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Showing 1 to 15 of 31 results Save | Export
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Allie Michael; Abdullah O. Akinde – Assessment Update, 2024
Open-ended responses to surveys can be highly beneficial to higher education institutions, providing clarity and context that quantitative data can sometimes lack. However, analyzing open-ended responses typically takes time and manpower most institutional assessment offices do not have to spare. This study focused on finding a potential solution…
Descriptors: Artificial Intelligence, Natural Language Processing, Student Surveys, Feedback (Response)
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Corrie Wilder; Shannon Calderone – Impacting Education: Journal on Transforming Professional Practice, 2025
This study explores the integration of generative artificial intelligence (AI) into qualitative research within a higher education context. Through a collaborative self-study, a doctoral candidate and their dissertation supervisor examined the application of Google's Gemini 1.5 to analyze interview data from a dissertation of practice (DiP)…
Descriptors: Technology Integration, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
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Phillips, Tanner M.; Saleh, Asmalina; Ozogul, Gamze – International Journal of Artificial Intelligence in Education, 2023
Encouraging teachers to reflect on their instructional practices and course design has been shown to be an effective means of improving instruction and student learning. However, the process of encouraging reflection is difficult; reflection requires quality data, thoughtful analysis, and contextualized interpretation. Because of this, research on…
Descriptors: Reflection, Artificial Intelligence, Natural Language Processing, Data Collection
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Wilson, Joseph; Pollard, Benjamin; Aiken, John M.; Lewandowski, H. J. – Physical Review Physics Education Research, 2022
Surveys have long been used in physics education research to understand student reasoning and inform course improvements. However, to make analysis of large sets of responses practical, most surveys use a closed-response format with a small set of potential responses. Open-ended formats, such as written free response, can provide deeper insights…
Descriptors: Natural Language Processing, Science Education, Physics, Artificial Intelligence
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Abdur R. Shahid; Sushma Mishra – Journal of Information Systems Education, 2024
Due to the increasing demand for efficient, effective, and profitable applications of Artificial Intelligence (AI) in various industries, there is an immense need for professionals with the right skills to meet this demand. As a result, several institutions have started to offer AI programs. Yet, there is a notable gap in academia: the absence of…
Descriptors: Masters Programs, Information Systems, Computer Science Education, Artificial Intelligence
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Yi-Ping Wu; Hui-Hsien Feng; Bo-Ren Mau – Interpreter and Translator Trainer, 2025
Corpus analysis methods have been widely employed in literary translation research by numerous scholars. However, their integration into literary translation training has yet to be developed. With the advancement of AI technology, this paper explores the potential of employing AI-enhanced corpus text analysis and text mining techniques in this…
Descriptors: Translation, Computer Software, Comparative Analysis, Language Styles
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Fitzpatrick, Noel – Educational Philosophy and Theory, 2020
The article sets out to develop the concept of attention as a key aspect to building the possible therapeutics that Bernard Stiegler's recent works have pointed to (The Automatic Society, 2016, The "Neganthropocene", 2018 and "Qu'appelle-t-on" Panser, 2018). The therapeutic aspect of pharmacology takes place through processes…
Descriptors: Educational Philosophy, Pharmacology, Information Technology, Natural Language Processing
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Wonkyung Choi; Jun Jo; Geraldine Torrisi-Steele – International Journal of Adult Education and Technology, 2024
Despite best efforts, the student experience remains poorly understood. One under-explored approach to understanding the student experience is the use of big data analytics. The reported study is a work in progress aimed at exploring the value of big data methods for understanding the student experience. A big data analysis of an open dataset of…
Descriptors: College Students, Data Analysis, Data Collection, Learning Analytics
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Švábenský, Valdemar; Baker, Ryan S.; Zambrano, Andrés; Zou, Yishan; Slater, Stefan – International Educational Data Mining Society, 2023
Students who take an online course, such as a MOOC, use the course's discussion forum to ask questions or reach out to instructors when encountering an issue. However, reading and responding to students' questions is difficult to scale because of the time needed to consider each message. As a result, critical issues may be left unresolved, and…
Descriptors: Generalization, Computer Mediated Communication, MOOCs, State Universities
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Talan, Tarik; Kalinkara, Yusuf – International Society for Technology, Education, and Science, 2022
With the rapid development of science and technology in recent years, the application areas of fuzzy logic have also gained speed. Fuzzy logic is a frequently preferred approach in the educational process, and it can be said that scientific publications on this topic have recently gained momentum in the literature. In this context, the present…
Descriptors: Databases, Research Reports, Foreign Countries, Universities
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Jiménez, Haydée G.; Casanova, Marco A.; Finamore, Anna Carolina; Simões, Gonçalo – International Educational Data Mining Society, 2021
Sentiment Analysis is a field of Natural Language Processing which aims at classifying the author's sentiment in text. This paper first describes a sentiment analysis model for students' comments about professor performance. The model achieved impressive results for comments collected from student surveys conducted at a private university in…
Descriptors: Natural Language Processing, Data Analysis, Classification, Student Surveys
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Liu, Chengyuan; Cui, Jialin; Shang, Ruixuan; Xiao, Yunkai; Jia, Qinjin; Gehringer, Edward – International Educational Data Mining Society, 2022
An online peer-assessment system typically allows students to give textual feedback to their peers, with the goal of helping the peers improve their work. The amount of help that students receive is highly dependent on the quality of the reviews. Previous studies have investigated using machine learning to detect characteristics of reviews (e.g.,…
Descriptors: Peer Evaluation, Feedback (Response), Computer Mediated Communication, Teaching Methods
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Charlotte N. Gunawardena; Yan Chen; Nick Flor; Damien Sánchez – Online Learning, 2023
Gunawardena et al.'s (1997) Interaction Analysis Model (IAM) is one of the most frequently employed frameworks to guide the qualitative analysis of social construction of knowledge online. However, qualitative analysis is time consuming, and precludes immediate feedback to revise online courses while being delivered. To expedite analysis with a…
Descriptors: Models, Learning Processes, Knowledge Level, Online Courses
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Chen, Zhaorui; Demmans, Carrie – International Educational Data Mining Society, 2020
Discussion forums are used to support socio-collaborative learning processes among students in online courses. However, complex forum structures and lengthy discourse require that students spend their limited time searching and filtering through posts to find those that are relevant to them rather than spending that time engaged in other…
Descriptors: Cooperative Learning, Computer Mediated Communication, Recordkeeping, Online Courses
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West, Jason – Curriculum Journal, 2017
Interdisciplinarity requires the collaboration of two or more disciplines to combine their expertise to jointly develop and deliver learning and teaching outcomes appropriate for a subject area. Curricula and assessment mapping are critical components to foster and enhance interdisciplinary learning environments. Emerging careers in data science…
Descriptors: Curriculum Development, Validity, Data Analysis, Interdisciplinary Approach
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