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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)
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
Atsushi Miyaoka; Lauren Decker-Woodrow; Nancy Hartman; Barbara Booker; Erin Ottmar – Grantee Submission, 2023
More than ever in the past, researchers have access to broad, educationally relevant text data from sources such as literature databases (e.g., ERIC), an open-ended response from online courses/surveys, online discussion forums, digital essays, and social media. These advances in data availability can dramatically increase the possibilities for…
Descriptors: Coding, Models, Qualitative Research, Focus Groups
Cui, Ying; Guo, Qi; Leighton, Jacqueline P.; Chu, Man-Wai – International Journal of Testing, 2020
This study explores the use of the Adaptive Neuro-Fuzzy Inference System (ANFIS), a neuro-fuzzy approach, to analyze the log data of technology-based assessments to extract relevant features of student problem-solving processes, and develop and refine a set of fuzzy logic rules that could be used to interpret student performance. The log data that…
Descriptors: Inferences, Artificial Intelligence, Data Analysis, Computer Assisted Testing
Nagle, Courtney; Tracy, Tyler; Adams, Gregory; Scutella, Daniel – International Journal of Mathematical Education in Science and Technology, 2017
This paper investigates outcomes of building students' intuitive understanding of a limit as a function's predicted value by examining introductory calculus students' conceptions of limit both before and after instruction. Students' responses suggest that while this approach is successful at reducing the common "limit equals function…
Descriptors: Calculus, Student Reaction, Thinking Skills, Mathematical Logic
ahmed Shafi, Adeela; Hatley, Jenny; Middleton, Tristan; Millican, Richard; Templeton, Sian – Assessment & Evaluation in Higher Education, 2018
This research focuses on the everyday challenge in academic learning of assessment, and argues that academic buoyancy is a key factor in academic success. To scaffold students' learning and effectively support academic buoyancy, there is arguably a need for a better understanding of: (i) what students find most and least useful in their assessment…
Descriptors: Student Evaluation, Feedback (Response), Academic Achievement, Resilience (Psychology)