Data Literacy 101 - 36221
Data is everywhere - in our systems, reports, dashboards, and daily decisions. Data Literacy 101 is an interactive workshop designed to help participants build confidence in reading, interpreting, and communicating with data, no matter their technical background. In this session, participants will explore the fundamentals of data literacy through real-world examples from our organization’s context. We’ll demystify terms like data sources, metrics, trends, and visualizations, and practice turning raw numbers into meaningful insights. Participants will learn how to ask better data questions, identify common pitfalls in interpretation, and use data to tell clear, compelling stories that drive action. This session is hands-on and discussion based. No prior data experience is required - just curiosity and an open mind!
Schedule & Location
Audiences
ASCENDER, Business Personnel, Data Resource Systems, Technology/Technical Support Personnel, TSDS (Texas Student Data System) Personnel, Administrative Assistants, Assistant Principals, Directors, ESC 11 Personnel, ESC Personnel, Federal Program Directors/Coordinators, Industry Members, Industry/Business/Community Leaders, Instructional Leaders, Instructional Technology Personnel, Librarians, McKinney-Vento, Paraprofessionals, PEIMS (Public Education Information Management System) Staff, Principals, School Board Members, Superintendents/Chief Executive Officers, Teacher - Early Childhood/PreK/Kindergarten, Teacher - Elementary (Grades 1-5), Teacher - General Education, Teacher - Gifted Talented/Advanced Academics, Teacher - High School (Grades 9-12), Teacher - Middle School (Grades 6-8), Teacher - Special Education
Objectives
By the end of this session, participants will be able to:
1.) Define what it means to be “data literate” in their role.
2.) Identify different types of data and how they are used for decision-making.
3.) Read and interpret charts, dashboards, and key performance indicators with confidence.
4.) Recognize data quality issues and sources of bias.
5.) Communicate data findings in a clear and actionable way.
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Duration
00:00
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