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Ellie Ingle; Andrew Williams – International Journal for Students as Partners, 2025
This case study reports on a co-creation initiative that explored the use of generative artificial intelligence (AI) technologies in the context of higher education assessments. The AI Co-Creators project aimed to promote dialogue between students and staff on the impact of AI with the objective of using AI tools more effectively. The case study…
Descriptors: Teacher Student Relationship, Test Construction, Artificial Intelligence, Man Machine Systems
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Edmund De Leon Evangelista – Contemporary Educational Technology, 2025
The rapid advancement of artificial intelligence (AI) technologies, particularly OpenAI's ChatGPT, has significantly impacted higher education institutions (HEIs), offering opportunities and challenges. While these tools enhance personalized learning and content generation, they threaten academic integrity, especially in assessment environments.…
Descriptors: Artificial Intelligence, Integrity, Educational Strategies, Natural Language Processing
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Andrew M. Olney – Grantee Submission, 2023
Multiple choice questions are traditionally expensive to produce. Recent advances in large language models (LLMs) have led to fine-tuned LLMs that generate questions competitive with human-authored questions. However, the relative capabilities of ChatGPT-family models have not yet been established for this task. We present a carefully-controlled…
Descriptors: Test Construction, Multiple Choice Tests, Test Items, Algorithms
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Thinley Wangdi; Karma Sonam Rigdel; Tashi Dawa; Kinga Tshering – Issues in Educational Research, 2025
In the last two years, there has been a significant increase in research studies on ChatGPT and its role in educational assessment. However, there is no comprehensive systematic literature review (SLR) on the potential use of ChatGPT for educational assessment, particularly with a focus on its practices and limitations. To address this gap, our…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Evaluation Methods
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Shuqiong Luo; Di Zou – European Journal of Education, 2025
Recent AI-based language learning research highlights learners' crucial role, yet university learner readiness in ChatGPT-based English learning remains unexplored. Accordingly, this current research attempted to develop and validate a tool to evaluate university learner readiness for ChatGPT-assisted English learning (LRCEL) to address the…
Descriptors: College Students, Readiness, Artificial Intelligence, Natural Language Processing
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Chahna Gonsalves – Journal of Learning Development in Higher Education, 2023
Multiple-choice quizzes (MCQs) are a popular form of assessment. A rapid shift to online assessment during the COVID-19 pandemic in 2020, drove the uptake of MCQs, yet limited invigilation and wide access to material on the internet allow students to solve the questions via internet search. ChatGPT, an artificial intelligence (AI) agent trained on…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Multiple Choice Tests
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Shin, Jinnie; Gierl, Mark J. – International Journal of Testing, 2022
Over the last five years, tremendous strides have been made in advancing the AIG methodology required to produce items in diverse content areas. However, the one content area where enormous problems remain unsolved is language arts, generally, and reading comprehension, more specifically. While reading comprehension test items can be created using…
Descriptors: Reading Comprehension, Test Construction, Test Items, Natural Language Processing
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Naveed Saif; Sadaqat Ali; Abner Rubin; Soliman Aljarboa; Nabil Sharaf Almalki; Mrim M. Alnfiai; Faheem Khan; Sajid Ullah Khan – Educational Technology & Society, 2025
In the swiftly evolving landscape of education, the fusion of Artificial Intelligence's ingenuity with the dynamic capabilities of chat-bot technology has ignited a transformative paradigm shift. This convergence is not merely a technological integration but a profound reshaping of the fundamental principles of pedagogy, fundamentally redefining…
Descriptors: Artificial Intelligence, Technology Uses in Education, Readiness, Technological Literacy
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Carmen Köhler; Johannes Hartig – Contemporary Educational Technology, 2024
Since ChatGPT-3.5 has been available to the public, the potentials and challenges regarding chatbot usage in education have been widely discussed. However, little evidence exists whether and for which purposes students even apply generative AI tools. The first main purpose of the present study was to develop and test scales that assess students'…
Descriptors: Artificial Intelligence, College Students, Natural Language Processing, Technology Uses in Education
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Lu, Owen H. T.; Huang, Anna Y. Q.; Tsai, Danny C. L.; Yang, Stephen J. H. – Educational Technology & Society, 2021
Human-guided machine learning can improve computing intelligence, and it can accurately assist humans in various tasks. In education research, artificial intelligence (AI) is applicable in many situations, such as predicting students' learning paths and strategies. In this study, we explore the benefits of repetitive practice of short-answer…
Descriptors: Test Items, Artificial Intelligence, Test Construction, Student Evaluation
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Chukharev-Hudilainen, Evgeny; Ockey, Gary J. – ETS Research Report Series, 2021
This paper describes the development and evaluation of Interaction Competence Elicitor (ICE), a spoken dialog system (SDS) for the delivery of a paired oral discussion task in the context of language assessment. The purpose of ICE is to sustain a topic-specific conversation with a test taker in order to elicit discourse that can be later judged to…
Descriptors: Intercultural Communication, Oral Language, Communicative Competence (Languages), Error Analysis (Language)
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Yu, Xiaoli – International Journal of Language Testing, 2021
This study examined the development of text complexity for the past 25 years of reading comprehension passages in the National Matriculation English Test (NMET) in China. Text complexity of 206 reading passages at lexical, syntactic, and discourse levels has been measured longitudinally and compared across the years. The natural language…
Descriptors: Reading Comprehension, Reading Tests, Difficulty Level, Natural Language Processing
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Sheehan, Kathleen M.; Kostin, Irene; Futagi, Yoko; Hemat, Ramin; Zuckerman, Daniel – ETS Research Report Series, 2006
This paper describes the development, implementation, and evaluation of an automated system for predicting the acceptability status of candidate reading-comprehension stimuli extracted from a database of journal and magazine articles. The system uses a combination of classification and regression techniques to predict the probability that a given…
Descriptors: Automation, Prediction, Reading Comprehension, Classification