The app is designed to provide an automated workflow for training machine learning models to predict student outcomes.
Within the app there is a pipeline on top of our Machine Learning Toolkit that allows users to follow some simple click-and-select steps to load their e-learning data and select some important features in the data. The app then decides how it should be processed by an ML algorithm – including automatically deciding how the data should be pre-processed in preparation for an algorithm.
Ultimately the app provides non-expert users with a recommended model to apply to their particular data to predict: how likely a student was to pass or fail; and how likely a student was to drop off the course.
There are also a set of dashboards that can provide some easy to understand reports using the predictive models.
Prerequesites for this app:
- Splunk Machine Learning Toolkit Installed: https://splunkbase.splunk.com/app/2890/
- Creation of an index called learning_analytics_model_testing_metrics for storing the model training metrics
A blog that provided the inspiration for the app can be found here: https://www.splunk.com/en_us/blog/splunk4good/euvsvirus-predicting-online-student-outcomes-with-automated-ml-pipelines.html
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