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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
Lokkila, Erno; Christopoulos, Athanasios; Laakso, Mikko-Jussi – Journal of Information Systems Education, 2023
Educators who teach programming subjects are often wondering "which programming language should I teach first?" The debate behind this question has a long history and coming up with a definite answer to this question would be farfetched. Nonetheless, several efforts can be identified in the literature wherein pros and cons of mainstream…
Descriptors: Comparative Analysis, Programming Languages, Probability, 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
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
Enhancement of the Command-Line Environment for Use in the Introductory Statistics Course and Beyond
Gerbing, David W. – Journal of Statistics and Data Science Education, 2021
R and Python are commonly used software languages for data analytics. Using these languages as the course software for the introductory course gives students practical skills for applying statistical concepts to data analysis. However, the reliance upon the command line is perceived by the typical nontechnical introductory student as sufficiently…
Descriptors: Statistics Education, Teaching Methods, Introductory Courses, Programming Languages
Taipalus, Toni; Siponen, Mikko; Vartiainen, Tero – ACM Transactions on Computing Education, 2018
SQL is taught in almost all university level database courses, yet SQL has received relatively little attention in educational research. In this study, we present a database management system independent categorization of SQL query errors that students make in an introductory database course. We base the categorization on previous literature,…
Descriptors: Programming Languages, Database Management Systems, Database Design, College Students
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
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
Velez, Martin – ProQuest LLC, 2019
Software is an integral part of our lives. It controls the cars we drive every day, the ships we send into space, and even our toasters. It is everywhere and we can easily download more. Software solves many real-world problems and satisfies many needs. Thus, unsurprisingly, there is a rising demand for software engineers to maintain existing…
Descriptors: Computer Science Education, Programming, Introductory Courses, Computer Software
Becker, Brett A.; Glanville, Graham; Iwashima, Ricardo; McDonnell, Claire; Goslin, Kyle; Mooney, Catherine – Computer Science Education, 2016
Programming is an essential skill that many computing students are expected to master. However, programming can be difficult to learn. Successfully interpreting compiler error messages (CEMs) is crucial for correcting errors and progressing toward success in programming. Yet these messages are often difficult to understand and pose a barrier to…
Descriptors: Computer Science Education, Programming, Novices, Error Patterns
Park, Thomas H.; Dorn, Brian; Forte, Andrea – ACM Transactions on Computing Education, 2015
Many people are first exposed to code through web development, yet little is known about the barriers beginners face in these formative experiences. In this article, we describe a study of undergraduate students enrolled in an introductory web development course taken by both computing majors and general education students. Using data collected…
Descriptors: Programming Languages, Computer Science Education, Hypermedia, Web Sites
Veerasamy, Ashok Kumar; D'Souza, Daryl; Laakso, Mikko-Jussi – Journal of Educational Technology Systems, 2016
This article presents a study aimed at examining the novice student answers in an introductory programming final e-exam to identify misconceptions and types of errors. Our study used the Delphi concept inventory to identify student misconceptions and skill, rule, and knowledge-based errors approach to identify the types of errors made by novices…
Descriptors: Computer Science Education, Programming, Novices, Misconceptions
Bringula, Rex P.; Manabat, Geecee Maybelline A.; Tolentino, Miguel Angelo A.; Torres, Edmon L. – World Journal of Education, 2012
This descriptive study determined which of the sources of errors would predict the errors committed by novice Java programmers. Descriptive statistics revealed that the respondents perceived that they committed the identified eighteen errors infrequently. Thought error was perceived to be the main source of error during the laboratory programming…
Descriptors: Error Patterns, Programming, Programming Languages, Predictor Variables
Hughes, Michael C.; Jadud, Matthew C.; Rodrigo, Ma. Mercedes T. – Computer Science Education, 2010
In Java, "System.out.printf" and "String.format" consume a specialised kind of string commonly known as a format string. In our study of first-year students at the Ateneo de Manila University, we discovered that format strings present a substantial challenge for novice programmers. Focusing on their first laboratory we found…
Descriptors: Foreign Countries, Computer Science Education, Programming Languages, Introductory Courses
Le, Nguyen-Thinh; Menzel, Wolfgang – International Journal of Artificial Intelligence in Education, 2009
In this paper, we introduce logic programming as a domain that exhibits some characteristics of being ill-defined. In order to diagnose student errors in such a domain, we need a means to hypothesise the student's intention, that is the strategy underlying her solution. This is achieved by weighting constraints, so that hypotheses about solution…
Descriptors: Intelligent Tutoring Systems, Logical Thinking, Programming, Models