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USBE offers data-literacy training to LEA staff; presenters stress limits of simple charts and cautions about causal claims
Summary
Utah State Board of Education presenters ran a session on data literacy for LEA staff, covering definitions, key competencies, limitations of education data, the difference between descriptive and inferential statistics and an example showing how chart design and causal language can mislead.
Utah State Board of Education staff delivered a data literacy module aimed at LEA staff that defined data literacy and walked attendees through practical guidance for interpreting and communicating educational data.
Why it matters: LEA staff regularly use state data and reports to make program and operational decisions. The training emphasized how to avoid common interpretation errors that can lead to misleading conclusions or poor decisions.
Key takeaways: - Data literacy definition and competencies: presenters defined data literacy as the ability to accurately understand, communicate and use data for decisions and highlighted competencies such as analysis, visualization and ethical data use. - Limitations of education data: speakers noted that data often do not capture the full reality (for example, inconsistent absence definitions across schools or inconsistent course naming), and that vendor or reporting changes over time affect comparability. - Descriptive vs. inferential statistics: presenters recommended starting with descriptive statistics, then using inferential methods carefully and with proper assumptions if trying to draw broader conclusions or predictions. - Causation vs. correlation: presenters used a classroom example where a tutoring program’s group averaged higher test scores, but stressed that the difference alone does not prove the program caused the gain without further design or analysis. They advised avoiding emotional or generalized language and urged including caveats about other possible factors. - Chart best practices: presenters explained common visual mistakes such as truncated y-axes and missing axis labels that exaggerate differences and recommended always labeling axes and starting bars at zero unless intentionally and transparently using a different scale.
Materials and follow-up: Presenters said training materials are available for LEAs to adapt and use locally and invited attendees to contact datastatshelp@schoolsutah.gov for the slide deck and follow-up questions. The team also asked LEAs to attend the May 22 year-end training for additional instruction.
