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Competitive Programming Participation Rates: An Examination of Trends in U.S. ICPC Regional Contests
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
Xin Gong; Weiqi Xu; Ailing Qiao; Zhixia Li – Journal of Computer Assisted Learning, 2025
Background: Robot programming can simultaneously cultivate learners' computational thinking (CT) and spatial thinking (ST). However, there is a noticeable gap in research focusing on the micro-level development patterns of learners' CT and ST and their interconnections. Objectives: This study aims to uncover the intricate development patterns and…
Descriptors: Mental Computation, Thinking Skills, Skill Development, Robotics
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
Pere J. Ferrando; Ana Hernández-Dorado; Urbano Lorenzo-Seva – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A frequent criticism of exploratory factor analysis (EFA) is that it does not allow correlated residuals to be modelled, while they can be routinely specified in the confirmatory (CFA) model. In this article, we propose an EFA approach in which both the common factor solution and the residual matrix are unrestricted (i.e., the correlated residuals…
Descriptors: Correlation, Factor Analysis, Models, Goodness of Fit
Ezeamuzie, Ndudi O. – Education and Information Technologies, 2023
Several instructional approaches have been advanced for learning programming. However, effective ways of engaging beginners in programming in K-12 are still unclear, especially among low socioeconomic status learners in technology-deprived learning environments. Understanding the learning path of novice programmers will bridge this gap and explain…
Descriptors: Programming, Constructivism (Learning), Programming Languages, Computer Science Education
Kane Meissel; Esther S. Yao – Practical Assessment, Research & Evaluation, 2024
Effect sizes are important because they are an accessible way to indicate the practical importance of observed associations or differences. Standardized mean difference (SMD) effect sizes, such as Cohen's d, are widely used in education and the social sciences -- in part because they are relatively easy to calculate. However, SMD effect sizes…
Descriptors: Computer Software, Programming Languages, Effect Size, Correlation
Chiu, Po-Sheng; Zhong, Hua-Xu; Lai, Chin-Feng – Innovations in Education and Teaching International, 2023
In recent years, flipping classrooms has become a popular topic of discussion. However, few previous studies have focused on the effect of the flow experience on programming self-efficacy. To address this gap, the present researchers developed a model that included six research hypotheses. The study applied a flipped classroom model to a…
Descriptors: Flipped Classroom, Programming, Self Efficacy, College Students
Damira Belessova; Almira Ibashova; Aziza Zhidebayeva; Guldana Shaimerdenova; Venera Nakhipova – Open Education Studies, 2024
This study aimed to investigate the impact of the Scratch programming environment on student engagement and academic performance in primary informatics education. The research was conducted over three academic years (2020-2023) in educational organizations (ADAN and Navoiy schools) involving 170 first and third-grade students. The Student…
Descriptors: Programming, Learner Engagement, Academic Achievement, Elementary School Students
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
Imran, Hazra – Journal of Educational Computing Research, 2023
Adding gaming elements to conventional teaching methodologies has gained a lot of attention because of its ability to incorporate an engaging, motivating, and fun-based environment. As a result, learners' dedication and performance are also better. Unfortunately, current gamification models do not consider the effect of different levels of…
Descriptors: Introductory Courses, Game Based Learning, Learning Motivation, Learner Engagement
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
Feiya Luo; Pavlo Antonenko; Natercia Valle; Emily Sessa; Gordon Burleigh; Lorena Endara; Stuart McDaniel; Sarah Carey; E. Christine Davis – International Journal of Designs for Learning, 2020
This design case discusses the complex collaborative design reasoning processes involved in developing an online interactive learning tool for learners of all ages to explore and understand the role of flagellate plants in our society. The learning tool consists of a main website (the "Voyager") and an interactive, dynamic map of the…
Descriptors: Interdisciplinary Approach, Instructional Design, Web Sites, Plants (Botany)
McCall, Davin; Kölling, Michael – ACM Transactions on Computing Education, 2019
The types of programming errors that novice programmers make and struggle to resolve have long been of interest to researchers. Various past studies have analyzed the frequency of compiler diagnostic messages. This information, however, does not have a direct correlation to the types of errors students make, due to the inaccuracy and imprecision…
Descriptors: Computer Software, Programming, Error Patterns, Novices
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