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Davi Bernardo Silva; Deborah Ribeiro Carvalho; Carlos N. Silla – IEEE Transactions on Learning Technologies, 2024
Throughout a programming course, students develop various source code tasks. Using these tasks to track students' progress can provide clues to the strengths and weaknesses found in each learning topic. This practice allows the teacher to intervene in learning in the first few weeks of class and maximize student gains. However, the biggest…
Descriptors: Computation, Models, Ability Grouping, Programming
Samuel Mergendahl – ProQuest LLC, 2024
While the introduction of memory-safe programming languages into embedded, Cyber-Physical Systems (CPS) offers an opportunity to eliminate many system vulnerabilities, a pragmatic adoption of memory-safe programming languages often necessitates incremental deployment due to practical development constraints, such as the size of many legacy code…
Descriptors: Programming Languages, Information Systems, Information Security, Memory
Shraddha Govind Barke – ProQuest LLC, 2024
The dream of intelligent assistants to enhance programmer productivity has now become a concrete reality, with rapid advances in artificial intelligence. Large language models (LLMs) have demonstrated impressive capabilities in various domains based on the vast amount of data used to train them. However, tasks which require structured reasoning or…
Descriptors: Artificial Intelligence, Symbolic Learning, Programming, Programming Languages
Austin Wyman; Zhiyong Zhang – Grantee Submission, 2025
Automated detection of facial emotions has been an interesting topic for multiple decades in social and behavioral research but is only possible very recently. In this tutorial, we review three popular artificial intelligence based emotion detection programs that are accessible to R programmers: Google Cloud Vision, Amazon Rekognition, and…
Descriptors: Artificial Intelligence, Algorithms, Computer Software, Identification
Alex Yue Feng Zhu – British Journal of Educational Technology, 2024
Research has shown that even though standardized financial education has gained prevalence to promote financial literacy over the past decade, it has had little effect on personal financial planning. The present study used a randomized control trial to examine the effectiveness of a Python-based personalized financial projection on young working…
Descriptors: Financial Education, Programming Languages, Financial Literacy, Money Management
Lucy D'Agostino McGowan; Travis Gerke; Malcolm Barrett – Journal of Statistics and Data Science Education, 2024
This article introduces a collection of four datasets, similar to Anscombe's quartet, that aim to highlight the challenges involved when estimating causal effects. Each of the four datasets is generated based on a distinct causal mechanism: the first involves a collider, the second involves a confounder, the third involves a mediator, and the…
Descriptors: Statistics Education, Programming Languages, Statistical Inference, Causal Models
Elena Novak; Chia-Ling Kuo; Janet Lynne Tassell; Grace Morris – TechTrends: Linking Research and Practice to Improve Learning, 2024
Recently, creativity has been acknowledged for its importance in improving computer science learning and attitudes. However, very little is known about how to integrate creativity in preservice teacher computing education. Toward this end, we developed a creativity-enhancement intervention in an online Creative Computing instructional module to…
Descriptors: Preservice Teachers, Elementary School Teachers, Creativity, Intervention
Yuhan Lin – ProQuest LLC, 2024
Block-based programming environments have become increasingly commonplace in computer science education. Despite a rapidly expanding ecosystem of block-based programming environments, text-based languages remain the dominant programming paradigm outside of educational contexts, motivating the transition from block-based to text-based programming.…
Descriptors: Computer Science Education, Programming, Coding, Scaffolding (Teaching Technique)
Maria Llambrich; Pau Satorra; Eudald Correig; Josep Gumà; Jesús Brezmes; Cristian Tebé; Raquel Cumeras – Research Synthesis Methods, 2024
Meta-analysis is a useful tool in clinical research, as it combines the results of multiple clinical studies to improve precision when answering a particular scientific question. While there has been a substantial increase in publications using meta-analysis in various clinical research topics, the number of published meta-analyses in metabolomics…
Descriptors: Meta Analysis, Programming Languages, Information Technology, Computer Oriented Programs
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
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
Mark W. Isken – INFORMS Transactions on Education, 2025
A staple of many spreadsheet-based management science courses is the use of Excel for activities such as model building, sensitivity analysis, goal seeking, and Monte-Carlo simulation. What might those things look like if carried out using Python? We describe a teaching module in which Python is used to do typical Excel-based modeling and…
Descriptors: Spreadsheets, Models, Programming Languages, Monte Carlo Methods
Suppanut Sriutaisuk; Yu Liu; Seungwon Chung; Hanjoe Kim; Fei Gu – Educational and Psychological Measurement, 2025
The multiple imputation two-stage (MI2S) approach holds promise for evaluating the model fit of structural equation models for ordinal variables with multiply imputed data. However, previous studies only examined the performance of MI2S-based residual-based test statistics. This study extends previous research by examining the performance of two…
Descriptors: Structural Equation Models, Error of Measurement, Programming Languages, Goodness of Fit
Andrea Maffia; Carola Manolino; Elisa Miragliotta – Educational Studies in Mathematics, 2025
Research literature about visually impaired students' approach to mathematics is still very scarce, especially in the case of algebra, even though mathematical content is becoming increasingly accessible thanks to assistive technologies. This paper presents a case study aimed at describing a blind subject's process of algebraic symbol manipulation…
Descriptors: Algebra, Blindness, Mathematics Education, Symbols (Mathematics)
Amedeo Pachera; Stefania Dumbrava; Angela Bonifati; Andrea Mauri – ACM Transactions on Computing Education, 2025
Query languages are the foundations of database teaching and education practices. The broad adoption of graph databases contrasts with the limited research into how they are taught. Contrary to relational databases, graph databases allow navigational queries with higher expressivity and lack an a priori schema. In this article, we design a…
Descriptors: Error Patterns, Graphs, Programming Languages, Databases

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