EC Data University – Data Analysis Path


Introduction

The data analysis path expands on the pre-requisite courses to include concepts ranging from statistics to data use as well as their practical application. Data analysis is critical for transforming the ever-growing volume of raw data available to early childhood programs into meaningful information that may be used for checking data quality, identifying/answering programmatic questions, and decision-making. Completion of this path will further build on the knowledge and skills needed to analyze and use data.

This path contains twelve courses:

  • Looking at Trends and Patterns in Data
  • Understanding basic statistics
  • Manipulating and analyzing different types of data
  • Common Data Challenges: Small “n” Sizes
  • Common Data Challenges: Missing Data
  • Evaluating the Implementation of Evidence-Based Practices
  • Excel: Overview of All DaSy Excel Tools
  • Excel: Using Formulas
  • Excel: Pivot Tables
  • Excel: Conditional Formatting
  • Calculating Meaningful Differences
  • Data Analyses Using an Equity Lens

Each course has learning objectives, content, and practice / reflection activities. Scroll down to access the courses.


Course #1 – Looking at Trends and Patterns in Data

Take a Look at Your Child Outcomes Data Profile
Here at the DaSy Center we know that states don’t have a lot of time to conduct ongoing reviews of their child outcomes data collection procedures. To support states in taking the pulse of their child outcomes data, we annually provide each state with its own child outcomes data report, called the State Child Outcomes Data Profile. This profile will help you review different aspects of data quality for your child outcomes.

Checking Outcome Data for Quality: Looking for Patterns
This Early Child Outcomes Center (ECO) resource can be used to check for anomalies in child outcomes data.


Course #2 – Understanding Basic Statistics

(coming soon)


Course #3 – Manipulating and analyzing different types of data

You Collected the Data, Now What? Analysis Plans for Critical Questions
The poster contains information on Critical Questions and analysis plans that provide meaningful information about programs and child and family outcomes. It also includes resources to select Critical Questions; analyze data; share data in understandable ways; and use data to support program improvement.

Taking your Evaluation Plan to the Next Level: Developing Evaluation Analysis Plans to Inform Data Collection Processes and Measurement
This interactive session discusses methods for analyzing various types of performance measures and developing analysis plans to inform data collection processes and performance measures. Participants have opportunities to learn from other states and develop/refine analysis plans.

Planning, Conducting, and Documenting Data Analysis for Program Improvement
DaSy’s new guide, Planning, Conducting, and Documenting Data Analysis for Program Improvement, was developed to help technical assistance (TA) providers and state staff define and limit the scope of data analysis for program improvement efforts, including the State Systemic Improvement Plan (SSIP). The tool was designed to help states in developing a plan for data analysis, documenting alternative hypotheses and additional analyses as they are generated, summarizing findings, and documenting results. Find the document on our Publications Page.

Preventing Data Analysis Paralysis: Strategic Data Analysis Using Data Analysis Plans
This 2014 presentation shares state approaches to data analysis in Phase I of the SSIP. Through their experiences, these states illustrate the importance of having a data analysis plan to provide the foundation for making decisions about program improvement in any initiative requiring data analysis.

SSIP Phase I: Data Analysis
This 2014 webinar is Part 2 of a 3-Part SSIP webinar series. The webinar provides information about the Phase I Data Analysis process; resources and strategies that can support this process; and ideas for engaging stakeholders.


Course #4 = Common Data Challenges: Small “n” Sizes

Best Practices for Determining Subgroup Size in Accountability Systems While Protecting Personally Identifiable Student Information
This 2017 report from the Institute of Education Sciences’ National Center for Education Statistics was created to assist states as they develop accountability systems that (1) comply with ESSA; (2) incorporate sound statistical practices and protections; and (3) meet the information needs of state accountability reporting, while still protecting the privacy of individual students.


Course #5 – Common Data Challenges: Missing Data

(coming soon)


Course #6 – Evaluating the Implementation of Evidence-Based Practices

Evaluating the Implementation of Evidence-based Practices—Tip Sheet Series
This tip sheet series provides concise guidance for collecting and analyzing high-quality data on the implementation of evidence-based practices. The content was designed for staff of state and local early intervention (IDEA Part C) and preschool programs for children with disabilities (IDEA Part B 619), but it is relevant for anyone evaluating the implementation of evidence-based practices.


Course #7 – Excel: Overview of All DaSy Excel Tools

Excel calculator for computing the Number and Percentage of Infants and Toddlers who did not Receive Early Intervention Services for at Least Six Months
This Excel tool can be used to compute the difference between valid entry and exit dates for children receiving early intervention services and count the number of children with less than or more than 6 months of service. The tool will generate a count of the number of infants and toddlers who were in the Part C program at least 6 months. The tool contains embedded edit checks for out of range dates and invalid dates so the final count generated is accurate.

619 Child Outcomes Data Completeness Calculator
This 619 Child Outcomes Data Completeness Calculator is an Excel template that determines the percent of children exiting the program with complete child outcomes data as a proportion of the 3 – 5 child count. The calculator is designed to support state staff in monitoring child outcomes data completeness across programs.

Part C Child Find Funnel Chart Tool
The Child Find Funnel Chart tool is an Excel-based analytic tool for displaying data about infants and toddlers at each step of the Part C process, from referral through exit, for a set of infants and toddlers referred within a specified time span. State or local Part C programs may use this tool to generate a funnel chart that allows for easy visualization of the data.

Identifying Meaningful Differences in Child Find
This Excel-based calculator allows states to make several comparisons related to the percentage of infants and toddlers served: State percentage compared to state target, local program percentage compared to state target, and year-to-year comparisons of the state percentages. It also computes confidence intervals to determines whether the difference between the two numbers is large enough to be considered meaningful (i.e., statistically significant). The intended user for this product are state staff responsible for analysis and use of child find data. The calculator computes statistical differences for both the 0 – 1 child count (Indicator C5) and the 0 – 3 child count (Indicator C6).

Introduction to Self-Assessment Comparison Tool
This 5-minute video is designed to help you get starting with using the Excel-based Self-Assessment Comparison Tool to examine changes over time in the implementation of the ECTA and DaSy System Frameworks. Introduction to Self-Assessment Comparison Tool offers instructions and demonstrations of the tool.

Response Rate and Representativeness Calculator
This 2015 Excel-based calculator allows states to easily compute response rates for their family survey data and determine if the surveys they received are representative of the target population. The calculator uses a statistical formula to determine if two percentages should be considered different from each other. The user enters the values by subgroup and the calculator computes the statistical significance of the difference between the two percentages and highlights significant differences.


Course #8 – Excel: Using Formulas

(coming soon)


Course #9 – Excel: Pivot Tables

Developing Advanced Pivot Tables Workshop
Discover how to create more user-friendly, interactive pivot tables through advanced features in Excel that allow deeper analysis of raw data.


Course #10 – Excel: Conditional Formatting

(coming soon)


Course #11 – Calculating Meaningful Differences

Examining Data to Identify Meaningful Difference
Data analysis is a key process for making data useful. Mistakes in analysis can cloud interpretation and distract from important results. In this session TA providers will discuss key considerations in selecting and using statistical analyses. The focus is on approaches to both describing data and making inferences from data, with specific attention on the role of statistical testing in interpretation.

Identifying Meaningful Differences in Child Find
This Excel-based calculator allows states to make several comparisons related to the percentage of infants and toddlers served: State percentage compared to state target, local program percentage compared to state target, and year-to-year comparisons of the state percentages. It also computes confidence intervals to determines whether the difference between the two numbers is large enough to be considered meaningful (i.e., statistically significant). The intended user for this product are state staff responsible for analysis and use of child find data. The calculator computes statistical differences for both the 0 – 1 child count (Indicator C5) and the 0 – 3 child count (Indicator C6).


Course #12 – Data Analyses Using an Equity Lens

State-Researcher Partnerships to Improve Equity in EI/ECSE
In this webinar, participants learned about state-researcher partnerships to examine state-level trends regarding service provision to diverse children, as well as the development of policy recommendations that reduce such concerns.

Using Child Outcomes Data to Understand Equity
In this session, DaSy staff facilitated discussion with state Part C and Part B/619 staff about analyzing child outcomes data through an equity lens. Topics included asking critical questions without bias, considering data elements to use for disaggregation, and digging deeper in Part C and Part B/619 child outcomes data. Small groups shared out their discussions about data review scenarios and approaches to further equity analyses. Part C and Part B 619 staff can learn from the reflections of their peers on analyzing child outcomes data with an equity mindset.

Using Part C Family Outcomes Data to Examine Equity and Representativeness
In this session, presenters shared how they examine Family Outcomes representativeness using a self-assessment tool adapted using the Family Outcomes Measurement System Framework. They explained how the “Look-Think-Act” protocol and critical data questions can be used for the process of examining and strengthening representativeness. This presentation can help Part C staff and other stakeholders gain strategies for identifying representativeness in response rates and how to ensure all families’ voices are represented in family survey data.