Student data is vitally important information that can be used in the assessment of student learning. Collecting, recording, and analyzing student data helps teachers make decisions about instruction (when it’s working, when it needs to be changed). Furthermore, federal laws (NCLB, the 2001 reauthorization of the Elementary and Secondary Education Act, or ESEA) and state laws/policies (e.g., Common Core State Standards, or CCSS) require the collection and reporting of student data, which is used to evaluate the performance of teachers and schools. Yet while teachers are required to collect and report student data, they are not always trained in how to interpret and use such data.
Data is of minimal value unless teachers are data literate. Data Literacy for Teachers by Nancy Love is a practical, quick-reference laminated guide designed to help teachers feel comfortable, knowledgeable, and skilled in using a variety of data on a regular basis to improve teaching and learning.
The guide
- Provides a simple framework for strengthening teachers’ data literacy
- Identifies multiple types of data teachers should analyze
- Describes different methods for data analysis
- Explains how data can be used to immediately and directly impact instruction and student achievement
The six-page (bi-fold) guide depicts The Data Pyramid, which illustrates the following five data types, along with an approximate frequency of use for each
- Formative Classroom Assessment
- Formative Common Assessment
- Benchmark Common Assessment
- Data About People, Practices and Perceptions
- Summative Assessment
A concise description of each type of data is provided, along with suggested methods for collecting and accurately analyzing data (individually and with colleagues in data teams).
Data Literacy for Teachers will help teachers build data literacy skills and unleash the power of data to improve teaching and learning.
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