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Introduction: When you picture a good student, what comes to mind? You might imagine a student who is well-regulated – who can pay attention, sit still, and plan ahead. But there is more to learning than good executive functions (EFs), the higher-order cognitive skills that support goal directed activities and self-regulation: Motivation also plays an important role. In this study, we focus on one specific aspect of motivation, challenge preference (CP). Although CP is theoretically important for learning (Elliott & Dweck, 1988), we know little about how it relates to academic achievement, especially in longitudinal analyses that control for earlier achievement. Further, we lack basic descriptive information about the degree to which CP and EFs are associated, and whether CP predicts academic achievement over and above students’ EF skills.
Method: Participants are 569 third-, fourth-, and fifth-graders from eight schools (33 classrooms) in the San Francisco Bay Area in California. Data were collected at three different times, each spaced approximately one year apart: (1) standardized achievement tests were administered in spring of 2013; (2) students’ EFs and CP were assessed in the spring of 2014; and (3) standardized achievement tests were administered again in the spring of 2015. Students reported on their CP using a five question scale (Developmental Studies Center, n.d.). EFs were assessed using a battery of four widely used, developmentally appropriate tasks (Obradović, Sulik, Finch, & Tirado-Strayer, 2018) and teachers’ reports. Students’ English language arts and mathematics achievement were measured using standardized achievement tests administered by the State of California in the spring of 2013 and 2015 (California Department of Education, 2016a, 2016b).
Results: CP was positively correlated with parental educational attainment (r = .19, p < .001), directly-assessed EFs (r = .21, p < .001) and teacher-reported EFs (r = .08, p = .048), and all measures of students’ achievement (rs range from .27 to .34, ps < .001). In multilevel models, CP was associated with English language arts achievement (p = .005) and mathematics achievement (p < .001) even while controlling for school fixed effects, demographic characteristics, and EFs. While also controlling for prior achievement, CP continued to explain unique variance in mathematics achievement (p = .012), see Table 1c, but not English language arts achievement (p = .927), see Table 2c.
Discussion: Children who seek out challenges are believed to have more opportunities to learn and grow their skills. Our results underscore the importance of including students’ motivation in addition to EFs to obtain a comprehensive understanding of academic achievement. Motivational characteristics such as CP are particularly attractive as an intervention target because they can be influenced in a relatively low-cost manner. Although EFs can be improved experimentally (Diamond & Lee, 2011), doing so requires a comparatively heavy investment (Jacob & Parkinson, 2015). CP has been less studied relative to some other aspects of student motivation, and there is still much to learn about what influences CP, how it is related to other aspects of motivation, and whether it is causally related to achievement.