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Effective time management is associated with greater academic performance and lower levels of anxiety in students; however many students find it hard to find a balance between their studies and their day-to-day lives. This article examines the self-reported time management behaviors of undergraduate engineering students using the Time Management Behavior Scale. Correlation analysis, regression analysis, and model reduction are used to attempt to determine which aspects of time management the students practiced, which time management behaviors were more strongly associated with higher grades within the program, and whether or not those students who self-identified with specific time management behaviors achieved better grades in the program. It was found that students' perceived control of time was the factor that correlated significantly with cumulative grade point average. On average, it was found that time management behaviors were not significantly different across gender, age, entry qualification, and time already spent in the program.

In this paper we discuss perceptions of the benefits of learner-generated podcasts for supporting postgraduate engineering students in a mathematics-intensive course. The course under study had previously been highlighted as one in which students had struggled to attain knowledge that formed an essential underpinning to their degree programme. Podcasts were used as a means of concretising abstract mathematical knowledge so that students could access and share such concepts in a meaningful way. The experiences of three students (in a single cohort) were examined qualitatively at every stage of the exercise: introduction, pre-test, podcast creation, podcast peer evaluation, post-test, and focus-group session. The data suggest that this specific technique led to improvements in mathematical learning through the analysis of podcasts rather than through the creation of them.

In the Caribbean context, entry into university is primarily based on Caribbean Examinations Council (CXC) qualifications, and specifically the CXC Advanced Proficiency Examination (CAPE). The goal of this work is to examine the degree to which CAPE entry-grades predict both student final-graduating and in-programme course performance in a Caribbean engineering undergraduate programme. The data set included graduation, course and entry data for 140 students who graduated from the programme between 2014 and 2016. Students in the sample had grades in the four CAPE units associated with Pure Mathematics and Physics upon entry into the programme. The data set was analysed using crosscorrelation, linear regression, classification and logistic regression. We note that a significant correlation of 0.40 to 0.51 exists between the scores of the four CAPE units. However, the multiple linear regression models reflect the relatively low influence of two of the CAPE units on graduating and course GPA. Despite the poor fit of the regression models (i.e., R2 of 17% for graduating GPA and R2 of 7% for course GPA) we were able to demonstrate clear patterns in the success rates, based on entry bands (e.g., approximately 45% of top-scoring entrants graduate with First Class Honours degrees, whereas 12.5% of lower-scoring entrants achieved same). There was no inherent bias by gender or entry band in any of the models generated. The results suggest that the entry criteria serve as a means of predicting the probability of achieving success, rather than the actual success level. [ABSTRACT FROM AUTHOR]