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Showing 1 to 15 of 16 results Save | Export
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Rebecka Weegar; Peter Idestam-Almquist – International Journal of Artificial Intelligence in Education, 2024
Machine learning methods can be used to reduce the manual workload in exam grading, making it possible for teachers to spend more time on other tasks. However, when it comes to grading exams, fully eliminating manual work is not yet possible even with very accurate automated grading, as any grading mistakes could have significant consequences for…
Descriptors: Grading, Computer Assisted Testing, Introductory Courses, Computer Science Education
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On-Soon Lee – Journal of Pan-Pacific Association of Applied Linguistics, 2024
Despite the increasing interest in using AI tools as assistant agents in instructional settings, the effectiveness of ChatGPT, the generative pretrained AI, for evaluating the accuracy of second language (L2) writing has been largely unexplored in formative assessment. Therefore, the current study aims to examine how ChatGPT, as an evaluator,…
Descriptors: Foreign Countries, Undergraduate Students, English (Second Language), Second Language Learning
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Dan Song; Alexander F. Tang – Language Learning & Technology, 2025
While many studies have addressed the benefits of technology-assisted L2 writing, limited research has delved into how generative artificial intelligence (GAI) supports students in completing their writing tasks in Mandarin Chinese. In this study, 26 university-level Mandarin Chinese foreign language students completed two writing tasks on two…
Descriptors: Artificial Intelligence, Second Language Learning, Standardized Tests, Writing Tests
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Leonid Chernovaty – Advanced Education, 2024
This first attempt aims to determine the extent of students' covert use of machine translation (MT) in the online assessment of their sight translation, the strategies of such use, and its signs. The study is based on the analysis of target texts (TT) of specialised online sight translation from Ukrainian into English by 13 BA and 10 MA students.…
Descriptors: Computer Assisted Testing, Translation, Ukrainian, English (Second Language)
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Yildirim-Erbasli, Seyma N.; Bulut, Okan; Demmans Epp, Carrie; Cui, Ying – Journal of Educational Technology Systems, 2023
Conversational agents have been widely used in education to support student learning. There have been recent attempts to design and use conversational agents to conduct assessments (i.e., conversation-based assessments: CBA). In this study, we developed CBA with constructed and selected-response tests using Rasa--an artificial intelligence-based…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Computer Mediated Communication, Formative Evaluation
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Nikolic, Sasha; Daniel, Scott; Haque, Rezwanul; Belkina, Marina; Hassan, Ghulam M.; Grundy, Sarah; Lyden, Sarah; Neal, Peter; Sandison, Caz – European Journal of Engineering Education, 2023
ChatGPT, a sophisticated online chatbot, sent shockwaves through many sectors once reports filtered through that it could pass exams. In higher education, it has raised many questions about the authenticity of assessment and challenges in detecting plagiarism. Amongst the resulting frenetic hubbub, hints of potential opportunities in how ChatGPT…
Descriptors: Artificial Intelligence, Performance Based Assessment, Engineering Education, Integrity
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Gerd Kortemeyer; Julian Nöhl; Daria Onishchuk – Physical Review Physics Education Research, 2024
[This paper is part of the Focused Collection in Artificial Intelligence Tools in Physics Teaching and Physics Education Research.] Using a high-stakes thermodynamics exam as the sample (252 students, four multipart problems), we investigate the viability of four workflows for AI-assisted grading of handwritten student solutions. We find that the…
Descriptors: Grading, Physics, Science Instruction, Artificial Intelligence
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Derar Serhan; Natalie Welcome – International Society for Technology, Education, and Science, 2023
Recently, institutions have increased their online course offerings as well as their online degrees. With this significant growth in online offerings, assessment integrity becomes a concern. In response to this concern, many institutions have adopted the use of online proctoring services. The aim of using these online proctoring services is to…
Descriptors: Computer Assisted Testing, Privacy, Student Attitudes, Ethics
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Jia, Jiyou; He, Yunfan – Interactive Technology and Smart Education, 2022
Purpose: The purpose of this study is to design and implement an intelligent online proctoring system (IOPS) by using the advantage of artificial intelligence technology in order to monitor the online exam, which is urgently needed in online learning settings worldwide. As a pilot application, the authors used this system in an authentic…
Descriptors: Artificial Intelligence, Supervision, Computer Assisted Testing, Electronic Learning
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Çinar, Ayse; Ince, Elif; Gezer, Murat; Yilmaz, Özgür – Education and Information Technologies, 2020
Worldwide, open-ended questions that require short answers have been used in many exams in fields of science, such as the International Student Assessment Program (PISA), the International Science and Maths Trends Research (TIMSS). However, multiple-choice questions are used for many exams at the national level in Turkey, especially high school…
Descriptors: Foreign Countries, Computer Assisted Testing, Artificial Intelligence, Grading
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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
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Thao-Trang Huynh-Cam; Long-Sheng Chen; Tzu-Chuen Lu – Journal of Applied Research in Higher Education, 2025
Purpose: This study aimed to use enrollment information including demographic, family background and financial status, which can be gathered before the first semester starts, to construct early prediction models (EPMs) and extract crucial factors associated with first-year student dropout probability. Design/methodology/approach: The real-world…
Descriptors: Foreign Countries, Undergraduate Students, At Risk Students, Dropout Characteristics
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Matayoshi, Jeffrey; Uzun, Hasan; Cosyn, Eric – International Educational Data Mining Society, 2022
Knowledge space theory (KST) is a mathematical framework for modeling and assessing student knowledge. While KST has successfully served as the foundation of several learning systems, recent advancements in machine learning provide an opportunity to improve on purely KST-based approaches to assessing student knowledge. As such, in this work we…
Descriptors: Knowledge Level, Mathematical Models, Learning Experience, Comparative Analysis
Josh Freeman – Higher Education Policy Institute, 2025
Building on our 2024 AI Survey, we surveyed 1,041 full-time undergraduate students through Savanta about their use of generative artificial intelligence (GenAI) tools. In 2025, we find that the student use of AI has surged in the last year, with almost all students (92%) now using AI in some form, up from 66% in 2024, and some 88% having used…
Descriptors: Student Surveys, Student Attitudes, Cheating, Artificial Intelligence
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Liu, Sze-Chu; Hung, Po-Yi – Universal Journal of Educational Research, 2016
The purpose of this study is to evaluate the effectiveness of computer assisted pronunciation instruction in English pronunciation for students in vocational colleges and universities in Taiwan. The participants were fifty-one first-year undergraduate students from a technological university located in central Taiwan. The participants received an…
Descriptors: Pronunciation Instruction, Pronunciation, Computer Assisted Instruction, Foreign Countries
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