ThoTh Lab: A Personalized Learning Framework for CS Hands-on Projects (Abstract Only)

Yuli Deng, Dijiang Huang, Chun-Jen Chung
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引用次数: 10

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.
thth实验室:CS实践项目的个性化学习框架(仅摘要)
个性化学习通常指的是一种新的学习方法,它将学习偏好、能力、技能和知识等个人参数考虑在内。在这张海报中,我们提出了一个针对计算机网络、系统和网络安全的个性化学习解决方案,重点是实践项目。个性化的学习模式是建立在ThoTh实验室-一个基于云的动手计算机科学(CS)教育的虚拟实验室。ThoTh Lab是一个远程网络访问虚拟实验室,它最初的设计是为了减少教师的实验室管理开销,改善计算机科学学生的学习体验。通过引入新的个性化学习功能,我们可以将ThoTh Lab从传统的动手实验室资源供应系统转变为面向计算机科学教育的主动个性化电子学习平台。该系统可以跟踪和评估学生的动手项目活动,以监控学生的实验表现,然后提供智能建议或资源,以改善学生的学习体验和成果。我们的个性化学习框架与现有的方法有三个显著特点:(1)它被构建成一个动手和虚拟的实验室环境,通常涉及多个虚拟计算机及其相互连接;(2)它已经纳入了广泛的学习者特征,如个人的学习风格、先验知识和学习效率,并且它被设计成能够包括新的和可定制的特征;(3)它使用机器学习方法来模拟学习过程中的学生特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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