Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)

First Advisor

Stephen Gilliland


This research examined technology training (using computers as a specific instance of technology) in a framework that integrated concepts drawn from cognitive and social learning theory. Borrowing from cognitive learning theory, two types of knowledge were assessed: declarative knowledge (knowing what) and procedural knowledge (knowing how). Behavior modeling training, drawn from social learning theory, was used as the primary training methodology. It was proposed that the factors contributing to learning as a function of behavior modeling are the same factors that lead to procedural knowledge acquisition. I also examined the effects of two major attitudes toward computers in predicting computer knowledge and the role of training methodology in altering attitudes. Using 255 undergraduate subjects divided into four training conditions, the study explored the effects of modeling training and lecture training (in a crossed design) on declarative and procedural knowledge (measured using both a paper and pencil test and a performance test). Knowledge and computer attitude assessment occurred before and after training. I found declarative and procedural knowledge to be highly related to performance with the latter being significantly more so than the former. Analysis of the training methods indicated that modeling was an effective means of instructing individuals on computer use. Lecture training was not superior to practice alone in increasing trainee knowledge, but was effective in improving performance. Pertaining to attitudes, beliefs in the computer as a beneficial tool were increased in training conditions that received a lecture whereas beliefs in the computer as an autonomous entity were decreased in conditions that did not receive a lecture. Pre-test autonomous entity beliefs significantly predicted computer knowledge acquisition. This research suggests that modeling training does not require a lecture component to be effective as a means of training individuals on computers. Future research should replicate these findings and further explore the proposed relationship between cognitive and social learning theory in other domains aside from computers. The study also suggests implications for research on how computer attitudes effect learning, and on how training programs can alter trainee attitudes toward the machines.