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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
Michelle Pauley Murphy; Woei Hung – TechTrends: Linking Research and Practice to Improve Learning, 2024
Constructing a consensus problem space from extensive qualitative data for an ill-structured real-life problem and expressing the result to a broader audience is challenging. To effectively communicate a complex problem space, visualization of that problem space must elucidate inter-causal relationships among the problem variables. In this…
Descriptors: Information Retrieval, Data Analysis, Pattern Recognition, Artificial Intelligence
Teck Kiang Tan – Practical Assessment, Research & Evaluation, 2024
The procedures of carrying out factorial invariance to validate a construct were well developed to ensure the reliability of the construct that can be used across groups for comparison and analysis, yet mainly restricted to the frequentist approach. This motivates an update to incorporate the growing Bayesian approach for carrying out the Bayesian…
Descriptors: Bayesian Statistics, Factor Analysis, Programming Languages, Reliability
Ghislain Nono Gueye; Jonathan R. Peterson – Journal of Economic Education, 2024
The authors present a Web application they designed in the R programming language as an experiential learning tool for teaching production theory. The app simulates production decisions where a manager is tasked to find the optimal mixture of inputs through experimentation. Users of the application are instructed to use calculations and intuitions…
Descriptors: Economics Education, Teaching Methods, Computer Oriented Programs, Programming Languages
Jesennia Cárdenas-Cobo; Cristian Vidal-Silva; Lisett Arévalo; Magali Torres – Education and Information Technologies, 2024
The information society is part of current life, and algorithmic thinking and programming are relevant for everybody regardless of educational background. Today's world needs professionals with computing competencies from WEIRD (Western, Educated, Industrialized, Rich, and Democratic Societies) and non-WEIRD contexts. Traditional programming…
Descriptors: Programming, Skill Development, Competence, Artificial Intelligence
Vispoel, Walter P.; Lee, Hyeryung; Xu, Guanlan; Hong, Hyeri – Journal of Experimental Education, 2023
Although generalizability theory (GT) designs have traditionally been analyzed within an ANOVA framework, identical results can be obtained with structural equation models (SEMs) but extended to represent multiple sources of both systematic and measurement error variance, include estimation methods less likely to produce negative variance…
Descriptors: Generalizability Theory, Structural Equation Models, Programming Languages, Scores
Ainsley Miller; Kate Pyper – Journal of Statistics and Data Science Education, 2024
R is becoming the standard for teaching statistics due to its flexibility, and open-source nature, replacing software programs like Minitab and SPSS. The main driver for reform within Scottish statistical undergraduate programs is the creation of the Scottish Qualification Authority's Higher Applications of Mathematics course which has statistics…
Descriptors: College Freshmen, Undergraduate Study, Anxiety, Programming Languages
Allison S. Theobold; Megan H. Wickstrom; Stacey A. Hancock – Journal of Statistics and Data Science Education, 2024
Despite the elevated importance of Data Science in Statistics, there exists limited research investigating how students learn the computing concepts and skills necessary for carrying out data science tasks. Computer Science educators have investigated how students debug their own code and how students reason through foreign code. While these…
Descriptors: Computer Science Education, Coding, Data Science, Statistics Education
Janice Padula – Australian Mathematics Education Journal, 2024
In this paper the author explores and demonstrates the vital role mathematics plays in technology by showing how algebra, and in particular Boolean algebra, has become an essential part of how computers and computer languages work. Both Boolean logic and algebra are core competencies in Computer Science at the university level which may encourage…
Descriptors: Algebra, Logical Thinking, Computers, Artificial Intelligence
Oscar Karnalim; Simon; William Chivers – Computer Science Education, 2024
Background and Context: To educate students about programming plagiarism and collusion, we introduced an approach that automatically reports how similar a submitted program is to others. However, as most students receive similar feedback, those who engage in plagiarism and collusion might feel inadequately warned. Objective: When students are…
Descriptors: Teaching Methods, Plagiarism, Computer Science Education, Programming
Tippawan Meepung – International Education Studies, 2024
This study explores the application of the Project-Based Learning with Gamification Model (PBLGM) through Visual Programming Language (VPL) to enhance digital competencies and problem-solving skills in learners. The PBLGM model integrates project-based learning and gamification techniques using Kodu Game Lab, aiming to develop essential…
Descriptors: Student Projects, Active Learning, Gamification, Foreign Countries
Yang Shi; Robin Schmucker; Keith Tran; John Bacher; Kenneth Koedinger; Thomas Price; Min Chi; Tiffany Barnes – Journal of Educational Data Mining, 2024
Understanding students' learning of knowledge components (KCs) is an important educational data mining task and enables many educational applications. However, in the domain of computing education, where program exercises require students to practice many KCs simultaneously, it is a challenge to attribute their errors to specific KCs and,…
Descriptors: Programming Languages, Undergraduate Students, Learning Processes, Teaching Models
Ünal Çakiroglu; Seval Bilgi – Interactive Learning Environments, 2024
The aim of this explanatory study is to identify the causes of intrinsic cognitive load in programming process. For this purpose, a method based on two dimensions; programming knowledge types (syntactic, semantic, and strategic) and programming constructs was proposed. The proposed method was tested with high school students enrolled in Computer…
Descriptors: Cognitive Processes, Difficulty Level, Programming, Interaction
Guangyao Zhang; Lili Wang; Furong Shang; Xianwen Wang – Journal of Higher Education Policy and Management, 2025
The growth in digitalisation has led to an increasing demand for digital skills in various job sectors. In particular, employers in scientific job areas have shown interest in candidates possessing digital competencies. This study aims to analyse the digital skill requirements for candidates in scientific job opportunities. The content analysis is…
Descriptors: Technological Literacy, Job Skills, Employment Qualifications, Employer Attitudes
Toni Taipalus; Hilkka Grahn; Saima Ritonummi; Valtteri Siitonen; Tero Vartiainen; Denis Zhidkikh – ACM Transactions on Computing Education, 2025
SQL compiler error messages are the primary way users receive feedback when they encounter syntax errors or other issues in their SQL queries. Effective error messages can enhance the user experience by providing clear, informative, and actionable feedback. Despite the age of SQL compilers, it still remains largely unclear what contributes to an…
Descriptors: Computer Science Education, Novices, Information Systems, Programming Languages

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