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Christopher Dann; Petrea Redmond; Melissa Fanshawe; Alice Brown; Seyum Getenet; Thanveer Shaik; Xiaohui Tao; Linda Galligan; Yan Li – Australasian Journal of Educational Technology, 2024
Making sense of student feedback and engagement is important for informing pedagogical decision-making and broader strategies related to student retention and success in higher education courses. Although learning analytics and other strategies are employed within courses to understand student engagement, the interpretation of data for larger data…
Descriptors: Artificial Intelligence, Learner Engagement, Feedback (Response), Decision Making
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Ignacio L. Montoya; Julien De Jesus; Macario Mendoza-Carrillo – Language Documentation & Conservation, 2024
This paper focuses on the development, planning, and implementation of Numu (Northern Paiute) language classes at the University of Nevada, Reno. The authors' engagement with the Numu classes as well as the description and analysis presented in this paper are guided by principles of decolonization, language reclamation, and community-based…
Descriptors: Expertise, Decolonization, Universities, Courses
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Nahar, Khaledun; Shova, Boishakhe Islam; Ria, Tahmina; Rashid, Humayara Binte; Islam, A. H. M. Saiful – Education and Information Technologies, 2021
Information is everywhere in a hidden and scattered way. It becomes useful when we apply Data mining to extracts the hidden, meaningful, and potentially useful patterns from these vast data resources. Educational data mining ensures a quality education by analyzing educational data based on various aspects. In this paper, we have analyzed the…
Descriptors: Learning Analytics, College Students, Engineering Education, Data Collection
Michalski, Greg V. – Association for Institutional Research (NJ1), 2011
Excessive college course withdrawals are costly to the student and the institution in terms of time to degree completion, available classroom space, and other resources. Although generally well quantified, detailed analysis of the reasons given by students for course withdrawal is less common. To address this, a text mining analysis was performed…
Descriptors: College Instruction, Courses, Withdrawal (Education), College Students
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Ornek, Funda – International Journal of Environmental and Science Education, 2008
In this paper, I discuss different types of models in science education and applications of them in learning and teaching science, in particular physics. Based on the literature, I categorize models as conceptual and mental models according to their characteristics. In addition to these models, there is another model called "physics model" by the…
Descriptors: Physics, Science Education, Models, Classification
Richlin, Laurie – Stylus Publishing, LLC, 2006
Laurie Richlin has been running a workshop on course design for higher education for over fifteen years, modifying and improving it progressively from the feedback of participants, and from what they in turn have taught her. Her goals are to enable participants to appropriately select teaching strategies, to design and create the conditions and…
Descriptors: Teaching Methods, Higher Education, Courses, Instructional Design