ThoTh Lab

Abstract

Personalized learning is often referred to a new learning approach by taking individual parameters such as learning preferences, abilities, skills and knowledge into account. In this poster, we present a personalized learning solution for computer networks, system, and cybersecurity focusing on hands-on projects. The personalized learning models are established in ThoTh Lab - a cloud-based hands-on virtual laboratory for Computer Science (CS) education. ThoTh Lab is a remote web-accessing virtual laboratory and it was originally designed to reduce lab management overhead for instructors and improve learning experience for CS students. By introducing new personalized learning capabilities, we can transfer ThoTh Lab from a traditional hands-on lab resource provisioning system to an active personalized e-learning platform for CS education. The system can track and assess students' hands-on projects' activities to monitor students' lab performance, and then provide intelligent suggestions or resources to improve students' learning experience and outcomes. Our personalized learning framework is distinguished from existing approaches by three salient features: (1) it is built into a hands-on and virtualized laboratory environment usually involving multiple virtual computers and their interconnections, (2) it has incorporated into a wide range of learners' characteristics such as individuals' learning style, prior knowledge and learning effectiveness, and it is designed to be able to include new and customizable features, (3) it uses machine learning approaches to model student characteristics during the learning process.