Embedded Files
Data Strategy
With respect to data, the best place to start is at the end. What is our goal? What does mastery look like? Then we choose assessment tools that allow students to demonstrate mastery. Then we have to ask what data forms our baseline. What data provides us with progress monitoring along the way? This section will hold examples of baseline data, formative data, and summative data for postsecondary tasks such as career plans, financial aid, and postsecondary enrollment.
What data do we collect?
Postsecondary data is unique from academic classroom data in that we have multiple tasks happening at once, each with its own set of data. There are overlapping tasks and many of the tasks have long-term timelines.
A tracker such as the one attached here can help you identify key data points for seniors that can drive your PLC work.
What do we do with data once we have it?
Once you have data, it's critical to USE it. We recommend using a structured protocol in order to keep the conversation on track, positive, and productive.
The ATLAS data protocol is a good one to consider for analyzing postsecondary data.
ATLAS data protocol.pdfAcademic vs Postsecondary PLCs
Postsecondary PLCs may have to do some translating from academic terms to the postsecondary domain, but the slide deck below can help make that shift.
Analyze data:
List of data types to consider
Set goals:
Lists postsecondary task goals for school and students
Individual & Collaborative Learning:
What are practices that yield results?
Collaborate on relevant student information.
Monitor, Assess, Adjust:
Ongoing support and follow-up
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