Publication Date
In 2025 | 8 |
Since 2024 | 27 |
Descriptor
Classification | 27 |
Computer Software | 27 |
Artificial Intelligence | 18 |
Accuracy | 9 |
Comparative Analysis | 9 |
Computational Linguistics | 9 |
Foreign Countries | 9 |
Models | 7 |
Teaching Methods | 6 |
Algorithms | 5 |
Error Patterns | 5 |
More ▼ |
Source
Author
Sangjin Kim | 2 |
Alex J. Mechaber | 1 |
Andrea Horbach | 1 |
Anil Damle | 1 |
Ariunaa Enkhtur | 1 |
Baptiste Moreau-Pernet | 1 |
Beverley Anne Yamamoto | 1 |
Brian E. Clauser | 1 |
Büsra Aras | 1 |
Chang Xu | 1 |
Chi Hong Leung | 1 |
More ▼ |
Publication Type
Journal Articles | 22 |
Reports - Research | 19 |
Reports - Evaluative | 3 |
Dissertations/Theses -… | 2 |
Information Analyses | 2 |
Numerical/Quantitative Data | 1 |
Reports - Descriptive | 1 |
Education Level
Audience
Researchers | 1 |
Students | 1 |
Teachers | 1 |
Location
South Korea | 2 |
Africa | 1 |
Chile | 1 |
China | 1 |
Ghana | 1 |
Massachusetts (Boston) | 1 |
New York | 1 |
Nigeria | 1 |
Portugal | 1 |
South Africa | 1 |
Spain | 1 |
More ▼ |
Laws, Policies, & Programs
Assessments and Surveys
Flesch Reading Ease Formula | 1 |
What Works Clearinghouse Rating
Yiting Wang; Tong Li; Jiahui You; Xinran Zhang; Congkai Geng; Yu Liu – ACM Transactions on Computing Education, 2025
Understanding software modelers' difficulties and evaluating their performance is crucial to Model-Driven Engineering (MDE) education. The software modeling process contains fine-grained information about the modelers' analysis and thought processes. However, existing research primarily focuses on identifying obvious issues in the software…
Descriptors: Computer Software, Engineering Education, Models, Identification
Gamon Savatsomboon; Phamornpun Yurayat; Ong-art Chanprasitchai; Warawut Narkbunnum; Jibon Kumar Sharma; Surapol Svetsomboon – Journal of Practical Studies in Education, 2024
The paper has three major objectives. The first objective of the paper is to synthesize and define common categories of meta-analysis. The second objective is to propose a way to comprehend these common categories of meta-analysis through learning from their respective generic conceptual frameworks. The third objective is to point out which R…
Descriptors: Classification, Meta Analysis, Computer Software, Educational Research
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
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
Yuan Tian; Xi Yang; Suhail A. Doi; Luis Furuya-Kanamori; Lifeng Lin; Joey S. W. Kwong; Chang Xu – Research Synthesis Methods, 2024
RobotReviewer is a tool for automatically assessing the risk of bias in randomized controlled trials, but there is limited evidence of its reliability. We evaluated the agreement between RobotReviewer and humans regarding the risk of bias assessment based on 1955 randomized controlled trials. The risk of bias in these trials was assessed via two…
Descriptors: Risk, Randomized Controlled Trials, Classification, Robotics
Andrea Horbach; Joey Pehlke; Ronja Laarmann-Quante; Yuning Ding – International Journal of Artificial Intelligence in Education, 2024
This paper investigates crosslingual content scoring, a scenario where scoring models trained on learner data in one language are applied to data in a different language. We analyze data in five different languages (Chinese, English, French, German and Spanish) collected for three prompts of the established English ASAP content scoring dataset. We…
Descriptors: Contrastive Linguistics, Scoring, Learning Analytics, Chinese
Rumeysa Demir; Metin Demir – Educational Process: International Journal, 2025
Background/purpose: This study aims to reveal in detail the extent to which the variables in The Primary and Secondary Education Institutions Scholarship Examination (PSEISE) predict the success of students on the scholarship exam with the help of artificial neural networks (ANN). In addition, in light of the findings obtained as a result of the…
Descriptors: Elementary Secondary Education, Foreign Countries, Artificial Intelligence, Computer Software
Ming Li; Ariunaa Enkhtur; Beverley Anne Yamamoto; Fei Cheng; Lilan Chen – Open Praxis, 2025
Generative Artificial Intelligence (GAI) models, such as ChatGPT, may inherit or amplify societal biases due to their training on extensive datasets. With the increasing usage of GAI by students, faculty, and staff in higher education institutions (HEIs), it is urgent to examine the ethical issues and potential biases associated with this…
Descriptors: Artificial Intelligence, Ethics, Technology Integration, Computer Software
Yoonjae Noh; YoonIl Yoon; Sangjin Kim – Measurement: Interdisciplinary Research and Perspectives, 2024
The default risk, one of the main risk factors for bonds, should be measured and reflected in the bond yield. Particularly, in the case of financial companies that treat bonds as a major product, failure to properly identify and filter customers' workout status adversely affects returns. This study proposes a two-stage classification algorithm for…
Descriptors: Prediction, Classification, Accuracy, Risk
Jehanzeb Rashid Cheema – Journal of Education in Muslim Societies, 2024
This study explores the relationship between the Spiral Dynamics and the 3H (head, heart, hands) models of human growth and development, using constructs such as empathy, moral reasoning, forgiveness, and community mindedness that have been shown to have implications for education. The specific research question is, "Can a combination of…
Descriptors: Correlation, Factor Analysis, Computer Software, Moral Values
Hyemin Yoon; HyunJin Kim; Sangjin Kim – Measurement: Interdisciplinary Research and Perspectives, 2024
We have maintained the customer grade system that is being implemented to customers with excellent performance through customer segmentation for years. Currently, financial institutions that operate the customer grade system provide similar services based on the score calculation criteria, but the score calculation criteria vary from the financial…
Descriptors: Classification, Artificial Intelligence, Prediction, Decision Making
Rebeckah K. Fussell; Megan Flynn; Anil Damle; Michael F. J. Fox; N. G. Holmes – Physical Review Physics Education Research, 2025
Recent advancements in large language models (LLMs) hold significant promise for improving physics education research that uses machine learning. In this study, we compare the application of various models for conducting a large-scale analysis of written text grounded in a physics education research classification problem: identifying skills in…
Descriptors: Physics, Computational Linguistics, Classification, Laboratory Experiments
Xieling Chen; Haoran Xie; Di Zou; Lingling Xu; Fu Lee Wang – Educational Technology & Society, 2025
In massive open online course (MOOC) environments, computer-based analysis of course reviews enables instructors and course designers to develop intervention strategies and improve instruction to support learners' learning. This study aimed to automatically and effectively identify learners' concerned topics within their written reviews. First, we…
Descriptors: Classification, MOOCs, Teaching Skills, Artificial Intelligence
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
Xuandong Zhao – ProQuest LLC, 2024
The rapid advancement of powerful Large Language Models (LLMs), such as ChatGPT and Llama, has revolutionized the world by bringing new creative possibilities and enhancing productivity. However, these advancements also pose significant challenges and risks, including the potential for misuse in the form of fake news, academic dishonesty,…
Descriptors: Computational Linguistics, Intellectual Property, Artificial Intelligence, Productivity
Previous Page | Next Page »
Pages: 1 | 2