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Welcome!

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We thank you for your time and attendance

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https://bit.ly/OLRdecember14

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USED Non-Regulatory Guidance:

Using Evidence to Strengthen Education Investments

Dr. Richard Lewis, ARP Program Administrator

Jay Johnson, Program Manager

Rachel Wright-Junio, Director

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Purpose

Assist PSUs in making wise choices with their investments during the last year of ESSER funds to ensure the greatest positive impact on students

Outcomes

  • Ensure that all PSUs are aware of the new Non- Regulatory Guidance for Using Evidence to Strengthen Education Investments resource from USED
  • Provide an overview of the document
  • Provide an example of how PSUs may utilize this document within their own contexts

OLR District USED Guidance Example

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Overview

  • Guidance Document Link:
    • https://www2.ed.gov/fund/grant/about/discretionary/2023-non-regulatory-guidance-evidence.pdf

  • Purpose of USED guidance: Help organizations successfully choose and implement evidence-based project components that are designed to improve outcomes for learners

  • Project Components: Evidence-Based activities, strategies, and interventions

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Steps of the Process

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U.S. Department of Education. (2023). Non-Regulatory Guidance: Using Evidence to Strengthen Education Investments. Pg.4

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What is involved in the specific step

Questions to consider during the step

U.S. Department of Education. (2023). Non-Regulatory Guidance: Using Evidence to Strengthen Education Investments. Pg.5

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Part 1: Section 1: Identify Local Needs

What are the needs of the learner population being served?

Who should be at the table with you?

  • Families
  • Students
  • Educators
  • State and local governments
  • community partners/stakeholders

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Do you reach all stakeholders, especially from underserved groups?

Are you ensuring diversity and inclusion?

How do we identify local needs? 🧐

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Part 1: Section 1: Identify Local Needs

What are the needs of the learner population being served?

  • Data sources you may already have:

    • OLR R&E

    • NCStar

    • CCIP

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Remember to use the data you have.

What else (other data) can you use to help better understand your local learner population?

How will you determine what should be prioritized?

What do we have to inform us about our local needs? 🧐

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Part 1: Section 2:

Select Relevant, Evidence-Based Project Components

  • Explore the broadest possible range of evidence

WWC | Find What Works! (ed.gov)

  • Select Project Components that are supported by evidence and have been demonstrated to be effective
  • Select Project Components that are feasible to implement

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How do we know if it is relevant to our needs? 🧐

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Additional Federal Evidence Clearinghouses

  • Dept. of Labor’s Clearinghouse for Labor Evaluation and Research

Homepage | CLEAR (dol.gov)

  • Department of Justice’s CrimeSolutions

Reliable Research. Real Results. | CrimeSolutions, National Institute of Justice (ojp.gov)

  • Dept. of Health and Human Services’ Evidence-Based Practices Resource Center

Resource Center | SAMHSA

  • Americorps’ Evidence Exchange

Evidence Exchange | AmeriCorps

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Where would I go for some cool resources/ideas? 😎

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Considerations

  • The target population and setting in which the evidence used to support the project component was conducted

  • Ability to implement
    • Available funding, staff resources, staff skills, and support for sustaining a project component

Database of Federally Funded Technical Assistance and Research Centers | OSEP Ideas That Work

  • List of additional questions to consider when selecting evidence-based project components can be found on pages 7 & 8 of the guidance document

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Part 1: Section 3: Plan for Implementation

  • Create a Logic Model (OLR Logic Model - v3.0)

  • SMART goals
    • Specific, Measurable, Achievable, Relevant, and Time-Bound

  • Clearly outlined roles and responsibilities for people and organizations involved

  • Timeline for implementation

  • List of resources required

  • Strategies to monitor and evaluate program effectiveness

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What is our plan for implementation? 🧐

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Part 1: Section 3: Plan for Implementation

Basic Logic Model Template

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Resources

Inputs

Activities

Outputs

Outcomes

Impact

Planned work

Your intended results

From: W.K. Kellogg Foundation (2004). Logic Model Development Guide. Retrieved from https://wkkf.issuelab.org/resource/logic-model-development-guide.html

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3

4

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Certain resources are needed to operate your program

If you have access to them, then you can use them to accomplish your planned activities

If you accomplish your planned activities, then you will hopefully deliver the service that you intended

If these benefits to participants are achieved, then certain changes in organizations, communities, or systems might be expected to occur

If you accomplish your planned activities to the extent you intended, then your participants will benefit in certain ways

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Part 1: Section 3: Plan for Implementation

SMART (specific, measurable, achievable, relevant, and time-bound) Goals:

  • Short Term Goals (this school year)
  • Long-term goal (next 3 years)

Roles and Responsibilities:

  • CATS, Teachers, Administrative Staff

Implementation timelines:

  • Professional Development - October
  • Classrooms will begin using the fractions-focus video games - November.

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What is our plan for implementation? 🧐

  • Post-Program Assessments - no more than 10 days after the conclusion of the program
  • Feedback - after the first “round” of implementation and post-program assessment results

Resources required to support the project component:

  • Funding to contract with CATS for the PD and software
  • Buy-in from the participating teachers
  • Time to allow teachers to participate in the required Professional Development

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Part 1: Section 4: Implement

How will you collect relevant information about how your efforts are working and how to make changes?

  • What data do you have?
  • Is this occurring with fidelity?
  • Resource usage
  • Who’s at the table?
  • Scalability

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Is the implementation plan being followed, including partner roles in implementation? If not, why not?

What are unforeseen barriers or potential biases in assumptions or inaccuracies to successful implementation?

What is our plan to ensure fidelity?

How will we collect data?

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Part 1: Section 5: Examine & Reflect

Performance Monitoring - involves regularly collecting and analyzing data to track progress against targets and goals, including data on program outputs and when available, program outcomes.

  • Logic Model expectations

    • Interim goals/milestones
    • continuous improvement insights

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What are the expectations of success and how can success be measured?

What are interim progress and performance milestones that can be tracked?

What have participants (i.e., learners and educators) shared about their experience?

How did we define progress?

How do we define success?

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Part 1: Section 5: Examine & Reflect

Performance Evaluation - demonstrates whether a project component (or the project as a whole) is causing an observed outcome.

  • Evidence of effectiveness
    • Impact of project on relevant outcomes
      • Continue
      • Modify
      • Discontinue
    • How will you share with others?

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What forms of evidence—performance monitoring, evaluation, or both—are needed for decision-making?

Are evidence needs expected to change over time?

Did we meet our goals?

Where do we go from here?

🧐

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Part 2: Guidance on the Meaning of “Evidence-Based”

  • Supported by strong evidence, moderate evidence, promising evidence, or evidence that use of the component demonstrates a rationale.

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U.S. Department of Education. (2023). Non-Regulatory Guidance: Using Evidence to Strengthen Education Investments. Pg.12

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Evidence Required

Level of Evidence

Strong Evidence

Moderate Evidence

Promising Evidence

Demonstrate a Rationale

Outcomes

At least one statistically significant and positive effect on a relevant outcome; no statistically significant and negative effects on a relevant outcome

At least one statistically significant and positive effect on a relevant outcome; no statistically significant and negative effects on a relevant outcome

At least one statistically significant and positive effect on a relevant outcome

N/A

Study Design

Experimental Study

Experimental study or quasi-experimental design study

Experimental study, quasi-experimental design study, or correlational study with statistical controls for selection bias

Logic model informed by research or evaluation findings

WWC Evidence Rating

Meets WWC without reservation

Meets WWC with or without reservation

N/A

N/A

Sample Size

A large sample (n=350+) and a multi-site sample

A large sample (n=350+) and a mult-site sample

N/A

N/A

U.S. Department of Education. (2023). Non-Regulatory Guidance: Using Evidence to Strengthen Education Investments. Pg.16

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Dr. Richard W. Lewis, richard.lewis@dpi.nc.gov

ARP Program Administrator

Office of Learning Recovery and Acceleration

Jay Johnson, jay.johnson@dpi.nc.gov

Program Manager

Office of Learning Recovery and Acceleration

Rachel Wright Junio, rachel.wrightjunio@dpi.nc.gov

Director

Office of Learning Recovery and Acceleration

OLR Program Team

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Thank you

Please complete our

exit ticket

https://bit.ly/OLRdecember14

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