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Central Beliefs about Data Inquiry Teams

Created By

EL Education

Topic

  • Classroom Instruction
  • Instructional Leadership

Type

Guidance Documents

Grade Level

Data inquiry teams are teams of teachers that meet regularly to analyze student data, to reflect on student progress, and to create action plans that will improve instructional effectiveness. Data inquiry teams focus exclusively on analyzing data for the students they teach and developing plans for responding to the needs and strengths of individual students, groups of students, and particular areas of curriculum. However, data inquiry teams are part of a larger system for using data to raise student achievement and close achievement gaps. In EL schools, data is defined as information that has been systematically collected and organized to support analysis, inquiry, and decision-making.

  1. Data inquiry is built on the foundation of a collaborative, trusting professional culture in which accountability for achievement is shared by teachers, leaders, and students.  In order to improve student achievement, teachers and leaders must work together to look deeply at data, ask questions, and propose and test solutions that they believe will impact student learning. This inquiry and “no blame” collaboration depend on strong relational trust and clear roles and norms. It is the cornerstone of a school culture in which teachers demonstrate a growth mindset, viewing themselves as inquiring practitioners who work to continually improve instruction in order to close achievement gaps for all students.
  2. Data inquiry teams generate and implement concrete action plans to improve teaching and learning.  Collaborative inquiry is at the heart of using data to improve student achievement. Rather than using data to identify who “got it” and who didn’t, data inquiry teams generate questions to deeply reflect on where students need to be, where they are now, and how to close the gap.  Working collaboratively allows teachers to calibrate their expectations, analyze current instructional practice, and create action plans to improve teaching and learning. (Boudett, City, and Murnane, 2005). Teachers collect evidence to ensure action plan goals are being met and use this evidence to modify their instruction. These action plans often include how data will be shared with students to engage them in setting their own goals for improvement.
  3. Data inquiry teams use high-quality data sources to analyze student achievement.  The work of data inquiry teams is only as good as the data that they have.  Planning for data inquiry starts with determining which data sources the team will analyze.  These sources should include student work as well as formal assessments (interim assessments, standardized tests, etc.) When selecting or developing assessments, teachers and leaders ensure that the assessments are appropriately rigorous and aligned to standards, available to teachers before instruction begins, common across all sections of a course or grade, and administered frequently enough for the resulting data to be actionable (Bambrick-Santoyo, 2010).  While data inquiry teams might occasionally analyze data regarding non-academic indicators, the majority of their time and focus is directed toward indicators of academic achievement.
  4. The work of data inquiry teams is inclusive, cyclical, and structured.  Schools that most productively use data include ALL teachers in data inquiry cycles that align with the instructional sequence and assessment calendar. Data inquiry may happen in pre-existing grade level or subject area teams, or it may occur with a separate team that includes additional staff members. Regularly scheduled meetings, adherence to team norms and the use of protocols support the effectiveness of data inquiry teams. Leaders review action plans and provide coaching on an ongoing basis.
  5. School leaders ensure that data is organized and displayed to support effective analysis. Prior to data inquiry team meetings, data are organized and displayed by one or more staff members who serve as data managers for the school.  Through the use of clear charts, graphs and tables, the designated data manager presents data in ways that provide user-friendly, succinct item-level data, standards-level data, and bottom-line results to support the identification of patterns, successes and areas for improvement.  In addition, data inquiry teams might also utilize data walls or school-wide data dashboards as a part of their work.  

Role of School Designers in Supporting Data Teams

School designers support schools in implementing, restructuring, or refining a school’s data inquiry teams. Support may include identifying various types of evidence and high-quality data sources to use, creating systems for organizing and sharing data, facilitating protocols with data inquiry teams, and leading professional development to build data capacity. While school designers are equipped to support the analysis of data and build data capacity, the goal is to establish site-based systems and structures to sustain this work.  

Recommended Reading

Bambrick-Santoyo, Paul (2010) Driven by Data. San Francisco, CA: Jossey-Bass.

Boudett, Kathryn Parker; City, Elizabeth A., Munane, Richard  J. (2005) Data Wise, Cambridge, MA:Harvard Education Press.


Created By

EL Education

Topic

  • Classroom Instruction
  • Instructional Leadership

Type

Guidance Documents

Grade Level

Data inquiry teams are teams of teachers that meet regularly to analyze student data, to reflect on student progress, and to create action plans that will improve instructional effectiveness. Data inquiry teams focus exclusively on analyzing data for the students they teach and developing plans for responding to the needs and strengths of individual students, groups of students, and particular areas of curriculum. However, data inquiry teams are part of a larger system for using data to raise student achievement and close achievement gaps. In EL schools, data is defined as information that has been systematically collected and organized to support analysis, inquiry, and decision-making.

  1. Data inquiry is built on the foundation of a collaborative, trusting professional culture in which accountability for achievement is shared by teachers, leaders, and students.  In order to improve student achievement, teachers and leaders must work together to look deeply at data, ask questions, and propose and test solutions that they believe will impact student learning. This inquiry and “no blame” collaboration depend on strong relational trust and clear roles and norms. It is the cornerstone of a school culture in which teachers demonstrate a growth mindset, viewing themselves as inquiring practitioners who work to continually improve instruction in order to close achievement gaps for all students.
  2. Data inquiry teams generate and implement concrete action plans to improve teaching and learning.  Collaborative inquiry is at the heart of using data to improve student achievement. Rather than using data to identify who “got it” and who didn’t, data inquiry teams generate questions to deeply reflect on where students need to be, where they are now, and how to close the gap.  Working collaboratively allows teachers to calibrate their expectations, analyze current instructional practice, and create action plans to improve teaching and learning. (Boudett, City, and Murnane, 2005). Teachers collect evidence to ensure action plan goals are being met and use this evidence to modify their instruction. These action plans often include how data will be shared with students to engage them in setting their own goals for improvement.
  3. Data inquiry teams use high-quality data sources to analyze student achievement.  The work of data inquiry teams is only as good as the data that they have.  Planning for data inquiry starts with determining which data sources the team will analyze.  These sources should include student work as well as formal assessments (interim assessments, standardized tests, etc.) When selecting or developing assessments, teachers and leaders ensure that the assessments are appropriately rigorous and aligned to standards, available to teachers before instruction begins, common across all sections of a course or grade, and administered frequently enough for the resulting data to be actionable (Bambrick-Santoyo, 2010).  While data inquiry teams might occasionally analyze data regarding non-academic indicators, the majority of their time and focus is directed toward indicators of academic achievement.
  4. The work of data inquiry teams is inclusive, cyclical, and structured.  Schools that most productively use data include ALL teachers in data inquiry cycles that align with the instructional sequence and assessment calendar. Data inquiry may happen in pre-existing grade level or subject area teams, or it may occur with a separate team that includes additional staff members. Regularly scheduled meetings, adherence to team norms and the use of protocols support the effectiveness of data inquiry teams. Leaders review action plans and provide coaching on an ongoing basis.
  5. School leaders ensure that data is organized and displayed to support effective analysis. Prior to data inquiry team meetings, data are organized and displayed by one or more staff members who serve as data managers for the school.  Through the use of clear charts, graphs and tables, the designated data manager presents data in ways that provide user-friendly, succinct item-level data, standards-level data, and bottom-line results to support the identification of patterns, successes and areas for improvement.  In addition, data inquiry teams might also utilize data walls or school-wide data dashboards as a part of their work.  

Role of School Designers in Supporting Data Teams

School designers support schools in implementing, restructuring, or refining a school’s data inquiry teams. Support may include identifying various types of evidence and high-quality data sources to use, creating systems for organizing and sharing data, facilitating protocols with data inquiry teams, and leading professional development to build data capacity. While school designers are equipped to support the analysis of data and build data capacity, the goal is to establish site-based systems and structures to sustain this work.  

Recommended Reading

Bambrick-Santoyo, Paul (2010) Driven by Data. San Francisco, CA: Jossey-Bass.

Boudett, Kathryn Parker; City, Elizabeth A., Munane, Richard  J. (2005) Data Wise, Cambridge, MA:Harvard Education Press.


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