These states often have fewer resources and less funding to invest in special education assessments and programs, despite having higher levels of poverty that are associated with greater need for special education services. I am also curious about the factors that contribute to the relationship between higher poverty levels and increased rates of special education identification.

The data collection tool itself appears to be flawed. It is hard to fathom that an entire states education system would rely on a tool that is biased and ineffective and one that overlooks a large population of students with disabilities, particularly students of color.

Ahh this story makes me so upset. Sarah received consistently positive feedback from those who observed her teaching on a daily basis and recognized her effectiveness in the classroom. However, a new scoring method(likely not developed by educators)was used to evaluate her performance. The evaluation tool may not have captured her strengths or accurately reflected her teaching practice, and there could be many reasons for her low score that are unrelated to her ability as a teacher.

It is interesting to me that after a major crisis, such as the 2008 market crash, there was a shift toward trying entirely new techniques rather than revisiting and improving existing ones. There also appeared to be a sense of panic; because the outcomes in 2008 were so alarming, the existing techniques were deemed ineffective.

This is a concerning reality, as data can be taken out of context and used for marketing purposes or to advance someone’s agenda. Including the caveats and nuances of data is essential, as it provides a more complete and accurate picture rather than presenting partial truths.