Poverty Training A school hired us to help them with their School Improvement Plan. They had provided a Poverty Framework professional development for all of the staff in which they learned that low-income kids differ from not-low-income kids in several ways, including their spiritual beliefs, the types of relationships they have, and their speech register, among other things. This was the first time they had attempted to implement a data-driven School Improvement Plan, with measurable objectives. Until this time, their professional development had taught them that low-income students are different in these ways, and they believed they are also less successful academically. They wrote their School Improvement Plan to change the low-income students to be more like the non-low-income students in hopes that they would then become more academically successful. Each staff member identified a student whom they believed to be low-income and then mentored them to change them to be more like non-poor students in these areas. They surveyed the staff to have them document how they were mentoring the students, and what progress they were making in these areas. They weren’t sure what to do with the data from the surveys, or how to measure success so they hired us mid year, after staff had completed two surveys to document how they were changing the students, and what progress they were making. They were not using any academic data to measure progress. Just staff reported changes in the students. Which beliefs are influencing their Equity Lens? Click to check your answer. B.1 Cause and Effect B.2 Expert vs. Evidence B.3 What At-Risk Means B.4 Desired Outcomes and Goals B.5 What is STEM and Why We Need to Fill STEM Pipeline Which skills are influencing their Equity Lens? Click to check your answer. S.1 Knowing What Can Be Known S.2 How to Identify Kids to Align Services S.3 How to Classify Things S.4 Working With Data S.5 Understanding Data Details S.6 Understanding Federal Data-Handling Laws BeliefsB.1 Cause and Effect They were trying something innovative that they hoped would simply result in better academic outcomes. They thought the speech register, types of relationships, etc. of poor students CAUSED them to be unsuccessful in school, so if they could change those things, they would be successful. B.2 Expert vs. Evidence NA B3. What At-Risk Means They thought teachers could identify academically "at-risk" students without using any academic data, simply by looking for students who had low-income characteristics as described in the Poverty Training. B.4 Desired Outcomes and Goals They told us the low-expectations for these students they identified to mentor would not hurt them because rigorous and challenging work are just not for them. B.5 What is STEM and Why We Need to Fill STEM Pipeline NA SkillsS.1 Knowing What Can Be Known When we showed the administrators in the school the academic data profiles of the students who were being mentored, they were stunned that we could put this information together and know this. S.2 How to Identify Kids to Align Services They identified the academically "at-risk" students one student at a time, and did not run any lists of students with specific characteristics. S.3 How to Classify Things NA S.4 Skill-Set Required for Working With Data They had never had any reason to develop skills for working with data. In the second year that we worked with them, Edstar organized all their data for them, helped them interpret it, and use it. S.5 Understanding Data Details NA S.6 Understanding Federal Data-Handling Laws NA
