Support For Students A national non-profit that describes itself as serving at-risk students hired Edstar to conduct an evaluation of the effectiveness of the services it provided in one large school district. They had three very concrete goals: to raise academic achievement, raise attendance, and reduce suspensions. They had written their own reports about effectiveness, but they were not based on hard data and the way they stated their objectives were in some cases not relevant to success in school. For example, they reported the number of students served who were absent fewer than 18 days. This school district had an attendance policy that students would fail after 10 absences. To begin the evaluation of their services, we needed to build a data set of students served, what services they received, and then merge in the relevant data from the school system. We would need at the very least, the student IDs for school and what services each received from the program. The non-profit provided us with a data file of all the information they had on the students. Their state-level parent organization provided a database for keeping these records. The file they gave us had a column for name, one for either the student ID or the students' birthday, then one for either the services they were enrolled in or the school they attended. We spent at least a month then going through their paper enrollment forms and working with the school district to create a data set that had Student ID in one column and birthday in another, and school attended and services separate, etc. It took at least two people working full time for a month to get the data set created. In the meantime, others Edstar staff was interviewing the non-profit's staff to describe the services, and how they aligned with the intended outcomes. The services were all general, and intended to improve the quality of life of the students. After a year, we were able to create a report showing the academic, attendance, and suspension data for students served. The full spectrum of results in these categories were represented in the students served. What they had in common were that they were primarily low-income and minority students. Many were highly successful in school, some were gifted, some were failing their courses, etc. We helped the staff together with the Student Support Services in the school district to write different objectives for the different needs of these students. For example, the high achieving well behaved low-income students might need a mentor to advise them on what courses to take and how to apply to college. The low-achieving students might need tutoring. The staff pointed out to us that these are not the kind of services they provide. They provide general services for "at-risk" students. We helped them decide to have the school system generate a list of the low-income students who were failing academically, had high absences, and who had suspensions for misbehaving. Then, if they served those students, we'd be able to compare pre-post outcomes on those measures and determine if their "quality of life" services had an impact in those domains. Which beliefs are influencing his 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 his 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 thought that providing activities and services to raise the quality of life for these students would result in more success in school. B.2 Expert vs. Evidence NA B3. What At-Risk Means They primarily served students based on where they lived. They looked only at demographic information, and not any data related to their stated goals. B.4 Desired Outcomes and Goals Their desired outcomes were not relevant because the non-profit did not understand K-12 and how it worked. Students could meet their goal of fewer than 18 absences and fail all of their courses because of the district's attendance policy. Their goals were stated in terms of academic, attendance, and behavior metrics and many of the students they served already exceeded those metrics. B.5 What is STEM and Why We Need to Fill STEM Pipelin NA SkillsS.1 Knowing What Can Be Known NA S.2 How to Identify Kids to Align Services They identified students for services based primarily on where they lived. S.3 How to Classify Things Their parent organization, that created their record-keeping system did not know the importance of unique classification of each variable. For example, you cannot determine the effectiveness of a service if you have recorded either the service received or the school attended. And, you can't pull the data at all if you don't have the Student ID. S.4 Skill Set Required for Working With Data The school system did not have the skills to produce lists of students who met certain academic, attendance, and suspension criteria. S.5 Understanding Data Details NA S.6 Understanding Federal DATA-Handling Laws NA
