Education and Children In the United States

Key Concepts:

  • High school drop out rate
  • Poverty rate
  • Juvenile Arrest Rate for Violent crime
  • Juvenile Arrest Rate for Property Crime
  • Single Parent Household Rate
  • Percent of Teens Not Attending School and Not Working
  • Teen Birth Rate
  • Rate of Teen Deaths
  • Correlation
  • Scatterplot
  • Ranking
  • Hypothesis
  • Variables

Learning Objectives
After the completion of this module, the learner should be able to:

  1. State a hypothesis
  2. Explore and Examine the relationships between various indicators in KIDS COUNT data
  3. Use KIDS COUNT data to make a scatterplot and rank data.
  4. Interpret data presented in both table and graphic form.
  5. Define the various indicators(variables) used in the module
  6. Discuss the relationship between the dropout and other indicators in the United States and Ohio.
  7. Discuss the relationship between education and other social problems in the United States.
  8. Demonstrate critical thinking skills and use of the sociological imagination.

Pre-Assessment:

  1. What factors do you think are related to teenagers dropping out of high school? Why?


  2. What major social problems do you think are related to teenagers dropping out of high school? Why?


  3. What areas of the country do you believe have the most educational problems? Why?


  4. How do you think Ohio does compared to other States? Why?


Exploration #1:

Go to the Kids Count web site click on 2002 Kids Count Data Book online and look at how "percent of teens who are high school dropouts" varies across states.
[MAP: dropouts]

Looking at the map, how does Ohio compare to other states in terms of the percent of high school dropouts? (You can click on the states on the maps to find out rankings.)

Now examine the actual rankings of the states on this indicator.
[RANKING: dropouts]

List the 5 states with the highest dropout rates.

1.
2.
3.
4.
5.

List the 5 states with the lowest dropout rates.

1.
2.
3.
4.
5.

Were you surprised by the above findings? Why or why not?

Exploration #2: Correlations and Causations

Social Scientists as well as all educators are very interested in trying to understand the factors related to teenagers dropping out of high school. Why do some teenagers stay in high school and why do some drop out? Hopefully, by understanding this information, various educational and programs can be developed to help decrease the numbers of teenagers dropping out of high school.

In this exploration, you as a researcher will be exploring the relationship between the dependent variable Percent of teenagers dropping out of high school and two independent variables (indicators) Percent of children in poverty and Percent of families with children headed by a single parent.

In order to examine these relationships, you will need to use the KIDS COUNT DATA set in a different format. You can minimize the web site or close it. You will use an excel file called "tool_us.xls." On the desktop of your computer, you will see a KIDS COUNT UNITED STATES ICON. Click on this to start the Microsoft Excel Program using KIDS COUNT data. (It can also be downloaded from the SSDAN Kids Count webpage, under Data Resource and Analysis Tool.) Open this file. (Note: When the screen appears, there will be a messaging asking if you want to enable macros, you can click on enable macros.)

This analysis tool enables you to examine the strengths of relationships between variables. One measure of the strength of relationships between variables is called the correlation coefficient. The correlation coefficient can vary from -1.0 to + 1.0. If the correlation coefficient equals +1.00 this means the two variables are perfectly related to one another in a positive direction; in other words, if one variable increases, the other one increases by a corresponding amount. If the correlation coefficient equals -1.00 this also means the two variables are perfectly related to one another, but in a negative direction; if one variables increases, the other variables decreases by a corresponding amount. A coefficient of 0 means there is no relationship. Use the following Correlation Coefficient Key to help you decide about the relationships between variables:

+.70 or higher= Very strong positive
+.40-+.69 =Strong positive
+.30 to +.39=Moderate positive
+.20 to +.29= Weak positive
Less than +.19= Little to no relationship		 -.70 or lower= Very strong negative
-.40 to -.69= Strong negative
-.30 to -.39= Moderate negative
-. 20 to -.29=Weak negative
more than -.19=Little to no relationship

Keep in mind if there is a negative sign in front of the coefficient, this means it is a negative relationship. An increase in one variable causes a decrease in the other variable. Otherwise, the relationship is positive, an increase in one variable causes an increase in the other. You will be using this information to examine the relationships between variables.

You are now ready to examine the relationship between dropping out of high school to several other variables. For this exploration, "Percent of Teenagers Who Drop Out of High School" will be our dependent variable (the x-variable). This is the variable we want to examine in more depth. The other two variables will be the independent variables. Let's begin examining the relationships:

Relationship 1 - DROPOUT and POVERTY

Click on Chart. On the Chart, in the area where it asks for the X-variable, scroll down to DROPOUT. Then for the Y-variable scroll down until you find Poverty (Choose 1999 for both). You will immediately see the scatterplot on the screen. You can click Charts and Rankings below to examine the actual data that created this scatterplot. In order to go back to scatterplots, just click on charts.

What seems to be the relationship between the two variables? Explain (Keep in mind the above chart of correlation coefficient?

Relationship 2 - DROPOUT AND SINGLE PARENTS

Keep your X-variable the same; now choose Percent of Families Headed by Single Parent (Choose 1999 for both). Explore the charts and rankings using your mouse.

What seems to be the relationship between the two variables? Explain (Keep in mind the above chart of correlation coefficient?

Exploration #3: Causation and Consequences

Now, lets examine the consequences of teenagers dropping out of high school. In other words, you will be examining "Dropping out of high school" as an independent variable rather than a dependent variable.

Relationship 1 - Dropping Out and Teen Birth Rate

You need to click on Chart to get back to the screen to choose your indicators. This time, DROPOUT should be your y-variable (Your independent variable) and choose TEEN BIRTHRATE as your x-variable (Your dependent variable).

What hypothesis will you be examining using the above information?

What seems to be the relationship between the two variables? Explain (Keep in mind the above chart of correlation coefficients)?

Relationship 2 - Dropping Out and Teen Deaths

Now examine whether or not the "Percentage of Teenagers Dropping Out of School" is related to an increase in Teen Deaths. Again, choose DROPOUTS as your y-variable and TEEN DEATHS as your x-variable.

What seems to be the relationship between the two variables? Explain (Keep in mind the above chart of correlation coefficients)?

Relationship 3 - Dropping Out and Arrest Rate For Juvenile Violent Crime

Now examine whether or not the Percentage of Teenagers Drop Outing of School is related to an increase in Teen Deaths. Again, choose DROPOUTS as your y-variable and TEEN DEATHS as your x-variable.

What seems to be the relationship between the two variables? Explain (Keep in mind the above chart of correlation coefficients)?

Final Question:

Go back and choose five other indicators to correlate with DROPOUT. List the indicator below and the correlation coefficient you found.

  Indicator Correlation
Coefficient
1. __________ __________
2. __________ __________
3. __________ __________
4. __________ __________
5. __________ __________

What surprised you most about the findings from the final question? Explain?

Go back and look at all the relationships you examined in this exercise, what appears to be the strongest relationship? Why do you think this relationship appears to be strong?

What suggestions would make for social policy makers based on the findings of this module?

Post-Assessment:

  1. What factors do you think are related to teenagers dropping out of high school?

  2. What social problems are related to teenagers dropping out of high school?

  3. How does data help researchers understand social problems?