Using Data to Guide Intervention Strategies

Hey #highered leaders - if you're still using static pivot tables to inform strategy, this post is for you ⤵ Take a peak at the below screenshot. This example, which shows two "paired predictors", is just one way you can turn data into action: 📈 ▶ The top right quadrant are “high achievers”. They have a high GPA + high credit earn ratio. These students might simply receive a message of encouragement. ▶ The top left quadrant are “strivers”. They have lower GPAs, but higher credits earned. These students might receive a nudge related to maximizing their use of available academic resources. ▶ The bottom right quadrant are “setbacks”. They have higher overall GPA, likely from good grades in their early coursework, but are earning fewer credits towards graduation requirements in key courses in their major. These students should probably receive messaging about the need for high-touch interaction with their advisors to stay on track and not lose their early momentum. ▶ The students in the bottom left quadrant are in "survival mode”. They are below average in both areas. These students are probably due for some real human-to-human conversation to better understand their needs. They may need in-depth intervention, with accompanied supports for finding the most successful path towards goals that match the students’ strengths and interests. You may consider nudging and re-nudging them throughout a term. ⤵ There's so many more examples of how Civitas Learning partners are disaggregating data to close equity gaps. If you're curious to learn more, let's connect 💌 #studentsuccessanalytics

I've always believed that assessment is the unlock for systemic education transformation. What you measure IS what matters. Healthcare was transformed by a diagnostic revolution and now we are about to enter a golden era of AI-powered diagnostics in education. BUT we have to figure out WHAT we are assessing! Ulrich Boser's article in Forbes points the way for math: rather than assessing right answer vs wrong answer, assessments can now drill down to the core misconceptions in a matter of 8-12 questions. Instead of educators teaching the curriculum or "to standards" we now have tools that allow them teach to and resolve foundational misunderstandings of the core building blocks of math. When a student misses an algebra question is it due to algebraic math skills or is it multiplying and dividing fractions? Now we will know! Leading the charge is |= Eedi - they have mapped millions of data points across thousands of questions to build the predictive model that can adaptively diagnose misconceptions (basically each question learns from the last question), and then Eedi suggests activities for the educator or tutor to do with the student to address that misconception. This is the same kind of big data strategy used by Duolingo, the leading adaptive language learning platform. It's exciting to see these theoretical breakthroughs applied in real classrooms with real students! Next time we should talk about the assessment breakthroughs happening in other subjects. Hint: performance assessment tasks - formative & summative - are finally practical to assess!! #ai #aieducation Edtech Insiders Alex Kumar Schmidt Futures Eric The Learning Agency Meg Tom Dan #math Laurence Norman Eric https://lnkd.in/gxjj_zMW

Good story about University of Kentucky thinking more intentionally about student success. "Back in 2016, the University of Kentucky doubled down on student success as a strategic goal. The commitment involved a realignment of resources toward the four main reasons the university has found that students persist, or don’t: academic preparation, mental and physical well-being, financial stability, and sense of belonging and community. As part of this restructuring, UK officials also rethought student communication strategies, prioritizing deliberate, multimodal communication, and worked toward building a culture of care. Lastly, leaders wanted data analytics—and a related culture of evidence— to guide much of their work. But getting administrators, faculty and staff members to speak student success data is of course easier said than done. One thing that’s helped UK adopt that common language? Holding weekly, open-door data meetings focused on retention. Todd Brann, executive director of institutional research, analytics and decision support at UK, calls these meetings the “secret sauce” to the university’s success thus far. Process and purpose: Originally attracting about 10 attendees, the meetings now draw scores from across departments, offices and programs. Attendees help contextualize and identify barriers to success from the billions of student data points that Brann and his colleagues collect from various university platforms. This process can work in reverse, too: Sometimes meeting attendees share on-the-ground problems or anecdotes and then look to the data for larger patterns or explanations. Either way, the real purpose of the meeting is to brainstorm data-based interventions and solutions. “We’re creating a space where folks can ask questions about the data, get interested in the data, and then we come back the next week and we close the loop and we provide answers,” Brann says. “And we’re going to prioritize those data points that can actually lead to an action.” Example: One year, a dip in priority registration among first-year women tipped student success leaders off to a conflict within a particular social club, and interventions were arranged. Why it helps: Kirsten Turner, vice president for student success and chief student affairs officer, says the meetings are particularly helpful in democratizing and speeding up problem-solving."