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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
Miller, Craig S.; Settle, Amber – ACM Transactions on Computing Education, 2019
We investigate conditions in which novices make some reference errors when programming. We asked students from introductory programming courses to perform a simple code-writing task that required constructing references to objects and their attributes. By experimentally manipulating the nature of the attributes in the tasks, from identifying…
Descriptors: Error Patterns, Novices, Programming, Introductory Courses
Singla, Adish; Theodoropoulos, Nikitas – International Educational Data Mining Society, 2022
Block-based visual programming environments are increasingly used to introduce computing concepts to beginners. Given that programming tasks are open-ended and conceptual, novice students often struggle when learning in these environments. AI-driven programming tutors hold great promise in automatically assisting struggling students, and need…
Descriptors: Programming, Computer Science Education, Task Analysis, Introductory Courses
Qian, Yizhou; Hambrusch, Susanne; Yadav, Aman; Gretter, Sarah; Li, Yue – Journal of Educational Computing Research, 2020
A quality computer science (CS) teacher needs to understand students' common misconceptions in learning CS. This study explored one aspect of CS teachers' understanding of student misconceptions: their perceptions of student misconceptions related to introductory programming. Perceptions in this study included three parts: teachers' perceived…
Descriptors: Teacher Attitudes, Misconceptions, Introductory Courses, Programming
Qian, Yizhou; Lehman, James D. – SAGE Open, 2019
With the expansion of computer science (CS) education, CS teachers in K-12 schools should be cognizant of student misconceptions and be prepared to help students establish accurate understanding of computer science and programming. Digital tools, such as automated assessment systems, can be useful and supportive in teaching CS courses. This…
Descriptors: Feedback (Response), Student Attitudes, Misconceptions, Introductory Courses
Broisin, Julien; Hérouard, Clément – International Educational Data Mining Society, 2019
How to support students in programming learning has been a great research challenge in the last years. To address this challenge, prior works have mainly focused on proposing solutions based on syntactic analysis to provide students with personalized feedback about their grammatical programming errors and misconceptions. However, syntactic…
Descriptors: Semantics, Programming, Syntax, Feedback (Response)
Kwon, Kyungbin – International Journal of Computer Science Education in Schools, 2017
Understanding the students' programming misconceptions is critical in that it identifies the reasons why students make errors in programming and allows instructors to design instructions accordingly. This study investigated the mental models of programming concepts held by pre-service teachers who were novice programmers. In an introductory…
Descriptors: Programming, Novices, Misconceptions, Instructional Design
Qian, Yizhou – ProQuest LLC, 2018
With the expansion of computer science (CS) education, CS teachers in K-12 schools should be cognizant of student misconceptions and be prepared to help students establish accurate understanding of computer science and programming. This exploratory design-based research (DBR) study implemented a data-driven approach to identify secondary school…
Descriptors: Misconceptions, Data, Decision Making, Computer Science Education
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
Vahrenhold, Jan; Paul, Wolfgang – Computer Science Education, 2014
We report on the development, validation, and implementation of a collection of test items designed to detect misconceptions related to first-year computer science courses. To this end, we reworked the development scheme proposed by Almstrum et al. ("SIGCSE Bulletin" 38(4):132-145, 2006) to include students' artifacts and to…
Descriptors: Computer Science Education, Introductory Courses, Test Items, Evaluation Methods
Sorva, Juha – ACM Transactions on Computing Education, 2013
This article brings together, summarizes, and comments on several threads of research that have contributed to our understanding of the challenges that novice programmers face when learning about the runtime dynamics of programs and the role of the computer in program execution. More specifically, the review covers the literature on programming…
Descriptors: Computer Science Education, Programming, Introductory Courses, Misconceptions
Drake, John R. – Journal of Information Technology Education: Innovations in Practice, 2012
Active learning has been championed in academic circles as the pedagogical fix to boring lectures typically found in introduction to information systems courses. However, the literature on active learning is mixed. In this paper, we critically examine active learning research and discover a misplaced emphasis leading to paradoxical findings in…
Descriptors: Classroom Techniques, Learning Theories, Class Activities, Course Objectives
Sien, Ven Yu – Computer Science Education, 2011
Object-oriented analysis and design (OOAD) is not an easy subject to learn. There are many challenges confronting students when studying OOAD. Students have particular difficulty abstracting real-world problems within the context of OOAD. They are unable to effectively build object-oriented (OO) models from the problem domain because they…
Descriptors: Foreign Countries, Computer Science Education, Undergraduate Students, Computer Software
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