A number of metrics exist for quantifying the complexity of academic program curricula. Complexity in this case relates the extent to which the structure of a curriculum impacts a student's ability to progress through that curriculum towards graduation. The ability to quantify curricular complexity in this manner allows us to order programs according to their complexity, and to compare and contrast similar programs at different institutions according to these complexity measures. When sharing this type of information with faculty and program administrators, those at programs at the higher end of the complexity scale often speculate that high complexity implies a higher quality program. Which leads to the more general question, what does curricular complexity tell us about program quality? In cursory investigations of this conjecture, a surprising relationship emerged. Specifically, anecdotal review provided significant evidence to support the proposition that higher quality engineering programs have lower complexity curricula. It is worth noting that if this proposition is indeed true, then the contrapositive proposition, that higher complexity curricula imply lower quality programs also holds. In this study we collected a sufficient amount of data to determine the veracity of this proposition for undergraduate electrical engineering programs. The methodology employed in this study involved partitioning a large set of undergraduate electrical engineering curricula into three categories (top tier, mid tier and bottom tier) according to their quality. The curricular complexity variance within and between these groups was then analyzed using ANOVA methodologies. Because program quality is a subjective measure, we used the 2018 U.S. News & World Report Best Undergraduate Engineering Program rankings as a proxy for quality. The first group included schools in the top decile of this ranking, the medium group included schools from the fourth and fifth deciles, and the low group included those schools that were grouped together at the bottom of the list (approximately the bottom decile). The null hypothesis was that there are no significant differences between the intragroup and intergroup curricular complexity measures. This analysis found that with a low margin of error, and a 95% confidence interval, the null hypothesis should be rejected. Furthermore, the most significant difference was between the set of highly-ranked programs and the lowest-ranked programs, with a less pronounced difference between the medium- and lowest-ranked programs. It is generally the case that higher ranked schools admit better prepared students, and they have more resources available to support these students than do lower ranked schools. Thus, we expect the students at higher ranked schools to graduate at higher rates than those at lower ranked schools. The study reported in this paper shows that electrical engineering undergraduate students at higher ranked schools receive another student success advantage; namely, they encounter less complex curricula.
|Original language||English (US)|
|Journal||ASEE Annual Conference and Exposition, Conference Proceedings|
|State||Published - Jun 15 2019|
|Event||126th ASEE Annual Conference and Exposition: Charged Up for the Next 125 Years, ASEE 2019 - Tampa, United States|
Duration: Jun 15 2019 → Jun 19 2019
ASJC Scopus subject areas