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

Chrysikos, Alexandros and Bamford, Neal (2024) 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. In: ICDAM2023, 23-24 June 2023, London Metropolitan University - London, UK.

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Abstract / Description

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 during the post-Covid-19 era using learned optimism as a lens. 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 main outcome of the data analysis is that the CODE-It initiative positively affected student optimism score, especially black ethnicity students. Furthermore, a slight increase in the least optimistic students was observed. Returning to in person interaction with classmates and lecturers could be a major factor in reducing the minimum score compared to the previous year’s study (2021). However, there is still a very real post pandemic effect being experienced by many students, especially around matters of hardship and finance. 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.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Learned Optimism, Student Retention, Computing, R Programming, Quantitative Research, Data Analysis
Subjects: 000 Computer science, information & general works
300 Social sciences > 370 Education
Department: School of Computing and Digital Media
Depositing User: Alexandros Chrysikos
Date Deposited: 16 Jun 2023 08:36
Last Modified: 23 Jan 2024 12:23
URI: https://repository.londonmet.ac.uk/id/eprint/8591

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