Tag: Math

Effects of Zearn Math and balancing analyses in large-scale trials

Effects of Zearn Math and balancing analyses in large-scale trials

A new EdWorkingPaper from the Annenberg Institute at Brown University highlights not only the effects of Zearn Math, a digital K–8 platform, but also how education researchers balance confirmatory and exploratory analyses in large-scale trials. Conducted by the RAND Corporation, the two-year randomized controlled study involved more than 10,500 students in Grades 3 to 5 across 64 schools in a large urban Texas district. The study focused on the STAAR state assessment as its preregistered confirmatory outcome, given the test’s central role in Texas accountability policy and its alignment with grade-level standards. The NWEA MAP served as a preregistered exploratory outcome. Researchers use confirmatory outcomes in preregistration to indicate the primary outcomes they will use to test their key questions and interpret as the main evidence of impact. Exploratory outcomes can still have hypotheses and be preregistered, but they are typically secondary measures (like a district test vs. the state test) and are interpreted with more caution, helping researchers see if patterns replicate across measures without overclaiming from secondary data.

The study provides important context on Zearn Math’s implementation and usage patterns. Schools received beginning-of-year training, biweekly coaching for instructional leads, and classroom-level incentives to promote engagement. In the second year, usage increased substantially. By the final semester, most students met recommended weekly usage goals, and half completed the full sequence of on-grade-level lessons for the year. On the confirmatory STAAR outcomes, students in Zearn schools showed small positive effects, with effect sizes of +0.07 for all students and +0.10 for those who were below proficient at baseline. Although these results were not statistically significant, they may suggest improvement relative to business-as-usual practice.

Exploratory analyses of the MAP adaptive math assessment revealed larger and statistically significant effects, including an effect size of +0.13 for students who began below proficiency. While these results fall outside the preregistered plan and are reported with caution, they suggest that Zearn Math may support broader math learning that extends beyond grade-level benchmarks. Clearly identifying preregistered versus exploratory outcomes helps ground the study’s conclusions in rigor while still surfacing insights that can inform future research. Together, the consistent direction of the findings, strong second-year implementation, and significant exploratory gains suggest that Zearn Math holds promise for helping students, especially those below proficiency, build foundational skills and make progress in math.

Leveraging artificial intelligence to predict young learners’ online learning engagement

Leveraging artificial intelligence to predict young learners’ online learning engagement

By Zia Hassan, Center for Research and Reform in Education, Johns Hopkins University

With many schools rushing to adopt Generative AI, it is important to consider the real learning gains (or lack thereof) that these tools offer. A 2023 study by Pardos & Bhandari examined the use of AI-generated hints as a scaffolding mechanism with Algebra students.

Seventy-seven participants (high school graduates selected via Amazon’s MTURK system) were assigned to a control group (which provided human-generated hints) or an experimental group (which provided AI-generated hints). The researchers wanted to learn the rate of “low quality” AI-generated hints, as well as if the hints produced learning gains compared to the control group. The questions from the lesson were fed, verbatim, to ChatGPT in order to generate the hints. Quality checks were performed manually to ensure that all AI-generated hints were correct and showed the proper steps. This was then contrasted with the control group, whose hints were generated by undergraduate tutors. Pre and post tests were administered to check for learning gains between the two groups.

The results showed that 70% of the hints generated by ChatGPT were considered to be good quality, and that there was a statistically significant learning gain in the control group. A major limitation of the study is that the researchers did not prompt the AI to use any scaffolding strategies. Therefore, the quality of the hints between groups not only differed by human or AI creator, but also by pedagogical theory. Human tutors were probably more likely to employ Vygotsky-esque scaffolds, while ChatGPT was more likely to provide an immediate answer. Future work could improve upon the prompts used in this study and create a multi-tiered approach with less consequential hints being revealed at first.

The impact of Kentucky’s Math Achievement Fund

The impact of Kentucky’s Math Achievement Fund

By Cynthia Lake, Johns Hopkins University

Early intervention in mathematics is crucial for improving student outcomes and closing achievement gaps. A study in Educational Evaluation and Policy Analysis examined Kentucky’s Math Achievement Fund (MAF), a statewide initiative aimed at enhancing math performance in grades K–3 through targeted interventions, teacher professional development, and peer collaboration. The study utilized a difference-in-differences (DiD) design to analyze data from 395 schools, comparing MAF schools with non-MAF schools to assess the program’s effectiveness on student math achievement, reading performance, and non-academic outcomes such as attendance and disciplinary incidents.

The findings revealed that MAF led to gradual but significant improvements in student outcomes. After four years, math scores in MAF schools increased by +0.09 standard deviations compared to non-MAF schools, with reading scores also seeing a +0.06 standard deviation improvement. The program contributed to reductions in disciplinary incidents and absenteeism, without any unintended negative consequences. Notably, the benefits were consistent across socioeconomic groups, with slightly greater gains observed among racial minority students. The structured intervention model, which emphasized early screening, small-group instruction, and teacher collaboration, played a key role in these positive outcomes. Despite the encouraging results, the study emphasized the need for sustained efforts and complementary strategies to maximize the long-term impact of early math interventions. The estimated four-year per-pupil cost of $750 suggests that MAF provides a cost-effective approach to improving math achievement. The findings underscored the potential of statewide, structured intervention programs as scalable solutions to address early math deficiencies and support student success across diverse populations.

The effect of student-centered strategies on learning outcomes in math teaching

The effect of student-centered strategies on learning outcomes in math teaching

By Liu Ziyu; Institute of Curriculum and Pedagogy, Faculty of Education, Beijing Normal University, China

Mathematics education has undergone significant evolution over the years, transitioning from traditional teacher-centered methods to more dynamic student-centered approaches. Grounded in constructivist learning theory, contemporary mathematics teaching fundamentally relies on learners’ autonomous knowledge-building activities. Consequently, student-centered strategies are widely expected to positively impact the learning process.

To investigate the potential relationship between student-centered strategies and mathematical problem-solving skills, researchers from Turkey conducted a meta-analysis of relevant literature in both Turkish and English. A total of 55 studies and 69 effect sizes were analyzed, revealing a large effect size (Hedge’s g = +0.87). Further analysis indicated that this positive effect is consistent across primary, secondary, and tertiary education levels, with longer interventions (exceeding nine weeks) yielding the most substantial impact. Based on these findings, the authors concluded that student-centered strategies, methods, or techniques in mathematics teaching are particularly effective in enhancing students’ problem-solving skills.