Is RCT the Gold Standard? - Civitas Learning Space
Randomized controlled trials (RCTs) have been touted as the gold standard in causal inference for many years. But is it true? Is there room to leverage modern data analytics to go beyond RCT? Unfortunately, the answer is a lot more nuanced. The emergence of big data and associated processing capabilities led to complacency that big ...
The Secret Sauce for Strong Signal Processing - Civitas Learning Space
I wanted to take this opportunity to investigate the important role of digital signal processing and machine learning in improving our ability to harness student success knowledge from SIS, LMS, and student touchpoint data in an observational setting. In machine learning, many tend to focus on learning algorithms, but the real magic comes from feature ...
Three Basic Big Ideas When Understanding Results - Civitas Learning Space
All around us in Higher Education are tantalizing reports of "results" or gains in student outcomes achieved by colleges and universities through new programming, products, or initiatives. "11% increase in first-year retention" "8% increase in four-year graduation rate" "4.5% increase in persistence for new transfers" Can they be believed?
Measuring Impact: Recent Journal Article Details How to Scale & Evaluate Support Services - Civitas Learning Space
How do you know if your student success initiatives are moving the needle? How will you report to leadership on its effectiveness and truly understand if it worked or had any impact? How do you evaluate your impact of your campus innovations? We know that measuring the effectiveness of new strategies or programs is no simple ...
Eight Nuanced Ideas When Understanding Results from Matched Pilots - Civitas Learning Space
In our prior post, we addressed the most common issues with outcomes reporting through Three Big Ideas. Now we are going to dig in deeper with eight nuanced topics for inspecting impact results based on matched control groups to help you become the Sherlock Holmes of impact. Number 1: Ask yourself...