NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing 1 to 15 of 45 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Selcuk Acar; Peter Organisciak; Denis Dumas – Journal of Creative Behavior, 2025
In this three-study investigation, we applied various approaches to score drawings created in response to both Form A and Form B of the Torrance Tests of Creative Thinking-Figural (broadly TTCT-F) as well as the Multi-Trial Creative Ideation task (MTCI). We focused on TTCT-F in Study 1, and utilizing a random forest classifier, we achieved 79% and…
Descriptors: Scoring, Computer Assisted Testing, Models, Correlation
Peer reviewed Peer reviewed
Direct linkDirect link
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
Jing Ma – ProQuest LLC, 2024
This study investigated the impact of scoring polytomous items later on measurement precision, classification accuracy, and test security in mixed-format adaptive testing. Utilizing the shadow test approach, a simulation study was conducted across various test designs, lengths, number and location of polytomous item. Results showed that while…
Descriptors: Scoring, Adaptive Testing, Test Items, Classification
Peer reviewed Peer reviewed
Direct linkDirect link
Firoozi, Tahereh; Bulut, Okan; Epp, Carrie Demmans; Naeimabadi, Ali; Barbosa, Denilson – Journal of Applied Testing Technology, 2022
Automated Essay Scoring (AES) using neural networks has helped increase the accuracy and efficiency of scoring students' written tasks. Generally, the improved accuracy of neural network approaches has been attributed to the use of modern word embedding techniques. However, which word embedding techniques produce higher accuracy in AES systems…
Descriptors: Computer Assisted Testing, Scoring, Essays, Artificial Intelligence
Peer reviewed Peer reviewed
Direct linkDirect link
Cathy Cavanaugh; Bryn Humphrey; Paige Pullen – International Journal on E-Learning, 2024
To address needs in one US state to provide a professional development micro-credential for tens of thousands of educators, we automated an assignment scoring workflow in an online course by developing and refining an AI model to scan submitted assignments and score them against a rubric. This article outlines the AI model development process and…
Descriptors: Artificial Intelligence, Automation, Scoring, Microcredentials
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Tri Sedya Febrianti; Siti Fatimah; Yuni Fitriyah; Hanifah Nurhayati – International Journal of Education in Mathematics, Science and Technology, 2024
Assessing students' understanding of circle-related material through subjective tests is effective, though grading these tests can be challenging and often requires technological support. ChatGPT has shown promise in providing reliable and objective evaluations. Many teachers in Indonesia, however, continue to face difficulties integrating…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Scoring, Tests
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Wang, Wei; Dorans, Neil J. – ETS Research Report Series, 2021
Agreement statistics and measures of prediction accuracy are often used to assess the quality of two measures of a construct. Agreement statistics are appropriate for measures that are supposed to be interchangeable, whereas prediction accuracy statistics are appropriate for situations where one variable is the target and the other variables are…
Descriptors: Classification, Scaling, Prediction, Accuracy
Peer reviewed Peer reviewed
Direct linkDirect link
Kunal Sareen – Innovations in Education and Teaching International, 2024
This study examines the proficiency of Chat GPT, an AI language model, in answering questions on the Situational Judgement Test (SJT), a widely used assessment tool for evaluating the fundamental competencies of medical graduates in the UK. A total of 252 SJT questions from the "Oxford Assess and Progress: Situational Judgement" Test…
Descriptors: Ethics, Decision Making, Artificial Intelligence, Computer Software
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Zhang, Mengxue; Heffernan, Neil; Lan, Andrew – International Educational Data Mining Society, 2023
Automated scoring of student responses to open-ended questions, including short-answer questions, has great potential to scale to a large number of responses. Recent approaches for automated scoring rely on supervised learning, i.e., training classifiers or fine-tuning language models on a small number of responses with human-provided score…
Descriptors: Scoring, Computer Assisted Testing, Mathematics Instruction, Mathematics Tests
Botarleanu, Robert-Mihai; Dascalu, Mihai; Allen, Laura K.; Crossley, Scott Andrew; McNamara, Danielle S. – Grantee Submission, 2021
Text summarization is an effective reading comprehension strategy. However, summary evaluation is complex and must account for various factors including the summary and the reference text. This study examines a corpus of approximately 3,000 summaries based on 87 reference texts, with each summary being manually scored on a 4-point Likert scale.…
Descriptors: Computer Assisted Testing, Scoring, Natural Language Processing, Computer Software
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
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Lu, Chang; Cutumisu, Maria – International Educational Data Mining Society, 2021
Digitalization and automation of test administration, score reporting, and feedback provision have the potential to benefit large-scale and formative assessments. Many studies on automated essay scoring (AES) and feedback generation systems were published in the last decade, but few connected AES and feedback generation within a unified framework.…
Descriptors: Learning Processes, Automation, Computer Assisted Testing, Scoring
Wood, Scott; Yao, Erin; Haisfield, Lisa; Lottridge, Susan – ACT, Inc., 2021
For assessment professionals who are also automated scoring (AS) professionals, there is no single set of standards of best practice. This paper reviews the assessment and AS literature to identify key standards of best practice and ethical behavior for AS professionals and codifies those standards in a single resource. Having a unified set of AS…
Descriptors: Standards, Best Practices, Computer Assisted Testing, Scoring
Peer reviewed Peer reviewed
Direct linkDirect link
Pfordresher, Peter Q.; Demorest, Steven M. – Journal of Research in Music Education, 2021
The purpose of this study was to analyze a large sample of volunteers from the general population who were tested with an identical online measure of singing accuracy. A sample of 632 participants completed the Seattle Singing Accuracy Protocol (SSAP), a standardized measure of singing accuracy, available online, that includes a test of pitch…
Descriptors: Correlation, Accuracy, Singing, Computer Assisted Testing
Previous Page | Next Page »
Pages: 1  |  2  |  3