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Zeng, Ziheng; Chaturvedi, Snigdha; Bhat, Suma – International Educational Data Mining Society, 2017
Characterizing the nature of students' affective and emotional states and detecting them is of fundamental importance in online course platforms. In this paper, we study this problem by using discussion forum posts derived from large open online courses. We find that posts identified as encoding confusion are actually manifestations of different…
Descriptors: Online Courses, Large Group Instruction, Educational Technology, Technology Uses in Education
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Farnsworth, Megan – Studying Teacher Education, 2016
In order to improve her practice, a teacher educator explored emotions as catalysts for teaching and learning by asking the research question, "How can I support preservice teachers' emotional intelligence (EI), as well as my own, as we negotiate the impact of strong emotions in the pedagogical environment?" Three levels of reflection…
Descriptors: Teacher Educators, Self Evaluation (Individuals), Preservice Teacher Education, Preservice Teachers
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Goh, Tiong T.; Sun, Pei-Chen – Journal of Information Systems Education, 2015
Unstructured data in social media is as part of the "big data" spectrum. Unstructured data in Social media can provide useful insights into social phenomena and citizen opinions, both of which are critical to government policy and businesses decisions. Teachers of business intelligence and analytics commonly use quantitative data from…
Descriptors: Foreign Countries, Social Media, Data Analysis, Natural Disasters
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O'Connor, Melissa L.; McFadden, Susan H. – Educational Gerontology, 2012
According to Terror Management Theory as applied to ageism, older adults may be associated with mortality, thereby generating death-thought accessibility, stereotypes, and mixed emotions among younger adults. However, it is unclear how older adults' health conditions, such as dementia, affect ageist attitudes and mortality salience. In the current…
Descriptors: Alzheimers Disease, Empathy, Young Adults, Health Conditions
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Heath, Phyliss A.; Camarena, Phame M. – Journal of Early Adolescence, 2002
This 3-year longitudinal study examined depressed affect during early adolescence. Variable-centered analyses yielded general stability in depressed affect for both boys and girls. Person-centered analysis revealed five patterns of depressed affect, with gender differences only in smaller subgroups that showed patterns of change in depressed…
Descriptors: Adolescent Development, Affective Behavior, Behavior Patterns, Data Analysis
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Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
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Cundy, Donald T. – Journal of Politics, 1979
Describes a political socialization model which applied social conditioning principles to the understanding of political attitudes. Findings show political attitudes depend on positive responses to persons in one's environment. Journal available from Manning J. Dauer, Department of Political Science, University of Florida, Gainesville, Florida,…
Descriptors: Affective Behavior, Childhood Attitudes, Concept Formation, Conditioning
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection