The eye-of-the-storm technique is an experiential teaching technique heralded by Jane Elliot, and used to enlighten youngsters on the impact of overt racism and discrimination.

In Ch. 3, you learned about micro-assaults (e.g., micro-invalidation, micro-aggression). As a reminder, micro-assaults are covert or subtle acts of discrimination that plague minority, dis-empowered or disenfranchised groups in our contemporary world.

Watch the following video on the Eye of the Storm technique:

Then, reflect upon applying this pedagogical exercise to microaggressions from Ch. 3. It is advised that you review microaggressions from Ch. 3.

Identify a current social cause (example: gender discrimination) and write a paper describing how you would implement an eye-of-the-storm teaching technique/demonstration to highlight micro-assaults plaguing a group.

Please identify the social cause (e.g., gender discrimination), the social group (e.g., women), the micro-assaults you want to expose your “class” to, and the strategy(-ies) you will use to induce the eye-of-the-storm technique (i.e., what will you do). Please be creative and concise. More specifically, please address the following points in your paper:

1. Explain micro-aggressions/assaults/invalidations (3 points)
2. Describe the social cause, the social group affected, and the micro-assaults you want to expose your “class” to; i.e., describe to whom and how you will do “eye of the storm” (3 points)
3. Describe strategies you will use to induce the eye-of-the-storm technique (4 points)

Statistical analysis software is a valuable tool that helps researchers perform the complex calculations. However, to use such a tool effectively, the study must be well designed. The social worker must understand all the relationships involved in the study. He or she must understand the study’s purpose and select the most appropriate design. The social worker must correctly represent the relationship being examined and the variables involved. Finally, he or she must enter those variables correctly into the software package. This assignment will allow you to analyze in detail the decisions made in the “Social Work Research: Chi Square” case study and the relationship between study design and statistical analysis. Assume that the data has been entered into SPSS and you’ve been given the output of the chi-square results. (See Week 4 Handout: Chi-Square findings).

Submit a 1-page paper of the following:

An analysis of the relationship between study design and statistical analysis used in the case study that includes:

• An explanation of why you think that the agency created a plan to evaluate the program

An explanation of why the social work agency in the case study chose to use a chi square statistic to evaluate whether there is a difference between those who participated in the program and those who did not (Hint: Think about the level of measurement of the variables)

• A description of the research design in terms of observations (O) and interventions (X) for each group.

• Interpret the chi-square output data. What do the data say about the program?Week 4 Handout: Chi-Square Findings

  The chi square test for independence is used to determine whether there is a relationship between the two variables that are categorical in the level of measurement. In this case, the variables are: employment level and treatment condition. It tests whether there is a difference between groups. The research question for the study is: Is there a relationship between the independent variable, treatment, and the dependent variable, employment level? In other words, is there a difference in the number of participants who are not employed, employed part-time and employed full-time in the program and the control group (i.e., waitlist group)? The hypotheses are:

  H0 (The null hypothesis): There is no difference in the proportions of individuals in the three employment categories between the treatment group and the waitlist group. In other words, the frequency distribution for variable 2 (employment) has the same proportions for both categories of variable 1 (program participation).

  ** It is the null hypothesis that is actually tested by the statistic. A chi square statistic that is found to be statistically significant, (e.g. p< .05) indicates that we can reject the null hypothesis (understanding that there is less than a 5% chance that the relationship between the variables is due to chance).

  H1 (The alternative hypothesis): There is a difference in the proportions of individuals in the three employment categories between the treatment group and the waitlist group.

  ** The alternative hypothesis states that there is a difference. It would allow us to say that it appears that the treatment (voc rehab program) is effective in increasing the employment status of participants.

   

  Assume that the data has been collected to answer the above research question. Someone has entered the data into SPSS. A chi-square test was conducted, and you were given the following SPSS output data: