Data-Driven Synthesis of Study Plans

Data-Driven Synthesis of Study Plans

Our new technical report describes the outcome of our audacious undertaking to design a tool that algorithmically synthesizes study plan for a course offering from the sole input of concept phrases representing the course content. We welcome your feedback, particularly from teachers and students.

Data-Driven Synthesis of Study Plans
Rakesh Agrawal, Behzad Golshan and Evangelos Papalexakis
Technical Report TR-2015-003

Abstract:

A study plan for an educational course refers to the choice of concepts to be covered and the organization and sequencing of course content. While a good study plan is essential for the success of any course offering, the design of study plans currently remains largely a manual task. We present a novel data-driven method, which given a list of concepts can automatically propose candidate plans to cover all the concepts. The output of our method both identifies which concepts should be studied together and how students should move from one group of concepts to another. For our experimental validation, we use a dataset that contains a list of concept names from the field of physics. We find that our method is able to produce good plan.

Bibtex Entry:

@techreport{AGP15:data-driven,
title={Data-Driven Synthesis of Study Plans},
author={Rakesh Agrawal and Behzad Golshan and Evangelos Papalexakis},
number={TR-2015-003},
institution={Data Insights Laboratories},
address={San Jose, California},
month={March},
year={2015}
}