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Showing 1 to 15 of 54 results Save | Export
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Kangkang Li; Chengyang Qian; Xianmin Yang – Education and Information Technologies, 2025
In learnersourcing, automatic evaluation of student-generated content (SGC) is significant as it streamlines the evaluation process, provides timely feedback, and enhances the objectivity of grading, ultimately supporting more effective and efficient learning outcomes. However, the methods of aggregating students' evaluations of SGC face the…
Descriptors: Student Developed Materials, Educational Quality, Automation, Artificial Intelligence
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Reese Butterfuss; Harold Doran – Educational Measurement: Issues and Practice, 2025
Large language models are increasingly used in educational and psychological measurement activities. Their rapidly evolving sophistication and ability to detect language semantics make them viable tools to supplement subject matter experts and their reviews of large amounts of text statements, such as educational content standards. This paper…
Descriptors: Alignment (Education), Academic Standards, Content Analysis, Concept Mapping
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Rui Wang; Haili Ling; Jie Chen; Huijuan Fu – International Journal of Distance Education Technologies, 2025
This study adopted the Latent Dirichlet Allocation (LDA) to extract learners' needs based on 70,145 reviews from online course designed for software design and development in China and then applied Quality Function Deployment (QFD) to map learners' differentiated needs into quality attributes. Taking national first-class courses as the…
Descriptors: Educational Improvement, Student Needs, Computer Science Education, Foreign Countries
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Putnikovic, Marko; Jovanovic, Jelena – IEEE Transactions on Learning Technologies, 2023
Automatic grading of short answers is an important task in computer-assisted assessment (CAA). Recently, embeddings, as semantic-rich textual representations, have been increasingly used to represent short answers and predict the grade. Despite the recent trend of applying embeddings in automatic short answer grading (ASAG), there are no…
Descriptors: Automation, Computer Assisted Testing, Grading, Natural Language Processing
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Jessica M. Lammert; Angela C. Roberts; Ken McRae; Laura J. Batterink; Blake E. Butler – Journal of Speech, Language, and Hearing Research, 2025
Purpose: Recent advances in artificial intelligence provide opportunities to capture and represent complex features of human language in a more automated manner, offering potential means of improving the efficiency of language assessment. This review article presents computerized approaches for the analysis of narrative language and identification…
Descriptors: Identification, Natural Language Processing, Artificial Intelligence, Barriers
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Yucheng Chu; Peng He; Hang Li; Haoyu Han; Kaiqi Yang; Yu Xue; Tingting Li; Yasemin Copur-Gencturk; Joseph Krajcik; Jiliang Tang – International Educational Data Mining Society, 2025
Short answer assessment is a vital component of science education, allowing evaluation of students' complex three-dimensional understanding. Large language models (LLMs) that possess human-like ability in linguistic tasks are increasingly popular in assisting human graders to reduce their workload. However, LLMs' limitations in domain knowledge…
Descriptors: Artificial Intelligence, Science Education, Technology Uses in Education, Natural Language Processing
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Aditi Jhaveri – Journal of the Scholarship of Teaching and Learning, 2025
This essay examines the potential impact of paid-for or premium language models, where some students may be able to afford advanced models generating superior outputs while others could face inequities due to financial constraints. It explores how this dynamic can exacerbate the digital divide, challenge traditional as well as more recent…
Descriptors: Natural Language Processing, Artificial Intelligence, Technology Uses in Education, Equal Education
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Stephanie Fuchs; Alexandra Werth; Cristóbal Méndez; Jonathan Butcher – Journal of Engineering Education, 2025
Background: High-quality feedback is crucial for academic success, driving student motivation and engagement while research explores effective delivery and student interactions. Advances in artificial intelligence (AI), particularly natural language processing (NLP), offer innovative methods for analyzing complex qualitative data such as feedback…
Descriptors: Artificial Intelligence, Training, Data Analysis, Natural Language Processing
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Ishrat Ahmed; Wenxing Liu; Rod D. Roscoe; Elizabeth Reilley; Danielle S. McNamara – Grantee Submission, 2025
Large language models (LLMs) are increasingly being utilized to develop tools and services in various domains, including education. However, due to the nature of the training data, these models are susceptible to inherent social or cognitive biases, which can influence their outputs. Furthermore, their handling of critical topics, such as privacy…
Descriptors: Artificial Intelligence, Natural Language Processing, Computer Mediated Communication, College Students
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Maira Klyshbekova; Pamela Abbott – Electronic Journal of e-Learning, 2024
There is a current debate about the extent to which ChatGPT, a natural language AI chatbot, can disrupt processes in higher education settings. The chatbot is capable of not only answering queries in a human-like way within seconds but can also provide long tracts of texts which can be in the form of essays, emails, and coding. In this study, in…
Descriptors: Artificial Intelligence, Higher Education, Technology Uses in Education, Evaluation Methods
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Soomaiya Hamid; Narmeen Zakaria Bawany – Interactive Learning Environments, 2024
E-learning is the process of sharing knowledge out of the traditional classrooms through different online tools using internet. The availability and use of these tools are not easy for every student. Many institutions gather e-learning feedback to know the problems of students to improve their systems. In e-learning systems, typically a high…
Descriptors: Feedback (Response), Electronic Learning, Automation, Classification
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Marrone, Rebecca; Cropley, David H.; Wang, Z. – Creativity Research Journal, 2023
Creativity is now accepted as a core 21st-century competency and is increasingly an explicit part of school curricula around the world. Therefore, the ability to assess creativity for both formative and summative purposes is vital. However, the "fitness-for-purpose" of creativity tests has recently come under scrutiny. Current creativity…
Descriptors: Automation, Evaluation Methods, Creative Thinking, Mathematics Education
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Mohammadreza Farrokhnia; Seyyed Kazem Banihashem; Omid Noroozi; Arjen Wals – Innovations in Education and Teaching International, 2024
ChatGPT is an AI tool that has sparked debates about its potential implications for education. We used the SWOT analysis framework to outline ChatGPT's strengths and weaknesses and to discuss its opportunities for and threats to education. The strengths include using a sophisticated natural language model to generate plausible answers,…
Descriptors: Artificial Intelligence, Synchronous Communication, Computer Software, Technology Uses in Education
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Ibrahim Adeshola; Adeola Praise Adepoju – Interactive Learning Environments, 2024
The launch of OpenAI ChatGPT's language-generation model has raised alarms within many sectors, especially the academic sector. Several academicians have urged universities to develop new forms of assessment after the launch of ChatGPT, which solves academic questions in less than a few minutes. Academic cheating is not a new phenomenon, and the…
Descriptors: Opportunities, Barriers, Artificial Intelligence, Natural Language Processing
Ying Fang; Rod D. Roscoe; Danielle S. McNamara – Grantee Submission, 2023
Artificial Intelligence (AI) based assessments are commonly used in a variety of settings including business, healthcare, policing, manufacturing, and education. In education, AI-based assessments undergird intelligent tutoring systems as well as many tools used to evaluate students and, in turn, guide learning and instruction. This chapter…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Student Evaluation, Evaluation Methods
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