FIPSE LSDL Modules

 

PLE 4: Module 6

PLE 4: Exploring student data

Purpose

This PLE is designed to develop participants understanding of how to look critically at student and school level data from an equity framework.  It is also designed to explore measures of central tendency and the limitations of demographic variables such as race, gender, and poverty level. Students will learn to:

  • Identify possible equity issues from multiple and overlapping perspectives
  • Learn to request data in formats that make it possible to explore equity issues
  • Explore appropriate measures of central tendency
  • Distinguish inferential statistics from descriptive statistics 
  • Learn to do proportional within group analysis

Essential Question

How do we examine existing data for insights into the experiences and achievements of multiple racial, ethnic, and language groups?

Activity:  Understanding a data set

For this activity, we have provided you with a data set of student level data. This data set is to be used to explore a series of equity questions and to prepare you for using data from your own setting.

 

Often educators look at a data set and aren’t sure what they are seeing.  One of the first steps in using data is to become familiar with what variables are included in the data set, how they are described, how they are numerically represented, and who is included in the data set.  This is a scan and description activity to become familiar with the data available.

Break into small groups and examine the data set.  Assume that the data included here are representative of the entire school.  After examining the data set, respond to the following questions.  

  1. How would you describe the students who are included?  How many? What grade(s) are represented?  What demographic and descriptive data are included?  How are the data coded?
  2. What achievement data are provided?  What do the achievement entries represent?  What is being measured and what are the scales being used.
  3. What other descriptive or outcome data are included in the spreadsheet?
  4. How would you describe the school that these data represent? 

For additional discussion:  What variable do we use to indicate poverty status?  Is this a good measure?  Why or why not? 

How do we gather information about student race?  What are the possible definitional issues?

Activity:  Describing the group

Looking at achievement, discipline and attendance data for the entire grade, answer these questions.

  1. What is the total number of students in the grade?
  2. What is the average achievement in reading?
  3. What is the average number of discipline reports?
  4. What is the average number of days missed?
  5. What percentage of students have been suspended?

Activity:  Identifying groups for equity disaggregation

Looking again at the data, answer these questions:

  1. What are the student numbers and proportions based upon student sex, student race, student ethnicity, student poverty indicator?  What are the number and proportion of students who are identified as ESL?  As receiving special education services? 
  2. Identify the number and proportion of students by sex, race, and poverty proxy status.

Activity:  Identifying proportional representation

Looking again at the data, compare the proportionality of students receiving special education services by each of the following: race, ethnicity, gender, poverty proxy status.  Compare proportion of students in each group who receive special education services.  What do you see? 

Now disaggregate even further and compare by at least two variables.  For instance, what is the proportion of black females who receive special education services v. black males, white females, white males, Asian females, Asian males, Latino students and Latina students?  What do you see?