Using Data to Drive School Guidance and Advisement

Activities

Barbara Blackburn, MA, LPCWVDE School Counseling Coordinator

Objectives:

Participants will:

Learn how to access, interpret and present data

Learn how to use data to guide your Guidance and Advisement Program

Student Success

Equity?

Opportunity Gaps: Are some students provided more opportunities than others?

Access to rigorous curriculum Access to quality teachers School policies and climate Special Education Screening and Placement Participation in Support Services

Tutoring, Mentoring/Participation in Support Services

Participation in Extra/Co curricular programs Special Needs Accommodations Test Prep Programs Dual Credit Programs Early enrollment in college courses

Opportunity Gap DataWhat do you want to know?

Accountability System Results Report –

Program Guidance Curriculum Closing the Gap Impact Over Time

School Counselor Performance Standards

The Program Audit

What Is Your Relationship with Education Data?

Nonexistent?

Reactive?

Proactive?

The Power of Data

Provide objective snapshots of the students, school, community

Surface evidence of access or equity issues

Break old myths – eliminate denial Create urgency/energy for change Provide direction – data driven

decisions

The Power of Data

Challenge existing behavior, funding patterns, programs, & policies

Use as an accountability tool Focuses resources where they

are most needed Supports grant writing efforts

Using Data to Spur Systemic Change

School Counselors must be proficient in: Accessing data Analyzing data Interpreting data Presenting data

School Counselors must use data to: - Recognize barriers to learning Point out the system inequities Advocate for system change Create urgency for change

Demographic DataWhat do you want to know?

Student demographics: what are the characteristics of our students?

Gender Ethnicity Socio-economic status (free/reduced

lunch) Limited English Proficiency Family configuration Mobility

Rhode Island Shifts in Student Demographics

77.2 75.4 73.4

7.5 7.7 8.1

1 1 1

13.1 14.8

43.23.2

11.5

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1997 1999 2001

Hispanic

American Indian,non-Hispanic

Asian and PacificIslander, non-HispanicBlack, non-Hispanic

White, non-Hispanic

Source: US Census Bureau, Population Projections, in Education Week, September 27, 2000.

Attainment DataWhat do you want to know?

Attainment: How many make it to - and beyond key points in the system?

Advance to next grade Transition from middle school to high

school Graduation rate Type of high school diploma Matriculation to an institution of

higher education Persistence beyond freshman year Earning a college diploma

Highest Educational Attainment

for Every 100 Kindergartners

African Americans

Asians Latinos Whites

Graduate from High School

87

90

63

93

Complete at Least Some College

50

74

32

65

Obtain at Least a Bachelor’s Degree

18

51

11

33

Source: US Department of Commerce, Bureau of the Census. March Current Population Survey, 1971-2001, In The Condition of Education 2002

(Age 25-29)

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Ninth Grade Retention Rate Reduction as a Result of School Counselor Interventions

Achievement DataWhat do you want to know?

Achievement: What does achievement look like at different levels and with different groups of students?

Overall Achievement Grade point average Standardized test scores, SAT, ACT, State

tests Passing all subjects

Periodic assessment Semester grades End of course tests

Ongoing classroom assessment Class assignment grades Tests

Achievement-Related Data

Course enrollment patterns Discipline referrals Suspension rates Alcohol, tobacco and other drug

violations Attendance rates Parent involvement Extracurricular activities

African American and Latino 17 Year Olds Do Math at Same Levels As White 13 Year Olds

0%

100%

200 250 300 350

White 8th Graders

African American 12th Graders

Latino 12th Graders

Source: NAEP 1999 Long Term Trends Summary Tables (online)

State Data

Black eight-graders and white fourth-graders had almost identical scores in math on a national standardized test in 2003.

Student Behavior DataWhat do you want to know?

Student Behavior Choices: What are students doing?

Attendance Discipline referrals Classroom behavior Homework completion Enrollment patterns

Algebra in 9th grade Upper level math and science Honors, AP, college credit

Low-Income Students are Less Likely to be Enrolled in a College Prep. Track

28.3

48.8

65.1

20

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Socio-Economic Status

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Low Medium High

Source: US Department of Education, National Center for Education Statistics. National Education Longitudinal Study of 1988: Second Follow-Up, 1992 in: A Profile of the American High School Senior in 1992. (p. 36) Washington, DC: US Department of Education, June 1995.

Program Evaluation Data What do you want to know?

Process data Perception data Results data

Process data What do you want to know?

“What you did for whom” Evidence that event occurred How activity was conducted Did the program follow the

prescribed practice?

Process Data - Examples

Weekly (32) academic support groups with 12 students each were held

586 9th grade students received the “The Four Year Plan” guidance lessons

All 4th and 5th (112) grade students participated in the “bus buddy” (4) guidance lessons

Academic Results Interventions (6-8)

72 students avoided retention

ACADEMICCareer

Personal/ Social

0

20

40

60

80

100

120

6thgrade

7thgrade

8thgrade

on retentionoff retention

Perception Data What do you want to know?

“What others think, know or demonstrate” data.

Measures competency achieved, knowledge gained or attitudes beliefs of students Pre-post Competency achievement Surveys Evaluations

Measures what students are perceived to have gained in knowledge

Perception Data - Examples Competency Achievement

Every student in grades 9-12 completed a 4 year plan

Every 10th grade student completed an interest inventory

Knowledge Gained 89% of students demonstrate knowledge of

promotion/ retention criteria 92% can identify Early Warning Signs of violence

Attitudes or Beliefs 74%of students believe fighting is wrong 29% of students feel safe at school 78% know the name of their school counselor

Results Data What do you want to know?

“So WHAT” data Hard data Application data Proof your program has (or has not)

positively impacted students ability to utilize the knowledge, attitudes and skills to effect behavior Attendance Behavior Academic achievement

Results Data - Examples

42 students avoided retention

Graduation rates improved 14% over three years

Attendance improved among 9th grade males by 49%

Possibilities…

There are schools that show things can be different? Find schools like yours that have:

Closed the opportunity gaps Closed the achievement gap

Learn to Analyze and Interpret Data

Data Analysis: Keep It Simple

Descriptive Data Powerful Numbers and percentages

Rationale for Use The benchmark is ALL Usually working with entire population Easier for educators and public to

understand

Basic Ways to Analyze Data

Start with simple statistics - averages, %’s

0102030405060708090

100

02-03

MathEng/ LA

Basic Ways to Analyze Data

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Data Over Time - Examples

Immediate – data measures the immediate impact - pre-post test, p.70-71

Intermediate – data collected over a short period of time - improved grades after counseling group, p. 72-73

Long-range – Longitudinal - data “stretch over time”, p.73

Basic Ways to Analyze Data Start with simple statistics - averages,

%’s Longitudinal

= “stretching” data out over time

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100

98-99 99-00 00-01 01-02 02-03

MathEnglish

Spencer Owen School Corporation ISTEP Tests

Bus Buddy Program Results

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100

97-98 98-99 99-00 00-01 01-02 02-03

Bus Referrals

Basic Ways to Analyze Data Start with simple statistics - averages,

%’s Longitudinal Disaggregate

= “slicing” a piece of dataThe Power of Disaggregated Data

Disaggregation is not a problem-solving strategy. It is a

problem-finding strategy--Victoria Bernhardt

Basic Ways to Analyze Data Start with simple statistics - averages,

%’s Longitudinal Disaggregate

Average MPS Graduation Rate46%

African American32%

Asian52%

Latino31%

Native American27%

White66%

= “slicing” a piece of data

Basic Ways to Analyze Data Disaggregate

0%

10%

20%

30%

40%

50%

60%

70%

Native Am

erican

Asian

Hispa

nic

Afric

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White

GraduationRate

The Power of Data Provide objective snapshots of the students,

school, community Surface evidence of access or equity issues Break old myths – eliminate denial Create urgency/energy for change Provide direction – data driven decisions Challenge existing behavior, funding

patterns, programs, & policies Use as an accountability tool Focuses resources where they are most

needed Supports grant writing efforts

How Not to Use Data

To place blame

To focus on the past

To maintain the status quo

Data Challenges May be the most difficult piece for counselors Counselors must

interpret data collect data get comfortable with data

Not turning counselors into statisticians or researchers

Simplify/streamline by delivering to counselors that data which will serve to reach overall goals

The Payoff… Who Did This?

Reduced 9th grade failure rate by 61.9% Reduced Senior failure by 78.4%. Increased PSAT participation by 106

students Doubled the number of African American

students that took the AP Exam Received 70-80% approval ratings from

students about SC programs

Collaborate on Data Data may be difficult to get – it is

“confidential” Determine who has the data

School level District level State level

Find out what data is available Can they make it simple to use?

Who do you collaborate with?

Evaluation and research experts Counselor Educators Staff development experts

Conduct Data Academies Independent Organizations

Private groups – EDSTAR.org Student View – Hazelden Zoomerang.com, SurveyMonkey.com

Set Measurable Goals and Objectives

Goals - broad statements that describe expected outcomes

Objectives - clear, realistic, measurable and time-limited statements of actions which, when completed, will move towards goal achievement.

Example of Goals and Objectives

Area Goal ObjectiveAcademic

To increase number of promotions

In 05-06, the promotion rate of 3rd grade students will increase by 10% as compared to 04-05.

Behavior To create a safer school climate

In 05-06, incidents of fighting at school will be reduced by 5% as compared to 2004-05.

Attendance

To increase the attendance rate

In 05-06, the attendance rate of 9th grade repeating students will increase by 50%.

Results Report

How are students different as a RESULT of what you do?

What does the data tell you? Was the program successful? What worked? What did NOT work? What needs to be changed?

Longitudinal StudyQuestions

1) Will the use of the Protective School’s Model have any impact on academic progress and attendance for the participating students?

2) Will lowering the student to counselor ratio and fully implementing the CCBG program have an increase on academic progress and attendance for the students?

Reading

4445464748495051525354

2000-01 2001-02 2002-03

districtproject students

2000-01 – 3rd grade, 2001-02 – 4th grade, 2002-03 – 5th grade

40

42

44

46

48

50

52

54

56

2000-01 2001-02 2002-03

districtproject students

Math

2000-01 – 3rd grade, 2001-02 – 4th grade, 2002-03 – 5th grade

92

93

93

94

94

95

95

96

96

97

2000-01 2001-02 2002-03

districtproject students

Attendance

2000-01 – 3rd grade, 2001-02 – 4th grade, 2002-03 – 5th grade

School Climate Results

Examples of preliminary gains are as follows: Teachers reported an increase in student

safety at the project schools. (Source: TUSD School Quality Survey)

Students responded that students of different races & ethnic backgrounds are getting along better at their school. (Source: TUSD School Quality Survey)

Parents indicated an increase in satisfaction with their school. (Source: TUSD School Quality Survey)

All Principals indicated increased contact with students and a more consistent program (in classrooms, groups and interventions) with increased counseling staff. Principals consider the

counselor indispensable. (Source: Principal interviews – March and April 2003)

School Climate Results

Principal Comments

Principals saw counselor as the primary change agent for the school

Principals understood how the counselor can contribute to student achievement

Principals acknowledge that the school counselor knows every student and is the soul or heart of the school.

Advocacy/LeadershipAsk “Hard” QuestionsGather & Present Data Task Group Facilitation

Classroom GuidanceSmall Group InterventionsIndividual Interventions

Referral

DATA

System FocusedActivities

Student FocusedActivities

School Counseling Connected to the Mission of the School

Results Report

How are students different as a RESULT of what you do?

What does the data tell you? Was the program successful? What worked? What did NOT work? What needs to be changed?

Results Report- A Tool For

Ensuring program is carried out Every student is served National Student Standards are addressed Developmentally appropriate Documenting process, perception, results data;

immediate, intermediate, and long range impact of program

Analyze effects Share successes Advocate for systemic change

Results Report Examples

Guidance Curriculum Results Report, p.118

Closing the Gap Results Report, p. 117

DATA GOAL

BrainstormWhat needs to change?Strategies/programs to address need

Reality Check

What does the data tell you about the current situation in your school?

What needs to change? What can the school counseling

program do to create the necessary changes to support student success?

Data Interpretation

Look for:Patterns Gaps

Questions: What problems or needs

surface? What achievement gaps exist? What opportunity gaps do the

data suggest?

Writing Goals and Objectives for Action Plans Choose a reasonable number of

action plans Guidance and Advisement

goals should be written in the terms of improving: Academics Behavior Attendance

Examples of Data to ExamineTest Scores

AchievementStateNational

Enrollment Honors/AP Classes College Track Special Education LEP

Graduation Rate By Gender By Ethnicity By SES

Attendance Absences Tardies By Grade Level

Discipline By Classroom Types of Problems Gender

GPA/Class Rank By Gender By Ethnicity By SES

Retention Rates By Subject Area By Grade Level By Gender, Ethnicity

Post Secondary Plans

Special Education By Gender By Ethnicity By SES

Dropout Rate Grade Levels Gender, Ethnicity… Reasons Why

Accountability …Getting Started

Use what you are already doing (e.g., small group or one classroom).

Use data that are already being collected such as attendance, behavior, grades, or other scores.

Keep it simple – percent change, pre to post changes.

Accountability …Getting Started

Show several years of growth Connect to student standards Don’t measure EVERYTHING Make decisions based on needs of

district, site and access to data Goal is to learn from data, not be

evaluated on data

Questions and Comments

CONTACT INFORMATION

Barbara Brady Blackburn, MA, LPCSchool Counseling CoordinatorWV Department of EducationBldg. 6, Room 2211900 Kanawha Blvd. EastCharleston,  WV 25305-0330Phone: 304-558-2348     Fax: 304-558-3946bblackbu@access.k12.wv.us