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Showing 1 to 15 of 51 results Save | Export
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Kelli A. Bird; Benjamin L. Castleman; Yifeng Song – Journal of Policy Analysis and Management, 2025
Predictive analytics are increasingly pervasive in higher education. However, algorithmic bias has the potential to reinforce racial inequities in postsecondary success. We provide a comprehensive and translational investigation of algorithmic bias in two separate prediction models--one predicting course completion, the second predicting degree…
Descriptors: Algorithms, Technology Uses in Education, Bias, Racism
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Thomas McAndrew; Rochelle L. Frounfelker; Lorenzo Servitje – PRIMUS, 2024
There is a need for public health undergraduates to acquire skills in data collection, statistical programming, and infectious diseases modeling. Public health officials and accreditation bodies underline the importance of a cumulative, "real-world" experience as part of a student's education. The Watermelon Meow Meow (WMM) outbreak is a…
Descriptors: Undergraduate Students, Graduate Students, Statistics, Data Collection
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Hongyu Liu; Young Chun Ko – International Journal of Web-Based Learning and Teaching Technologies, 2024
With the development of the information age, the quality of physical education teaching in universities has become an important goal of teaching reform. Improving the quality of physical education and significantly improving students' physical fitness is one of the development goals of higher education. Therefore, this article proposes an…
Descriptors: Physical Education, Higher Education, Educational Quality, Educational Improvement
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Jacob Whitehill; Jennifer LoCasale-Crouch – Journal of Educational Data Mining, 2024
With the aim to provide teachers with more specific, frequent, and actionable feedback about their teaching, we explore how Large Language Models (LLMs) can be used to estimate "Instructional Support" domain scores of the CLassroom Assessment Scoring System (CLASS), a widely used observation protocol. We design a machine learning…
Descriptors: Artificial Intelligence, Teacher Evaluation, Models, Transcripts (Written Records)
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Haynes-Brown, Tashane K. – Journal of Mixed Methods Research, 2023
The purpose of this article is to illustrate the dynamic process involved in developing and utilizing a theoretical model in a mixed methods study. Specifically, I illustrate how the theoretical model can serve as the starting point in framing the study, as a lens for guiding the data collection and analysis, and as the end point in explaining the…
Descriptors: Theories, Models, Mixed Methods Research, Teacher Attitudes
Chad J. Coleman – ProQuest LLC, 2021
Determining which students are at-risk of poorer outcomes -- such as dropping out, failing classes, or decreasing standardized examination scores -- has become an important area of both research and practice in K-12 education. The models produced from this type of predictive modeling research are increasingly used by high schools in Early Warning…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Elementary Secondary Education
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
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Griggs, Dana M.; Crain-Dorough, Mindy – Qualitative Research Journal, 2021
Purpose: The purposes of this paper are to provide a description of AI and to document and compare two applications of AI, one in program evaluation and another in an applied research study. Design/methodology/approach: Focus groups, interviews and observations were used to gather rich qualitative data which was used to detail Appreciative…
Descriptors: Program Evaluation, Artificial Intelligence, Research Methodology, Qualitative Research
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Prieto, Luis P.; Magnuson, Paul; Dillenbourg, Pierre; Saar, Merike – Technology, Pedagogy and Education, 2020
Improving educational practice through reflection is one important focus of teacher professional development approaches. However, such teacher reflection operates under practical classroom constraints that make it happen infrequently, including the reliance on disruptive peer/supervisor observations or recordings. This article describes three…
Descriptors: Faculty Development, Reflection, Secondary School Teachers, Educational Technology
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Pardo, Abelardo – Assessment & Evaluation in Higher Education, 2018
Feedback has been identified as one of the factors with the largest potential for a positive impact in a learning experience. There is a significant body of knowledge studying feedback and providing guidelines for its implementation in learning environments. In parallel, the areas of learning analytics or educational data mining have emerged to…
Descriptors: Feedback (Response), Models, Learning Experience, Educational Technology
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Gibson, David; Broadley, Tania; Downie, Jill; Wallet, Peter – Educational Technology & Society, 2018
The UNESCO Institute for Statistics (UIS) has been measuring ICT in education since 2009, but with such rapid change in technology and its use in education, it is important now to revise the collection mechanisms to focus on how technology is being used to enhance learning and teaching. Sustainable development goal (SDG) 4, for example, moves…
Descriptors: Models, Information Technology, Data Collection, Statistics
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Boticki, Ivica; Akçapinar, Gökhan; Ogata, Hiroaki – Interactive Learning Environments, 2019
In this paper log data on e-book usage is used as part of a learning analytics approach to generate user models which describe university students' characteristics in multiple dimensions. E-book usage is logged and analysed to extract information on how users use e-books for academic purposes. Two cases contributing to user modelling are…
Descriptors: Electronic Publishing, Data Collection, Data Analysis, Books
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Attaran, Mohsen; Stark, John; Stotler, Derek – Industry and Higher Education, 2018
Business leaders around the world are using emerging technologies to capitalize on data, to create business value and to compete effectively in a digitally driven world. They rely on data analytics to accelerate time to insight and to gain a better understanding of their customers' needs and wants. However, big data and data analytics solutions in…
Descriptors: Models, Higher Education, Data Collection, Program Implementation
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Wu, Pengfei; Yu, Shengquan; Wang, Dan – Educational Technology & Society, 2018
The present study uses a text data mining approach to automatically discover learner interests in open learning environments. We propose a method to construct learner interests automatically from the combination of learner generated content and their dynamic interactions with other learning resources. We develop a learner-topic model to discover…
Descriptors: Data Collection, Data Analysis, Educational Technology, Technology Uses in Education
Almatrafi, Omaima – ProQuest LLC, 2018
A Massive Open Online Course (MOOC) is a course that is offered fully online and is usually open for enrollment by any individual, with no limit on the number of participants. MOOCs are a popular resource for learning worldwide with over 23 million new learners registering for MOOCs in 2017 alone. Coursera, the most popular MOOC platform, has…
Descriptors: Large Group Instruction, Online Courses, Educational Technology, Technology Uses in Education
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