Effect of Self-efficacy and Emotional Engagement on Introductory Programming Students

Today organisations both in the private and public sectors rely on Information Technology (IT) solutions and continue to make significant investments enabling business via IT. The increase in investment in IT is due to the demand for more efficient and cost-effective delivery of products and services. The dependency on IT and the increased level of investment in IT have both motivated a wider accountability focus on strategic technology initiatives, and a complex mix of political, organisational, technical and cultural shifts requiring far-sighted management and governance of IT. Throughout the last decade, systems, processes, standards and best practice frameworks have been developed to facilitate effective IT governance. However, a large number of IT initiatives fail to deliver. Getting value from technology deployment via effective IT governance remains a key concern of management. This paper presents the outcome of the analysis of four IT deployment cases studies. The analysis of the four case studies demonstrated a strong connection between project failures and inadequate governance practices

Self-Efficacy and Engagement as Predictors of Student Programming Performance

Programming is a core subject introduced in the first year of an Undergraduate Computer Science programme. Since programming is a core subject, it is a major concern that high attrition and failure rates continue to be reported in such courses. Evidence from the literature suggests that programming is cognitively demanding, and the solutions proposed have had minimal impact on students in introductory programming courses. However, in the literature on learning theory, there is evidence suggesting that the self-efficacy beliefs of students affect their engagement, and that their engagement affects their performance. In the literature on introductory programming courses, there is a lack of research examining the effect of self-efficacy on engagement, and the effect of engagement on the programming performance of students. This leaves a gap in programming research that this research seeks to fill. Based on student engagement frameworks in the literature on learning theory, a conceptual model was developed. To operationalise and validate the conceptual model within the context of learning programming, a study consisting of focus group interviews and a survey on students in introductory programming courses is proposed. The results of the survey will be analysed using structural equation modelling (SEM) techniques

Self-efficacy and engagement as predictors of student programming performance: An international perspective

High attrition and failure rates are a common phenomenon in introductory programming courses and are a major concern since course instructors are not able to successfully teach novice programmers the fundamental concepts of computer programming and equip them with skills to code solutions to programming problems. Existing solutions that attempt to minimise the high failure and attrition rates have had little impact on improving the performance of the novice programmers. However, the behaviour of the novice programmer has received little attention from introductory programming course instructors although the literature on learning theory suggests that self-efficacy and engagement are two behavioural factors that affect a student’s performance. This study fills the gap in existing research by examining the effect of programming self-efficacy on the engagement of novice programmers, and the effect of their engagement on their programming performance. A research model that proposes a link between programming self-efficacy and the indicators of engagement that are specific to the context of introductory programming courses, and a link between the indicators of engagement to the programming performance of the novice programmer was developed. A three-phased mixed methods approach which consists of two survey questionnaires and focus groups was used to validate the research model. Data was collected in New Zealand and in Malaysia with 433 novice programmers participating in the survey questionnaires while 4 focus groups were held to refine and validate the indicators of engagement in introductory programming courses. The findings of the focus groups confirmed that participation, help-seeking, persistence, effort, deep learning, surface learning, trial and error, interest, and enjoyment were indicators of engagement while gratification emerged as a new indicator of engagement in introductory programming courses. The data from the survey questionnaires were analysed using Partial Least Squares Structural Equation Modeling (PLS-SEM). This study found that the programming self-efficacy beliefs of novice programmers had a strong influence on their engagement behaviour with the exception of help-seeking, while effort, enjoyment, deep learning, and surface learning were predictors of programming performance. These findings have implications for introductory programming course instructors and the recommendations emerging from this study include making clear behavioural expectations, designing courses which stimulate and support effective behaviour, and making novice programmers aware of the engagement behaviour that does not lead to better programming performance. This study contributes to the theory of teaching computer programming, and to the practice of designing and delivering introductory programming courses