Retention in Second Year Computing Students in a London-Based University During the Post-COVID-19 Era Using Learned Optimism as a Lens: A Statistical Analysis in R

Abstract

The aim of the current research project is to investigate the low retention rate in second-year undergraduate computing students at a London-based university. The research is conducted in 2022 during the post-COVID-19 era using learned optimism as a lens and compares to the 2021 study Chrysikos et al. [1]. The main aim is to support the university’s efforts to improve retention rate as the overall dropout has been increasing in the last few years. The research methodology employed was an exploratory investigation approach by using statistical modelling analysis in R to predict behavioural patterns. The study aimed to discover any effect the CODE-It initiative had on student grades and optimism scores, to quantify its success as an initiative. The primary outcome of the data analysis indicates that the CODE-It initiative had a positive impact on student optimism scores, particularly among black ethnicity students. Additionally, a slight increase in optimism was observed among the least optimistic students. The return to in-person interaction with classmates and lecturers may have played a significant role in raising the minimum scores compared to the 2021 study [1]. Nevertheless, many students continue to grapple with the lasting effects of the post-pandemic era, particularly in matters of financial hardship.  Finally, for those students who did attend CODE-It, 85% showed that they felt it was a worthwhile exercise. Specifically, black ethnicity students had a higher proportion of attendance and were no longer the student ethnicity group with the lowest optimism score.