Student satisfaction and service quality are interrelated constructs that are associated with improving student retention. This research investigated the relationships between these constructs in the context of an institution of higher education as an information system and sought to reduce the dimensionality of what have traditionally been considered orthogonal factors of these constructs in order to produce a parsimonious model and survey instrument that may be useful in assessing and predicting overall student satisfaction and overall service quality. The methods of analysis used in this study are quantitative in nature and included the use of descriptive univariate, bivariate, and multivariate analyses; exploratory factor analysis to examine latent dimensions within the data; and multiple linear regressions to measure the predictive efficacy of combinations of variables with respect to overall student satisfaction and overall service quality. It was hypothesized that the statistical treatment of the data would show that some dimensions routinely collapse, leading to possible valuable theoretical implications.

This study in the aerospace ground equipment (AGE) apprentice course at Sheppard Air Force Base, Texas, examined the use of mobile digital devices to determine which device leveraged the best results and was most compatible with military technical training requirements. The sample consisted of 160 students who attended the course between January and June, 2010. Three devices loaded with course materials were issued to the students, who used the devices in the classroom and were encouraged to use the devices to enhance their study time after class. Quantitative data were obtained by comparing block test scores to determine if any device produced a significant change in student learning. Qualitative data were collected from surveys administered to instructors and students to measure which device instructors and students found easiest to understand and use, and student satisfaction with the device. An analysis of variance (ANOVA) revealed a statistically significant difference (p < .05) in the block test mean scores between groups using mobile devices and the students in the control group that had no device. Post hoc comparisons on each block showed that there was a statistically significant difference between students using the smartphone and students using the other devices, but no …