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Miedema, Daphne; Fletcher, George; Aivaloglou, Efthimia – ACM Transactions on Computing Education, 2023
Prior studies in the Computer Science education literature have illustrated that novices make many mistakes in composing SQL queries. Query formulation proves to be difficult for students. Only recently, some headway was made towards understanding why SQL leads to so many mistakes, by uncovering student misconceptions. In this article, we shed new…
Descriptors: Computer Science Education, Novices, Misconceptions, Programming Languages
Dan Sun; Fan Ouyang; Yan Li; Chengcong Zhu; Yang Zhou – Journal of Computer Assisted Learning, 2024
Background: With the development of computational literacy, there has been a surge in both research and practice application of text-based and block-based modalities within the field of computer programming education. Despite this trend, little work has actually examined how learners engaging in programming process when utilizing these two major…
Descriptors: Computer Science Education, Programming, Computer Literacy, Comparative Analysis
Kristina Litherland; Anders Kluge – Computer Science Education, 2024
Background and Context: We explore the potential for understanding the processes involved in students' programming based on studying their behaviour and dialogue with each other and "conversations" with their programs. Objective: Our aim is to explore how a perspective of inquiry can be used as a point of departure for insights into how…
Descriptors: Programming, Programming Languages, Secondary School Students, Computer Science Education
Qian, Yizhou; Lehman, James – Journal of Research on Technology in Education, 2022
This study investigated common student errors and underlying difficulties of two groups of Chinese middle school students in an introductory Python programming course using data in the automated assessment tool (AAT) Mulberry. One group of students was from a typical middle school while the other group was from a high-ability middle school. By…
Descriptors: Middle School Students, Programming, Computer Science Education, Error Patterns
Yun Huang; Christian Dieter Schunn; Julio Guerra; Peter L. Brusilovsky – ACM Transactions on Computing Education, 2024
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…
Descriptors: Programming, Computer Science Education, Error Patterns, Classification
Jahnke, Maximilian; Höppner, Frank – International Educational Data Mining Society, 2022
The value of an instructor is that she exactly recognizes what the learner is struggling with and provides constructive feedback straight to the point. This work aims at a step towards this type of feedback in the context of an introductory programming course, where students perform program execution tracing to align their understanding of Java…
Descriptors: Programming, Coding, Computer Science Education, Error Patterns
Casterella, Gretchen I.; Vijayasarathy, Leo – Journal of Information Systems Education, 2019
SQL query writing is a challenging task for novices, even after considerable training. Query writing is a programming task and a translation task where the writer must translate a user's request for information into code that conforms to the structure, constraints, and syntax of an SQL SELECT statement and that references specific tables and…
Descriptors: Information Retrieval, Programming Languages, Programming, Coding
McCall, Davin; Kölling, Michael – ACM Transactions on Computing Education, 2019
The types of programming errors that novice programmers make and struggle to resolve have long been of interest to researchers. Various past studies have analyzed the frequency of compiler diagnostic messages. This information, however, does not have a direct correlation to the types of errors students make, due to the inaccuracy and imprecision…
Descriptors: Computer Software, Programming, Error Patterns, Novices
Yang, Jeong; Lee, Young; Fernandez, Amanda; Sanchez, Joshua – Journal of Cybersecurity Education, Research and Practice, 2020
As the cyber security landscape dynamically evolves and security professionals work to keep apace, modern-day educators face the issue of equipping a new generation for this dynamic landscape. With cyber-attacks and vulnerabilities substantially increased over the past years in frequency and severity, it is important to design and build secure…
Descriptors: Computer Security, Programming Languages, Programming, Computer Uses in Education
Ben-Yaacov, Anat; Hershkovitz, Arnon – Journal of Educational Computing Research, 2023
Block programming has been suggested as a way of engaging young learners with the foundations of programming and computational thinking in a syntax-free manner. Indeed, syntax errors--which form one of two broad categories of errors in programming, the other one being logic errors--are omitted while block programming. However, this does not mean…
Descriptors: Programming, Computation, Thinking Skills, Error Patterns
Shmallo, Ronit Shmallo; Shrot, Tammar – Journal of Information Systems Education, 2020
A class diagram is one of the most important diagrams of Unified Modeling Language (UML) and can be used for modeling the static structure of a software system. Learning from errors is a teaching approach based on the assumption that errors can promote learning. We applied a constructive approach of using errors in designing a UML class diagram in…
Descriptors: Programming Languages, Programming, Information Systems, Engineering Education
Sirinda Palahan – IEEE Transactions on Learning Technologies, 2025
The rise of online programming education has necessitated more effective personalized interactions, a gap that PythonPal aims to fill through its innovative learning system integrated with a chatbot. This research delves into PythonPal's potential to enhance the online learning experience, especially in contexts with high student-to-teacher ratios…
Descriptors: Programming, Computer Science Education, Artificial Intelligence, Computer Mediated Communication
Guozhu Ding; Xiangyi Shi; Shan Li – Education and Information Technologies, 2024
In this study, we developed a classification system of programming errors based on the historical data of 680,540 programming records collected on the Online Judge platform. The classification system described six types of programming errors (i.e., syntax, logical, type, writing, misunderstanding, and runtime errors) and their connections with…
Descriptors: Programming, Computer Science Education, Classification, Graphs
Jegede, Philip Olu; Olajubu, Emmanuel Ajayi; Ejidokun, Adekunle Olugbenga; Elesemoyo, Isaac Oluwafemi – Journal of Information Technology Education: Innovations in Practice, 2019
Aim/Purpose: The study examined types of errors made by novice programmers in different Java concepts with students of different ability levels in programming as well as the perceived causes of such errors. Background: To improve code writing and debugging skills, efforts have been made to taxonomize programming errors and their causes. However,…
Descriptors: Programming Languages, Programming, Low Achievement, High Achievement
Villamor, Maureen M. – Research and Practice in Technology Enhanced Learning, 2020
High attrition and dropout rates are common in introductory programming courses. One of the reasons students drop out is loss of motivation due to the lack of feedback and proper assessment of their progress. Hence, a process-oriented approach is needed in assessing programming progress, which entails examining and measuring students' compilation…
Descriptors: Novices, Problem Solving, Computer Science Education, Introductory Courses