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Educator preparation, professional development, performance and evaluation
Displaying 1 - 10 of 145
Expanding School Counseling: The Impacts of California Funding Changes
Counselors are a common school resource for students navigating complicated and consequential education choices. However, most students have limited access to school counselors. We study one of the largest U.S. policies to increase access to school counselors - California's Supplemental School Counseling Program. The program increased the average number of counselors per high school by 0.7 and reduced student to counselor ratios by over 150 students. Counselors hired as a result of the program had less experience on average. The expansion of counseling had positive effects on high school graduation and public college enrollment rates as well as on student perceptions of school climate. Impacts on college enrollment were largest in high poverty and rural schools. Thus, expanding access to counselors may help schools address equity gaps in college access and concerns over students' mental health.
Do Pensions Enhance Worker Effort and Selection? Evidence from Public Schools
Why do employers offer pensions? We empirically examine two theoretical rationales, namely that pensions improve worker effort and worker selection. We test these hypotheses using rich administrative measures on effort and output for teachers around the pension-eligibility notch. When workers cross the notch, their effective compensation falls by roughly 50 percent of salary, but we observe no reduction in worker effort or output. This implies that pension payments do not increase effort. As for selection, we find that pensions retain low-value-added and high-value-added workers at the same rate, implying similar preferences across teacher quality and no influence on selection.
Same Idea, Shifting Standards: An Experimental Study of Racial-Ethnic Biases in Ambitious Math Teaching
Teacher expectations and judgments about student capabilities are predictive of student achievement, yet such judgments may be influenced by salient dimensions of student identity and invite biases. Moreover, ambitious math teaching may also invite teacher biases due to the emphasis on student-generated inputs and ideas. In this pre-registered audit experiment, we investigate teacher biases in a) expectations and judgments about student capabilities in math and b) teacher responsiveness to students’ mathematical thinking. Through a between-subjects design, we randomly assigned teachers to a simulated classroom composed of predominantly Black, Latinx/e, or White students and prompted them to respond to a student’s mathematical solution. We also prompted teachers to judge the quality of the student’s mathematical thinking and rate their expectations about the difficulty of the problem for the typical student. Our findings show teachers expected greater task difficulty in both the Latinx/e and Black classroom conditions relative to the White. We also found teachers may be more likely to support student sense-making and provide more positive, substantive affirmations to Black students relative to White students for the same mathematical solution. We did not find differences by condition in other dimensions. Our findings have implications for teacher training and reform-oriented mathematics instruction.
The Reform Logics of Teaching: How Institutionalized Conceptions of Teaching Shape Teacher Professional Identity
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.
Accelerating Opportunity: The Effects of Instructionally Supported Detracking
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.
Teaching Teachers to Use Computer Assisted Learning Effectively: Experimental and Quasi-Experimental Evidence
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.
Untapped Potential? Understanding the Paraeducator-to-Teacher Pipeline and its Potential for Diversifying the Teacher Workforce
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.
A Quantitative Study of Mathematical Language in Upper Elementary Classrooms
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.
Scaffolding Middle-School Mathematics Curricula With Large Language Models
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.
A Meta-Analysis of the Experimental Evidence Linking Mathematics and Science Professional Development Interventions to Teacher Knowledge, Classroom Instruction, and Student Achievement
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.