Building Capacity for Data-Driven Coaching
Data-Driven Coaching supports teachers in using data to reflect on their practice and make instructional decisions to improve student learning outcomes. Note that earning this Microcredential requires prerequisites as aligned with the USBE Instructional Coaching Endorsement and is intended as a competency path for an experienced instructional coach.
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Utah Effective Teaching Standards > Standard 2: Instructional Design Clarity
Element 2: Learning Progression - Demonstrating a comprehensive understanding of where students have been, where they are now and where they are going using strategically sequenced learning experiences aligned within and across grade levels. -
Utah Effective Teaching Standards > Standard 3: Instructional Practice
Element 2: Assessment Practices - Critically analyzing evidence from both formative and summative assessments to inform and adjust instruction and provide feedback to students to support learning and growth. -
Utah Effective Teaching Standards > Standard 5: Professional Responsibility
Element 2: Continuous Professional Learning - Engaging in and valuing constructive feedback, reflective practices, professional learning and collaborative activities that support professional, instructional and schoolwide improvement.
To earn this microcredential you will need to collect and submit three sets of evidence demonstrating your effective and consistent use of appropriate instructional coaching strategies. You will also complete a written or video reflective analysis.
Note that earning this Microcredential requires prerequisites as aligned with the USBE Instructional Coaching Endorsement and is intended as a competency path for an experienced instructional coach. In order to qualify for earning this microcredential the applicant must:
- have at least 5 years of classroom experience or equivalent (been an active, certificated educator)
- have strong experience providing instruction and professional learning to adult educators
- have at least 3 consecutive years of effective or higher rating on UETS according to the LEA rating system or equivalent
- have completed at least 1 year full-time experience in the Utah education system
to gather together a database of information about student learning, and use that information to improve the quality of instruction delivered in the classroom.
Data-Driven Instructional Coaching:using instructional data to focus on student achievement connected to the instructional goals of the teacher. Data-driven instructional coaching involves an ongoing cycle of goal-setting, learning, observation and data collection, and reflection.
Elementary Scenario Cameron Oden is an elementary instructional math coach. He works at Sun Valley Elementary School supporting teachers in data-driven instructional coaching. He is currently working with the third-grade team as they are working to improve their math instruction and student mathematical performance. They meet together each week to collaborate and share their weekly math data. They then use that data to inform instruction for the following week. Mr. Oden has supported the team in establishing norms for their data collaboration meetings. Team members are expected to come to each meeting prepared with data already entered into their Grade Level Tracking Sheet.
The third-grade team is beginning their next math unit on fractions. The team brings their common fractions pre-assessment data to their weekly collaboration. Mr. Oden asks probing and reflective questions of the team to help them interpret their data. He asks the team to consider how their instructional practices should change based on the data gathered. The team identifies what mastery of the standard looks like and sets an instructional goal for student learning. The team works together with Mr. Oden’s support and guidance to plan their instructional strategies for the coming week. They also sort students needing extra support by common misconceptions identified through the data. Mr. Oden helps the team develop a common exit ticket that will be used for their data collection the following week.
Throughout the week Mr. Oden checks in with individual team members and discusses their progress towards the goal identified. He works with one member of the team that expresses concern in meeting the goal and implementing the instructional strategies planned by the team with students. He works with the teacher on building their skills in implementing the math teaching practices identified by the team through co-teaching and observation.
At their next weekly collaboration, the team comes back together bringing their completed data and formative observations about student learning. Mr. Oden supports the team in interpreting their data compared to the instructional goal established by the team. They then continue through the data-driven instruction process of establishing a new goal based on that data, planning instructional strategies based on the data, grouping students for Tier 2 support and intervention, and identifying a common assessment to be used the following week.
Secondary Scenario Luciana Noble is middle school instructional coach supporting 7th, 8th, and 9th grade educators in using data to drive instructional decision making and increase student learning outcomes. Miss Noble is currently working with the science department at Evergreen Middle School. They are working as a department to identify academic areas of strength and areas in need of improvement based on the end-of-year standardized assessment results.
Miss Noble meets with the entire department and supplies each educator the science assessment data from the previous school year. She has the educators work in groups and first identify the areas of greatest strength as a department. As they identify the areas with the highest level of student performance, Miss Noble asks probing and reflective questions of the group. Through her questioning they identify instructional practices that supported student performance. Miss Noble guides the group in creating an ongoing plan for future implementation of instructional practices and strategies they identified as contributors to student success.
Miss Noble then asks the group to identify the standards and areas in which the students showed need for more support. As they are working Miss Noble provides encouragement and support; however, she also participates in questioning with the educators to help them identify areas in which they can improve their instructional skills and practices to increase student learning.
At the close of the meeting, Miss Noble asks each participant to complete an exit ticket as a team or an individual and choose one academic area or standard identified through the data. She explains that following the meeting they will work with her on a data-driven instructional coaching cycle in the identified area. Following the meeting, Miss Noble creates a schedule and begins working with each team or individual in the area in which they identified.
Category: Preparation and Planning
Submit the evidence listed below to demonstrate your effective and consistent preparation and planning for instructional coaching.
Submit a plan that you have used for data-driven instructional coaching with individuals and/or teams. Include the following in the plan: ● the steps you will take as the instructional coach to facilitate data-driven instructional coaching ● skills for analyzing and utilizing data ● instructional decision making skills and best-practices for supporting educators ● reflective questions to incorporate for various situations
Category: Implementation
Submit the evidence listed below to demonstrate your effective and consistent implementation of appropriate practices for instructional coaching.
Participate in data-driven instructional coaching with at least three educators or teams. Submit data that was used by the instructional coach and teacher(s) to assess the effectiveness of instruction and inform instruction. Each data set should include pre-assessment and post-assessment data. Additional formative assessment used during the data-driven instructional coaching may also be included.
Category: Supplemental
Submit BOTH of the evidence sets listed below to demonstrate your effective and consistent implementation of appropriate practices for instructional coaching.
Submit a written testimonial from at least one representative from each data conversation held during the implementation section. The three participating representatives should describe their experience with data-driven instructional coaching. Testimonial should include how the instructional coach supported the teacher in each of the following components: ● Describe the experience with the instructional coach and how it supported their ability use data to inform instructional decision making ● Describe the data that was used to inform instruction ● Describe the instructional decisions that were made from interpreting the data ● Describe the results of the post assessment data Include educator name, position, school, and signature for each of the three educators/team testimonials.
Submit a completed copy of the Instructional Coaching Microcredential Eligibility Prerequisite form, found in the Resources section below. This will verify your teaching and coaching experience as signed by your LEA’s Human Resources or Business Office.
Review Criteria
EVIDENCE OF PREPARATION AND PLANNING CRITERIA Criterion 1: The plan identifies the steps that will be taken to facilitate data-driven instructional coaching with educators. Example: An instructional coach explains in detail the steps they will take in working with teams through data-driven instructional coaching. The plan includes a specific timeline and checkpoints to refer to throughout the process. Non-Example: The instructional coach plans to provide educators access to their data and a list of questions for the teacher to consider. The plan does not include detailed steps for data-driven instructional coaching.
Criterion 2: The plan includes skills the instructional coach can use during implementation for analyzing and utilizing data. Example: The instructional coach includes the following skills in the plan for analyzing and utilizing the data: ● Modeling the data ● Interpreting the results ● Desegregating important pieces of the data ● Communication regarding results Non-Example: The submission does not include example skills for analyzing and utilizing the data with educators.
Criterion 3: The plan includes instructional decision-making skills and best practices that could be provided to educators during the data-driven instructional coaching. Example: The plan includes instructional decision making skills and best practices. These skills include strategies for the following areas: ● Student Learning Outcomes ● Lesson Pacing ● Engagement Strategies ● Formative Assessment Strategies ● Lesson Planning and Delivery Non-Example: The submission does not include specific instructional decision making skills and best practices.
Criterion 4: The plan includes reflective questions to incorporate for various situations during data driven instructional coaching. Example: The instructional coach includes guiding and reflective questions to use during data-driven instructional coaching. The questions include: ● What is it we want all students to learn? ● How will we know when a student gets there? ● What does mastery of the standard look like? ● What do we do when a student does not learn? Non-Example: The submission does not include guiding and reflective questions to use during data-driven instructional coaching.
EVIDENCE OF IMPLEMENTATION CRITERIA Criterion 1: The academic standard and student learning outcome identified during data-driven instructional coaching is included in the submission. Example: An instructional coach supports a teacher through the use of data-driven coaching. The teacher identifies the language arts standard being targeted. Together they determine the intended student learning outcomes. The instructional coach includes both the language arts standard and the intended learning outcomes in the artifact. Non-Example: The instructional coach submits learner performance data that does not include the academic standard(s) and intended learning outcomes that were used during the data-driven coaching.
Criterion 2: The pre-assessment data that was used for data-driven instructional coaching is present. The assessment data match the standards and learning outcomes identified. Example: An instructional coach provides an elementary teacher with their beginning-of-year reading fluency and accuracy data. Together they interpret the pre-assessment data and make a plan for instructional implementation, formative assessment, and post-assessment. The pre-assessment data used is included in the submission. Non-Example: The submission does not include the pre-assessment data or the data does not match the intended learning outcomes identified.
Criterion 3: The post-assessment that was used for data-driven instructional coaching is present. The assessment data match the standards and learning outcomes identified. Example: Following a data-driven instructional coaching cycle, an instructional coach and teacher use the post-assessment data to plan re teaching as needed. The post-assessment data is used to design instructional practices to meet student learning needs. The post-assessment data used is included in the submission. Non-Example: The submission does not include the post-assessment data or the data does not match the pre-assessment and the intended learning outcomes identified.
SUPPLEMENTAL EVIDENCE CRITERIA Criterion 1: The testimonial describe the experience with the instructional coach and how it supported their ability use data to inform instructional decision making. Example: Marco Spalding is a teacher whose instructional coach supported his professional learning through data-driven instructional coaching. Mr. Spalding wrote a testimonial for his experience: “I worked with my instructional coach Anita Lancer, to improve my student’s performance in math. We looked at the data from my student’s Unit 1 math pre-assessment. Together we interpreted the data looking for significant misconceptions in student learning. We identified two main areas of concern and developed a plan for improving learning around those areas of struggle. Together we identified that most student’s errors on the pre-assessment were commonly missing a step or a computation error. Mrs. Lancer and I determined that the students needed more step-by-step strategy instruction including teacher modeling, guided practice, and independent practice. We also identified that students would benefit from strategies to organize their work as they are completing the steps and checking their work with another strategy. Those instructional skills and strategies were identified to support students in identifying if they had a computation errors or missed any step during completion of the problem. During the planning and implementation of the plan, Mrs. Lancer was very helpful in asking me thought provoking questions that helped me to understand the data and supported me in identifying instructional practices that would reinforce and support students in the target areas. We tracked student’s success toward mastery of the skill throughout the Unit. We used formative assessment methods such as anecdotal note-taking and quick checks. At the close of the unit students took the post-assessment with 76% of students showed mastery toward the standards and skills identified. Mrs. Lancer and I met together to use the data to identify and plan intervention for the 24% of students that required additional support in mastering the standard. We also used the data to identify effectiveness of the instructional strategies used. Working with Mrs. Lancer was very beneficial and gave me the confidence moving forward in making data-driven math decisions.” Signed: Marco Spalding 5th Grade Teacher Middleton Elementary Non-Example: The testimonial has been completed by the participating educator. However, it does not include a description of the experience with the instructional coach and how it supported their ability to use the data to inform instructional decision making.
Criterion 2: The testimonial describes the data that was used to inform instruction. Example: See example for Criterion 1. Non Example: The testimonial has been completed by the participating educator. However, it does not describe the data that was used to inform instruction.
Criterion 3: The testimonial describes the instructional decisions that were made from interpreting the data. Example: See example for Criterion 1. Non-Example: The testimonial has been completed by the participating educator. However, it does not describe instructional decisions that were made from interpreting the data.
Criterion 4: The testimonial describes the results of the post assessment data. Example: See example for Criterion 1. Non-Example: The testimonial has been completed by the participating educator. However, it does not describe the results of the post-assessment data.
Criterion 5: The testimonial includes educator name, position, school, and signature. Example: See example for Criterion 1. Non-Example: The testimonial does not include the educator name, position, school, and signature.
Provide a written description regarding your experiences guiding and supporting teachers in using data to assess the effectiveness of instruction and making adjustments in planning and instruction. Embed data collected and analyzed through the data-driven instructional coaching process in your response.
How do you support teachers in using data to assess the effectiveness of instruction?
What does it look like to use data to make adjustments in planning and instruction?
Review Criteria
Criterion 1: Reflection includes methods and practices of support provided to educators in using data to assess the effectiveness of instruction.
Criterion 2: Reflection includes description of what is looks like to use data to make adjustments in planning and instruction.
Criterion 3: Reflection includes data collected and analyzed during data-driven instructional coaching.
Criterion 4: Reflection indicates a level of professionalism and personal reflection that demonstrates the educator’s learning experience.
https://usbe.midaseducation.com/microcredentials/resource/asset/38220810-bd3b-11ed-a73d-02420a00020a/Area%203%20Human%20Resources%20Experience%20Verification%20Form%20.pdf
This form must be filled out and signed by your LEA’s HR or Business Office to verify your eligibility to obtain this Microcredential per the prerequisites outlined above.
Competencies of a Quality Instructional Coach
https://www.schools.utah.gov/curr/educatordevelopment/instructionalcoaches?mid=5125&tid=1
This page includes the competencies a quality Instructional Coach should possess in order to support teachers in delivering high-quality instruction to meet the learning needs of all students. These competencies can also be used to identify an educator’s readiness for instructional coaching.
Development for Instructional Coaches
https://www.schools.utah.gov/curr/educatordevelopment/instructionalcoaches
This website was created by the Utah State Board of Education and includes information regarding development of instructional coaches.
Learning Plan Checklist - Building Capacity for Data Driven Coaching
https://livedsdmail-my.sharepoint.com/:b:/g/personal/augardner_dsdmail_net/EchB8-IsAL9AravUNZMU64oBtQxB7kN3kqAEa3zi-Y4XjA?e=qwWO3C
Use this checklist to evaluate your plans before you submit them as evidence.
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