NotesFAQContact Us
Collection
Advanced
Search Tips
Publication Date
In 20250
Since 20243
Since 2021 (last 5 years)10
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Showing all 10 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Nie, Rui; Guo, Qi; Morin, Maxim – Educational Measurement: Issues and Practice, 2023
The COVID-19 pandemic has accelerated the digitalization of assessment, creating new challenges for measurement professionals, including big data management, test security, and analyzing new validity evidence. In response to these challenges, "Machine Learning" (ML) emerges as an increasingly important skill in the toolbox of measurement…
Descriptors: Artificial Intelligence, Electronic Learning, Literacy, Educational Assessment
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
PDF on ERIC Download full text
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
Peer reviewed Peer reviewed
PDF on ERIC Download full text
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
Peer reviewed Peer reviewed
PDF on ERIC Download full text
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Berry, Alex Joshua – ProQuest LLC, 2022
In this research, social media data from a public school district was utilized to help improve district communication during and after a crisis. Data was analyzed by utilizing the programming languages R and Python. The programming languages helped generate data that allowed this research to evaluate how the quality of crisis communication could…
Descriptors: Social Media, Data Analysis, Public Schools, School Districts