Generational cohorts are groups of individuals sharing birth years, history, and a characteristics. The last Generation Y students are currently college and the Generation Z students are currently starting to stream into the tertiary level education. In a few years, the generation Z cohort will comprise the majority of the college and university students. Much research has been performed on matching learning styles to teaching styles, but not enough research has been done to match the learning preference to generational cohorts. Many instructors and educators believe that there are too many learning styles and factors to consider for each student, thereby deeming the classroom changes too difficult to institute.  The goal of this research is to find the most significant predictors of student learning for generation Y and generation Z students. This study determined that generational cohort and learning preference are associated with each other. Specifically, this paper sought to ascertain if there is a significant difference between the learning styles and perceived level of importance of factors affecting engineering student’s level of satisfaction when grouped according to their respective generational cohort – Generation Y and Generation Z. This study used Descriptive Method. The survey questionnaire is pilot tested and validated for deployment to engineering student respondents. Statistical treatment is applied and the results of the data analysis showed that there is significant difference on the learning style of Generation Y and Generation Z engineering students.  Results also showed that Generation Y engineering students see Teaching Method and Feedback and Learning Preferences as significant indicators of overall student satisfaction. On the other hand, Generation Z students find Teaching Method, Learning Environment and Feedback and Learning Preferences  From these significant findings, the study puts forward the I-E-M method—Integrate, Evolve and Modernize framework that engineering colleges could adapt to optimize engineering student’s satisfaction.