Early Warning Indicator
In education, we utilize many of the techniques we have gleaned in other areas to derive expertise based on the common use cases and value we observe. Our basic approach for early warning indicators stems from our work in Churn in retail. If we can predict when a student starts to fail to predict the right intervention, we can most effectively assist their performance.
Optimal Intervention Prediction
Utilizing the same techniques from retail and consumer goods once again, we have found it is quite effective to segment and predict which students will operate best after which intervention. This technique enable us to best help students in education.
Neal Analytics has designed workshops to train researchers and business analysts on how to use Azure Machine Learning. Our workshops are designed to illustrate Azure’s easy-to-use platform and make your research more effective and efficient.
Student Dropout Prevention
Every school suffers from student attrition to some degree. Neal Analytics works with educational institutions to identify factors that can lead students to drop out and factors that can improve student retention. Schools can use this information to keep students enrolled and improve graduation rates. This is a brief video which describes some of the results we’ve seen in Australia working with our local Dynamics partner, S1 Consulting.
Many students are not engaged in a way which is a best fit for their learning styles and educational needs. Microsoft has partnered closely with Neal Analytics to address this problem, with the ultimate goal of better engaging students to increase their performance. Using modern Machine Learning applications, data enhancement techniques, and product integration over the Microsoft technology suite, Microsoft and Neal Analytics are working together to drive improved student performance. We expect a full algorithm-based solution and recommendation library will be completed and rolled out through the Azure marketplace within the next year.
Azure Advanced Analytics Kit
The Azure Advanced Analytics Kit provides an easy way for students to get started with and understand the value of Azure technologies in the context of interaction with sensor data. This is an extremely valuable skillset in today’s marketplace, and this kit teaches how to use sensors in conjunction with cloud computing. The kit is designed to be used as a hands-on lab for Azure and sensors. It allows engineering, computer science, management information systems, and business students to gain a fundamental understanding of Azure and how sensor-based applications can drive value in business.