How State Accountability Systems May Overlook Low Performers

Even as education leaders are encouraged to look at the data to understand which pockets of students need special kinds of support for their learning, a new article and infographic from a research organization have suggested that some "subgroups" of students are too small to register on the radar, which means they get passed over.

A project described by the Regional Educational Laboratory Program set out to understand why some states had a disproportionate number of middle schools with low-performing students with disabilities. In one state, according to the project, middle schools accounted for two-thirds of all schools targeted for improvement under the rules of the Every Student Succeeds Act. As a result, those schools received additional support from the state to help those subgroups improve. But what about the same subgroups in elementary school or high school? How come they weren't targeted for extra help too?

The problem is tucked into the process states may use to identify the "Targeted Support and Improvement" (TSI) schools. Each state comes up with a plan for identifying those schools that underperform through their accountability systems. Those systems typically look at academic achievement, progress and graduation rates within their schools, among other aspects. Each state sets a minimum number of students that each school and subgroup must meet for each performance element before that element is included in the overall accountability score. Schools are tagged for TSI when their subgroup accountability scores are low compared to the overall student population in the state.

The study found that those middle schoolers with disabilities didn't perform "substantially and consistently worse" than the ones in lower or upper grades. However, the schools they attended were "much more likely" to have a sufficient number of students with disabilities taking the state exams to meet state-set minimum thresholds. That meant the subgroups' proficient rates counted more often toward those schools' accountability scores.

The researchers concluded that the sample sizes in elementary and high schools were just too small, thereby masking poor performance.

The article and infographic offered two ways states can overcome this blind spot:

To update their accountability systems so schools "are only compared with other schools that meet minimum sample size requirements for the same performance dimensions"; and

To incorporate statistical techniques to make the accountability scores or small sample sizes more precise.

The coverage of the project is openly available as a blog article and infographic on the REL Mid-Atlantic website.

About the Author

Dian Schaffhauser is a former senior contributing editor for 1105 Media's education publications THE Journal, Campus Technology and Spaces4Learning.

Featured

  • glowing digital human brain composed of abstract lines and nodes, connected to STEM icons, including a DNA strand, a cogwheel, a circuit board, and mathematical formulas

    OpenAI Launches 'Reasoning' AI Model Optimized for STEM

    OpenAI has launched o1, a new family of AI models that are optimized for "reasoning-heavy" tasks like math, coding and science.

  • landscape photo with an AI rubber stamp on top

    California AI Watermarking Bill Supported by OpenAI

    OpenAI, creator of ChatGPT, is backing a California bill that would require tech companies to label AI-generated content in the form of a digital "watermark." The proposed legislation, known as the "California Digital Content Provenance Standards" (AB 3211), aims to ensure transparency in digital media by identifying content created through artificial intelligence. This requirement would apply to a broad range of AI-generated material, from harmless memes to deepfakes that could be used to spread misinformation about political candidates.

  • clock with gears and digital circuits inside

    Report Estimates Cost of AI at Nearly $300K Per Minute

    A report from cloud-based data/BI specialist Domo provides a staggering estimate of the minute-by-minute impact of today's generative AI boom.

  • glowing lines connecting colorful nodes on a deep blue and black gradient background

    Juniper Intros AI-Native Networking and Security Management Platform

    Juniper Networks has launched a new solution that integrates security and networking management under a unified cloud and artificial intelligence engine.