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Rubén Buitrago; Jesús Salinas; Oscar Boude – Knowledge Management & E-Learning, 2024
Design patterns for learning are about articulating, testing and sharing the principles of problem solving in the educational context. In this way, multiple patterns are developed to solve common problems, described in various pattern language formats. Therefore, this work is about characterizing and establishing functional relationships between…
Descriptors: Delphi Technique, Programming Languages, Programming, Computer Software
Peter Baldwin; Victoria Yaneva; Kai North; Le An Ha; Yiyun Zhou; Alex J. Mechaber; Brian E. Clauser – Journal of Educational Measurement, 2025
Recent developments in the use of large-language models have led to substantial improvements in the accuracy of content-based automated scoring of free-text responses. The reported accuracy levels suggest that automated systems could have widespread applicability in assessment. However, before they are used in operational testing, other aspects of…
Descriptors: Artificial Intelligence, Scoring, Computational Linguistics, Accuracy
Xinping Zhang – International Journal of Information and Communication Technology Education, 2024
As technology continues to evolve, the process of English translation has become easier. A technology called widget, which is used in modern research, provides an efficient graphical user interface for the interaction between the user and the application. This paper compares the newly proposed wireless widget system with existing models of English…
Descriptors: Internet, Computer Software, Information Technology, Information Storage
Chi Hong Leung; Winslet Ting Yan Chan – Asian Journal of Contemporary Education, 2025
This paper explores the efficacy of ChatGPT, a generative artificial intelligence in educational contexts, particularly concerning its potential to assist students in overcoming academic challenges while highlighting its limitations. ChatGPT is suitable for solving general problems. When a student comes across academic challenges, ChatGPT may…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Error Patterns
Özlem Çeziktürk – International Journal of Mathematical Education in Science and Technology, 2025
I explore some facts about the area, position, etc. of the Steiner ellipse using GeoGebra and numerical analysis. Students can use these for mathematical inquiry.
Descriptors: Computer Software, Mathematics Instruction, Elective Courses, Teacher Education Programs
Wendy Swenson Roth – Journal of Education for Business, 2024
Spreadsheets help businesses run effectively and efficiently. However, many spreadsheets contain errors. Research provides taxonomies and guidance on preventing spreadsheet errors; this information often is not incorporated into training. Training students to use Excel functions and good spreadsheet practices is critical. This instructional…
Descriptors: Spreadsheets, Business Skills, Error Patterns, Business Administration Education
James McGibney – ProQuest LLC, 2024
This phenomenological study's objective was to review the existing initiatives for cybersecurity awareness and training that are in place for the K-12 education system throughout the United States. Every facet of life is now plagued by the potential, perceived, and real threat of cyber warfare, which includes, but is not limited to, K-12 schools…
Descriptors: Information Security, Computer Security, Crime, Kindergarten
Shari Cavicchi; Abdulaziz Abubshait; Giulia Siri; Magda Mustile; Francesca Ciardo – Cognitive Research: Principles and Implications, 2025
Cognitive load occurs when the demands of a task surpass the available processing capacity, straining mental resources and potentially impairing performance efficiency, such as increasing the number of errors in a task. Owing to its ubiquity in real-world scenarios, the existence of offloading strategies to reduce cognitive load is not new to…
Descriptors: Robotics, Psychological Patterns, Cognitive Processes, Computer Software
Guozhu Ding; Xiangyi Shi; Shan Li – Education and Information Technologies, 2024
In this study, we developed a classification system of programming errors based on the historical data of 680,540 programming records collected on the Online Judge platform. The classification system described six types of programming errors (i.e., syntax, logical, type, writing, misunderstanding, and runtime errors) and their connections with…
Descriptors: Programming, Computer Science Education, Classification, Graphs
Geoffrey Currie; Josie Currie; Sam Anderson; Johnathan Hewis – Health Education Journal, 2024
Introduction: In Australia, 54.3% of medical students are women yet they remain under-represented in stereotypical perspectives of medicine. While potentially transformative, generative artificial intelligence (genAI) has the potential for errors, misrepresentations and bias. GenAI text-to-image production could reinforce gender biases making it…
Descriptors: Gender Bias, Artificial Intelligence, Computer Software, Medical Education
Mimi Ismail; Ahmed Al - Badri; Said Al - Senaidi – Journal of Education and e-Learning Research, 2025
This study aimed to reveal the differences in individuals' abilities, their standard errors, and the psychometric properties of the test according to the two methods of applying the test (electronic and paper). The descriptive approach was used to achieve the study's objectives. The study sample consisted of 74 male and female students at the…
Descriptors: Achievement Tests, Computer Assisted Testing, Psychometrics, Item Response Theory
Kristina Litherland; Anders Kluge – Computer Science Education, 2024
Background and Context: We explore the potential for understanding the processes involved in students' programming based on studying their behaviour and dialogue with each other and "conversations" with their programs. Objective: Our aim is to explore how a perspective of inquiry can be used as a point of departure for insights into how…
Descriptors: Programming, Programming Languages, Secondary School Students, Computer Science Education
Kyeng Gea Lee; Mark J. Lee; Soo Jung Lee – International Journal of Technology in Education and Science, 2024
Online assessment is an essential part of online education, and if conducted properly, has been found to effectively gauge student learning. Generally, textbased questions have been the cornerstone of online assessment. Recently, however, the emergence of generative artificial intelligence has added a significant challenge to the integrity of…
Descriptors: Artificial Intelligence, Computer Software, Biology, Science Instruction
Yi Gui – ProQuest LLC, 2024
This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…
Descriptors: Writing Tests, Natural Language Processing, Writing Evaluation, Scoring
Yun Huang; Christian Dieter Schunn; Julio Guerra; Peter L. Brusilovsky – ACM Transactions on Computing Education, 2024
Programming skills are increasingly important to the current digital economy, yet these skills have long been regarded as challenging to acquire. A central challenge in learning programming skills involves the simultaneous use of multiple component skills. This article investigates why students struggle with integrating component skills--a…
Descriptors: Programming, Computer Science Education, Error Patterns, Classification
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