Data mining has become a new research topic in learning science that aims to combine research, data, and practices to help educators teach better and students learn more. On the one hand, digital techniques are adopted to support the activities, including teaching, learning, and managing in today's education environment. Especially for the current COVID-19 situation, many students are learning through online platforms and digital systems. On the other hand, more and more countries and people have started to pay attention to improving learning outcomes by deeply personalizing student learning. Many studies have been developed to understand the learning patterns from brain images, electronic records, and school behaviors.
Learning science is drawn from multi-disciplines fields. In this workshop, we aim to bring together researchers in data mining, brain cognition, education, and social computation fields to discuss the challenges, definitions, and formalisms in the studies on DMLS. We hope that the proposed workshop is fruitful in attracting more attention to developing more data mining algorithms and models for scientific education.
The 1st Workshop on DMLS will be held with the 22nd IEEE International Conference on Data Mining on Dec. 1, 2022. Welcome researchers, educators, and Intelligent education enterprises to join this meeting.
The conference papers are encouraged to be expanded and submitted to the following journals.