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Bhagya Munasinghe; Tim Bell; Anthony Robins – ACM Transactions on Computing Education, 2023
In learning to program and understanding how a programming language controls a computer, learners develop both insights and misconceptions whilst their mental models are gradually refined. It is important that the learner is able to distinguish the different elements and roles of a computer (compiler, interpreter, memory, etc.), which novice…
Descriptors: Computation, Thinking Skills, Programming, Programming Languages
Tetsuo Tanaka; Ryo Horiuchi; Mari Ueda – International Association for Development of the Information Society, 2024
We evaluate the effectiveness of reading aloud a program code in learning programming from a neuroscientific perspective by measuring brain activity using a near-infrared spectroscopy device. The results show that when reading aloud and then reading silently, brain activity increases during reading aloud; a similar trend is observed when the…
Descriptors: Oral Reading, Programming, Coding, Neurosciences
Phung, Tung; Cambronero, José; Gulwani, Sumit; Kohn, Tobias; Majumdarm, Rupak; Singla, Adish; Soares, Gustavo – International Educational Data Mining Society, 2023
Large language models (LLMs), such as Codex, hold great promise in enhancing programming education by automatically generating feedback for students. We investigate using LLMs to generate feedback for fixing syntax errors in Python programs, a key scenario in introductory programming. More concretely, given a student's buggy program, our goal is…
Descriptors: Computational Linguistics, Feedback (Response), Programming, Computer Science Education
Maya B. Mathur – Research Synthesis Methods, 2024
As traditionally conceived, publication bias arises from selection operating on a collection of individually unbiased estimates. A canonical form of such selection across studies (SAS) is the preferential publication of affirmative studies (i.e., those with significant, positive estimates) versus nonaffirmative studies (i.e., those with…
Descriptors: Meta Analysis, Research Reports, Research Methodology, Research Problems
Buteau, Chantal; Muller, Eric; Mgombelo, Joyce; Sacristán, Ana Isabel; Dreise, Kirstin – Digital Experiences in Mathematics Education, 2020
In this article, we seek to understand how university students learn to use programming as an instrument for 'authentic' mathematical investigations. We use the instrumental approach as a framework, focusing on how the transformation of the programming language into an instrument requires that the user develops or mobilizes multiple schemes at…
Descriptors: Undergraduate Students, Programming, Mathematics Education, Mathematics Skills
Goldenberg, E. Paul; Carter, Cynthia J.; Mark, June; Reed, Kristen; Spencer, Deborah; Coleman, Kate – Digital Experiences in Mathematics Education, 2021
This article reports on an exploration of how second-graders can learn mathematics through programming. We started from the theory that a suitably designed programming language can serve children as a language for expressing and experimenting with mathematical ideas and processes in order to do mathematics and thereby, with appropriate tasks and…
Descriptors: Elementary School Students, Grade 2, Elementary School Mathematics, Programming
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
Allbee, Quinn; Barber, Robert – Biochemistry and Molecular Biology Education, 2021
Biology is a data-driven discipline facilitated greatly by computer programming skills. This article describes an introductory experiential programming activity that can be integrated into distance learning environments. Students are asked to develop their own Python programs to identify the nature of alleles linked to disease. This activity…
Descriptors: Genetics, Science Instruction, Programming Languages, Biology
Tan, Teck Kiang – Practical Assessment, Research & Evaluation, 2023
Researchers often have hypotheses concerning the state of affairs in the population from which they sampled their data to compare group means. The classical frequentist approach provides one way of carrying out hypothesis testing using ANOVA to state the null hypothesis that there is no difference in the means and proceed with multiple comparisons…
Descriptors: Comparative Analysis, Hypothesis Testing, Statistical Analysis, Guidelines
Michael Kolling – Informatics in Education, 2024
The principles of programming language design for learning and teaching have been described and discussed for several decades. Most influential was the work of Niklaus Wirth, describing principles such as simplicity, modularity, orthogonality, and readability. So why is this still an area of fundamental disagreement among educators? Why can…
Descriptors: Programming Languages, Design, Novices, Computer Science Education
Robertson, Judy; Gray, Stuart; Martin, Toye; Booth, Josephine – International Journal of Computer Science Education in Schools, 2020
We argue that understanding the cognitive foundations of computational thinking will assist educators to improve children's learning in computing. We explain the conceptual relationship between executive functions and aspects of computational thinking. We present initial empirical data from 23 eleven year old learners which investigates the…
Descriptors: Executive Function, Computation, Thinking Skills, Mathematics Skills
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
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
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
Laurent Cervoni; Julien Brasseur – International Association for Development of the Information Society, 2022
A Prolog program consists of a set of facts and rules rather than imperative statements, commonly used in most other programming languages. Therefore, the Prolog language is used to encode logic, from which the inference engine deduces logical conclusions. In this article, we argue that the use of the Prolog language can be useful to help students…
Descriptors: Teaching Methods, Mathematics Instruction, Problem Solving, Programming Languages