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Natalie Brezack; Wynnie Chan; Mingyu Feng – Grantee Submission, 2024
Perseverance is critical for students' achievement and may be particularly important after COVID-19. This paper includes analyses of teacher and principal interviews and student educational technology usage data to examine students' perseverance during math problem-solving across three cohorts of students during and after COVID-19. Data were…
Descriptors: COVID-19, Pandemics, Academic Persistence, Mathematics Education
Clarissa A. Thompson; Jennifer M. Taber; Pooja G. Sidney; Charles J. Fitzsimmons; Marta K. Mielicki; Percival G. Matthews; Erika A. Schemmel; Nicolle Simonovic; Jeremy L. Foust; Pallavi Aurora; David J. Disabato; T. H. Stanley Seah; Lauren K. Schiller; Karin G. Coifman – Grantee Submission, 2021
At the onset of the coronavirus disease (COVID-19) global pandemic, our interdisciplinary team hypothesized that a mathematical misconception--whole number bias (WNB)--contributed to beliefs that COVID-19 was less fatal than the flu. We created a brief online educational intervention for adults, leveraging evidence-based cognitive science…
Descriptors: COVID-19, Pandemics, Cognitive Processes, Logical Thinking
Wang, Yutao; Heffernan, Neil T.; Heffernan, Cristina – Grantee Submission, 2015
The well-studied Baker et al., affect detectors on boredom, frustration, confusion and engagement concentration with ASSISTments dataset were used to predict state tests scores, college enrollment, and even whether a student majored in a STEM field. In this paper, we present three attempts to improve upon current affect detectors. The first…
Descriptors: Majors (Students), Affective Behavior, Psychological Patterns, Predictor Variables