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Using Data in School Counseling Programs

Using Data in School Counseling Programs. By Katie Ackerman, Karla DeCoster, Lisa Lyke. 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? 

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Using Data in School Counseling Programs

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  1. Using Data in School Counseling Programs By Katie Ackerman, Karla DeCoster, Lisa Lyke

  2. 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)

  3. 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)

  4. 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) 

  5. 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)

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. Activity • 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

  14. 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

  15. Sources American School Counseling Association. (2008). ASCA national model:Use of data. Retrieved     from: http://ascanationalmodel.org/content.asp?pl=21&sl=24&contentid=24Camizzi, 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. 471-479. 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. 86-94. Holcomb-McCoy, C., Gonzalez, I., & Johnston, G. (June 2009). School counselor dispositions as     predictors of data usage. Professional School Counseling. 12. p. 343-351. Isaacs, M.L. (April 2003). Data-driven decision making: The engine of accountability.     Professional School Counseling. 12. p. 288-295. Kaffenberger, C., & Davis, T. (August 2009). Introduction to special issue: a call for     practitioner research. Professional School Counseling.12. p. 392-394. Poynton, T.A., & Carey, J.C. (Dec 2006). An integrative model of data-based decision making     for school counseling. Professional School Counseling. 10. p. 121-130. 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. 413-420.

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