Publication Date
In 2025 | 4 |
Since 2024 | 8 |
Descriptor
Source
Advances in Physiology… | 1 |
Grantee Submission | 1 |
IEEE Transactions on Learning… | 1 |
Innovation in Language… | 1 |
International Journal of… | 1 |
International Journal of… | 1 |
Journal of Educational… | 1 |
Reading and Writing: An… | 1 |
Author
Ahmet Can Uyar | 1 |
Alex J. Mechaber | 1 |
Amanda Huee-Ping Wong | 1 |
Brian E. Clauser | 1 |
Chandranath Adak | 1 |
Denis Dumas | 1 |
Dilek Büyükahiska | 1 |
Huaibo Wang | 1 |
Ivan Cherh Chiet Low | 1 |
Kai North | 1 |
Karim Sadeghi | 1 |
More ▼ |
Publication Type
Reports - Research | 8 |
Journal Articles | 7 |
Tests/Questionnaires | 1 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
Foreign Language Classroom… | 1 |
International English… | 1 |
Test of English as a Foreign… | 1 |
Test of English for… | 1 |
Torrance Tests of Creative… | 1 |
What Works Clearinghouse Rating
Zebo Xu; Prerit S. Mittal; Mohd. Mohsin Ahmed; Chandranath Adak; Zhenguang G. Cai – Reading and Writing: An Interdisciplinary Journal, 2025
The rise of the digital era has led to a decline in handwriting as the primary mode of communication, resulting in negative effects on handwriting literacy, particularly in complex writing systems such as Chinese. The marginalization of handwriting has contributed to the deterioration of penmanship, defined as the ability to write aesthetically…
Descriptors: Handwriting, Writing Skills, Chinese, Ideography
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
Yishen Song; Qianta Zhu; Huaibo Wang; Qinhua Zheng – IEEE Transactions on Learning Technologies, 2024
Manually scoring and revising student essays has long been a time-consuming task for educators. With the rise of natural language processing techniques, automated essay scoring (AES) and automated essay revising (AER) have emerged to alleviate this burden. However, current AES and AER models require large amounts of training data and lack…
Descriptors: Scoring, Essays, Writing Evaluation, Computer Software
Ahmet Can Uyar; Dilek Büyükahiska – International Journal of Assessment Tools in Education, 2025
This study explores the effectiveness of using ChatGPT, an Artificial Intelligence (AI) language model, as an Automated Essay Scoring (AES) tool for grading English as a Foreign Language (EFL) learners' essays. The corpus consists of 50 essays representing various types including analysis, compare and contrast, descriptive, narrative, and opinion…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Teaching Methods
Selcuk Acar; Denis Dumas; Peter Organisciak; Kelly Berthiaume – Grantee Submission, 2024
Creativity is highly valued in both education and the workforce, but assessing and developing creativity can be difficult without psychometrically robust and affordable tools. The open-ended nature of creativity assessments has made them difficult to score, expensive, often imprecise, and therefore impractical for school- or district-wide use. To…
Descriptors: Thinking Skills, Elementary School Students, Artificial Intelligence, Measurement Techniques
Swapna Haresh Teckwani; Amanda Huee-Ping Wong; Nathasha Vihangi Luke; Ivan Cherh Chiet Low – Advances in Physiology Education, 2024
The advent of artificial intelligence (AI), particularly large language models (LLMs) like ChatGPT and Gemini, has significantly impacted the educational landscape, offering unique opportunities for learning and assessment. In the realm of written assessment grading, traditionally viewed as a laborious and subjective process, this study sought to…
Descriptors: Accuracy, Reliability, Computational Linguistics, Standards
Yuko Hayashi; Yusuke Kondo; Yutaka Ishii – Innovation in Language Learning and Teaching, 2024
Purpose: This study builds a new system for automatically assessing learners' speech elicited from an oral discourse completion task (DCT), and evaluates the prediction capability of the system with a view to better understanding factors deemed influential in predicting speaking proficiency scores and the pedagogical implications of the system.…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Japanese
Karim Sadeghi; Neda Bakhshi – International Journal of Language Testing, 2025
Assessing language skills in an integrative form has drawn the attention of assessment experts in recent years. While some research data exists on integrative listening/reading-to-write assessment, there is comparatively little research literature on listening-to-speak integrated assessment. Also, little attention has been devoted to the role of…
Descriptors: Language Tests, Second Language Learning, English (Second Language), Computer Assisted Testing