Publication Date
In 2025 | 10 |
Since 2024 | 19 |
Since 2021 (last 5 years) | 36 |
Since 2016 (last 10 years) | 56 |
Since 2006 (last 20 years) | 76 |
Descriptor
Source
Author
Bridgeman, Brent | 2 |
Zechner, Klaus | 2 |
Abdalla, Mohamed | 1 |
Abedi, Jamal | 1 |
Aghayi, Mohammad Bagher | 1 |
Ahmet Can Uyar | 1 |
Ahn, Soojin | 1 |
Akbari, Alireza | 1 |
Al-Harthi, Aisha Salim Ali | 1 |
Alex J. Mechaber | 1 |
Allen, Laura | 1 |
More ▼ |
Publication Type
Journal Articles | 82 |
Reports - Research | 66 |
Reports - Descriptive | 10 |
Tests/Questionnaires | 8 |
Reports - Evaluative | 5 |
Information Analyses | 1 |
Numerical/Quantitative Data | 1 |
Education Level
Audience
Location
China | 4 |
Turkey | 3 |
Japan | 2 |
Algeria | 1 |
Australia | 1 |
Denmark | 1 |
Europe | 1 |
Finland | 1 |
Hong Kong | 1 |
Illinois (Urbana) | 1 |
Iran | 1 |
More ▼ |
Laws, Policies, & Programs
No Child Left Behind Act 2001 | 1 |
Assessments and Surveys
What Works Clearinghouse Rating
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
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
Qusai Khraisha; Sophie Put; Johanna Kappenberg; Azza Warraitch; Kristin Hadfield – Research Synthesis Methods, 2024
Systematic reviews are vital for guiding practice, research and policy, although they are often slow and labour-intensive. Large language models (LLMs) could speed up and automate systematic reviews, but their performance in such tasks has yet to be comprehensively evaluated against humans, and no study has tested Generative Pre-Trained…
Descriptors: Peer Evaluation, Research Reports, Artificial Intelligence, Computer Software
Yubin Xu; Lin Liu; Jianwen Xiong; Guangtian Zhu – Journal of Baltic Science Education, 2025
As the development and application of large language models (LLMs) in physics education progress, the well-known AI-based chatbot ChatGPT4 has presented numerous opportunities for educational assessment. Investigating the potential of AI tools in practical educational assessment carries profound significance. This study explored the comparative…
Descriptors: Physics, Artificial Intelligence, Computer Software, Accuracy
Kevin C. Haudek; Xiaoming Zhai – International Journal of Artificial Intelligence in Education, 2024
Argumentation, a key scientific practice presented in the "Framework for K-12 Science Education," requires students to construct and critique arguments, but timely evaluation of arguments in large-scale classrooms is challenging. Recent work has shown the potential of automated scoring systems for open response assessments, leveraging…
Descriptors: Accuracy, Persuasive Discourse, Artificial Intelligence, Learning Management Systems
Fatih Yavuz; Özgür Çelik; Gamze Yavas Çelik – British Journal of Educational Technology, 2025
This study investigates the validity and reliability of generative large language models (LLMs), specifically ChatGPT and Google's Bard, in grading student essays in higher education based on an analytical grading rubric. A total of 15 experienced English as a foreign language (EFL) instructors and two LLMs were asked to evaluate three student…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Computational Linguistics
Andrew Potter; Mitchell Shortt; Maria Goldshtein; Rod D. Roscoe – Grantee Submission, 2025
Broadly defined, academic language (AL) is a set of lexical-grammatical norms and registers commonly used in educational and academic discourse. Mastery of academic language in writing is an important aspect of writing instruction and assessment. The purpose of this study was to use Natural Language Processing (NLP) tools to examine the extent to…
Descriptors: Academic Language, Natural Language Processing, Grammar, Vocabulary Skills
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
Sanosi, Abdulaziz; Abdalla, Mohamed – Australian Journal of Applied Linguistics, 2021
This study aimed to examine the potentials of the NLP approach in detecting discourse markers (DMs), namely okay, in transcribed spoken data. One hundred thirty-eight concordance lines were presented to human referees to judge the functions of okay in them as a DM or Non-DM. After that, the researchers used a Python script written according to the…
Descriptors: Natural Language Processing, Computational Linguistics, Programming Languages, Accuracy
Reagan Mozer; Luke Miratrix; Jackie Eunjung Relyea; James S. Kim – Journal of Educational and Behavioral Statistics, 2024
In a randomized trial that collects text as an outcome, traditional approaches for assessing treatment impact require that each document first be manually coded for constructs of interest by human raters. An impact analysis can then be conducted to compare treatment and control groups, using the hand-coded scores as a measured outcome. This…
Descriptors: Scoring, Evaluation Methods, Writing Evaluation, Comparative Analysis
Shin, Jinnie; Gierl, Mark J. – Language Testing, 2021
Automated essay scoring (AES) has emerged as a secondary or as a sole marker for many high-stakes educational assessments, in native and non-native testing, owing to remarkable advances in feature engineering using natural language processing, machine learning, and deep-neural algorithms. The purpose of this study is to compare the effectiveness…
Descriptors: Scoring, Essays, Writing Evaluation, Computer Software
Crossley, Scott; Wan, Qian; Allen, Laura; McNamara, Danielle – Reading and Writing: An Interdisciplinary Journal, 2023
Synthesis writing is widely taught across domains and serves as an important means of assessing writing ability, text comprehension, and content learning. Synthesis writing differs from other types of writing in terms of both cognitive and task demands because it requires writers to integrate information across source materials. However, little is…
Descriptors: Writing Skills, Cognitive Processes, Essays, Cues
Leech, Tony; Chambers, Lucy – Research Matters, 2022
Two of the central issues in comparative judgement (CJ), which are perhaps underexplored compared to questions of the method's reliability and technical quality, are "what processes do judges use to make their decisions" and "what features do they focus on when making their decisions?" This article discusses both, in the…
Descriptors: Comparative Analysis, Decision Making, Evaluators, Reliability
Taichi Yamashita – Language Testing, 2025
With the rapid development of generative artificial intelligence (AI) frameworks (e.g., the generative pre-trained transformer [GPT]), a growing number of researchers have started to explore its potential as an automated essay scoring (AES) system. While previous studies have investigated the alignment between human ratings and GPT ratings, few…
Descriptors: Artificial Intelligence, English (Second Language), Second Language Learning, Second Language Instruction
Osama Koraishi – Language Teaching Research Quarterly, 2024
This study conducts a comprehensive quantitative evaluation of OpenAI's language model, ChatGPT 4, for grading Task 2 writing of the IELTS exam. The objective is to assess the alignment between ChatGPT's grading and that of official human raters. The analysis encompassed a multifaceted approach, including a comparison of means and reliability…
Descriptors: Second Language Learning, English (Second Language), Language Tests, Artificial Intelligence