Community teachers, particularly those who are Black and Latinx, are assumed to improve retention and outcomes depending on retention in schools that serve low-income Black and Latinx students. Based on a critical quantitative analysis of data collected on the career trajectories and retention of hundreds of alternatively certified mathematics teachers, the study shows that community insiders exhibit significantly higher rates of retention in district schools than community outsiders and, in particular, those from elite colleges. Utilizing quantitative critical theory methodology, the study helps to move the field beyond race-neutral analyses of teachers’ retention and careers. © 2023 AERA.

Although gender parity has been achieved in some STEM fields, gender disparities persist in computing, one of the fastest-growing and highest-earning career fields. In this systematic literature review, we expand upon academic momentum theory to categorize computing interventions intended to make computing environments more inclusive to girls and women and consider how those characteristics vary by the success of the intervention. Particular attention is given to the efficacy of broadening participation and success for women in computer science, information technology, and related fields. After scrutinizing 168 relevant studies, 48 met the inclusion criteria and were included. We introduce a framework for gender equity in computing, expanding on existing research on academic and STEM momentum to encompass new domains representing social and structural momentum. Our analysis reveals the complex roles of intervention domains, strategies, goals, levels, and duration in shaping their efficacy. Implications for theory, research, and practice are discussed.

The purposes of this study included conducting a meta-analysis and reviewing the study reporting quality of math interventions implemented in informal learning environments (e.g., the home) by children’s caregivers. This meta-analysis included 25 preschool to third-grade math interventions with 83 effect sizes that yielded a statistically significant summary effect (g = 0.26, 95% CI [0.07, 0.45) on children’s math achievement. Significant moderators of the treatment effect included the intensity of caregiver training and type of outcome measure. There were larger average effects for interventions with caregiver training that included follow-up support and for outcomes that were comprehensive early numeracy measures. Studies met 58.0% of reporting quality indicators, and analyses revealed that quality of reporting has improved in recent years. The results of this study offer several recommendations for researchers and practitioners, particularly given the growing evidence base of math interventions conducted in informal learning environments. © 2023 AERA.

Nationally, more than 75% of individuals who are credentialed to teach are prepared in traditional college- or university-based teacher education programs (TEPs). But the college and employment pathways that prospective teachers take to TEP enrollment and completion have not been comprehensively examined. A better understanding of how credentialed individuals find their way into TEPs helps us understand the sources of new teacher supply early in the prospective teacher pipeline. With that in mind, we analyze pathways into and through TEPs using historical postsecondary and unemployment insurance data from Washington State. We find that the pathways are quite varied, with around 40% of bachelor's-level TEP completers spending at least some time in community colleges and fewer than 40% enrolling and finishing at the same university directly after high school. Pathways to master's TEP completion are even more varied, with almost half of the completers having prior employment experience. For researchers, this varied landscape raises important questions about the relationship between pathways, candidate persistence, and eventual job performance. For policymakers, the results suggest that efforts to recruit the next generation of teachers need to look beyond the pool of students already enrolled at a 4-year university to include students at 2-year colleges or in the labor force who might be interested in entering a TEP.

A recent study published in Educational Researcher by White (2023) examined superintendent gender gaps. This work required 4 years of internet searches to identify and match superintendent names with each of the roughly 13,000 school districts in the United States. Although this study provided important insights into the superintendent gender gaps, the study is unable to examine gaps for females of color or the long-term career pathways of superintendents. The lack of a national longitudinal superintendent dataset has meant researchers and policymakers have limited insights into superintendent racial and gender gaps, turnover rates, experience, and career pathways to the superintendency. Drawing on data from the Texas State Longitudinal Data System, we offer several findings to provide a glimpse of what could be accomplished with a longitudinal dataset. Policymakers, school boards, search firms, and communities will fail to understand the full range of challenges and opportunities to diversifying and strengthening the superintendent workforce until such a dataset exists and is accessible to researchers and other interested parties. © 2024 AERA.

Reforming instruction is challenging. In this comparative case study of 12 school districts, we investigated the dilemmas that emerged for system leaders as they engaged in system building for elementary science and the approaches leaders took in managing them. We found that system leaders' efforts to manage their environments contributed to the preferential treatment of literacy and mathematics relative to science. Leaders managed this dilemma using three strategies: (a) integration of science with other subjects, (b) specialization of teachers, and (c) adopting curriculum materials. This study contributes to literature on dilemma management by showing that dilemmas in education system building are school-subject sensitive, emerge in relation to system building for other subjects, and are embedded in school and education systems' structural/organizational arrangements.

Understanding how marginalized students experience and perceive mathematics is critical to achieving the goal of inclusive and equitable math pedagogy. We report on 67 focus groups with 251 predominantly Black high schoolers experiencing economic marginalization in the Southern United States and attended to their achievement level and race-gender identities. Students often shared concerns about their teacher's math knowledge for teaching and effectiveness in supporting academic success. Their self-perceptions of math identities varied, and students often did not value advanced math even when they expressed career interests that require advanced math. We discuss practical implications for supporting the math development of marginalized high schoolers, including centering the needs and strengths of Black girls, and propose an expanded inclusive and equitable pedagogical framework.

Successful problem-based learning (PBL) often requires students to collectively regulate their learning processes as a group and engage in socially shared regulation of learning (SSRL). This paper focuses on how facilitators supported SSRL in the context of middle-school game-based PBL. Using conversation analysis, this study analyzed text-based chat messages of facilitators and students collected during gameplay. The analysis revealed direct modeling strategies such as performing regulative processes, promoting group awareness, and dealing with contingency as well as indirect strategies including prompting questions and acknowledgment of regulation, and the patterns of how facilitation faded to yield responsibilities to students to regulate their own learning. The findings will inform researchers and practitioners to design prompts and develop technological tools such as adaptive scaffolding to support SSRL in PBL or other collaborative inquiry processes.

Young learners today are constantly influenced by AI recommendations, from media choices to social connections. The resulting "filter bubble" can limit their exposure to diverse perspectives, which is especially problematic when they are not aware this manipulation is happening or why. To address the need to support youth AI literacy, we developed "BeeTrap", a mobile Augmented Reality (AR) learning game designed to enlighten young learners about the mechanisms and the ethical issue of recommendation systems. Transformative Experience model was integrated into learning activities design, focusing on making AI concepts relevant to students’ daily experiences, facilitating a new understanding of their digital world, and modeling real-life applications. Our pilot study with middle schoolers in a community-based program primarily investigated how transformative structured AI learning activities affected students’ understanding of recommendation systems and their overall conceptual, emotional, and behavioral changes toward AI.

Gesture has been shown to play an important role in how learners conceptualize phenomena in physics. However, we know little about how gesture is used to conceptualize instantaneity. Drawing on multimodal microanalysis of interaction, we examine how undergraduate physics students use representational gesture to make sense of instants while modeling energy dynamics. Our analysis describes four different forms of representational gesture used to capture instantaneity: These include (1) Replay loop of scenario, (2) Subinterval on timeline, (3) Freeze frame of scenario, and (4) Indexical location on timeline.