Model-driven processes and tools to design GLO for CS education
Renata Burbaitė, Kristina Bespalova · 2014
The paper introduces processes and tools to design generative learning objects (GLO) through feature model (FM) transformations for CS education. In the first stage, to represent the variability of CS education, we apply feature-based modelling using FAMILIAR and SPLOT tools. In the next stages we present processes and newly developed tools to design GLO through high-level transformations. Case study demonstrates our methodology in ARDUINO-based e-learning environment.