Mapping the Analysis of Students' Digital Footprint to Constructs of Learning

This research project explores the importance of learning theories in informing the objective evaluation of learning practice, as evidenced by the analysis of multimodal data collected from the eclectic mix of interactive technologies used in higher education. Frequently, learning analytics research builds models from trace data easily collected by technology, without considering the latent constructs of learning that data measures. Consequently, resulting models may fit the training data well, but tend not generalize to other learning contexts. This study will interrogate educational technology as a data collection instrument for constructs of learning, by considering the influence of learning design on how learning constructs can be curated from these data. Results will inform methodological guidelines for data curation and modelling in educational contexts, leading to more generalizable models of learning that can reliably inform how we act on data to optimize the learning context for students.