CRII: Cyberlearning: Keeping Computer Programming Learners Engaged Online

这项研究旨在创建创新的软件，以扩大免费在线编程教育的渠道。随着计算在21世纪继续变得越来越重要，越来越多的人转向可自由支配的在线资源来学习计算机编程等相关技能。这些资源是大量向公众传授知识的伟大工具，这对经济发展和创新非常重要。然而，这些资源中的许多都很难保持用户的参与度，而这是学习的关键组成部分。在教育下一代学习者方面，构建能够检测用户脱离并适应他们需求的互动系统将变得越来越重要。获得这些类型的免费、定制的学习体验将使每个人受益，尤其是那些代表性不足的群体和/或那些生活在农村或低收入地区的人，他们可能没有高质量的计算机教育资源。这个项目建立在Gidget的基础上，Gidget是一个在线教育学习工具，旨在通过调试谜题向初学者传授计算机编程的入门概念。本项目旨在将预测器集成到能够检测陷入困境和脱离学习的学习者的工具中，以便采取适当的行动(S)来帮助他们。课程生成器组件将生成和提供定制的级别，为有困难的学习者提供更多的概念练习。重新参与组件将及时生成和显示反馈，以帮助未参与的学习者重新参与。这项研究将对在线教育编程工具中这些技术在学习者参与度(使用该工具的总时间和完成的概念总数)和学习结果(由事后知识测试确定)方面的有效性提出新的见解，并为其他互动教育工具的设计提供参考。这项工作为计算机教育、交互式教育工具、人机交互、智能教学系统和学习科学等领域做出了贡献。

This research aims to create innovative software to broaden access to free online programming education. As computing continues to be increasingly important in the 21st century, more people are turning to discretionary online resources to learn related skills such as computer programming. These resources are great tools to teach the public in large numbers, which is important for economic development and innovation. However, many of these resources struggle to keep their users engaged, which is a critical component for learning. Building interactive systems that can detect users' disengagement and adapt to their needs will become increasingly important in teaching the next generation of learners. Access to these types of free, customized learning experiences will benefit everyone, but especially those in underrepresented groups and/or those living in rural or low income areas, who might not have quality computing education resources available to them otherwise.This project builds on Gidget, an online educational learning tool designed to teach novices introductory computer programming concepts through debugging puzzles. This project aims to integrate predictors into the tool that can detect struggling and disengaged learners, so that appropriate action(s) can be taken to help them. The curriculum generator component will produce and deliver customized levels to provide struggling learners more practice with concepts they are having difficulty with. The reengage component will produce and display just in time feedback to help reengage disengaged learners. This research will shed new insights into the effectiveness of these techniques on learners' engagement (operationalized as total time spent using the tool and total number of concepts completed) and learning outcomes (determined by a pre-post test of knowledge) in an online educational programming tool, and inform the design of other interactive educational tools. This work contributes to the fields of computing education, interactive educational tools, human-computer interaction, intelligent tutoring systems, and learning science.