An Insight Into the Relationship Between Confidence, Self-efficacy, Anxiety and Physiological Responses in a CS1 Exam-like Scenario

Computer Science typically has one of the highest attrition rates in tertiary level education. Many reasons have been put forward as to the cause, including, for example, no prior formal experience of programming, high workloads and poor mental health of students. Recent advancements in wearable technology have made it possible to accurately and easily measure aspects of physiological response associated with emotional arousal which can be indicative of stress, such as heart rate variability and skin conductance. A novel opportunity now exists to monitor learners in real-time and gain an insight on their physiological responses during a learning task. Such information, perhaps coupled with known factors that influence learning success, could provide new insight to allow educators to better tailor module design, delivery, and assessment. This paper builds on a study which concluded that there was no correlation between self-reported anxiety and Heart Rate and Electrodermal Activity. The goal of this paper is to investigate the relationship between measures such as self-reported anxiety, programming self-efficacy, confidence in responses and physiological responses during a controlled exam-like setting. An out-of-the-box psychological test was used to measure self-reported anxiety, a well-established questionnaire was used to measure self-efficacy and wearable sensors were used to measure physiological arousal, before and during the exam. Study design and methodology are described in detail in this paper. While no significant results were found, perhaps the most interesting finding is that students confidence in their answers weakly correlates with their physiological response when completing multiple choice programming questions. While the findings presented may not be major, they are novel and will provide direction for future research in the area

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

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