Modelling Student Satisfaction Through IEM Method for Improved Learning Experience of Selected Generation Y and Z Engineering Students Generational cohorts are groups of individuals sharing birth years, history, and characteristics. This study determined that generational cohort and learning preference are associated with each other. Data showed that there is significant difference on the learning style of Generation Y and Generation Z engineering students. But there is no significant difference izn the preferences when respondents are grouped according to gender. 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 IEM methodIntegrate, Evolve and Modernize framework that engineering colleges could adapt to optimize engineering studentu0027s satisfaction.

Gender and Age Differences in the Study Plan of University Students Effective study plan is a predictor of good academic performance. However, there are few evidences available on the role of gender and age in the study plan for students. This paper investigated the role of gender and age in the adoption of study plan that can guarantee success. A questionnaire was designed and administered to undergraduate students of a world class privately funded university located in Ogun State, Nigeria. Simple random sampling was used and 294 students responded. Chisquare test of independence revealed that gender and age are not associated with frequency of study, study environment, study content preferences and study motivation. There is no Gender difference in the preference of study type, factors that drive, motivation for study and satisfaction with the study plan whereas, age is significantly associated. The logistic regression model was significant and correctly classified 66.3% of satisfaction with the study plan. Gender was not significant and age of students can predict their satisfaction with their study plan. Older students have more odds to be satisfied with their study plan. As students progressed from year one to the final year, they tend to adopt a study plan that can help them obtain high grades and graduate with good result. Artificial Neural Network correctly classified 71.4% of satisfaction using only age as the only factor because, only age contributed significantly to the logistic regression model. Timely academic advising or mentorship is advocated especially for freshers.