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    Mental Health in Computer Science. An Investigation of How Mental Health Affects Learning Computer Science


    Nolan, Keith (2019) Mental Health in Computer Science. An Investigation of How Mental Health Affects Learning Computer Science. PhD thesis, National University of Ireland Maynooth.

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    Abstract

    The mental health of third level students is potentially at an all-time low. Reports such as the My World Survey, the My World Survey 2 and the Union of students of Ireland Report indicate that third level students in Ireland are suffering from mental health issues. For students, mental well-being is associated with effective learning, and their ability to navigate through university, coping with the challenges and stresses of student life. As such, this project attempted to investigate the effects that mental health factors such as stress and anxiety have on programming performance within a first-year Computer Science population. This project had four objectives. First, was to examine the relationship between student anxiety and CS1 programming performance. Second, was to examine the relationship between student stress and CS1 programming performance. Third, was to examine the relationship between student anxiety and stress. Finally, was a review the data obtained throughout the project, to identify analyse and identify gender differences. As an initial contribution of this project, a detailed systematic literature review on the role of anxiety in learning in Computer Science was carried out. No such review had previously been completed making this a timely addition to the field. As a second contribution, a novel study investigating the use of physiological sensors to investigate stress in an online MCQ examination with first-year Computer Science students was carried out. Findings suggest that there is a positive relationship between EDA and question difficulty. The third contribution was three studies on anxiety in Computer Science students, one containing a large sample (at least 65% of the CS1 cohort). Related to this was the novel finding that Computer Science students are more anxious. In addition was the investigation on programming self-efficacy and confidence in answers and their relationship to anxiety, arousal and performance. Evidence on the importance of programming self-efficacy was found to re-validate previous findings. The final contribution was a novel study on gender differences in stress, anxiety and self-efficacy. The findings presented are novel, providing telling insights into the role that different factors have on mental health when learning to program.

    Item Type: Thesis (PhD)
    Keywords: Mental Health; Computer Science; Investigation; Learning;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 13581
    Depositing User: IR eTheses
    Date Deposited: 16 Nov 2020 14:58
    URI:

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