioral Sciences


The dissertation follows a deductive and an inductive approach to understand the connection between memory and the enjoyment of a story that takes advantage of the attributes of digital media. Specifically, what is the impact of memory structures created by media use in the ability to free cognitive resources to enjoy hypermedia fiction. Through the use of data gathered by a tracking device embedded in the programming of a virtual experience, and an electronic questionnaire, the dissertation seeks to establish a causal relationship between memory and the behavior exhibited while experiencing the story.

For the deductive approach, theoretical constructs and theoretical linkages for the formation of the hypotheses derived from schema theory, cognitive flexibility theory, research on disorientation and cognitive overload while using computers, and flow theory. The dissertation employed a controlled exposure experimental design with a total of 435 Ss. Data shows a statistically significant negative correlation between reading and the amount of interactive behavior in the hypermedia story. To the contrary, some electronic media use have a statistically significant positive correlation with amount of interactive behavior. Electronic media use has a statistically significant positive correlation with how much the subjects felt in control of the medium while experiencing the non-linear story. Data also shows a strong correlation (r = .568, p < .001) between feeling in control and level of enjoyment. The dissertation concludes that certain media use has a combined multivariate effect on the experiencing of the hypermedia story.

The inductive approach includes a time series analysis of the data collected. The dissertation presents a mathematical model (y = a/bX + c) explaining user behavior while interacting with QTVR panoramas, a prominent form of content in the experience. The dissertation suggests a more robust methodological approach using current computer-based statistical tools to assign causation to a broader set of factors. The author also concludes that not only theoretical and statistical knowledge but also proficiency in multimedia and programming are fundamental requirements for in-depth research in digital media.

The experience is an original non-linear story written and produced by the author.


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