Characterising Graduateness in Computing Education: A Narrative Approach

This thesis examines the concept of graduateness in computing education. Graduateness is related to efforts to articulate the outcomes of a university education. It is commonly defined as the attributes all graduates should develop by the time they graduate regardless of university attended or discipline studied (Glover, Law and Youngman 2002). This work takes a different perspective grounded in disciplinary and institutional contexts. It aims to explore how graduates make sense of their experiences studying computing within their wider learning trajectories. The research presented here uses a narrative approach. Whilst narrative methodologies are not commonly used in computing education, people construct stories both to make sense of their experiences and to integrate the "past, present, and an anticipated future" (McAdams 1985, p.120). Stories are then a particularly appropriate way of examining the sense people make of their learning experiences. This work draws on narrative interviews with graduates from the School of Computing at the University of Kent and Olin College of Engineering in the United States. It contributes a new perspective about the effect of a computing education beyond short-term outcome measures and proposes several analytic constructs that expose significant aspects in participants' learning experiences. In this, it describes themes related to students' acquisition of disciplinary knowledge and examines the evolution of their stories of learning computing over time

An influence model of the experience of learning programming

Learning to program is difficult for many students all over the world with programming courses often experiencing high failure and attrition rates. The teaching of programming is still considered a major challenge by educators. At the same time, programming is becoming a key skill required not only of IT graduates but also of students in other disciplines and is becoming more important to a wider range of people. Today’s university students also practice their learning in an extended learning environment that extends well beyond the classroom. There has been considerable research into the teaching of programming in the computing education field, with many studies focussing on content and delivery. More recently, researchers have recognised the need for a greater understanding of how students experience learning to program, from the student’s perspective. This study contributes to this growing body of knowledge by exploring, in depth, the wide range of influences on the student learning experience of programming. A qualitative study was conducted that interviewed 31 Information Systems students about their experiences in learning programming. The interview transcripts were analysed using a Grounded Theory methodology. A new theory of the Influences on the Student Learning Experience of Programming was developed from the analysis, which is more holistic and comprehensive than previous theories. The learning experience of programming involves a complex interaction of a wide range of influences. A major influence is the student’s Perceived Personal Relevance towards programming. Students who perceive that programming is relevant to their future career goals are far more motivated to learn it. Perceived Personal Relevance, together with Learning Trait and Skill Level describe the Learner Nature of the student, which influences their Learning Behaviours. The influences within Learning Behaviours include Core Learning Perspectives (Ownership of learning, Learning Task Intent and Problem solving Behaviours), Patterns of Collaboration and Patterns of Information Use. Patterns of Collaboration describe how students interact with and use their Personal Networks, and include four levels of dependency: One Way Dependent, Two Way Co-Dependent, Collaborative Independent and Solitary Independent. Patterns of Information Use describe the different ways students interact with and use their information sources. The theory includes Programming Learner Profiles, which encapsulate the relationships and influences between Learner Nature and Learning Behaviours. Each profile describes, in essence, the nature and behaviour of different types of students. Seven distinct Programming Learner Profiles were identified in the study: Reluctant Beginner, Willing Beginner, Keen Beginner, Budding Manager, Budding Practitioner, Budding Developer and Advanced Developer. This new theory gives educators a greater insight into what students are thinking and doing when learning to program and potential strategies that can improve learning outcomes