An influence model of the experience of learning programming
Creators: name: Adamopoulos, Fran
Publisher: name: RMIT University
Year: 2024
Subjects: classificationCode: 399999
subject: Other education not elsewhere classified
classificationCode: 460999
subject: Information systems not elsewhere classified

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