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Vanessa Ayer Miller; Timothy Marks; Dorothea K. Thompson – Journal of Microbiology & Biology Education, 2025
Interest in virtual laboratory simulations as a pedagogical tool continues to grow, given the advantages of flexibility, scalability, technology integration, and interactive visualizations. We developed a laboratory model that integrates virtual lab simulations (VLS) and traditional in-person (IP) lab experiences for targeted skill development. In…
Descriptors: Microbiology, Science Achievement, Student Attitudes, Blended Learning
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Jones, Meredith; McNulty, Carol – International Electronic Journal of Elementary Education, 2022
The COVID-19 pandemic and the subsequent lockdown was particularly challenging for elementary students who experienced disruptions in almost all aspects of their daily activities. Our study addressed a dearth of U.S. studies documenting the adverse effects the pandemic created and continues to have for children by analyzing their drawings. This…
Descriptors: COVID-19, Pandemics, Elementary School Students, Preschool Children
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Valauri-Orton, Alexis; Bernd, Karen K. – American Biology Teacher, 2015
For many middle school students, connections between their lives and concepts like chemical reactivity, microbial contamination, and experimental sampling are not obvious. They may also feel that, even if there were connections, understanding the monitoring and quality of natural resources is something for grown-ups and beyond their…
Descriptors: Middle School Students, Secondary School Science, Microbiology, Chemistry
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Sabourin, Jennifer L.; Rowe, Jonathan P.; Mott, Bradford W.; Lester, James C. – Journal of Educational Data Mining, 2013
Over the past decade, there has been growing interest in real-time assessment of student engagement and motivation during interactions with educational software. Detecting symptoms of disengagement, such as off-task behavior, has shown considerable promise for understanding students' motivational characteristics during learning. In this paper, we…
Descriptors: Student Behavior, Classification, Learner Engagement, Data Analysis