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Motivation to learn is known to decline during middle and high school. However, the data that support these conclusions is typically collected infrequently and measured apart from learning tasks. We assessed the motivation (i.e. achievement goals and efficacy) of middle and high school samples at greater frequency and at multiple levels of specificity within software used to learn math to better understand cross-sectional and longitudinal differences in motivation to learn mathematics. At the domain level, cross-sectional differences (middle vs. high school) were observed. Longitudinal declines were observed for self-efficacy but not achievement goals. At the unit level, declines were observed but change was non-linear. We conclude that features of tasks may predict greater variance than temporal factors.
Rachel Part, University of Nevada - Las Vegas
Matthew L. Bernacki, University of Nevada - Las Vegas
Timothy James Nokes-Malach, University of Pittsburgh
Vincent Aleven, Carnegie Mellon University