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Showing 1 to 15 of 302 results Save | Export
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Yi Liu; Leen-Kiat Soh; Guy Trainin; Gwen Nugent; Wendy M. Smith – Computer Science Education, 2025
Background and Context: Professional development (PD) programs for K-12 computer science teachers use surveys to measure teachers' knowledge and attitudes while recognizing daily sentiment and emotion changes can be crucial for providing timely teacher support. Objective: We investigate approaches to compute sentiment and emotion scores…
Descriptors: Computer Science Education, Faculty Development, Elementary School Teachers, Secondary School Teachers
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Jeremy J. Blum – Discover Education, 2023
A wide range of benefits have been posited from participation in competitive programming contests. However, an analysis of participation in north American regional contests in the International Collegiate Programming Contest (ICPC) shows that participation in these contests is sharply declining, coinciding with the COVID-19 pandemic. Moreover,…
Descriptors: Programming, Higher Education, Competition, Trend Analysis
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Niloofar Mansoor; Cole S. Peterson; Michael D. Dodd; Bonita Sharif – ACM Transactions on Computing Education, 2024
Background and Context: Understanding how a student programmer solves different task types in different programming languages is essential to understanding how we can further improve teaching tools to support students to be industry-ready when they graduate. It also provides insight into students' thought processes in different task types and…
Descriptors: Biofeedback, Eye Movements, Computer Science Education, Programming Languages
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Henrique Mohallem Paiva; Flávia Maria Santoro; Victor Takashi Hayashi; Bianca Cassemiro Lima – IEEE Transactions on Education, 2025
Contribution: This article analyzes student assessment within a computing faculty employing a full project-based learning (PBL) approach. Examining 2078 final grades across 60 classes and periods, the study reveals a significant correlation between graded self-studies, exams, and projects. This result contributes to understanding the reliability…
Descriptors: Student Evaluation, Computer Science Education, College Faculty, Correlation
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Yong-Woon Choi; In-gyu Go; Yeong-Jae Gil – International Journal of Technology and Design Education, 2024
The purpose of this study is to derive a correlation between the technological thinking disposition and the computational thinking ability of gifted students in Korea. The correlation between each element was analyzed by looking at the sub-elements of computational thinking according to the components of technological thinking disposition. The…
Descriptors: Thinking Skills, Mental Computation, Gifted, Correlation
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Muhammed Murat Gümüs; Volkan Kukul; Özgen Korkmaz – Informatics in Education, 2024
This study aims to explain the relationships between secondary school students' digital literacy, computer programming self-efficacy and computational thinking self-efficacy. The study group consists of 204 secondary school students. A relational survey model was used in the research method and three different data collection tools were used to…
Descriptors: Correlation, Middle School Students, Thinking Skills, Digital Literacy
Sirazum Munira Tisha – ProQuest LLC, 2023
Most existing autograders used for grading programming assignments are based on unit testing, which is tedious to implement for programs with graphical output and does not allow testing for other code aspects, such as programming style or structure. We present a novel autograding approach based on machine learning that can successfully check the…
Descriptors: Computer Software, Grading, Programming, Assignments
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Václav Dobiáš; Václav Šimandl; Jirí Vanícek – Informatics in Education, 2024
The paper discusses an alternative method of assessing the difficulty of pupils' programming tasks to determine their age appropriateness. Building a program takes the form of its successive iterations. Thus, it is possible to monitor the number of times such a program was built by the solver. The variance of the number of program builds can be…
Descriptors: Difficulty Level, Computer Science Education, Programming, Task Analysis
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Ali Alshammari – Education and Information Technologies, 2024
In online education, it is widely recognized that interaction and engagement have an impact on students' academic performance. While previous research has extensively explored interactions between students, instructors, and content, there has been limited exploration of course design elements that promote the fourth type of interaction:…
Descriptors: Learning Analytics, Learning Management Systems, Academic Achievement, Correlation
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Ramon Mayor Martins; Christiane G. Von Wangenheim; Marcelo F. Rauber; Adriano F. Borgatto; Jean C. R. Hauck – ACM Transactions on Computing Education, 2024
As Machine Learning (ML) becomes increasingly integrated into our daily lives, it is essential to teach ML to young people from an early age including also students from a low socioeconomic status (SES) background. Yet, despite emerging initiatives for ML instruction in K-12, there is limited information available on the learning of students from…
Descriptors: Artificial Intelligence, Computer Science Education, Socioeconomic Status, Correlation
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Jinbo Tan; Lei Wu; Shanshan Ma – British Journal of Educational Technology, 2024
The purpose of this study was to investigate the collaborative dialogue patterns of pair programming and their impact on programming self-efficacy and coding performance for both slow- and fast-paced students. Forty-six postgraduate students participated in the study. The students were asked to solve programming problems in pairs; those pairs'…
Descriptors: Coding, Programming, Computer Science Education, Self Efficacy
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Christopher Hundhausen; Phill Conrad; Olusola Adesope; Ahsun Tariq – ACM Transactions on Computing Education, 2023
Assessing team software development projects is notoriously difficult and typically based on subjective metrics. To help make assessments more rigorous, we conducted an empirical study to explore relationships between subjective metrics based on peer and instructor assessments, and objective metrics based on GitHub and chat data. We studied 23…
Descriptors: Teamwork, Computer Software, Undergraduate Students, Computer Science Education
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Xinlei Li; Guoyuan Sang; Martin Valcke; Johan van Braak – Education and Information Technologies, 2024
Computational thinking (CT) is valued as a thinking process that is required to adapt to the development of curriculum in primary education. In the context of modern information technology, English as a language subject emphasizes the necessity for changes in both learning and teaching modes. However, there is a lack of up-to-date synthesis…
Descriptors: Computer Science Education, Technological Literacy, Pedagogical Content Knowledge, Elementary School Students
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Fowler, Max; Smith, David H., IV; Hassan, Mohammed; Poulsen, Seth; West, Matthew; Zilles, Craig – Computer Science Education, 2022
Background and Context: Lopez and Lister first presented evidence for a skill hierarchy of code reading, tracing, and writing for introductory programming students. Further support for this hierarchy could help computer science educators sequence course content to best build student programming skill. Objective: This study aims to replicate a…
Descriptors: Programming, Computer Science Education, Correlation, Introductory Courses
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Miitta Järvinen; Katriina Sipiläinen; Janne Roslöf; Sami Lehesvuori; Lauri Kettunen; Raija Hämäläinen – European Journal of Engineering Education, 2025
This study explored the learning experiences of first-year information technology students at the beginning of their studies. Identifying the early experiences is important, as we know they can predict later challenges and persistence in studies. We focus on a novel understanding of relations between learning approaches, self-efficacy and burnout…
Descriptors: Information Technology, College Freshmen, Computer Science Education, Self Efficacy
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