Creating a Data Inventory
Creating a Data Inventory Understanding Types of Data Data-literate educators appreciate that data come in many forms and understand, in particular, that assessment data, while they are critically important, are just one of many types of data used in the classroom. They know where to find various types of data and how to communicate the headlines from the data, and they understand the uses and limitations of each form.
Key Method Data-literate educators thoughtfully consider the many different forms of data at play in their classrooms, appreciate the strengths and limitations of each form, and catalogue this information in a classroom data inventory—a systematic list that reminds them of the data at their disposal and when and how to best leverage it.
Method Components To thoughtfully consider the many different forms of data at play in their classrooms, many data-literate teachers create classroom data inventories. Powerful inventories have three primary components: Classroom data inventories contain a range of examples representing a breadth of forms. Educators appreciate that classroom data come in many forms (student performance data, attendance data, student demographic data, behavior data, non-cognitive data, among others), come from many sources (interim assessments, student surveys, daily attendance log, measures of grit and perseverance, and so on), and are refreshed at different frequencies (annually, weekly, daily, or more often). There are likely many specific examples within a particular form of data. For instance, examples of student performance data include student-level standards mastery data, independent reading levels, student-level daily exit ticket performance, and so on). Classroom data inventories highlight the use of each example of data given the educator’s particular role and the problem of practice they are leveraging data to address. How is each example of data used in the classroom? What decisions are facilitated with each type of data? For example, attendance data may inform particular inferences about students’ learning (wasn’t present to learn the material vs. didn’t learn the material), inform topics for parent/guardian communication, and suggest possible grouping strategies (for instance, creating a group of students who all have high rates of absenteeism may create problems for catching students up later). Classroom data inventories include the limitations of each example of classroom data. The educator understands the limitations of each type of data. For example, student-level standards mastery data provides a high-level view of individual students’ performance against various standards, but item-level data might be useful to better understand why a student (or group of students) performed in a particular way on a standard.
Except where otherwise noted, this work is licensed under: http://creativecommons.org/licenses/by-nc-nd/4.0/
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Supporting Research §
Gummer, E.S., & Mandinach, E.B. (2015). Building a conceptual framework for data literacy. Teachers College Record, 117(4), http://www.tcrecord.org/library/abstract.asp?contentid=17856
§
Mandinach, E. B., Parton, B. M., Gummer, E. S., & Anderson, R. (2015). Ethical and appropriate data use requires data literacy. Kappan, 96(5), 25–28.
§
Love N., Stiles, K. E., Mundry, S., & DiRanna, K. (2008). A Data Coach’s Guide to Improving Learning for All Students: Unleashing the Power of Collaborative Inquiry. Thousand Oaks, CA: Corwin Press.
Resources §
Boudett, K.P., City, E.A., & Murnane, R.J. (Eds.). (2013). Data Wise: A Step-by-Step Guide to Using Assessment Results to Improve Teaching and Learning, revised and expanded edition. Cambridge, MA: Harvard Education Press.
§
Lachat, M. A., Williams, M., & Smith, S. C. (2006). Making sense of ALL your data. Principal Leadership, 7(2), 16–21.
Submission Guidelines & Evaluation Criteria To earn the micro-credential Creating a Data Inventory, you must describe your teaching context (optional) and provide a data inventory that includes a sample of 10 classroom data examples that are representative of the breadth of data regularly used in the classroom (required). Part 1. Overview questions § (OPTIONAL) Describe any important context that would help an external observer better appreciate the classroom data inventory or your particular teaching context (100-word limit). - Passing: (OPTIONAL) The educator provides information that will help the observer better understand the educator’s context. Part 2. Sample of classroom data examples Provide a sample of 10 classroom data examples similar in format to the example below. You can find an optional template for uploading the submission here: http://bit.ly/1KOMF7N. If you find it helpful to include screenshots of your data, please feel free to include them, ideally pasted below the table in the template (this is optional). If you include actual data, please remove all student identifiers.
Example submission Example
Score/Frequency
Description
Primary Use
Limitations
Example: Attendance reports
Daily attendance logs that roll up into weekly, monthly, and yearly reports (which I examine at each of those frequencies)
I created a spreadsheet that takes daily attendance records and displays them, by student, for the week, month, and year. This dashboard allows me to see trends in the data (e.g.,
I primarily use attendance data to determine which students may need remediation/materials for class periods they missed. Beyond that, I use patterns in attendance data to inform conversations with students, their parents, and other stakeholders (e.g., coaches) in which we try to figure out ways to bolster attendance. I also take attendance patterns into consideration when
The current version of my system doesn’t distinguish very well between excused (e.g., school field trips) and unexcused absences. From an academic perspective, this doesn’t really matter, but it does inform my conversations with key stakeholders. To improve the system, I
Except where otherwise noted, this work is licensed under: http://creativecommons.org/licenses/by-nc-nd/4.0/
2
Example: Studentlevel standards mastery results
School-based interim assessments administered quarterly to all students
student misses Fridays). (See Slide 1 on uploaded PowerPoint for a visual of this system.)
determining student groupings. (I try not to put more than one chronically absent student in the same group, as I often rely on students to help catch each other up.).
need to develop a coding system for absences (e.g., EA, UA) that would differentially display on a retooled set of dashboards.
For each standard I teach, I determine each student’s percent mastery by taking the total number of points the student earned on items associated with the standard divided by the possible points for the standard.
I use student-level standards mastery data for two primary purposes: (1) to help determine which standards should be retaught, in what way, and to whom, and (2) as a critical input for creating heterogeneous groups for our seating chart. (Beyond achievement, I also try to maximize group-level heterogeneity by gender and number of disciplinary referrals.)
Although studentlevel standards mastery data likely provides a high-level view of individual students’ performance on standards, I often want to see itemlevel data to better understand why a student performed in a particular way on a standard. Additionally, the level of mastery for a standard is highly sensitive to the number of items associated with it and the number of points for each item associated with the; having more items per standard helps to reduce this limitation.
Your submission will be assessed on the following rubric. You must earn a (3) Proficient or (4) Exemplary score on this portion of the submission in order to earn the micro-credential. Attempting (1)
Foundational (2)
Proficient (3)
Exemplary (4)
The educator describes a range of examples across multiple forms of classroom data.
Taken as a set, the examples highlight a single form of data or there are fewer than 10 distinct examples.
Taken as a set, the 10 examples highlight only a couple distinct forms of data (e.g., only assessment data and attendance data).
Taken as a set, the ten examples highlight several distinct forms of data.
Not only do the 10 examples highlight a variety of data forms, but the educator strikes a powerful balance between showcasing the breadth of forms while also providing several examples of depth within a given form of data.
The educator
Taken as a set, the
Taken as a set, the
Taken as a set, the
Taken as a set, the
Except where otherwise noted, this work is licensed under: http://creativecommons.org/licenses/by-nc-nd/4.0/
3
describes the use of each example.
examples raise many questions about how the educator uses the data in the classroom.
examples provide evidence that the educator uses the data, but a few questions remain about how the educator employs the data in the classroom.
examples stand as compelling evidence that the educator thoughtfully uses the data as articulated.
examples not only stand as compelling evidence that the educator thoughtfully uses the data as articulated, but also highlights a level of intentionality that goes beyond the typical use case.
The educator describes the limitations of each example.
The educator articulates limitations, but either they are not really limitations or they are unlikely to substantively affect inferences made from the data.
The educator articulates limitations, but there are questions as to whether the limitations are substantive given the data.
The educator articulates compellingly substantive limitations likely to substantively affect inferences made from the data.
The educator not only articulates compellingly substantive limitations, but also suggest ways to work around or reduce the limitations to improve inferences made from the data.
Except where otherwise noted, this work is licensed under: http://creativecommons.org/licenses/by-nc-nd/4.0/
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Key Method Data-literate educators thoughtfully consider the many different forms of data at play in their classrooms, appreciate the strengths and limitations of each form, and catalogue this information in a classroom data inventory—a systematic list that reminds them of the data at their disposal and when and how to best leverage it.
Method Components To thoughtfully consider the many different forms of data at play in their classrooms, many data-literate teachers create classroom data inventories. Powerful inventories have three primary components: Classroom data inventories contain a range of examples representing a breadth of forms. Educators appreciate that classroom data come in many forms (student performance data, attendance data, student demographic data, behavior data, non-cognitive data, among others), come from many sources (interim assessments, student surveys, daily attendance log, measures of grit and perseverance, and so on), and are refreshed at different frequencies (annually, weekly, daily, or more often). There are likely many specific examples within a particular form of data. For instance, examples of student performance data include student-level standards mastery data, independent reading levels, student-level daily exit ticket performance, and so on). Classroom data inventories highlight the use of each example of data given the educator’s particular role and the problem of practice they are leveraging data to address. How is each example of data used in the classroom? What decisions are facilitated with each type of data? For example, attendance data may inform particular inferences about students’ learning (wasn’t present to learn the material vs. didn’t learn the material), inform topics for parent/guardian communication, and suggest possible grouping strategies (for instance, creating a group of students who all have high rates of absenteeism may create problems for catching students up later). Classroom data inventories include the limitations of each example of classroom data. The educator understands the limitations of each type of data. For example, student-level standards mastery data provides a high-level view of individual students’ performance against various standards, but item-level data might be useful to better understand why a student (or group of students) performed in a particular way on a standard.
Except where otherwise noted, this work is licensed under: http://creativecommons.org/licenses/by-nc-nd/4.0/
1
Supporting Research §
Gummer, E.S., & Mandinach, E.B. (2015). Building a conceptual framework for data literacy. Teachers College Record, 117(4), http://www.tcrecord.org/library/abstract.asp?contentid=17856
§
Mandinach, E. B., Parton, B. M., Gummer, E. S., & Anderson, R. (2015). Ethical and appropriate data use requires data literacy. Kappan, 96(5), 25–28.
§
Love N., Stiles, K. E., Mundry, S., & DiRanna, K. (2008). A Data Coach’s Guide to Improving Learning for All Students: Unleashing the Power of Collaborative Inquiry. Thousand Oaks, CA: Corwin Press.
Resources §
Boudett, K.P., City, E.A., & Murnane, R.J. (Eds.). (2013). Data Wise: A Step-by-Step Guide to Using Assessment Results to Improve Teaching and Learning, revised and expanded edition. Cambridge, MA: Harvard Education Press.
§
Lachat, M. A., Williams, M., & Smith, S. C. (2006). Making sense of ALL your data. Principal Leadership, 7(2), 16–21.
Submission Guidelines & Evaluation Criteria To earn the micro-credential Creating a Data Inventory, you must describe your teaching context (optional) and provide a data inventory that includes a sample of 10 classroom data examples that are representative of the breadth of data regularly used in the classroom (required). Part 1. Overview questions § (OPTIONAL) Describe any important context that would help an external observer better appreciate the classroom data inventory or your particular teaching context (100-word limit). - Passing: (OPTIONAL) The educator provides information that will help the observer better understand the educator’s context. Part 2. Sample of classroom data examples Provide a sample of 10 classroom data examples similar in format to the example below. You can find an optional template for uploading the submission here: http://bit.ly/1KOMF7N. If you find it helpful to include screenshots of your data, please feel free to include them, ideally pasted below the table in the template (this is optional). If you include actual data, please remove all student identifiers.
Example submission Example
Score/Frequency
Description
Primary Use
Limitations
Example: Attendance reports
Daily attendance logs that roll up into weekly, monthly, and yearly reports (which I examine at each of those frequencies)
I created a spreadsheet that takes daily attendance records and displays them, by student, for the week, month, and year. This dashboard allows me to see trends in the data (e.g.,
I primarily use attendance data to determine which students may need remediation/materials for class periods they missed. Beyond that, I use patterns in attendance data to inform conversations with students, their parents, and other stakeholders (e.g., coaches) in which we try to figure out ways to bolster attendance. I also take attendance patterns into consideration when
The current version of my system doesn’t distinguish very well between excused (e.g., school field trips) and unexcused absences. From an academic perspective, this doesn’t really matter, but it does inform my conversations with key stakeholders. To improve the system, I
Except where otherwise noted, this work is licensed under: http://creativecommons.org/licenses/by-nc-nd/4.0/
2
Example: Studentlevel standards mastery results
School-based interim assessments administered quarterly to all students
student misses Fridays). (See Slide 1 on uploaded PowerPoint for a visual of this system.)
determining student groupings. (I try not to put more than one chronically absent student in the same group, as I often rely on students to help catch each other up.).
need to develop a coding system for absences (e.g., EA, UA) that would differentially display on a retooled set of dashboards.
For each standard I teach, I determine each student’s percent mastery by taking the total number of points the student earned on items associated with the standard divided by the possible points for the standard.
I use student-level standards mastery data for two primary purposes: (1) to help determine which standards should be retaught, in what way, and to whom, and (2) as a critical input for creating heterogeneous groups for our seating chart. (Beyond achievement, I also try to maximize group-level heterogeneity by gender and number of disciplinary referrals.)
Although studentlevel standards mastery data likely provides a high-level view of individual students’ performance on standards, I often want to see itemlevel data to better understand why a student performed in a particular way on a standard. Additionally, the level of mastery for a standard is highly sensitive to the number of items associated with it and the number of points for each item associated with the; having more items per standard helps to reduce this limitation.
Your submission will be assessed on the following rubric. You must earn a (3) Proficient or (4) Exemplary score on this portion of the submission in order to earn the micro-credential. Attempting (1)
Foundational (2)
Proficient (3)
Exemplary (4)
The educator describes a range of examples across multiple forms of classroom data.
Taken as a set, the examples highlight a single form of data or there are fewer than 10 distinct examples.
Taken as a set, the 10 examples highlight only a couple distinct forms of data (e.g., only assessment data and attendance data).
Taken as a set, the ten examples highlight several distinct forms of data.
Not only do the 10 examples highlight a variety of data forms, but the educator strikes a powerful balance between showcasing the breadth of forms while also providing several examples of depth within a given form of data.
The educator
Taken as a set, the
Taken as a set, the
Taken as a set, the
Taken as a set, the
Except where otherwise noted, this work is licensed under: http://creativecommons.org/licenses/by-nc-nd/4.0/
3
describes the use of each example.
examples raise many questions about how the educator uses the data in the classroom.
examples provide evidence that the educator uses the data, but a few questions remain about how the educator employs the data in the classroom.
examples stand as compelling evidence that the educator thoughtfully uses the data as articulated.
examples not only stand as compelling evidence that the educator thoughtfully uses the data as articulated, but also highlights a level of intentionality that goes beyond the typical use case.
The educator describes the limitations of each example.
The educator articulates limitations, but either they are not really limitations or they are unlikely to substantively affect inferences made from the data.
The educator articulates limitations, but there are questions as to whether the limitations are substantive given the data.
The educator articulates compellingly substantive limitations likely to substantively affect inferences made from the data.
The educator not only articulates compellingly substantive limitations, but also suggest ways to work around or reduce the limitations to improve inferences made from the data.
Except where otherwise noted, this work is licensed under: http://creativecommons.org/licenses/by-nc-nd/4.0/
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