ENHANCING TEACHER DATA LITERACY: WHAT SEAS AND

THEIR PARTNERS CAN DO

A Joint Event from theMid-Atlantic Comprehensive Center and

the Appalachia Regional Comprehensive CenterFebruary 5, 2014

Welcome from MACC and ARCC• Marty Orland, MACC Director

Delaware District of ColumbiaMaryland New JerseyPennsylvania

• Sharon Harsh, ARCC DirectorKentucky TennesseeVirginia West Virginia

HousekeepingOverall format of webinar

• Technical issues to jpeters2@wested.orgKey features for attendees

• Participants• All participants are muted

• Chat• Use chat box to share questions or thoughts• Specify public vs. private

• Polling• Questions/results will appear in polling box

• Evaluation• Link to evaluation will be provided at end• Please provide email address if not registered

Polls are located on the right side of the screen.To better see the poll questions, minimize the participant and chat windows by clicking on the light blue arrow.

Poll 1: Tell Us About YourselfWhat is your job responsibility/role?

• State education agency staff• Credentialing/licensing

agency staff• Dean or administrator from a

school of education• Faculty member• School or school district staff• Comprehensive Center staff• Other

What state(s) do you represent?

• Delaware• District of Columbia• Kentucky• Maryland• New Jersey• Pennsylvania• Tennessee• Virginia• West Virginia• Multiple states – Mid-Atlantic• Multiple states – Appalachia • Other

Agenda• Setting the stage – Ellen Mandinach, WestEd• The role of the SEA – Janice Poda, CCSSO• The role of IHEs and licensure agencies

– Ellen Mandinach, Edith Gummer, & Jeremy Friedman, WestEd

• Description from Delaware – Elizabeth Farley-Ripple, University of Delaware

• Discussion – all• Next steps – Ellen Mandinach

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Today’s Agenda

The Need to Improve Teacher Preparation and Data Literacy• Emphasis from policymakers• Emerging standards from CAEP and

other professional organizations• NCTQ

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Why is Data-Driven Decision-Making Important for Education?• Proliferation of diverse sources of

data• Need for evidence-based practice• Changes in policymakers’ emphasis

from data for accountability and compliance to data for continuous improvement

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What is Data Literacy for Teachers?• The ability to transform information into

actionable instructional knowledge and practices by collecting, analyzing, and interpreting all types of data (assessment, school climate, behavioral, snapshot, longitudinal, moment-to-moment, etc.) to help determine instructional steps. It combines an understanding of data with standards, disciplinary knowledge and practices, curricular knowledge, pedagogical content knowledge, and an understanding of how children learn.

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Data Literacy for Teaching: Categories of Skills• Inquiry Processes• Habits of Mind• General Data Use• Data Quality• Data Properties• Data Use Procedural Skills• Transform Data to Information• Transform Data to Implementation

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An Important Caveat• Data literacy is NOT the same as

assessment literacy

• There are differences

• The differences are important

• Typically called data literacy but most often really assessment literacy

• Counter example – CCSSO (2012)11

Systemic Nature of the Reform Issue• Complex• Interacting players• Change cannot happen in isolation• Change comes slowly

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Who Are the Key Players• State Education Agencies• State Licensure Agencies• Professional organizations• Schools of education• Testing organizations• Local Education Agencies• Others

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A Metaphor from the Data Quality Campaign

• The Flashlight

vs.

• The Hammer

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What Can SEAs Do?• Integrate data literacy into licensure

requirements

• Be informed by research and policy trends

• Recognize the difference between data literacy and assessment literacy

• Work with schools of education to align curricula

• Work with districts to understand needs15

Poll 2: Status of Reform in Your State• Is data literacy a topic of

action/reform in your state?• Yes, definitely • Yes, but not a strong emphasis• No

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Poll 3: Data Literacy in Courses and Licensure Requirements• Is data literacy something that you

have included in courses and licensure requirements in your state agency or institution?• Yes, definitely • Yes, but not a strong emphasis• No

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Some Questions• Are any states in the process of updating data

literacy requirements for teacher preparation programs based on updated InTASC standards, the Danielson framework, or other guidance?

• If you are a state licensure person, are you trying to strengthen or make more explicit the requirements around data literacy skills?

• What are your challenges, successes? What kinds of resources, supports, or assistance might you need?

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The Role of the SEA

Janice PodaEducation WorkforceCouncil of Chief State School

Officers (CCSSO)

The Role of SEAs• SEAs have the power of persuasion through the

bully pulpit, role modeling, and the enforcement of law through policy to ensure that teachers and leaders are data literate.

• Examples of policy levers to ensure that teachers and leaders are data literate are:• Program approval• Licensure• Renewal of a license• Professional Learning

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CCSSO’s Emphasis on Data LiteracyInTASC Standards

• Task Force report titled “Our Responsibility, Our Promise”• 7 pilot states participating in the Network for Transforming

Educator Preparation

• Revision of Leadership Standards• ISLLC (practicing school leaders)• ELCC (candidates for school leadership)• Principal supervisor (district office employees who support,

develop and evaluate principals)

Where States Are Currently• Data from 49 states and the District of Columbia have

some sort of documentation that addresses what knowledge and skills teacher candidates need in order to be licensed. The documentation ranges from outdated to up-to-date. • 21 states address data literacy• 37 states address assessment literacy

• Six states (AR, AZ, DC, NV, ND, and SC) make strong use of the InTASC standards (CCSSO, 2011) and one state (SD) uses the Danielson framework (2013).

Source: Mandinach, Friedman, Gummer (2014)

Excerpt from Rhode Island Recently Adopted Program Approval Standards

1.4 Data-Driven Instruction: Approved programs ensure that candidates develop and demonstrate the ability to collect, analyze, and use data from multiple sources- including research, student work and other school-based and classroom- based sources- to inform instructional and professional practice.

Determining Success• Data literacy is not just knowledge but the

application of knowledge into effective practice.

• States need effective measures to determine if candidates are data literate.

• The results of these measures and the support and development teachers and leaders receive should help determine if a candidate is recommended for licensure.

The Role of IHEs

and Licensure Agencies

Ellen Mandinach, Edith Gummer, & Jeremy FriedmanWestEd

The Role of IHEs and Licensure Agencies – Mandinach, Gummer, & Friedman, WestEd

• Three Projects: The Foundation for our Thinking• Spencer Foundation convening• Gates Foundation data literacy

conference• Dell Foundation schools of education

project

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Take Home Messages from Prior Work• Lack of clarity in the terminology – data literacy means

different things to different people

• Developmental continuum for educators’ acquisition of data literacy skills and knowledge is unknown

• Process to elevate the importance to schools of education to have them help build human capacity is complex• How best to integrate data literacy into higher education – stand-alone

or cross program? • Courses or integrated suites of courses?

• Professional development is not enough

• Recognition of the systemic nature of the issue

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The Dell Project: Objective• To understand how many and

what kinds of courses and experiences are being offered in schools of education that help prepare educators to use data.

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The Dell Project: The Survey• Objective – Examine what schools of education

are doing to enhance teachers’ data literacy• Response rate: 24.9 percent (208 out of 836). [26.8 percent /

38 out of 142]

• Respondents were from 47 states, DC, and the Virgin Islands.

• Enroll between 51,840-96,543 pre-service teacher candidates.

• 67.3 [68.4] percent are public colleges or universities (this reflects the second sample).

• 83.7 percent offer teaching candidates bachelor’s degrees, 76.4 percent offer master’s degrees.

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The Dell Project: Syllabus Review• Purpose – To drill down to see

what courses address

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The Dell Project: Licensure Requirements• Purpose – To examine existing

licensure and certification requirements for data literacy skills

• Collaborators – The Data Quality Campaign, NASDTEC

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Survey Results • 91.1 [90.6] percent claim that a focus on

use of data is a sustained component of their teacher prep program in all or multiple courses.

• 45.7 [32.0] percent plan on developing and implementing at least one new course focused on use of data.

Note: “Don’t know” responses were not calculated into percentages for any survey results slides.

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Survey Results – What they’re doingStand-Alone Course• 24.1 [26.3] percent claim to have one

stand-alone use of data course, 38.2 [42.1] claim to have multiple stand-alone courses.• 44.2 percent say the stand-alone course is a

requirement for a teaching degree.• 47.6 percent say the target audience are pre-service

teacher candidates.• 63.5 percent of the time the course’s instructor of

record is tenured or tenure track.• 77.1 percent of the courses examine authentic data;

87.4 percent examine simulated data.

Survey Results – What they’re doingIntegrated Course(s)• 95.6 [97.0%] percent claim to have use of

data integrated within existing courses. • Integrated most prominently into pedagogy and

teaching methods courses.• Many respondents also stated data use was

prominently addressed in assessment courses. Confusing data literacy for assessment literacy?

• The course(s) instructors of record are most frequently tenured or tenure track professors.

• 76.9 percent of the courses examine authentic data; 85.4 percent examine simulated data.

Survey Interpretations and Caveats National• Many schools did not respond.

• Possible that some schools which did not participate did so because they do not have courses on data use.

• Clear that most schools believe they are teaching data use, particularly integrated into other courses. Is this really the case?

• Clear that data use is a focus among the responding schools. Or is it?

Results from the Syllabus Review - Focus• 76% focused on design,

implementation, and analysis of assessments that would be used at the individual student or classroom level

• Secondary focus – formative assessments, state assessments, or assessment policy issues

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Results from the Syllabus Review - Assignments• Lesson or unit plan with assignments• Analysis or writing of assessment items------------------------------------------------------• Summative assessment• Analysis of data• Rubric design• Formative assessment

• classroom and individual students (benchmark or interim)• Statistical analysis• Case studies• Portfolio assessment

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Results from the Licensure Review – General Characteristics• Amount of data-related skills (range across states)• Does it address data (12 states – no)• Does it address assessment (2 states without)• Does it list specific skills (7 states without)• How specific are the statements (range across states)• InTASC (6 states)• Developmental continuum (7 states)• Specific data standard (8 states)• Danielson (1 state)• Data literacy (22 states) vs. assessment literacy (37

states)

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Results from the Licensure Review – Skills (59)• Average number of states per skill = 18.61;

s.d. = 11.06• Average number of skills per state = 21.3;

s.d. = 13.8 [NJ – 19; PA – 15; DE – 49 (InTASC); MD – 12; DC – 10; VA – 20; WV – 21; KY – 24; TN – 20]

• Most frequent skills: assess, collaborate, plan, evaluate, monitor, communicate, use multiple sources, involve stakeholders, make decisions, document/review, provide feedback, self-assess, adjust, analyze, use data, collect/ gather, interpret

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Results from the Licensure Review - Skills• Moderately frequent skills: identify,

adapt, use technology, inquiry, reflect, question, differentiate, access, implement, design, ethics, use research, disaggregate

• Least frequent skills: individualize, use statistics, act, summarize, predict/ hypothesize, synthesize, solve problems, develop assessments, integrate, review, process, infer

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Results from the Licensure Review – Local Highlights• DE – strong data and data literacy emphasis• DC – data standard but really about assessment• MD – more about assessment literacy• NJ – little specifics, more on assessment• PA – more about assessment literacy• KY – more about assessment literacy• TN – has a data standard• VA – strong data emphasis• WV – quite specific, more on assessment

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Data Quality Campaign Survey Results - 2013• 19 states with licensure policies,

including DE, KY, MD, TN, & VA• DE is considered a “leading”

state• KY and VA considered “growing”

states

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Poll 4: Reality Check

• From your perspective do these results reflect the reality of what’s going on in your states?• Yes• No• Unsure

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Teacher and

Leader Data

Literacy

Elizabeth N. Farley-RippleSchool of EducationUniversity of Delaware

External• Delaware ahead of the curve in

data (DQC)• RTTT investment in data coaches

(Amplify)• DE DOE imposing regulations

based on CCSSO report

Context and Impetus for Change

Internal

• Shift in approach to staffing courses

Undergraduate• Internal data and

new performance assessment

• Change in program structure

Graduate• Ed Leadership

faculty research in EBDM

• Emerging teacher leadership program

Teacher and

Leader Data

Literacy

Data Literacy Efforts: What are we doing?

Teacher and

Leader Data

Literacy

Undergraduate• Shift in assessment course from strictly

assessment/measurement toward how you are using that information to make instructional decisions

• Baby steps toward bringing in more than assessment data

Graduate• MEd in Teacher Leadership forthcoming

with two courses to help teacher leaders to understand, manage, and use data for student assessment, instructional planning, and school improvement

• EdD program: program revision with 12 credits dedicated to data and evidence based decision-making (focus on secondary data, research use, and collecting data to identify, diagnose, and solve problems)

Bridging pre-service and in-service

training, differentiated to

roles and responsibilities

How is making this happen?What’s still challenging

Teacher and

Leader Data

Literacy

Structure• Need for dialogue across

content areas Culture

• Academic freedom (to be respected!) and other traditions

Leadership• Need for faculty buy-in

External• Cooperating teachers• Testing culture• Lack of clear standards

for data literacy• Lack of consequential

external demands

What’s workingStructure

• School of Education has no silos so faculty time can flow between programs

Culture• Culture of being proactive

and responsive to external demands

Leadership• Program coordinators use

levers - such as external demands and faculty representation in national dialogue - to achieve goals

TakeawaysHigher education may be hard to move but it is possible!

Internally, structures, culture and leadership can support change

Externally, national dialogue, consumer demand, and regulation are important levers

Thank you!University of Delaware School of Education

Elementary Teacher Education

M.Ed. In Teacher Leadership

Ed.D. in Education Leadership

Teacher and

Leader Data

Literacy

What Needs to Happen?• Schools of education need to discuss how

to introduce data literacy

• Licensure agencies need to be more explicit

• Discussions about what if Praxis includes data literacy

• Discussions among stakeholders about how to make the integration happen

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Discussion

Discussion• How will the certification

agencies respond?• Who are your partners in the

effort to reform and change?• What are your biggest

challenges?50

Discussion• Do you think schools of

education want to change?• Do you think schools of

education will change?

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Continuing Efforts• What is the difference between

elephants mating and establishing the importance of data literacy?

Photo by Ellen Mandinach and Eli Gruber

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Next Steps•https://www.surveymonkey.com/s/TeacherDataLiteracyWebinar

• Questions and ideas for followup

• Closing comments from Caitlin Howley, ARCC and Marty Orland, MACC