Head Start was created in 1964 to assist low-income families with equitable access to schooling. President Lyndon B. Johnson's "War on Poverty" goal was to eliminate educational inequality, and one of the strategies he used was the Head Start program. In addition to helping families, one of the Head Start program's main goals was to get kids ready for school. Head Start data collection makes this possible. The Improving Head Start for School Readiness Act of 2007, states that Head Start and Early Head Start programs have to make decisions based on data. "Data-driven" is a term that needs to be explained, so we took a closer look at how Head Start describes and finds good data below.
Data Collection in Head Start Programs
The Head Start Program Performance Standards (HSPPS)
HSPPS oversee Head Start programs. They were developed in 1975 to make sure that Head Start programs deliver high-quality, comprehensive services that enhance school preparation. HSPPS 101 gives students an overview of the HSPPS and how it pertains to their work. Everyone working for Head Start or Early Head Start needs to know these general rules. This one-hour course covers everything from how the program works to how it is run. It also covers the changes that came with the final rule in 2016, which set higher standards depending on years of research and good practice:
Full-Day, Full-Year Service Duration
Outcomes-Based Standards
Reduction of Burdensome Requirements
Mixed-Delivery System Improvements
Preschool Slot Assessment
Standards, Professional Development and Continuous Improvement
Mixed-Income Programs
Data Privacy
Data Collection
Data collection refers to the systematic act of collecting facts and figures about a subject. During data collection, it is essential to double-check that all necessary fields are filled in and that the information was obtained legally and ethically. If you don't, your analysis won't be reliable, and that might have serious repercussions. Quantitative and qualitative (or contextual) data are both available, and although many techniques for gathering data are transferable between the two, some work far better than others.
Data collection is the first phase of the data lifecycle. The next step is making data useful for your team. To help your nonprofit make better decisions, you need to process, store, manage, analyze, and display this data. Learning about the several options for gathering data can help you choose the approach that will work best for your project's budget, timetable, and research topic. Data obtained through multiple sources such as the internet, email surveys, physical mail responses and phone conversations, will paint a complete picture of the group of people you are collecting data on and create a better representation for strategic decision-making.
Example Of Data Collection Regarding Children's Learning and Development
There is a growing demand for early childhood education programs to gather data on instructors and children to make decisions based on such data. The time and effort required to combine diverse sources of data and the possibility of alternative interpretations for observed patterns are two of the challenges associated with utilizing child data to guide program-level choices. The demand for data-informed decision making at the preschool level and some administrators' interest in correlating early learning goals to attendance statistics, exposed obstacles in merging and interpreting diverse data sources.
Specifically:
The information that is necessary to investigate the early educational experiences of children are often stored in a variety of different databases
Important information is often missing
More variables may help explain the patterns that appear from a single Head Start program's data
Collecting Data and Making Links Between Social Workers and Family
Head Start is a federally supported early childhood education and care program for children from low-income households in the United States. Fifty participants from a sample of Virginia Head Start FSW programs responded in full to a survey administered during the 2014 Virginia Head Start Association Health & Family Conference. Culpeper Head Start Family Support Workers participated in the CBPR by providing input on variable selection, survey instrument development, outcomes discussion, data triangulation, and member verification. Many Early Head Start and Head Start programs have engaged in strategic attempts to redesign their nonprofit’s organizational structures, culture and ways of delivering services to our youngest population, but without data, better-informed decisions will not be possible.
Data Collection in Head Start Programs
If workers and families are hesitant to provide information, it might be challenging to get such information. It's easy to put off gathering data when we have our own children to look after. So, the issue becomes, how can Head Start programs encourage data collecting and foster a "Data-Informed Culture" among teachers and students? The implementation of data gathering is a step-by-step procedure that requires everybody involved to be aware of and dedicated to its significance. Thus, Head Start promotes the Four "R" strategy:
Responsible:
Is your data use ethical? Programs need to get accurate information. The following are some of the criteria that software uses to designate high-quality data:
It paints a clear picture of the topic at hand (children, staff, family, program, etc.)
Data is processed and used promptly inside the software.
The amount of time spent collecting data is minimized while the amount of information gained is maximized.
It explains how to make good use of the data and how to deal with any limitations that may be there.
Respectful:
Have you treated the information with due regard? When gathering information from a family, workers must do it sensitively to the members' individual values, traditions, and worldviews. Here are a few things to think about:
Do you provide forms, questionnaires, and surveys to the family in their native tongue?
Do you value opinions from close relatives?
Are you showing that you value parents' role in a child's development?
Do you let family share their experiences?
Relevant:
Do you have access to up-to-date information? There are a few hallmarks of useful information:
Your information provides answers to specific questions concerning the design of the program, including the aims, methods, and results of the design.
Analyzing your data yields insights that aid in communication between your team and the families you serve.
You gather reliable facts.
You can trust the information you get because you are doing it right.
Your information meets all of the criteria for fairness, accessibility, and cultural and language competence.
Relationship-Based:
How relational is your data usage? Here are a few things to think about:
Do employees motivate parent leaders to instruct other parents on data collection? Do leaders' messages show responsibility, respect, and relevance?
Does the program include family participation methods in its data collection?
Following these principles, the Head Start program can better gather information to benefit the families it assists.