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Shindler, Michael; Pinpin, Natalia; Markovic, Mia; Reiber, Frederick; Kim, Jee Hoon; Carlos, Giles Pierre Nunez; Dogucu, Mine; Hong, Mark; Luu, Michael; Anderson, Brian; Cote, Aaron; Ferland, Matthew; Jain, Palak; LaBonte, Tyler; Mathur, Leena; Moreno, Ryan; Sakuma, Ryan – Computer Science Education, 2022
Background and Context: We replicated and expanded on previous work about how well students learn dynamic programming, a difficult topic for students in algorithms class. Their study interviewed a number of students at one university in a single term. We recruited a larger sample size of students, over several terms, in both large public and…
Descriptors: Misconceptions, Programming, Computer Science Education, Replication (Evaluation)
Esche, Svana; Weihe, Karsten – IEEE Transactions on Education, 2023
Contribution: Most work on languages in computing education currently focuses on non-native speakers. In contrast, to the best of the authors' knowledge, this article is the first response to the call for research on terms that takes into account the terms used by novices in their language. Background: Terms are key factors in communication,…
Descriptors: Programming Languages, Computer Science Education, Misconceptions, Undergraduate Students
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
Orly Barzilai; Sofia Sherman; Moshe Leiba; Hadar Spiegel – Journal of Information Systems Education, 2024
Data Structures and Algorithms (DS) is a basic computer science course that is a prerequisite for taking advanced information systems (IS) curriculum courses. The course aims to teach students how to analyze a problem, design a solution, and implement it using pseudocode to construct knowledge and develop the necessary skills for algorithmic…
Descriptors: Statistics Education, Problem Solving, Information Systems, Algorithms
Shmallo, Ronit; Ragonis, Noa – Education and Information Technologies, 2021
The paper presents research that aims to expose students' understanding of the "this" reference in object-oriented programming. The study was conducted with high school students (N = 86) and college engineering students (N = 77). Conceptualization of "this" reflects an understanding of objects in general and involves aspects of…
Descriptors: Computer Science Education, Programming, High School Students, College Students
Strömbäck, Filip; Mannila, Linda; Kamkar, Mariam – Informatics in Education, 2021
Concurrency is often perceived as difficult by students. One reason for this may be due to the fact that abstractions used in concurrent programs leave more situations undefined compared to sequential programs (e.g., in what order statements are executed), which makes it harder to create a proper mental model of the execution environment. Students…
Descriptors: College Students, Programming, Programming Languages, Concept Formation
Ragonis, Noa; Shmallo, Ronit – Informatics in Education, 2022
Object-oriented programming distinguishes between instance attributes and methods and class attributes and methods, annotated by the "static" modifier. Novices encounter difficulty understanding the means and implications of "static" attributes and methods. The paper has two outcomes: (a) a detailed classification of aspects of…
Descriptors: Programming, Computer Science Education, Concept Formation, Thinking Skills
Daniele Traversaro; Giorgio Delzanno; Giovanna Guerrini – Informatics in Education, 2024
Concurrency is a complex to learn topic that is becoming more and more relevant, such that many undergraduate Computer Science curricula are introducing it in introductory programming courses. This paper investigates the combined use of Sonic Pi and Team-Based Learning to mitigate the difficulties in early exposure to concurrency. Sonic Pi, a…
Descriptors: Misconceptions, Programming Languages, Computer Science Education, Undergraduate Students
Christina Kyriakou; Agoritsa Gogoulou; Maria Grigoriadou – Informatics in Education, 2023
This paper presents an educational setting that attempts to enhance students' understanding and facilitate students' linking-inferencing skills. The proposed setting is structured in three stages. The first stage intends to explore students' prior knowledge. The second stage aims to help students tackle their difficulties and misconceptions and…
Descriptors: Thinking Skills, Inferences, Computer Science Education, Computer System Design
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
Ioannis, Berdousis; Maria, Kordaki – Education and Information Technologies, 2019
The study of gender differences in Computer Science (CS) has captured the attention of many researchers around the world. Over time, research has revealed that negative stereotypes and 'myths' about the cognitive skills, academic abilities and interests of females in CS do exist, deterring females from entering the field. Thus, this study aims to…
Descriptors: Computer Science Education, Gender Differences, Stereotypes, Misconceptions
Hamouda, Sally; Edwards, Stephen H.; Elmongui, Hicham G.; Ernst, Jeremy V.; Shaffer, Clifford A. – Computer Science Education, 2020
Background and Context: Recursion in binary trees has proven to be a hard topic. There was not much research on enhancing student understanding of this topic. Objective: We present a tutorial to enhance learning through practice of recursive operations in binary trees, as it is typically taught post-CS2. Method: We identified the misconceptions…
Descriptors: Computer Science Education, Programming, Coding, Student Attitudes
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
Hamouda, Sally; Edwards, Stephen H.; Elmongui, Hicham G.; Ernst, Jeremy V.; Shaffer, Clifford A. – ACM Transactions on Computing Education, 2019
Recursion is one of the most important and hardest topics in lower division computer science courses. As it is an advanced programming skill, the best way to learn it is through targeted practice exercises. But the best practice problems are time consuming to manually grade by an instructor. As a consequence, students historically have completed…
Descriptors: Computer Science Education, Programming, Instructional Effectiveness, Difficulty Level
Elmali, Filiz; Tekin, Ahmet; Polat, Ebru – Turkish Online Journal of Distance Education, 2020
The main goal of this study is to determine the digital citizenship perceptions and digital citizenship levels of preschool teacher candidates in terms of digital rights and responsibilities, digital security and digital law by comparing them with Computer and Instructional Technologies teacher candidates' perception. To this end, we worked with…
Descriptors: Preservice Teachers, Preservice Teacher Education, Preschool Education, Computer Science Education