A multi-national study of reading and tracing skills in novice programmers

By Raymond Lister, Elizabeth S. Adams, Sue Fitzgerald, W. Fone, J. Hamer, Morten Lindholm, R. Mccartney, J. Moström, Kate Sanders, Otto Seppälä and 2 more. SIGCSE Bulletin Inroads, 2004

692 citations recorded by the source corpus.

Subfields: Computer Science Applications, Information Systems, Software

View Paper: https://www.semanticscholar.org/paper/161d617890001703cb3dc6334cbc175f264a2a57

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Citations in the corpus

Computing in the curriculum: Challenges and strategies from a teacher’s perspective (2016, methodology): “Reading and tracing code is also important in supporting the learning of programming (Lopez et al. 2008) and being able to do this is a pre-cursor to the problem-solving skills needed to write code (Lister et al. 2004).”
Students Struggle to Explain Their Own Program Code (2021, background): “Many students who completed programming courses have displayed symptoms of fragile learning, such as poor grasp of programming principles or difficulties in tracing the execution of a program [10].”
Explaining program code: giving students the answer helps - but only just (2011, background): “Many students in introductory programming courses appear unable to correctly explain the purpose of very small code fragments [7].”
Quality of student contributed questions using PeerWise (2009, background): “In a review of the literature on peer review, Topping [6] reported that almost three-quarters of the studies that compared grades assigned by students with the grades assigned by teachers showed a high degree of consistency between student and teacher assigned grades.”
Automatic Generation of Programming Exercises and Code Explanations Using Large Language Models (2022, background): “Code tracing questions typically ask students to determine the output or the value stored in a variable after a provided code block is executed and are often presented in multiple-choice format [50].”
Not seeing the forest for the trees: novice programmers and the SOLO taxonomy (2006, methodology): “Much of the work in the 1980s [12,13] focused on novice preconceptions and misconceptions of programming constructs, while the recent Leeds Working Group [ 9 ] focused upon the ability of students to reliably hand execute code.”
Code comprehension problems as learning events (2012, background): “questions can vary, the type of responses expected and the grading of those responses will vary as well [7].”
Introductory programming: a systematic literature review (2018, background): “[382], which have raised concerns about weaknesses in many students’ abilities.”
Methods and tools for exploring novice compilation behaviour (2006, background): “, Bootstrapping CS Education Research, Scaffolding CS Education Research, and both BRACE and BRACElet provide a model for a community of researchers to ask a question, collect a large amount of (potentially) diverse data, and address a research question from a number of different perspectives[8, 23,”
An Australasian study of reading and comprehension skills in novice programmers, using the bloom and SOLO taxonomies (2006, methodology): “This study has extended prior work by Lister et al (2004), and used a revised set of multiple choice and short answer questions, within two key pedagogical frameworks of analysis.”
Why students drop out CS1 course? (2006, background): “Several multi-institutional studies [19, 16, 23] have indicated that there are serious deficiencies in the learning outcomes of students who have passed one or several programming courses in CS programs.”
An Empirical Investigation into Programming Language Syntax (2013, background): “One important research line has been in evaluating the programming practices of novices or trying to make programming more natural [Bonar and Soloway 1983; Holmboe 2005; Lister et al. 2004; Lopes et al. 2003; Myers et al. 2008; Schulte and Magenheim 2005; Soloway et al. 1983].”
The Robots Are Here: Navigating the Generative AI Revolution in Computing Education (2023, background): “Although the ability to both read and trace code has always been important [19, 120], an examination of course syllabi showed that this is often an afterthought [36, 105].”
Developing a computer science-specific learning taxonomy (2007, background): “The inspiration for this taxonomy was research [41,73] indicating that comprehension of program code and the ability to produce program code are two semi-independent capabilities.”