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Using Data in School Counseling Programs
By Katie Ackerman, Karla DeCoster, Lisa Lyke
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Thinking About Data 1.) As a teacher, how do/did you assess the success of your lesson? 2.) As counselors, why is data collection important? A.) So we can be utilized to best fulfill students' needs B.) To show others how we can make a difference in students' lives Resource: ASCA (2008)
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The "Engine" of Accountability
Using data means we must 1.) collect data, which is crucial to decision-making 2.) analyze data 3.) make decisions that are guided by data 4.) show results for accountability and evaluation Source: Isaacs, M.L. (April 2003)
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Resistence to Data 1.) Using and understanding data is time-consuming.
2.) Some counselors do not possess the self- efficacy needed to carry out the process. Some dispositions of counselors included the following: A.) general self-efficacy B.) school counselor self-efficacy C.) commitment to counseling improvement D.) openness to change E.) years of experience Sources: Holcomb-McCoy, C., Gonzalez, I., & Johnston, G. (June 2009)
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How to Help 1.) increase counselor self-efficacy and help them to see
the time spent will benefit their program 2.) provide training and opportunities for them to practice learning 3.) provide situations for observing and assisting others with utilization of data 4.) provide time for them to discuss data 5.) provide time for them to work on the process (collect, analyze and evaluate data) 6.) provide them resources and any assistance they may need Sources: Holcomb-McCoy, C., Gonzalez, I., & Johnston, G. (June 2009)
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Types of Data 1) Process Data a) Demographics b) # of interventions
c) discipline referrals 2) Perception Data a)School climate survey b) Survey of students, parents, and administrators 3)Results Data a) Homework Completion b) GPA Source: ASCA 2008
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How to Collect Data 1) Interviews 2) Parent/Faculty/ Student Surveys
3) Student Records 4) Outside Community Resources Ex: Department of Health sees an increase in STDs in teenagers Source: Gysbers, N. 2006
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Resources that can help organize your data
Microsoft Excel spreadsheet or a similar program Online source like ezanalyze or google docs If necessary contact a local college and enlist the help of a graduate student in statistics and school counseling Source: Isaacs 2003
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What Data Can Tell Us 1) Effectiveness a) Entire Program
b) Use of time and resources c) Intervention 2) Areas of need a)Academic progress b)Barriers c)Achievement gaps d) Interventions Resource:Dimmitt, C 2003, Hayes, R L et. al. 2002
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How to Use Data 1) To make purposeful, consistent, and defendable decisions 2) To Plan 3) To implement changes 4) After the implementation re-evaluate 4) Communicate with stakeholders -Goals & Priorities -Benefits of program -Value of each dollar spent on program -High Expectations -Give others reason to support your efforts 5) To allocate resources 6) Make referrals Sources: Dimmitt 2003; Isaacs, 2003; Holcomb-McCoy et. al., 2009; Kaffenberger & Davis, 2009; Young et. al., 2009 As educators it is important we show our accountability in this era. Data can help us do this. I think the most beneficial use of data is to make purposeful, consistent and defendable decisions. Everything we do should have a purpose and have an impact on students. In addition students do better in a consistent environment (as do the teachers). So if we make consistent decisions that do not counteract with each other and that help make actions more predictable others will be more trustworthy of us. Not every situation is the same but if we approach all situations with similar philosophies others will see the consistency in that. We must also be able to defend our decisions and data can show the need for any of our actions. As we have discussed previously in class data guide our decisions as we plan our program, priorities and our program; implement changes and evaluate all of our actions. In addition, we can use data to communicate to students, staff, parents, and the community. Data can show our goals, areas we need to set as our priority, the benefit of the counseling program and the impact of each dollar spent. We must also communicate high expectations and to get others to support our efforts. Data can also help us see how to best allocate our resources and be used to show a need for us referring students to outside help.
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IDEAS Model of DBDM Stage 1: Identify a Question
Task 1: Form a DBDM Team Task 2: Identify a goal to address Task 3: Collect and analyze data Stage 2: Develop a Plan Task 1: Identify barriers to the goal Task 2: Create/choose an evidenced-based intervention Task 3: Develop an action plan Task 4: Develop an evaluation plan Sources: Poynton & Carey, 2006 It is one thing for a school to have data, then to collect and organize it in a way that it can be analyzed and then it is another thing if the school actually does something with what they learned from the data. What good does it do for students to take a standardized test if we do nothing with the results? If we want to implement and effective program we must do something with all the data available to us. In an article by Timothy Poyntion and John Carey titled, “An integrative model of data-based decision making for school counseling” found in the December 2006 edition of Professional School Counselor we learned about Data-Based Decision Making. These researchers looked at four different models of how to use data to make decisions and came up with their own model known as the IDEAS! Model. In the first stage you are creating your problem statement. You form a team to help you, chose the goal of your program that you are going to evaluate and make sure you are meeting, and then collect and analyze data to see where you are in meeting this goal. In Stage 2 you are going to use the data and develop a plan of action. The first task is to look at the data you analyzed and identify any barriers to the goal. Then from that information you will create or choose an evidenced based intervention that might solve your problem and eliminate the barriers that are preventing you from reaching your goal. Task 3 is where you create a blueprint for how the intervention will work and then you must, before you implement, establish a plan on how you will evaluate the intervention to ensure its effectiveness.
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IDEAS Model of DBDM (continued...)
Stage 3: Execute the Plan Task 1: Begin implementation Task 2: Monitor Implementation Task 3: Assess as you go and make adjustments Stage 4: Answer the Question Task 1: Analyze new data Task 2: Interpret results to see if you met goal Stage 5: Share Results Sources: Poynton & Carey, 2006 In Stage 3 you execute the plan. You begin implementation, then monitor it as it is implemented to make sure it is properly executed. For example, if the intervention is one being carried out by multiple classroom teachers you want to make sure each teacher is carrying it out in an equitable way. As you implement the plan you need to assess and make any necessary adjustments. In Stage 4 you are looking to see if you adequately answered the question you developed in stage one. You will need to follow through with your evaluation plan you created in stage two and analyze the new data. As you interpret this data look to see if you have met your goal. If you have move on to stage 5, if not go back to stage 2 and start over. Stage 5 is where you show your success by sharing the data with others. The data should be shared in a brief, to the point way that is easily understood by all intended readers.
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Activity 4) Now, write your question
For our activity we are going to carry out the first two stages of the IDEAS model Stage 1: Identify a Question 1) Divide into DBDM teams 2) We are going to focus on the following goal: to maximize the academic development of every student 3) Analyze the results of the state assessment (to keep the activity simple we are only looking at one set of data. In real life you will want to use multiple sources of data) 4) Now, write your question Give groups 10 minutes to work on these two stages then ask them to share what they have found. Hopefully they found that 3.3A1 and 4.1k3 were the lowest areas and developed some type of intervention for those areas. My suggestion for an intervention would be to have the math teachers spend more times on those units. The art teacher might be able to do an activity around 3.3A1 and the PE teacher might be able to do an activity around 4.1K3.
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Activity (continued...) Stage 2: Develop a Plan
1) Looking at the results, what areas are a barrier to our goal? 2) Create an intervention that could address this barrier to help us meet our goal 3) Outline a plan to implement the intervention 4) Outline a plan you would use to evaluate the intervention Give groups 10 minutes to work on these two stages then ask them to share what they have found. Hopefully they found that 3.3A1 and 4.1k3 were the lowest areas and developed some type of intervention for those areas. My suggestion for an intervention would be to have the math teachers spend more times on those units. The art teacher might be able to do an activity around 3.3A1 and the PE teacher might be able to do an activity around 4.1K3.
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Sources American School Counseling Association. (2008). ASCA national model:Use of data. Retrieved from: Camizzi, E., Clark, M.A., Yacco, S., & Goodman, W. (August 2009). Becoming 'difference makers' school-university collaboration to create, implement, and evaluate data-driven counseling interventions. Professional School Counseling, 12. p Dimmitt, C. (June 2003). Transforming school counseling practice through collaboration and the use of data: a study of academic faliure high school. Professional School Counseling. 6. p. 340- 349. Gysbers,N. (2006). Developing & managing: Your school guidance and counseling program (4th ed). American Counseling Association. Hayes, R.L., Nelson, J-L., Tabin, M., Pearson, G., & Worthy, C. (Dec 2002). Using school-wide data to advocate for student success. Professional School Counseling.6. p Holcomb-McCoy, C., Gonzalez, I., & Johnston, G. (June 2009). School counselor dispositions as predictors of data usage. Professional School Counseling. 12. p Isaacs, M.L. (April 2003). Data-driven decision making: The engine of accountability. Professional School Counseling. 12. p Kaffenberger, C., & Davis, T. (August 2009). Introduction to special issue: a call for practitioner research. Professional School Counseling.12. p Poynton, T.A., & Carey, J.C. (Dec 2006). An integrative model of data-based decision making for school counseling. Professional School Counseling. 10. p Young, A., Hardy, V., Hamilton, C., Biernesser, K. Sun, L.L., & Neibergall, S. (August 2009). Empowering sents: using data to transform a bullying prevention and intervention program. Professional School Counseling. 12. p
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