Welcome to DCL4D
Digital learning-support environments such as LMS, electronic portfolio systems, and digital textbooks are increasingly used in various schools and online courses. They can facilitate learning activities in and outside classrooms, and their exhaust data can be used to perform learning analytics, which is the measurement, collection, analysis, and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs. Such a data-centric approach also allows for a potential use of early prediction about learners as exemplified in various learning analytics projects in countries including Japan.
General Framework OF DCL4D
This project aims to develop a learning-support platform that integrates DTN mechanisms and model-driven crowdsensing techniques to deliver learning materials and collect educational data to perform learning analytics to help learners and teachers for areas with weak ICT infrastructure. Our platform will employ active learning to collect useful educational data in an intelligent and efficient manner. The data are shared across different regional facilities and the main campus via DTN, thereby enabling a variety of analysis and visualization. Thus, people without access to digital learning environments would be able to get evidence-based feedback from the system or an instructor, which could improve teaching and learning quality based on data in developing regions to expand equality in education.