The ALOSI adaptive engine is a web application that powers the recommendation of learning resources to learners based on real-time activity. This application is designed to be used with the Bridge for Adaptivity, which handles the serving of activities recommended by the engine.
This repository contains the Django web application code, and related documentation/writeups for the adaptive engine.
app/- Adaptive engine web application (python/django) code
data/- data for engine initialization and data processing/transform scripts
monitoring/- terraform files for setting up cloudwatch alarms on an elastic beanstalk deployment
python_prototype/- python prototype for adaptive engine
r_prototype/- R prototype for adaptive engine
tests/- Testing scripts, including load testing with Locust
writeup/- Writeup and LaTeX files to generate the document
- Web application folder and documentation
- Theoretical overview of the recommendation engine algorithm
- alosi library: Python package for recommendation engine algorithm utilities, and APIs for ALOSI Bridge and Engine (https://github.com/harvard-vpal/alosi)
- Bridge for Adaptivity: Application that handles serving of content recommended by this and other engines (https://github.com/harvard-vpal/bridge-adaptivity)