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Week 3: Data to Drive Instruction
NELP Standard 4: Learning and Instruction
Candidates who successfully complete a building-level educational leadership preparation program understand and demonstrate the capacity to promote the current and future success and well-being of each student and adult by applying the knowledge, skills, and commitments necessary to evaluate, develop, and implement coherent systems of curriculum, instruction, data systems, supports, and assessment.
Component 4.2: Program completers understand and can demonstrate the capacity to evaluate,
develop, and implement high-quality and equitable academic and non-academic instructional
practices, resources, technologies, and services that support equity, digital literacy, and the
school’s academic and non-academic systems.
PSEL 4: Curriculum, Instruction, and Assessment
Effective educational leaders develop and support intellectually rigorous and coherent systems of curriculum, instruction, and assessment to promote each student’s academic success and well-being.
Texas Principal Standards Pillar: Data-driven Instruction
Principal Domain and Competency
Domain II: Leading Learning
Competency 4
Domain II
Course-level Objectives (CLOs):
Week 3 Learning Objectives (W3LO):
Overview:
In Week 1 of this course you examined the framework of the Instructional Core. Aligning in Week 2, you focused on the curriculum by examining both external and internal accountability when aligning curriculum. Now in Week 3, you will focus on growing your understanding of the importance of making data driven decisions about the instructional practices on your campus. As an instructional leader it is your focus to provide students with academically challenging practices and assessments in the classroom by identifying needs using data. Identifying school-level needs through student achievement and other data sets pinpoint the areas of concentration an instructional leader should focus on during the planning stages of professional development. You will grow your knowledge, skills, and mindset on providing professional development on "how to identify" areas of need from data to drive effective instruction in the classroom that improves student achievement. This focus of continuous school improvement is a priority for most Instructional Leaders.
Resources:
Week 3 Readings: Be sure you are logged into Blackboard in order to access all of the readings from these links. All References listed below are in APA format for citation.
1. James-Ward, C., & Abuyen, J. (2015) McREL Leadership Responsibilities through the Lens of Data: The Critical Nine. Global Education Review, 2(3), 82-93. Retrieved from: https://libproxy.lamar.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=eric&AN=EJ1074111&site=eds-live
Click on the full text from ERIC link
2. Nelson, T. H., Duele, A., Slavit, D., & Kennedy, A. (2010) Leading deep conversations
in collaborative inquiry groups. The Clearing House, (5), 175. Retrieved from:
https://doi-org.libproxy.lamar.edu/10.1080/00098650903505498
Click on full article to access
3. EL Education Core Practices. (2017) (n.d.). Retrieved from https://eleducation.org/resources/core-practices-beta-version-2017. 77-78
4. Desravines, J., Aquino, J., & Fenton, B. (2016). Breakthrough principals: A step-by-step guide to building stronger schools. John Wiley & Sons. 76-87.
5. Bambrick-Santoyo, P. (2018). Leverage Leadership 2.0: A Practical Guide to Building Exceptional Schools. John Wiley & Sons. 25-87.
Suggested Optional Reading:
Sinnema, C., Sewell, A., & Milligan, A. (2011). Evidence-informed collaborative inquiry for improving teaching and learning. Asia-Pacific Journal of Teacher Education, 39(3), 247-261. Retrieved from:
Click on PDF Full Text
Week 3 Assignment Rubric:
Use the Rubric to guide your writing.
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Tasks |
Level 1: Does not meet the minimum criteria 0 points |
Level 2: Approaches minimum criteria 2 points |
Level 3: Meets minimum criteria 4 points |
Level 4: Meets target criteria 6 points |
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Part 1A: Data-driven Instructional Framework Summary
Candidate examines the approach of Data-driven Instruction, including the purpose of the approach and the components of the framework.
W3LO2: (CLO3)
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Candidate explains no elements of the framework of the Data-driven Instruction approach. (K) |
Candidate explains with little definition the components of the framework for the Data-driven Instruction approach. (K) |
Candidate explains the definition and the components of the framework for the Data-driven Instruction approach. (K) |
Candidate explains in depth the components of the framework for the Data-driven Instruction approach with clarity and specificity. (K) |
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Candidate provides no information on the purpose of the approach. (K) |
Candidate provides information, but no list on the purpose of the approach. (K) |
Candidate provides information, but an incomplete list of the purpose of the approach. (K) |
Candidate provides in depth description of the purpose of the approach with clarity and specificity. (K) |
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Candidate articulates no supporting evidence from the readings in the summary. (S) |
Candidate articulates little supporting evidence from the readings in the summary. (S) |
Candidate articulates general supporting evidence from the readings in the summary. (S) |
Candidate articulates comprehensive evidence from the readings with specificity and clarity in the summary. (S) |
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Part 1B: Data Point Analysis
Candidate conducts an analysis of the trends, patterns, and themes identified from the Data Points given in the Week 1 Assignment. Candidate will include the Topic chosen for Professional Development.
W3LO1: (CLO1 & 3) |
Candidate provides no evidence of the trends, patterns, and themes identified from the Data Points. (K) |
Candidate provides some evidence of the trends, patterns, and themes identified from the Data Points. (K) |
Candidate summarizes evidence of the trends, patterns, and themes identified from the Data Points. (K)
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Candidate provides in-depth analysis evidence of the trends, patterns, and themes identified from the Data Points. (K) |
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Candidate demonstrates no ability to analyze data and identify needs to determine a topic for effective professional development. (S)
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Candidate demonstrates some ability to analyze data and identify needs to determine a topic for effective professional development. (S)
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Candidate demonstrates the ability to analyze data and identify needs to determine a topic for effective professional development. (S)
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Candidate demonstrates great skill in analyzing data and identify needs to determine a targeted topic for effective professional development. (S) |
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Part 2: Scavenger Hunt for Data Points & Reflection
Candidate conducts a scavenger hunt to identify different data points, those locations, purpose, and frequency used to drive instruction and provides an in-depth reflection regarding the impact on learning this process has made on them as an instructional leader.
W3LO3: (CLO1 & 3)
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Candidate provides no examples of data points, their location, purpose, or frequency used to drive instruction. (M) |
Candidate provides vague examples of data points, their location, purpose, or frequency used to drive instruction, but the table is incomplete. (M) |
Candidate provides some examples of data points, their location, purpose, or frequency used to drive instruction, or the table is incomplete. (M) |
Candidate provides comprehensive knowledge and examples of data points, their location, purpose, or frequency used to drive instruction and the table is complete. (M) |
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Candidate demonstrates no self-reflection regarding the impact on learning this process has made on them as an instructional leader. (M) |
Candidate demonstrates little or superficial self-reflection regarding the impact on learning this process has made on them as an instructional leader. (M) |
Candidate demonstrates an emerging depth of self-reflection regarding the impact on learning this process has made on them as an instructional leader. (M) |
Candidate demonstrates and articulates a depth of knowledge of one’s self regarding the impact on learning this process has made on them as an instructional leader. (M) |
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Part 3: Draft: Element for Professional Development
Candidates use informal and formal culturally responsive data exploration to identify school-level needs, to provide effective professional development that is culturally responsive, and will lead to data-informed instructional improvements for students to experience deeper learning.
NELP Component 4.3
PSEL 4
SBEC 004
W3LO3: (CLO1 & 3) W3LO4: (CLO4)
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Candidate offers no evidence of resources or instruction that ensures the use of informal and formal culturally responsive data exploration to identify school-level need. (S)
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Candidate offers little evidence of resources or instruction that ensures the use of informal and formal culturally responsive data exploration to identify school-level need. (S)
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Candidate provides evidence of resources or instruction that ensures use of informal and formal culturally responsive data exploration to identify school-level need. (S) |
Candidate provides comprehensive evidence of resources or data (such as: “best practices” or evidence-based strategies) that ensures the use of informal and formal culturally responsive data exploration to identify school-level need. (S) |
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Candidate cannot provide examples, develop a schedule, or plan activities for teachers’ professional development that are focused on identifying needs and improving the learning process through data exploration. (S)
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Candidate provides few examples, partial schedule, or irrelevant activities for teachers’ professional development that are focused on identifying needs and improving the learning process through data exploration. (S)
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Candidate provides examples and develops a schedule, or activities for teachers’ professional development that are focused on identifying needs and improving the learning process through data exploration. (S)
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Candidate articulates a depth of knowledge and prepares a comprehensive schedule and activities for teachers’ professional development that is focused on identifying needs and improving the learning process through data exploration. (S)
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Candidate provides no focused objective about the data process that improves assessments and student learning and well-being. (S)
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Candidate provides an idea of the focused objective about the data process that improves assessments and student learning and well-being. (S)
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Candidate provides a developed focused objective about the data process that improves assessments and student learning and well-being. (S)
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Candidate articulates a depth of knowledge and prepares a comprehensive focused objective about the data process that improves assessments and student learning and well-being. (S) |
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Candidate offers no supporting evidence of resources for ongoing follow-up to measure progress from the professional development through benchmark review of the data, or assessments to check for deeper learning or student achievement. (S) |
Candidate offers little supporting evidence of resources for ongoing follow-up to measure progress from the professional development through benchmark review of the data, or assessments to check for deeper learning or student achievement. (S) |
Candidate offers some supporting evidence of resources for ongoing follow-up to measure progress from the professional development through benchmark review of the data, or assessments to check for deeper learning or student achievement. (S) |
Candidate provides comprehensive supporting evidence of resources for ongoing follow-up to measure progress from the professional development through benchmark review of the data, or assessments to check for deeper learning or student achievement. (S) |
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Writing Elements: W3LO4: (CLO4) |
Candidate had spelling, grammar, or technical writing errors. 0-points |
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Candidate had no spelling, grammar, or technical writing errors. 9-points |
Part 1A: Data-driven Instructional Framework Summary
Directions:
A. Summary W3LO2: (CLO3) The readings this week focus on the importance of looking at data in schools. The authors focus is directed at building the bridge between data and results. Examine purpose of data to drive instructions and the components of the framework you have read about. Using the Basic Writing Elements Model found in the Resource section of this course, complete the following summary regarding Data-driven Instruction data components and their influence on the framework of the Instructional Core.
B. Cite any sources and/or readings used as evidence to support your statements in APA format.
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Directions: Compose 1-2 paragraphs (minimum 200-word) summary of the approach of Data-driven Instruction. Include the purpose of the data components and their influence on the framework of the Instructional Core. |
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Summary: |
Bambrick-Santoyo (2018)), explained the Data-driven Instruction as…. |
Reference
Bambrick-Santoyo, P. (2018). Leverage Leadership 2.0: A Practical Guide to Building Exceptional Schools. John Wiley & Sons. 25-87.
Part 1B: Data Points
Directions:
A. Analysis W3LO1: (CLO1 & 3): Using the Basic Writing Elements Model found in the Resource section of this course, complete the following analysis regarding Data-driven Instruction. Analyze the trends, patterns, and themes you identified from the Data Points you were given in your Week 1 Assignment. Be sure to Include the 3-Day Professional Development Plan Topic you chose for Professional Development and why.
B. Cite any sources and/or readings used as evidence to support your statements in APA format.
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Data-driven Instruction: |
Directions: Compose 1-2 paragraph (minimum 200-word) analysis of the trends, patterns, and themes you identified from the Data Points you were given in your Week 1 Assignment. Include the 3-Day Professional Development Plan Topic you chose for Professional Development and why. |
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Analysis: |
James-War and Abuyen (2015), explained data-driven instruction as…. |
Reference
James-Ward, C., & Abuyen, J. (2015) McREL Leadership Responsibilities through the Lens of Data: The Critical Nine. Global Education Review, 2(3), 82-93. Retrieved from: https://libproxy.lamar.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=eric&AN=EJ1074111&site=eds-live
Click on the full text from ERIC link
Part 2: Scavenger Hunt for Data Points & Reflection
Directions:
A. Scavenger Hunt for Data Points W3LO3: (CLO1 & 3): Now that you have read about data-driven instruction, you will practice locating different data points that drive instruction. Please include the name of the data point, location, a short description of the data it provides, and the frequency in which you use it. Complete the table. Number 1 has been done for you as an example.
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Data Points: |
Location: (Ex. Website, URL, Office, or Instructor) |
Data Provided: |
Frequency: |
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1. TAPR |
https://tea.texas.gov/perfreport/tapr/index.html
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Performance is shown disaggregated by student groups, including ethnicity and socioeconomic status. |
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B. Reflections W3LO3: (CLO1 & 3): Now that you have read about data-driven instruction and practiced locating different data points complete the following in-depth reflection regarding the impact on your learning this process has made. Be sure to include how your perspective has changed from an instructor into an instructional leader in regard to data. Also, include, “best practices”, strategies, processes, and tools you learned about. Using the self-reflective model of What? So What? Now What? found in the Resource section of your course.
C. Cite any sources and/or readings used as evidence to support your statements in APA format.
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Data-driven Instruction: |
Directions: Compose 1-2 paragraphs (200-word) in-depth reflections regarding the impact on your learning this process has made. Include how your perspective has changed from an instructor into an instructional leader in regard to data. Include, “best practices”, strategies, processes, and tools you learned about. |
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Reflection: |
Bambrick-Santoyo (2018), described the importance of data-driven instruction as…… Previously my perspective on this was…. This has changed my perspective by…. Looking forward I want to grow this mindset by… |
Reference
Bambrick-Santoyo, P. (2018). Leverage Leadership 2.0: A Practical Guide to Building Exceptional Schools. John Wiley & Sons. p.1-21, 89-125.
Part 3: Draft: Element for Professional Development:
Comprehensive School-Level Instructional Leadership 3-Day Professional Development Plan
The final signature assessment in this course is to write a comprehensive, school-level instructional leadership 3-Day professional development plan. This plan will be due in Week 4 and include multiple elements. This week you will focus on one of the elements called Student Achievement: Exploring Data to Improve the Students Learning Process.
Directions:
A. Data to Drive Instruction W3LO4: (CLO4): Working with the data sets given with the Week 1 assignment, you began to identify trends, patterns, and themes from student work, the TAPR, and the results from a teachers’ professional development needs survey to identify the initial information for your 3-Day Professional Development Plan. Now, you will plan the activity portion of the 3-Day Professional Development Plan that will focus on examining Student Achievement through the data. You may reference your textbook Leverage Leadership 2.0 Chapter 1: Data-Driven Instruction pages 25-87. Also, reference the CD Resource Document from that textbook named: “001 DDI-3B North Star Assessment Teacher Reflection” this is an Exemplar example of the questions you should be asking your teachers during this process to target effective Professional Development. Examples are listed in gray for you to reference, delete examples prior to beginning.
B. Complete the Professional Development Student Achievement: Exploring Data to Improve the Students Learning Process.
C. Use 12 pt. black font: Times New Roman. The table cells will expand to fit your text.
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Student Achievement: Exploring the Data to Improve the Student Learning Process |
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Professional Development: Day 1: Data to Drive Instruction |
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Resources:
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Data Sets (Collected Data Points): o Student Achievement Benchmarks (campus or district) o TAPR o Survey Professional Development Needs Assessment (sent to campus faculty) o Student Intervention Data Reports o Teacher Evaluations (T-TESS) |
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Schedule & Activities: |
Schedule & Activities to be conducted: (Describe in depth the activities) o 9:00am-10:00am- Collect Data Points, Data Dig, Review Survey Professional Development Needs Assessment. o 10:00am-12:00pm- Identify trends, patterns, and themes in data sets. o 12:00pm-1:00pm- Lunch o 1:00pm-2:00pm-Identify which instructional improvement priority area to target in regard to continuous school improvement. Find research-based evidence to build goal. o 2:00pm-3:00pm-Build S.M.A.R.T. Goals based on the identifiable needs from data. |
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Student Achievement: |
Professional Development Goal: Data to Drive Instruction=Set S.M.A.R.T Goal |
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Evaluation/Follow-up Methods: Choose a “best practices” or evidence-based strategies to be used to measure progress:
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· Applications · Strategies · Implementation Tools · T-TESS Evaluations · Walk Throughs · 6- or 9-Week Check-ups-for progress monitor · Year-long calendar to document improvement from previous year |