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6th Conference on Computing Education Practice (CEP)

作者： Russell, Sean Univ Coll Dublin Dublin Ireland

ISBN: (纸本)9781450395618

The ability for students to read and comprehend code is a fundamental skill in computer programming. Relying on students to build this skill through typical programming assignments can lead to many persevering through trial and error rather than understanding. This paper describes Trace Generator, a work-in-progress application for generating automatically graded code tracing questions for Python and C programs. The fundamental principles behind this work are mastery through repetition and providing comprehensive and understandable feedback to enable students to learn from their mistakes. Feedback and reflections from the use of the generated questions with two introductory procedural programming classes (200 students) are also discussed. Analysis of student attempts suggests a willingness to complete quizzes multiple times until they achieved a satisfactory score (average final result of 91%).

关键词： code tracing code comprehension automatic grading generated feedback

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Unlimited Trace Tutor: Learning code tracing With Automatically Generated Programs 20

Unlimited Trace Tutor: Learning Code Tracing With Automatica...

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51st ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE)

作者： Qi, Ruixiang Fossati, Davide Emory Univ Atlanta GA 30322 USA

ISBN: (纸本)9781450367936

Previous research showed that creating specific types of tracing tables helps students learn code tracing, a fundamental skill in computer programming. This paper introduces Unlimited Trace Tutor, the first version of a code tracing tutoring system that can automatically generate tracing problems and create such tracing tables. We conducted a pilot experiment with volunteer students from an introductory level Computer Science course. We found that our software effectively helps student learn tracing "for" loops, "while" loops, and "if" statements. In this paper we describe the system's architecture, our algorithms for generating code and tracing tables, and the promising results of our pilot experiment.

关键词： code tracing automatic code generation tutoring systems

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Immediate Feedback Collaborative code tracing 19

Immediate Feedback Collaborative Code Tracing

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24th Western Canadian Conference on Computing Education (WCCCE)

作者： Zheng, Jun Kang, Sohee Harrington, Brian Univ Toronto Scarborough Dept Comp & Math Sci Toronto ON Canada

ISBN: (纸本)9781450367158

The Immediate-Feedback Collaborative Assessment Tool (IFCAT) is a web-based application originally designed to replace scratch-card based immediate feedback multiple choice quizzes. In this work, we detail IFCAT's code tracing ability, which allows for line-by-line immediate feedback of code tracing questions. This allows for scaffolded questions whereby subsequent questions on a test build upon previous results, without the danger of cascading errors caused my small mistakes. IFCAT also allows for think-pair-share and driver-passenger based collaborative assessment, and can be used on mobile devices for easy classroom integration.

关键词： CS1 code tracing collaboration think-pair-share

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When Does Scaffolding Provide Too Much Assistance? A code-tracing Tutor Investigation

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INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION 2021年第4期31卷 784-819页

作者： Jennings, Jay Muldner, Kasia Carleton Univ Inst Cognit Sci Ottawa ON Canada

When students are first learning to program, they not only have to learn to write programs, but also how to trace them. code tracing involves stepping through a program step-by-step, which helps to predict the output of the program and identify bugs. Students routinely struggle with this activity, as evidenced by prior work and our own experiences in the classroom. To address this, we designed a code tracing (CT)-Tutor. We varied the level of assistance provided in the tutor, based on (1) the interface scaffolding available during code tracing, and (2) instructional order, operationalized by when examples were provided, either before or after the corresponding problem was solved. We collected data by having participants use the tutor to solve code tracing problems (N = 97) and analyzed both learning outcomes and process data obtained by extracting features of interest from the log files. We used a multi-layered approach for the analysis, including standard inferential statistics and unsupervised learning to cluster students by their behaviors in the tutor. The results show that the optimal level of assistance for code tracing falls in the middle of the assistance spectrum included in the tutor, but also that there are individual differences in terms of optimal assistance for subgroups of individuals. Based on these results, we outline opportunities for future work around personalizing instruction for code tracing.

关键词： code tracing Tutoring system Assistance Worked examples Programming instruction

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Investigating Students' Reasoning in a code-tracing Tutor 1

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22nd International Conference on Artificial Intelligence in Education (AIED) - Mind the Gap - AIED for Equity and Inclusion

作者： Jennings, Jay Muldner, Kasia Carleton Univ Dept Cognit Sci Ottawa ON Canada

ISBN: (数字)9783030782924

ISBN: (纸本)9783030782924;9783030782917

code tracing involves stepping through a program in order to predict its output. In the present study (N = 45), we used the think-aloud protocol to gain insight into students' cognitive processes as they used a computer tutor to study code-tracing examples and work on code-tracing problems, using either a high-scaffolding or a reduced-scaffolding tutor interface. For the cognitive processes, we included both self-explanation and reading behaviors, relying on a qualitative coding to analyze the transcripts. Our results shed light on how different levels of assistance provided by a computer tutor impact student reasoning during code-tracing activities.

关键词： code tracing Verbal protocols Qualitative analysis Programming education

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tracing vs. Writing code: Beyond the Learning Hierarchy 18

Tracing vs. Writing Code: Beyond the Learning Hierarchy

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49th ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE)

作者： Harrington, Brian Cheng, Nick Univ Toronto Scarborough Dept Comp & Math Sci Scarborough ON Canada

ISBN: (纸本)9781450351034

Much work has been done on the achievement gap between code tracing and code writing in CS1 students. The generally accepted explanation for this gap is that tracing and writing form separate steps in a learning scaffolding;students must first learn to trace code before they can be expected to write code. The expectation is that once students have mastered these skills, future grades will be driven by their ability to understand the deeper learning concepts, and so the gap between tracing and writing should disappear. In this paper, we detail and evaluate a study on 384 CS2 students to evaluate whether a tracing-writing gap still exists, and assess whether anything can be deduced about students who continue to exhibit such a gap. We find that not only does the gap seem to have closed by CS2, students are equally likely to show a reverse gap in the writing-tracing direction. However, further analysis shows a strong correlation between students who do continue to have a gap (in either direction) and poor overall performance in the course.

关键词： Assessment CS1 Computer Science Education code tracing code Writing Exam Questions

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Tailoring video recording to support efficient GUI testing and debugging

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SOFTWARE QUALITY JOURNAL 2014年第2期22卷 273-292页

作者： Pham, Raphael Holzmann, Helge Schneider, Kurt Brueggemann, Christian Leibniz Univ Hannover Software Engn Grp D-30167 Hannover Germany Capgemini Deutschland GmbH Applicat Lifecycle Serv Ctr Hannover Germany

Automated GUI tests typically comprise of several test steps that are executed on the GUI before reaching a point of assertion. Comparing a longer and complex execution of a GUI test to its test instructions for debugging is a laborious task: re-establish the test environment, slow down test execution for human perception, and locate the currently executed test step. Video documentation of GUI tests for debugging purposes is already present in several industry tools. However, it is not optimized for effective documentation of on-screen actions nor synched with the executed test instructions. We present a video-based documentation of automated GUI tests that links the executed test case instruction to the on-screen response of the application under test. Screen recording is optimized for speed and memory consumption while all relevant details are captured. Additional browsing capabilities for easier debugging are introduced. Concepts of aspect-oriented programming are adapted for tracing of pre-compiled test case scripts. Our concepts are evaluated by a working implementation, a series of performance measurements during a technical experiment, and industrial experience from 370 real-world test cases carried out in a large software company. The limits of our implementation regarding video capturing and code tracing are explored with a specialized test frame.

关键词： Automated test Graphical user interface Video code tracing Aspect-oriented programming

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Why Students Cannot Easily Integrate Component Skills: An Investigation of the Composition Effect in Programming

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ACM TRANSACTIONS ON COMPUTING EDUCATION 2024年第3期24卷 1-37页

作者： Huang, Yun Schunn, Christian d. Guerra, Julio Brusilovsky, Peter Univ Austral Chile Valdivia Chile Univ Pittsburgh Pittsburgh PA USA

Programming skills are increasingly important to the current digital economy, yet these skills have long been regarded as challenging to acquire. A central challenge in learning programming skills involves the simultaneous use of multiple component skills. This article investigates why students struggle with integrating component skills-a challenge called the composition effect. This effect was first studied in learning mathematics, and findings in that area have led to more effective instruction in mathematics. In the current work, we systematically investigate the nature of the composition effect in novice code tracing through a classroom study in a university-level introductory programming course. We designed a set of problems that require integrating component skills, along with matched problems that use the same component skills separately. The composition effect was defined as the performance difference between these two types of problems. We further singled out errors that were committed in integration problems but not in the matched problems and conducted qualitative coding to categorize these errors. Statistical analyses produced three main findings. First, we found a robust composition effect across problems and students, mostly with small or medium effect sizes. Second, we identified two potential sources of errors for this composition effect: conceptual misunderstandings of how to integrate component skills and process errors resulting from slips related to cognitive load challenges. In particular, additional conceptual knowledge often appears to be needed when component skills are integrated in specific ways. Moreover, the primary source appears to be misunderstandings of how skills integrate. Composition effects may not generalize across topics, which suggests that domain topics may serve as the conceptual basis for the composition effect. Third, we found stable individual differences in susceptibility to the composition effect in both overall and fine

关键词： code tracing composition difficulties misconceptions cognitive task analysis assessment introductory programming education

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Supporting Novices and Advanced Students in Acquiring Multiple Coding Skills 26

Supporting Novices and Advanced Students in Acquiring Multip...

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26th INTERNATIONAL CONFERENCE ON COMPUTERS IN EDUCATION

作者： Fabic, Geela Venise Firmalo Mitrovic, Antonija Neshatian, Kourosh Univ Canterbury Comp Sci & Software Engn Christchurch New Zealand

ISBN: (纸本)9789869401289

We present our study on PyKinetic with various activities to target several skills: code tracing, debugging, and code writing. Half of the participants (control group) received the problems in a fixed order, while for the other half (experimental group) problems were selected adaptively, based on their performance. In a previous paper, we discussed the general findings from the study. In this paper we present further analyses and focus on differences between low performing students and students with higher pre-existing knowledge. We hypothesized that: (H1) novices will benefit more than advanced students, and (H2) advanced students in the experimental group will benefit more than those in the control group. The results confirmed H1 and revealed that this version of PyKinetic was more beneficial for novice learners. Moreover, novices showed evidence of learning multiple skills: code writing, debugging and code tracing. However, we did not have enough evidence for hypothesis H2.

关键词： mobile Python tutor Parsons problems adaptive problem selection code debugging code tracing code writing

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Extension of a study on Parsons' Problems reveals implications for SEE&T 36

Extension of a study on Parsons' Problems reveals implicatio...

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36th International Conference on Software Engineering Education and Training (CSEE and T)

作者： Wendt, Kevin D. Univ Minnesota Dept Comp Sci & Engn Minneapolis MN 55455 USA

ISBN: (纸本)9798350378986;9798350378979

'The code Mangler: Evaluating Coding Ability Without Writing Any code' [1] introduced a hypothetical bad actor into an established, but still relatively new, problem type - the Parsons' Problem [2]. When I replicated and extended the study, similar results to the original were observed: students found that rearranging lines of correct code that were in jumbled order was as difficult and as good at assessing their abilities as writing code from scratch [3]. Not only is this finding helpful in providing an accurate assessment tool with significantly reduced effort required to grade, it presents an interesting possibility for future software engineers: the ability to practice and gain confidence in working with unfamiliar code, a skill which may translate to industry. © 2024 IEEE.

关键词： Parsons' Problems code Mangler unfamiliar code code tracing code writing new grads

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