Combining diagnostic testing and student mentorship to increase engagement and progression of first-year computer science students. (3rd September 2022) - Knight, G.; Powell, N.; Woods, G.
ABSTRACT: Computer Science (CS) degrees have some of the poorest continuation rates across HE. This study describes an intervention within a diverse CS student cohort to identify students who may be at risk of mathematical academic failure and the success of student mentor-led workshops in enhancing these students' mathematical ability. Diagnostic screening identified 46% ( N  = 92) of the cohort with low mathematical knowledge, with prior entry qualification being the only significant ( p  < 0.0001) reason for this gap. These identified students were invited to attend weekly mathematical workshops, with a positive correlation between attendance and attainment and females more likely to attend. The CS students were satisfied with having the mathematical workshops delivered by student mentors. In summary, this combined intervention of screening and mentor-led academic support successfully identified gaps within first-year students' mathematical knowledge, with the workshops addressing the diversity in mathematical understanding and helping reduce a prior qualification awarding gap.