What is the potential of a 21st-century learning environment in a interconnected world of personalized Apps? In contrast to the standard linear or tree-like educational system of sequential lectures or chapters, we will discuss how to improve personalized education using the network of knowledge and the social network of learners and teachers. Particularly, we introduce a real-time, modular, adaptive teaching-learning environment for enhanced and personalized education that breaks away from the predictable pattern of traditional education models and provides content delivery that adapts to the capabilities, learning styles, and approaches to problem-solving of every learner.

The target audience comprises of scholars that have had exposure to at least one course in network science or social networks, and have a strong interest in the advancement of education and revolutionizing education as we know it. We will describe our view on how different learning tools can be joined into a web/network of knowledge that will individualize learning and leave a persistent impact on the learner's career. We introduce our unique structure and vision for catering to the needs, motivations, and supply of learners with a system that:

1. Offers intense, short, and focused educational modules.

2. Stimulates interest and relevance of topics.

3. Integrates new information with learner’s pre-existing knowledge.

4. Provides personalized and individualized education.

5. Optimizes content and methodology delivery to meet the needs of each learner.

Starts 1:30 - 4:00 PM CET on 8th November 2021

Prof. Dr. Ralucca Gera is a full professor at the Naval Postgraduate School and just finished her 3-year commitment of Associate Provost for Graduate Education and Director of Teaching and Learning Commons also at the NPS. She has delivered several invited presentations, conference presentations, and tutorials on education, network science, and graph theory with applications to AI and ML. She co-authored over 100 papers in Graph Theory, Education, and Network Science, along with a book chapter and two books. She is a co-organizer of the NetSciEd (Network Science in Education) community and an active contributor for building a network science based education learning tool. She has chaired conference sessions, mini-symposia, committees, and founded organizations, and has served on the editorial board of several journals.

Dr. Akrati Saxena is a Research Fellow at the Department of Mathematics and Computer Science, Eindhoven University of Technology (TU/e), Netherlands. She received her Ph.D. in Computer Science and Engineering from IIT Ropar, India. Her research interests include social network analysis, complex networks, computational social science, and Fairness. She has worked extensively at Network Science and Data Science and has published at well-known conferences and journals.