EDLDR540:
Lesson 2: Common Types of Data Used in Schools
Lesson 2 Overview
Introduction
There is a wide variety of data that schools now commonly collect and use to improve student outcomes. Much of this data focuses on student tests scores. However there is an increasing variety of data that schools now collect and use. Think about what data is available to you, in your setting, and what questions you may want to ask for the Lesson 15 Final Project.
Objectives
After completing this lesson, you should be able to
- identify the different types of commonly used data in school settings,
- understand the strengths and weaknesses of the different types of commonly used data in school settings,
- identify different types of variables, and
- identify and utilize resources to find specific school-related data.
Readings & Activities
By the end of this lesson, make sure you have completed the readings and activities found in the course schedule.
Pre-Lesson Pondering | Lesson 2
The following is designed to help gauge what you know and what you need to learn. Think of this not as a non-graded quiz but, instead, a triple shot of espresso to activate your critical thinking skills!
Please Take Note:
Although this is not graded, you are required to complete it. You will not be able to proceed with the lesson content or its assignments until this is completed.
Question 1
Which of the following constitutes “data”? (Choose all that apply.)
- Race
- Belief about teachers’ effectiveness
- State standardized achievement test
- Reading program used at a school
Question 2
When collecting data in an educational setting, which of the following are appropriate questions that could be asked? (Choose all that apply.)
- How many students do we have from each racial/ethnic group?
- When we instituted a new reading program, did parents’ beliefs about teachers’ effectiveness change?
- What percentage of students from different racial/ethnic groups score proficient on state standardized achievement tests?
- How have students of different racial/ethnic groups scored on state standardized achievement tests over the past 3 years?
Question 3
Think about why you as an educational leader would ask any of these questions. What would be gained? What other data would you need to know to better understand what you were trying to understand?
2.1. Different Types of Data
Data can take a variety of forms, from numbers, percentages, and ranks to words and descriptions. Schools can use many different types of data to answer an infinite number of questions that can help in their efforts at school improvement.
Data vs. Experience or Beliefs
Before we consider the different kinds of data most relevant to schools’ interests, we should insert a caveat about the difference between “data” on the one hand, and “personal experience,” “anecdotes,” and “beliefs” on the other hand. To illustrate, a speaker at a conference presented findings that contradicted conventional wisdom and what many researchers have concluded for a number of years. Apparently, another person on the panel was taken aback by these controversial findings and said, “Well, those are just numbers. I have been in schools all over [my state], and I know what I have seen.”
Pause to Reflect
Scientific Process
When we engage in the scientific process, we collect data systematically, aligned with the particular questions we are asking, so that we can collect evidence that we can generalize or transfer to multiple situations. The more evidence we collect indicating a particular conclusion, the more confidence we have that we are coming closer to understanding the reality of a phenomenon.
Read
Before proceeding through this module, please read the following:
- Bernhardt, Chapter 3
- ASCD: “No Schools Left Behind”
Watch Video
Before proceeding through this module, watch the following video on Lynda.com:
Reference
Bracey, G. W. (2006). Reading educational research: How to avoid getting statistically snookered. Portsmouth, NH: Heinemann.
2.2. Types of Data
A host of data is available to educators, most of which goes unused. They can use this data to answer many questions regarding school improvement. Victoria Bernhardt divides data into four common types:
- demographics,
- perceptions,
- student learning, and
- school processes.
We will not go into depth on all of these here, as you will be learning more about these different types of data throughout the course. Instead, we will briefly touch on each of Bernhardt's data types. As you read through the following list, think about benefits and potential challenges of using this data.
Demographic Characteristic and Behaviors
Click on the following accordion tabs to reveal expanded content.
Student Demographic Characteristics
Race/Ethnciity: This data identifies a student’s race/ethnicity. There can be complexities in how race and ethnicity is conceptualized. What box does a student check if that student has one parent who is African-American, and one parent who is Hispanic?
Gender: This identifies a student’s gender. Care should be taken to recognize transgender students appropriately.
Age: This identifies a student’s age. In collecting this data, you should identify students who are older or younger relative to their peers.
English Language Learner Status: This data identifies whether or not a student is an English language learner. In collecting this data, you should document the services provided to the student and the years in which the student has participated in ELL services. This is critically important because the Every Student Succeeds Act (ESSA) now requires states to administer new state assessments designed specifically for such students.
Special Education Status: You should collect data that identifies students who have an Individualized Education Plan (IEP) under the Individuals with Disabilities Education Act (IDEA) and, thus, are receiving special education services. Participation in special education requires extensive data collection on the services provided to such students and their academic progress. You should work closely with your special education coordinator and teachers to ensure this is happening.
Section 504 Status: Students with disabilities not covered under IDEA may be covered under Section 504, which is part of the Rehabilitation Act of 1973 that prohibits discrimination based upon disability. It is an anti-discrimination, civil rights statute that requires school personnel to meet the needs of students with disabilities. Section 504 states: “No otherwise qualified individual with a disability in the United States, as defined in section 706(8) of this title, shall, solely by reason of her or his disability, be excluded from the participation in, be denied the benefits of, or be subjected to discrimination under any program or activity receiving Federal financial assistance …” [29 U.S.C. §794(a), 34 C.F.R. §104.4(a)].
Home Language: Collecting data on the home language of students can facilitate school-parent and school-community communications and partnerships.
Homeless Status: Collecting data on homeless students can assist you in accessing fiscal and other resources for such students and can help the adults in the school provide the necessary supports.
Sexual Orientation: Collecting data on student sexual orientation—in an anonymous fashion—can assist in the identification of perceptions of harassment and bullying.
International Student Status: Collecting data on international students.
Grade Level: Knowing the number of students in each grade level can assist in the allocation of resources and planning.
Grade Retention: Calculation of retention in grade can identify areas of challenge that need further investigation to ensure students’ needs are being met.
Student Behaviors
Attendance: Collecting data on who attends and how often is not only important for impacts on student learning, but also as it affects school finances.
Enrollment: Like attendance data, schools must collect this data to report to the state, which then allocates resources based on these numbers.
School Mobility: Students may move from school to school for a variety of reasons. High student mobility can affect student achievement. Research suggests that schools with higher concentrations of mobile students had higher percentages of students with disabilities and fewer students in gifted education programs, and that high mobility may nullify the positive impact of reforms like small classes and more highly qualified teachers.
Bullying: Only recently have schools been more systematic about collecting information about bullying. Not only does this affect individual students, some disproportionately more than others, but it also affects the overall climate of the school.
Violence: The Centers for Disease Control and Prevention (CDC), U.S. Department of Education, and the Office of Juvenile Justice and Delinquency Prevention collect data from a variety of sources to gain a more complete understanding of school violence. This includes things like number of fights in a year, weapons confiscated, and teacher injury.
Teacher Demographic Characteristics
Race/Ethnicity: Just like race/ethnicity of students is important, so is the race/ethnicity of the teacher. Why might that be?
Gender: In 2011, 76% of public school teachers were female. These numbers increase for elementary schools and preschools.
Experience: Data on teacher experience is generally aggregated at the school level for state reporting purposes. However, within a school, such data can be disaggregated by grade level, subject area, and class type (remedial, regular, honors, advanced, Advanced Placement, International Baccalaureate, etc.). Teacher experience is typically measured in one of two ways: average teacher experience and percentage of teachers with specific ranges of experiences such as 0 years, 1–3 years, etc.
Grade Level: Administrators, at the elementary level especially, have to staff classes based on grade level, which is affected by student enrollment numbers as well as teacher certifications.
Subject Area: At the secondary level especially, knowing the areas of certification and the enrollments for different subject areas are critical for staffing. Math/science and special education continue to be areas of high need, especially in urban and rural schools.
Teacher Behaviors
Attrition: Data on how many teachers stay in a school, how many leave, and when they leave are important for the climate of the school, student learning, and teacher quality.
Discipline Referrals: Data on how often teachers refer students for discipline within the school can impact students’ access to academic content and affect their perceptions of the learning environment.
Perceptions
You can rely on surveys to collect data on the perceptions of students and teachers about a wide variety of topics. You may choose to administer surveys to parents and community members as well, but it is often difficult to get an adequate response rate that makes the results generalizable to all parents and community members.
Student Perceptions
Some of the more common topics in surveys of students include the following:
- high expectations,
- climate
- relationships with teachers and administrators
- discipline fairness,
- safety,
- welcoming culture, and
- support for diversity and inclusion.
Teacher Perceptions
Some of the more common topics in surveys of teachers include the following:
- high expectations for students and teachers,
- relationships with students and administrators,
- climate,
- discipline fairness,
- safety,
- welcoming culture for students and teachers,
- support for diversity and inclusion, and
- leadership behaviors.
Web Resource
To learn more about ROI for surveys, as well as tips and tricks to improve the response rate, please review the following resources:
- Practical Surveys: “Typical Response Rates”
- Survey Gizmo: “3 Ways to Improve Your Survey Response Rates”
- Survey Monkey: “Tips and Tricks to Improve Survey Response Rate”
Student Learning
Test Scores
Test scores are collected at the individual student level and then aggregated to the classroom, grade level, school level, and district level. The data is often disaggregated by school characteristics, such as participation in the federal free-/reduced-price lunch program, race/ethnicity, gender, grade level, and age. You will be learning more about different types of test score data in Modules 3 and 4.
Other Student Learning Data
Student test scores (standardized or not) are not the only ways to measure student learning. Teachers may also use formative assessments, which are a way to check for understanding as students are learning; digital portfolios; or even their own observations.
School Process
School processes are those things that happen in the school to create the outcomes (desired or undesired). These data include the school's programs, instructional strategies, assessment strategies, and classroom practices. For example, beyond the reading program selected, knowing how teachers at different grade levels implement that program and identify and remediate struggling readers are important school processes to document.
Frequently, there are unwritten rules, also referred to as the “hidden curriculum,” about how things operate within a school. Creating transparent processes that can be systematically examined is important for school improvement. Careful documentation is essential.
Reference
Jackson, P. W. (1968). Life in classrooms. New York: Holt, Rinehart and Winston.
Check for Understanding | Different Types of Data
Think about the different kinds of data schools use to make decisions in schools. Select at least three. Describe some strengths and weaknesses of using this data as a leader in a school. How might the weaknesses be overcome? (Write about 1–2 paragraphs.)
Please Take Note:
You will not be able to proceed with the lesson content or its assignments until this is completed.
2.3. Where to Find Data
Federal, state, and local governments collect a lot of data about schools. At the federal level, the following websites are useful:
- National Center for Education Statistics: “Search for Public Schools,”
- National Center for Education Statistics: “Search for Private Schools,”
- National Center for Education Statistics: “Assessments,”
- U.S. Department of Education: “Data and Statistics,” and
- Office of Civil Rights: “Data Collection”.
State Departments of Education also provide a lot of data.
Local governments, including school district websites, may provide useful information, including test score data and current initiatives (like Positive Behavior Support).
Hands On
Take a few minutes to peruse some of these sites to see what kind of information is available.
Check for Understanding | Your School's Data
Find a school, preferably one where you work or have some connection. Find the following information:
- racial background of students,
- percent of students on free or reduced lunch,
- teacher to pupil ratio,
- standardized test scores (could be state tests, SAT/ACT, NAEP),
- number of students receiving in-school suspensions, out of school suspensions, expulsions, and
- how much the school or district spends per pupil.
In one paragraph, please answer the following questions:
- Does anything surprise you about these data?
- What questions do these data raise for you? In your response, please explain why.
Please Take Note:
You will not be able to proceed with the lesson content or its assignments until this is completed.
2.4. Uses of Data
Once we have data, what do we do with it? We can use data to answer many different kinds of questions. Some questions involve one of the four categories previously discussed (e.g., demographics), while some questions involve more than one (e.g., demographics and learning). In Chapter 3, you read about 10 levels of analysis that Bernhadt identifies, which involve questions that cover one to four categories and involve either a snapshot or an “over time” analysis.
As you think about questions that may lead to school improvement, you should also think about data as serving any of the following uses:
1. Providing Descriptive Information
Descriptive information often sets the ground work for other kinds of questions about data. For example, let’s say we wanted to know the racial composition of the SAT test takers in 2015. This would be a question in the “Demographics” category of Bernhardt’s model. The following table provides us with this information.
| Test Takers | % Population |
|---|---|
| American Indian or Alaska Native | 1 |
| Asian, Asian American, or Pacific Islander | 12 |
| Black or African American | 13 |
| Mexican or Mexican American | 8 |
| Puerto Rican | 2 |
| Other Hispanic, Latino, or Latin American | 10 |
| White | 47 |
| Other | 4 |
| No Response | 4 |
| Total | 100 |
Pause to Reflect
Consider: Are there any questions that come to mind as you look at this data? Can this information alone answer those questions? What additional information would you need?
2. Exploring Group Differences
We can also use data to tell us if there are differences between groups. For example, our table above now includes scores on math and reading.
| Test Takers | % Population | Math Score | Reading Score |
|---|---|---|---|
| American Indian or Alaska Native | 1 | 482 | 481 |
| Asian, Asian American, or Pacific Islander | 12 | 598 | 525 |
| Black or African American | 13 | 428 | 431 |
| Mexican or Mexican American | 8 | 457 | 448 |
| Puerto Rican | 2 | 449 | 456 |
| Other Hispanic, Latino, or Latin American | 10 | 457 | 449 |
| White | 47 | 534 | 529 |
| Other | 4 | 519 | 490 |
| No Response | 4 | 438 | 434 |
| Total | 100 | 511 | 495 |
Pause to Reflect
Consider: Are there any questions that come to mind as you look at this data? Can this information alone answer those questions? What additional information would you need?
3. Evaluating a Program
We can use data to determine if a program is successful in producing particular outcomes. However, there are a few cautions. First, data needs to be collected before the program begins. This is because you need baseline information to know what was happening before any kind of intervention took place. Second, you need to make sure you are actually measuring the outcome(s) in which you are interested. For example, if you want to know if an SAT prep program was successful in improving students’ math scores, you would not want to look at the total SAT score, which include math and reading and writing.
4. Tracking Growth
In education, many folks are interested in something called “value-added” assessments, which are assessments that track growth over time. You will learn more about value-added assessments in a later module.
2.5. Variables
Variables are another way to talk about data. Essentially, a variable is “any entity that can take on different values.” Variables are critically important if we are to be able to do anything with data, like the data discussed on the previous page.
All of the data described above can be thought of as variables because they can take on different values. Race can be conceptualized as African American or Black, American Indian, Asian or Asian American, Hispanic, Mixed, etc. Test scores can be divided by numbers (like an SAT score of 511) or categories (like “proficient” or “basic”).
Watch Videos
Before proceeding through this module, watch the following videos on Lynda.com:
Note: Videos removed. You will have access to the videos in the actual course.
Lesson 2 Activities
Task 2.a. Quiz | Lesson 2
The purpose of this quiz is to ensure that you have acquired and embedded foundational knowledge from this lesson so that you can apply what you have learned at a higher level of thinking.
Mastery of new content requires both the possession of ready knowledge and the conceptual understanding of how to use it. We know from empirical research that practicing retrieval makes learning stick far better than just rereading. Repeated retrieval can embed knowledge and skills so that they become almost reflexive.
As such, you will not be able to proceed with the lesson's assessments until you have scored a minimum of 80% on this quiz. You will be granted unlimited attempts to achieve mastery. However, you are not permitted to use any course resources (e.g., textbook or online content). You should study for this quiz as you would any other exam.
You will have 5 minutes to complete this quiz. Good luck.
Task 2.b. Applied Learning | Data
Part 1
Look at the following data table referencing SAT takers in 2015.
| Test Takers | % Population | Math Score | Reading Score |
|---|---|---|---|
| American Indian or Alaska Native | 1 | 482 | 481 |
| Asian, Asian American, or Pacific Islander | 12 | 598 | 525 |
| Black or African American | 13 | 428 | 431 |
| Mexican or Mexican American | 8 | 457 | 448 |
| Puerto Rican | 2 | 449 | 456 |
| Other Hispanic, Latino, or Latin American | 10 | 457 | 449 |
| White | 47 | 534 | 529 |
| Other | 4 | 519 | 490 |
| No Response | 4 | 438 | 434 |
| Total | 100 | 511 | 495 |
- Write three questions that you could answer based on the data presented here. Identify and explain which of Bernhardt’s levels of analysis they represent.
- Explain at least two questions this data is not able to answer. What additional data would you need in order to answer these questions?
- Where could you go to find this data?
Part 2
Choose a school that is of interest to you and for which you have some knowledge. Complete the chart on p. 29 of Bernhardt, Chapter 3. Once completed, formulate two questions that are at level 5 or higher and that you believe will lead to improvement in the school.
- Identify the variables (dependent and independent, as appropriate) in your questions.
- Discuss how the data that are available influence the types of questions you chose to ask.
- Explain why you think these will lead to school improvement.
Submit as a single document both parts by Sunday at 11:59 p.m. (ET). Your written response should be approximately 500 words.