This study explores the relationship between new entrants’ own measure of self-efficacy, their resilience to everyday challenges during first year, and their likelihood of completing and proceeding to second year. The study takes place in the School of Computing of a post-1992 HEI and is ongoing.

HESA figures for 2012-13 showed a UK-wide non-continuation rate for Computer Science of an average 9.5% amongst young entrants, regardless of entry qualifications. This is the lowest retention of 18 subjects measured by HESA, a situation which has persisted for some years. Amongst mature entrants, a non-continuation rate of 16.6% is almost 5% above the average for all subjects (Higher Education Statistics Agency, 2015).

The high dropout rate seems to indicate an inability amongst Computer Science students to recover from adversity, or low resilience during the key transition to HE and first year. A large body of research, including Allan, Mckenna, & Dominey (2014) and Johnson, Taasoobshirazi, Kestler, & Cordova (2015), indicates a positive correlation between resilience and academic achievement. However, the majority of resilience studies focus on minority and disadvantaged groups, schoolchildren or early adolescents, or characterise resilience as a response to extreme adversity.

This study proposes that inability to recover from extreme adverse situations does not adequately explain the high non-continuation rates amongst Computer Science students, and explores the possibility that a combination of relatively trivial, everyday situations and occurrences during the transitional first year can accumulate and be exacerbated by coincidence or timing; students cannot recover and either abandon their studies prematurely or fail to proceed to second year.

Key research questions are:

1) Is level of self-efficacy a useful predictor of first year students’ outcome and achievement?
2) Is a high level of self-efficacy a better indicator than entrance qualifications of persistence and continuation amongst students on Computer Science-related courses?
3) Are reasons associated with a low level of self-efficacy a factor in students exiting the course during the academic year, or failing to continue to second year?

In order to investigate these, a new 20-item domain-specific self-efficacy instrument has been developed, derived from “routine but troublesome events and situations that students might face during their first year of study” contributed by 12 Computing students at the end of their first year.

Following refinement, the self-efficacy instrument was administered to the cohort entering a range of Computing degrees in September 2015, and 150 usable responses received. The next phase of data gathering will take place in April 2016, when the instrument will be re-administered to the year group. The final phase will explore any relationships between self-efficacy scores and students’ academic achievement.

Findings will be used to inform institutional strategies to support Computing students during the transition into HE.

Our presentation will outline the development and administering of the instrument, and report initial findings from exploring relationships between students’ first and second self-efficacy results and their academic achievement at the end of first year. The researcher is seeking feedback, suggestions and collaboration from colleagues interested in FYE, resilience, and retention.
References

Allan, J. F., Mckenna, J., & Dominey, S. (2014). Degrees of resilience: Profiling psychological resilience and prospective academic achievement in university inductees. British Journal of Guidance & Counselling, 42(1), 9-25.
J
ohnson, M., Taasoobshirazi, G., Kestler, J., & Cordova, J. (2015). Models and messengers of resilience: a theoretical model of college students’ resilience, regulatory strategy use, and academic achievement. Educational Psychology: An International Journal of Experimental Educational Psychology, 35(7), 869-885.