The racial/ethnic disparities and average declines in science, technology, engineering, and mathematics (STEM) motivation during adolescence are worrisome. Although STEM motivational beliefs are theorized to function in conjunction with one another, the unique patterns and how they change over time for different racial/ethnic groups remain understudied. Using data from the High School Longitudinal Study (N = 18,260), we identified four and five patterns of math and science motivational beliefs in 9th and 11th grade, respectively, and examined their prevalence among Asian, Black, Latina/o, White, and Multiracial adolescents. We found patterns with overall high/low beliefs, patterns with varying levels of motivational beliefs, and patterns characterized by domain differentiation. Then, we charted the stability and changes in those patterns from 9th to 11th grade for each racial/ethnic group and how the patterns at 11th grade were associated with adolescents' STEM career expectations and high school math and science grade point averages.

This exploratory paper highlights how problem-based learning (PBL) provided the pedagogical framework used to design and interpret learning analytics from Crystal Island: EcoJourneys, a collaborative game-based learning environment centred on supporting science inquiry. In Crystal Island: EcoJourneys, students work in teams of four, investigate the problem individually and then utilize a brainstorming board, an in-game PBL whiteboard that structured the collaborative inquiry process. The paper addresses a central question: how can PBL support the interpretation of the observed patterns in individual actions and collaborative interactions in the collaborative game-based learning environment? Drawing on a mixed method approach, we first analyzed students' pre- and post-test results to determine if there were learning gains. We then used principal component analysis (PCA) to describe the patterns in game interaction data and clustered students based on the PCA. Based on the pre- and post-test results and PCA clusters, we used interaction analysis to understand how collaborative interactions unfolded across selected groups. Results showed that students learned the targeted content after engaging with the game-based learning environment. Clusters based on the PCA revealed four main ways of engaging in the game-based learning environment: students engaged in low to moderate self-directed actions with (1) high and (2) moderate collaborative sense-making actions, (3) low self-directed with low collaborative sense-making actions and (4) high self-directed actions with low collaborative sense-making actions. Qualitative interaction analysis revealed that a key difference among four groups in each cluster was the nature of verbal student discourse: students in the low to moderate self-directed and high collaborative sense-making cluster actively initiated discussions and integrated information they learned to the problem, whereas students in the other clusters required more support. These findings have implications for designing adaptive support that responds to students' interactions with in-game activities.

Background Math anxiety (MA) and math achievement are generally negatively associated. Aims This study investigated whether and how classroom engagement behaviors mediate the negative association between MA and math achievement. Sample Data were drawn from an ongoing longitudinal study that examines the roles of affective factors in math learning. Participants consisted of 207 students from 4th through 6th grade (50% female). Methods Math anxiety was measured by self-report using the Mathematics Anxiety Scale for Children (Chiu & Henry, 1990, Measurement and valuation in Counseling and Development, 23, 121). Students self-reported their engagement in math classrooms using a modified version of the Math and Science Engagement Scale (Wang et al., 2016, Learning and Instruction, 43, 16). Math achievement was assessed using the Applied Problem, Calculations, and Number Matrices subtests from the Woodcock-Johnson IV Tests of Achievement (Schrank et al., 2014, Woodcock-Johnson IV Tests of Achievement. Riverside). Mediation analyses were conducted to examine the mediating role of classroom engagement in the association between MA and math achievement. Results Students with higher MA demonstrated less cognitive-behavioral and emotional engagement compared to students with lower MA. Achievement differences among students with various levels of MA were partly accounted for by their cognitive-behavioral engagement in the math classroom. Conclusions Overall, students with high MA exhibit avoidance patterns in everyday learning, which may act as a potential mechanism for explaining why high MA students underperform their low MA peers.

Staffing classrooms with effective teachers remains a persistent policy challenge in the U.S. Teaching positions requiringSTEM expertise are particularly difficult to fill. Scholars have identified similar trends in other industrialized nations. Yet, limited research examines international comparisons of the causes and consequences of staffing challenges. We use the 2015 Trends in Mathematics and Science Study to track teacher staffing difficulties in 27 countries. We find substantial variation across countries in the proportion of principals reporting difficulties filling STEM positions, with U.S. schools mirroring international averages. We also find consistent relationships between lower math and science achievement and attending a hard-to-staff school.

Introduction: This research examined the classification accuracy of the Quick Interactive Language Screener (QUILS) for identifying preschool-aged children (3;0 to 6;9) with developmental lan-guage disorder (DLD). We present data from two independent samples that varied in prevalence and diagnostic reference standard.Methods: Study 1 included a clinical sample of children (54 with DLD; 13 without) who completed the QUILS and a standardized assessment of expressive grammar (Syntax subtest from the Diagnostic Evaluation of Language Variation-Norm Referenced; Structured Photographic Expressive Language Test-Preschool 2nd Edition; or Structured Photographic Expressive Lan-guage Test-3 rd Edition). Study 2 included a community sample of children (25 with DLD; 101 without) who completed the QUILS and the Auditory Comprehension subtest of the Preschool Language Scales-5th Edition (PLS-5; Zimmerman et al., 2011). Discriminant analyses were con-ducted to compare classification accuracy (i.e., sensitivity and specificity) using the normrefer-enced cut score (< 25th percentile) with empirically derived cut scores. Results: In Study 1, the QUILS led to low fail rates (i.e., high specificity) in children without impairment and statistically significant group differences as a function of children's clinical status; however, only 65% of children with DLD were accurately identified using the norm -referenced cutoff. In Study 2, 76% of children with DLD were accurately identified at the 25th percentile cutoff and accuracy improved to 84% when an empirically derived cutoff (<32nd percentile) was applied.Conclusions: Findings support the clinical application of the QUILS as a component of the screening process for identifying the presence or absence of DLD in community samples of preschool-aged children.

Socioscientific issues (SSI) are often used to facilitate students' engagement in multiple scientific practices such as decision-making and argumentation, both of which are goals of STEM literacy, science literacy, and integrated STEM education. Literature often emphasizes scientific argumentation over socioscientific argumentation, which involves considering social factors in addition to scientific frameworks. Analyzing students' socioscientific arguments may reveal how students construct such arguments and evaluate pedagogical tools supporting these skills. In this study, we examined students' socioscientific arguments regarding three SSI on pre- and post-assessments in the context of a course emphasizing SSI-based structured decision-making. We employed critical integrative argumentation (CIA) as a theoretical and analytical framework, which integrates arguments and counterarguments with stronger arguments characterized by identifying and refuting counterarguments. We hypothesized that engaging in structured decision-making, in which students integrate multidisciplinary perspectives and consider tradeoffs of various solutions based upon valued criteria, may facilitate students' development of integrated socioscientific arguments. Findings suggest that students' arguments vary among SSI contexts and may relate to students' identities and perspectives regarding the SSI. We conclude that engaging in structured decision-making regarding personally relevant SSI may foster more integrated argumentation skills, which are critical to engaging in information-laden democratic societies.

What motivates faculty teaching gateway courses to consider adopting an evidence-based classroom intervention? In this nationally representative study of biology faculty members in the United States (N = 422), we used expectancy-value-cost theory to understand three convergent motivational processes the faculty members' underlying intentions to adopt an exemplar evidence-based classroom intervention: the utility value intervention (UVI). Although the faculty members perceived the intervention as valuable, self-reported intentions to implement it were degraded by concerns about costs and lower expectancies for successful implementation. Structural equation modeling revealed that the faculty members reporting lower intentions to adopt it tended to be White and to identify as male and had many years of teaching or were from a more research-focused university. These personal, departmental, and institutional factors mapped onto value, expectancies, and cost perceptions uniquely, showing that each process was a necessary but insufficient way to inspire intentions to adopt the UVI. Our findings suggest multifaceted, context-responsive appeals to support faculty member motivation to scale up adoption of evidence-based classroom interventions.

Using data from 12 studies, we meta-analyze correlations between parent number talk during interactions with their young children (mean sample age ranging from 22 to 79 months) and two aspects of family socioeconomics, parent education, and family income. Potential variations in correlation sizes as a function of study characteristics were explored. Statistically significant positive correlations were found between the amount of number talk in parent-child interactions and both parent education and family income (i.e., r = 0.12 for education and 0.14 for income). Exploratory moderator analyses provided some preliminary evidence that child age, as well as the average level of and variability in socioeconomic status, may moderate effect sizes. The implications of these findings are discussed with special attention to interpreting the practical importance of the effect sizes in light of family strengths and debate surrounding word gaps.