With data science continuing to emerge as a powerful differentiator across industries, almost every educational organization now focused on transforming the big educational data (gathered from various private/open/Social/IoT data islands) into actionable insights. Data Lakes have been introduced to store raw data and let the data analyst decide how to cook/curate them later, however, the main challenges are to understand the potentially interconnected data stored in various data islands and to prepare them for analytics. In this project, we introduce an Intelligent Data Lake to facilitate the analysis of Big educational Data. We introduce an Intelligent Educational Platform to support growth in data storage and analytics and to prepare the foundation for intelligently extract features from the Big educational Data. The goal is to establish a common approach for utilizing machine learning within the Sense & Respond framework, and to build a deep reinforcement learning model to seek to gain knowledge from students and teachers rather than extracting knowledge from data alone. The proposed platform will enable the analysts in education systems to unlock the value of big data so that better quality and faster insights can be delivered to determine processes for: automating best practice, to understand individual user context and incorporate this in the surfacing of relevant information, and to establish opportunities to capture user feedback within the Sense & Respond lifecycle (for the purposes of measuring impact and improving machine learning models). The final outcome will be novel techniques in the fields of Data science, Cognitive Technology, Human-Computer Interaction and Visualization.
|Effective start/end date||30/11/20 → 31/10/23|