Table of Contents
- Introduction
- Produce Your Own Analytics or Hire a Vendor?
- So You Have Decided to Partner with a Vendor…
- Ensure that Data and Tools are Flexible and Fit the Need
- Ensure Transparent Use of Data
- Issues with Predictive Analytics Vendor Contracts
- Ensure Privacy and Security
- Supporting Research and Evaluation Efforts
- Supporting Staff Professional Development and Implementation
- Conclusion
- Appendix: Interview List
Supporting Research and Evaluation Efforts
To use predictive analytics tools well, colleges will need to continuously improve their intervention efforts. At the same time, the tools themselves need to be externally validated through research.
Evaluate the Product’s Research Base
Many vendors say that their products are evidence-based. But it is important for administrators to look critically at that research and see if it is independent and high quality. For instance, has the research been published in a peer reviewed journal? Organizations like Teachers College at Columbia University partner with vendors to increase and strengthen their evidence base.{{41}} There are also a series of tools, mostly designed for the K–12 environment, which could help colleges evaluate the evidence (see Box TK).
Tools for Evaluating Ed Tech Research
Evaluating Studies of Ed-Tech Products
Assist with Intervention Design and Evaluation
Once colleges have access to a predictive analytics tool, what should they do to change the trajectory for students? It can be helpful for vendors to support the design and evaluation of a college’s efforts intervene with students. Many vendors have experience with messages and interventions that worked in other college contexts. And they can also help evaluate how interventions perform by helping create well-matched control groups and processing the data. Since evaluation is an important part of using predictive analytics well, colleges should ask vendors how they can support these efforts.
Explore the Toolkit
Have other challenges? Read about the other considerations when selecting a predictive analytics vendor: