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Charlie Bastyr; Charlee Johnson; Romesh Lakhan; Jacob W. Wainman – Journal of Chemical Education, 2022
Active learning is known to improve student outcomes in many STEM courses. Here, we present strategies for incorporating active learning into a large enrollment General Chemistry I course using small group activities during class time. This approach was found to mitigate gender disparities in overall course grades and reduced the number of General…
Descriptors: Chemistry, Females, Active Learning, College Students
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Copeland, Lauren – Journal of Service-Learning in Higher Education, 2017
The purpose of this research is to better understand the attitudes towards service-learning and course engagement of students in a service learning project based course in a larger class size.. This research incorporates a better understanding and exploration of how a larger class can affect the attitudes and engagement of students in service…
Descriptors: Service Learning, International Trade, Student Projects, Active Learning
Sharma, Kshitij; Jermann, Patrick; Dillenbourg, Pierre – International Educational Data Mining Society, 2015
Current schemes to categorise MOOC students result from a single view on the population which either contains the engagement of the students or demographics or self reported motivation. We propose a new hierarchical student categorisation, which uses common online activities capturing both engagement and achievement of MOOC students. A first level…
Descriptors: Foreign Countries, Online Courses, Large Group Instruction, Student Characteristics
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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