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Showing 1 to 15 of 20 results Save | Export
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Monika Mladenovic; Žana Žanko; Goran Zaharija – Journal of Educational Computing Research, 2024
The use of a pedagogical approach mediated transfer with the bridging method has been successful in facilitating the transitions from block-based to text-based programming languages. Nevertheless, there is a lack of research addressing the impact of this transfer on programming misconceptions during the transition. The way programming concepts are…
Descriptors: Programming, Misconceptions, Teaching Methods, Computer Science Education
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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
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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
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Jiang, Bo; Zhao, Wei; Zhang, Nuan; Qiu, Feiyue – Interactive Learning Environments, 2022
Block-based programing languages (BBPL) provide effective scaffolding for K-12 students to learn computational thinking. However, the output-based assessment in BBPL learning is insufficient as we can not understand how students learn and what mistakes they have had. This study aims to propose a data-driven method that provides insight into…
Descriptors: Programming Languages, Computer Science Education, Problem Solving, Game Based Learning
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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
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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
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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
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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
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Žanko, Žana; Mladenovic, Monika; Boljat, Ivica – Education and Information Technologies, 2019
There are known misconceptions about variables which are mostly the same since the first studies since more than 30 years ago. Consciousness about the misconceptions in programming can be crucial for teaching and learning programming for novices because, if we are aware of them, maybe we can minimise or even prevent them. Researchers mostly…
Descriptors: Misconceptions, Elementary Secondary Education, Programming, Programming Languages
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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
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
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Brown, Neil C. C.; Altadmri, Amjad – ACM Transactions on Computing Education, 2017
Teaching is the process of conveying knowledge and skills to learners. It involves preventing misunderstandings or correcting misconceptions that learners have acquired. Thus, effective teaching relies on solid knowledge of the discipline, but also a good grasp of where learners are likely to trip up or misunderstand. In programming, there is much…
Descriptors: Novices, Programming Languages, Programming, Error Patterns
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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
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Rashkovits, Rami; Lavy, Ilana – Journal of Information Technology Education: Innovations in Practice, 2012
This study examines how Information Systems Engineering School students on the verge of their graduation understand the mechanism of exception handling. The main contributions of this paper are as follows: we construct a questionnaire aimed at examining students' level of understanding concerning exceptions; we classify and analyse the students'…
Descriptors: Programming, Programming Languages, Computer Science Education, College Curriculum
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Boustedt, Jonas – Computer Science Education, 2012
The software industry needs well-trained software designers and one important aspect of software design is the ability to model software designs visually and understand what visual models represent. However, previous research indicates that software design is a difficult task to many students. This article reports empirical findings from a…
Descriptors: Foreign Countries, Computer Software, Computer Science Education, Programming
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