Data Literacy in Educational Leadership

Last week, I posted about data strategies’ tendency to focus on the data itself, overlooking the (data-driven) decisioning process itself. All it not lost. First, it is appropriate that the majority of the focus remains on the supply of high-quality #data relative to the perceived demand for it through the lenses of specific use cases. But there is an opportunity to complement this by addressing the decisioning process itself. 7 initiatives you can consider: 1) Create a structured decision-making framework that integrates data into the strategic decision-making process. This is a reusable framework that can be used to explain in a variety of scenarios how decisions can be made. Intuition is not immediately a bad thing, but the framework raises awareness about its limitations, and the role of data to overcome them. 2) Equip leaders with the skills to interpret and use data effectively in strategic contexts. This can include offering training programs focusing on data literacy, decision-making biases, hypothesis development, and data #analytics techniques tailored for strategic planning. A light version could be an on-demand training. 3) Improve your #MI systems and dashboards to provide real-time, relevant, and easily interpretable data for strategic decision-makers. If data is to play a supporting role to intuition in a number of important scenarios, then at least that data should be available and reliable. 4) Encourage a #dataculture, including in the top executive tier. This is the most important and all-encompassing recommendation, but at the same time the least tactical and tangible. Promote the use of data in strategic discussions, celebrate data-driven successes, and create forums for sharing best practices. 5) Integrate #datascientists within strategic planning teams. Explore options to assign them to work directly with executives on strategic initiatives, providing data analysis, modeling, and interpretation services as part of the decision-making process. 6) Make decisioning a formal pillar of your #datastrategy alongside common existing ones like data architecture, data quality, and metadata management. Develop initiatives and goals focused on improving decision-making processes, including training, tools, and metrics. 7) Conduct strategic data reviews to evaluate how effectively data was used. Avoid being overly critical of the decision-makers; the goal is to refine the process, not question the decisions themselves. Consider what data could have been sought at the time to validate or challenge the decision. Both data and intuition have roles to play in strategic decision-making. No leap in data or #AI will change that. The goal is to balance the two, which requires investment in the decision-making process to complement the existing focus on the data itself. Full POV ➡️ https://lnkd.in/e3F-R6V7

🚀 Unlocking the Potential of Data in Education: From Data-Driven to Data-Informed 📊✨ Do you think you're ready to elevate your approach to school improvement? My latest article dives into the often blurred lines between "data-driven" and "data-informed" decision-making and their profound educational implications. 🔍 Key Highlights: Data-Driven vs. Data-Informed: Understand the distinct differences and why it matters. Five-Level Hierarchy: Learn the stages from basic data collection to integrating R&D for innovation. Practical Examples: Real-world scenarios from schools and districts that illustrate each level. 📚 Levels of Transition: Data Collection and Basic Analysis: Reactive decision-making based on primary data. Descriptive Analytics: Identifying trends to inform improvement. Diagnostic Analytics: Understanding the root causes of trends and issues. Predictive Analytics: Forecasting outcomes for proactive planning. Prescriptive Analytics and R&D Integration: Driving innovation through evidence-based strategies. 👩🏫 Transformative Practices: Discover how transitioning to a data-informed approach can revolutionize school improvement, leading to more strategic, proactive, and innovative solutions. Dive into the full article to explore how these transformative practices can set the foundation for continuous educational growth and excellence. #Education #SchoolImprovement #DataDriven #DataInformed #Innovation #R&D #Analytics #EducationalLeadership #ContinuousImprovement

Too many schools are data rich and information poor. There's not a single school out there that probably wishes they had more data sources. State test scores. MAP or iReady reports. Exit tickets. Walkthrough trackers. There’s no shortage of numbers. But here’s the problem: The presence of data doesn’t guarantee the presence of insight. Too often, leadership teams: - Share data but don’t interpret it - Interpret it but don’t make decisions - Make decisions but don’t follow through The result? A spreadsheet full of information and no change in classroom practice. When we work with schools, one of the first things we teach is how to run an effective data meeting as a leadership team. A meeting that: 1) Clearly determines progress to goal 2) Celebrates bright spots 3) Determines areas of growth 4) Analyzes root causes behind those areas 5) Creates action plans that don't sit on a shelf Data alone doesn’t improve schools. Leadership decisions do.