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Educator preparation, professional development, performance and evaluation
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Teachers’ professional identities are the foundation of their practice. Previous scholarship has largely overlooked the extent to which the broader institutional environment shapes teachers’ professional identities. In this study, I bridge institutional logics with theory on teacher professional identity to empirically examine the deeply institutionalized, taken-for-granted ways American society has come to think of teaching (e.g., as a moral calling, as a profession, as labor) are internalized by K-12 teachers. I draw on survey data from 950 teachers across four US states (California, New York, Florida, and Texas), and develop an original survey measure to capture what I term teachers’ “institutionalized conceptions of teaching.” Across diverse state policy contexts, I find that teachers’ conceptions of teaching are guided by three underling logics: (1) an accountability logic, (2) a democratic logic, and (3) a moral calling logic. I then surface a typology of teacher professional and examine the relationship between these logics and teachers’ professional identities. I find that the taken-for-granted ways society frames teaching may be associated with dimensions of teachers’ professional identity, such as self-efficacy and professional commitment. Together, the findings suggest that supporting the professional well-being of K-12 teaching may demand shifting the deeply institutionalized norms of the profession to be more aligned with teachers’ democratic and moral aims—rather than our system's deep norms around external accountability. The study offers methodological contributions to the study of logics, as well as practical implications for the field of teaching.
The pivotal role of Algebra in the educational trajectories of U.S. students continues to motivate controversial, high-profile policies focused on when students access the course, their classroom peers, and how the course is taught. This random-assignment partnership study examines an innovative district-level reform—the Algebra I Initiative—that placed 9th-grade students with prior math scores well below grade level into Algebra I classes coupled with teacher training instead of a remedial pre-Algebra class. We find that this reform significantly increased grade-11 math achievement (ES = 0.2 SD) without lowering the achievement of classroom peers eligible for conventional Algebra I classes. This initiative also increased attendance, district retention, and overall math credits. These results suggest that higher expectations for the lowest-performing students coupled with aligned teacher supports is a promising model for realizing students’ mathematical potential.
Mastery learning – the process by which students must demonstrate proficiency with a single topic before moving on – is well recognized as one of the best ways to learn, yet many teachers struggle or remain unsure about how to implement it into a classroom setting. This study leverages two field experiments to test the efficacy of a program designed to encourage greater mastery learning through technology and proactive continuous teacher support. Focusing on elementary and middle school mathematics, teachers receive weekly coaching in how to use Computer Assisted Learning (CAL) for students to follow a customized roadmap of incremental progress. Results indicate significant intent-to-treat effects on math performance of 0.12-0.22 standard deviations. Further analysis shows that these gains are concentrated among students in classrooms with at least an average of 35 minutes of practice per week. Teachers able to achieve high-dosage practice have a high degree of initial buy-in, a clear implementation strategy for when practice occurs, and a willingness to closely monitor progress and follow-up with struggling students.
Paraeducators are among the largest categories of public education employees and are increasingly seen as a pool of potential teachers. However, little is known about paraeducator-to-teacher transitions. Using statewide administrative data, we show that while paraeducators may be more racially/ethnically diverse than the teacher workforce, Black and Hispanic paraeducators are less likely than White paraeducators to transition into teaching. We additionally show that teachers with paraeducator experience are similarly effective to teachers without paraeducator experience. Lastly, we use simulations to show that the potential for the paraeducator-to-teacher pipeline to diversify the teaching profession may be limited unless they are highly targeted. Our results have policy design implications for efforts to expand the paraeducator-to-teacher pipeline or to diversify the teacher workforce.
This study provides the first large-scale quantitative exploration of mathematical language use in upper elementary U.S. classrooms. Our approach employs natural language processing techniques to describe variation in teachers’ and students’ use of mathematical language in 1,657 fourth and fifth grade lessons in 317 classrooms in four districts over three years. Students’ exposure to mathematical language varies substantially across lessons and between teachers. Results suggest that teacher modeling, defined as the density of mathematical terms in teacher talk, does not substantially cause students to uptake mathematical language, but that teachers may encourage student use of mathematical vocabulary by means other than mere modeling or exposure. However, we also find that teachers who use more mathematical language are more effective at raising student test scores. These findings reveal that teachers who use more mathematical vocabulary are more effective math teachers.
Despite well-designed curriculum materials, teachers often face challenges in their implementation due to diverse classroom needs. This paper investigates whether Large Language Models (LLMs) can support middle-school math teachers by helping create high-quality curriculum scaffolds, which we define as the adaptations and supplements teachers employ to ensure all students can access and engage with the curriculum. Through Cognitive Task Analysis with expert teachers, we identify a three-stage process for curriculum scaffolding: observation, strategy formulation, and implementation. We incorporate these insights into three LLM approaches to create warmup tasks that activate background knowledge. The best-performing approach, which provides the model with the original curriculum materials and an expert-informed prompt, generates warmups that are rated significantly higher than warmups created by expert teachers in terms of alignment to learning objectives, accessibility to students working below grade level, and teacher preference. This research demonstrates the potential of LLMs to support teachers in creating effective scaffolds and provides a methodology for developing AI-driven educational tools.
Despite evidence that teacher professional development interventions in mathematics and science can increase student achievement, our understanding of the mechanisms by which this occurs – particularly how these interventions affect teachers themselves, and whether teacher-level changes predict student learning – remains limited. The current meta-analysis synthesizes 46 experimental studies of preK-12 mathematics and science professional development interventions to investigate how these interventions affect teachers’ knowledge and classroom instruction, and how these impacts relate to intervention effects on student achievement. Compared with controls, treatment group teachers had stronger performance on measures of knowledge and classroom instruction (pooled average impact estimate: +0.53 SD). Programs with larger impacts on teacher practice had significantly larger mean effects on student achievement. However, mean effects on student achievement were not significantly related to impacts on teacher knowledge. We discuss implications for future research and practice.
Inconsistent reporting of critical facets of classroom interventions and their related impact evaluations hinders the field’s ability to describe and synthesize the existing evidence base. In this essay, we present a set of reporting guidelines intended to steer authors of classroom intervention studies toward providing more systematic reporting of key intervention features and setting-level factors that may affect interventions’ success. The guidelines were iteratively developed using recommendations and feedback from scholars active in conducting and synthesizing classroom intervention research. This effort aims to open wider the ‘black box’ in classroom research, communicating key information with more precision and detail to practitioners and future researchers, and permitting the field to more efficiently accumulate and synthesize findings on classroom interventions, determining what works, for whom, and under what conditions.
“Free college” programs are widespread in American higher education. They are discussed as addressing college access, affordability, inequality, and skills shortages. Many are last-dollar tuition guarantees restricted to use at single community colleges. Using student-level data spanning the transition to college, we investigate how two similar local community college tuition guarantees in Pennsylvania affected college-going outcomes. The Morgan Success Scholarship has large impacts on community college attendance and associate degree attainment. The program diverts students away from four-year colleges, though much of this effect is temporary. Meanwhile, we find little evidence that the Community College of Philadelphia’s 50th Anniversary Scholars program has any impact on college-going behavior. We suggest reasons for divergent findings and offer suggestions for practice.