What is Data Literacy and How Do We Achieve It?

1. What is Data Literacy and How Do We Achieve It? • Ellen B. Mandinach • WestEd

2. About Data Literacy? • The Construct • Data Transformed into Information and Ultimately to Actionable Knowledge • Role-Based • Individual Versus Group (Data Teaming) - Findings from Means, Chen, DeBarger, & Padilla, 2011 • Who Needs to Be Data Literate?

3. So What is Data Literacy? (For Teachers) • Pedagogical data literacy or data literacy knowledge for teaching is the ability to transform information into actionable instructional knowledge and practices by collecting, analyzing, and interpreting all types of data (assessment, school climate, behavioral, snapshot, etc.) to help determine instructional steps. It combines an understanding of data with standards, disciplinary knowledge and practices, curricular knowledge, pedagogical content knowledge, and an understanding of how children learn.

4. Why is Data Use Important? • “Our best teachers today are using real time data in ways that would have been unimaginable just five years ago. They need to know how well their students are performing. They want to know exactly what they need to do to teach and how to teach it.” (Duncan, 2009) • “Data and data analyses are powerful tools that must be used to improve schools.” (Easton, 2009)

5. How Do Educators Gain Data Literacy?(Data Quality Campaign’s Action 9) • Professional development and in-service opportunities • Formal course work • Stand-alone courses • Integration into existing courses • Curriculum completely infused with data use principles • Other stakeholders • State credentialing and licensure agencies • NCATE, AACTE, NBPTS • CCSSO • Complex system on interconnected components to create change concerning how to train educators to use data.

6. Role-Based Nature of Data Literacy • How does the definition of data literacy differ based on educational role? • What different knowledge and skills do different groups of educators need to acquire? • Teachers • Principals • Superintendents • Others • What role does pedagogical content knowledge play? Administrative knowledge? • Should educators be data users or consumers of information?

7. Data Literacy Relates to Data Purposes, Uses, and Interpretations • Data need to be translated into action. • Data must be usable, make sense, align with a purpose, have relevance, have utility, and have meaning. • Educators must understand why they are being asked to use particular data – Alignment of needs to purposes. • Validity of data types must be considered. Validity resides in the interpretations made from the data. • Data and data analytics need to be linked to pressing educational issues such as graduation rate, dropout prevention, and growth modeling.

8. A Sample of Knowledge and Skills • Problem Focus • Frame questions • Formulate hypotheses • Understand context • Collect/Organize • Select the right data • Know how to access data • Collect data • Organize data

9. A Sample of Knowledge and SkillsContinued • Data Properties • Understand data properties • Use multiple sources of data • Use a variety of data sources (qualitative, quantitative) • Understand reliability, validity, sources of error • Understand different kinds of assessments (formative, summative, diagnostic) • Analyses • Examine patterns and trends • Analyze data • Troubleshoot data • Drill down to different levels of data

10. A Sample of Knowledge and SkillsContinued • Other Data Skills • Synthesize information • Summarize • Think critically • Engage in collaborative inquiry • Know how to use data systems, tools, and applications • Comprehend data displays and reporting • Transforming Data • Make interpretations • Draw inferences • Evaluate outcomes and consider consequences • Critique arguments and test assumptions • Apply data to instruction or administrative action • Transform data into actionable knowledge • Drill down to different levels of data

11. Components of the Work – The Study of How Schools of Education Can Build Educators’ Capacity to Use Data • Survey • Syllabus Review • Case Studies • Licensure Review • Dissemination and Outreach to Bring Stakeholders Together

12. Early Findings of Survey and Syllabus Review • Stand Alone Courses vs. Integrated Suites of Courses? • Who is Teaching the Courses? • Is There Capacity? • What is Being Taught? • Assessment vs. Data? • What About Practica? • A Related Issue – Administrators First, then Teachers?

13. The Issue is a Systemic One • Schools of Education Cannot Act Alone • The Role of Other Agencies • State Licensure and Credentialing Agencies • Testing Organizations • School Districts • Professional Organizations (AACTE, NCATE/CAEP, the National Board, NASDTEC)

14. Issues for You to Consider and Discuss? • Do you have a stand alone course on data use? • Do you integrate data use into existing courses? Practica? • If you don’t currently have a course or courses, do you have plans to implement one? What will it look like? • Do you have faculty who can teach data-driven decision making? • Is there wiggle room in your course offerings to include data-driven decision making? • Do you differentiate data literacy and assessment literacy? • Do your districts want their new hires to be data literate? • Does New York require data literacy for licensure? • How do we foster change?