Graduate student research paper by Aaron Isom.
Created for CS6460 Educational Technology at Georgia Institute of Technology.
This work involved a comparative analysis of randomly selected Data Science Massive Open Online Courses (MOOCs) and master’s degree programs in investigating how effectively interdisciplinary curricula approaches were being utilized in the course design. It also involved a second study, in the form of a qualitative survey, that asked students to share their perspective, satisfaction, and sentiment from MOOC experiences. These findings were combined, analyzed and utilized to support the foundation of the proposed case-based learning methodology. This approach provides a more real-world and project simulated approach that challenges students to solve problems analytically which is seen as a more effective framework for delivering data science offerings.