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Title: Using%20Data%20in%20School%20Counseling%20Programs


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
  • ResourceDimmitt, 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 modelUse of data. Retrieved
  •     from http//ascanationalmodel.org/content.asp
    ?pl21sl24contentid24    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. 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).
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