通过启发式学习和生成适应性在全国范围内达到96%的精通程度

Zoran Popovic
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摘要

目前大多数关于改善学习成果的研究都集中在学习生态系统中巨大多维空间的一小部分变量上。大多数数字学习工具主要关注单个学生,其他研究只关注教师的专业发展,或者只关注课程改进。在这次演讲中,我将描述我们如何发现整个生态系统的最佳参数的努力,考虑到学生因素(参与和掌握),课堂因素(混合学习变化和小组学习变化),课程因素(现有课程的多维变化)和教师因素(减轻弱点的课堂工具,促进教师发展)。我将描述我们在高维空间中发现最佳学习路径的算法方面的工作。我将以在美国两个州和挪威进行的代数挑战中部署我们平台的一部分的结果作为结束。Zoran Popovic是华盛顿大学游戏科学中心主任,也是Enlearn的创始人。作为一名计算机科学家,他的研究重点是为学习和科学发现创造互动的吸引人的环境。他的实验室创建了Foldit,这是一款生物化学游戏,在短短两年内就在《自然》杂志上发表了三篇文章,这是一款屡获殊荣的数学学习游戏,全世界有超过500万的学习者在玩。他目前专注于参与的方法,可以快速发展专家在任意领域,特别侧重于革命K-12数学教育。他在华盛顿、明尼苏达州和挪威进行的代数挑战表明,96%的小学生在1.5小时内就能学会关键的代数概念。他最近成立了Enlearn,将他在生成适应方面的研究应用于任何课程,以实现95%的学生完全掌握课程的目标。他对交互式计算机图形学领域的贡献得到了许多奖项的认可,包括NSF CAREER奖、Alfred P. Sloan奖学金和ACM SIGGRAPH重要新研究员奖。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Achieving 96% Mastery at National Scale through Inspired Learning and Generative Adaptivity
Most of the current research on improving learning outcomes focuses on a small subset of variables of an immensely multi-dimensional space of the learning ecosystem. Most digital learning tools primarily focus on individual students, other research focuses only on teacher professional development, or only on curriculum improvement. In this talk I will describe our efforts on how to discover optimal parameters of the entire ecosystem that considers student factors (engagement and mastery), classroom factors (blended learning variations and group learning variations), curriculum factors (multidimensional variation of existing curricula), and teacher factors (in-class tools that mitigate weaknesses, and promote teacher development). I will describe our work on algorithms to discover optimal learning pathways in this high-dimensional space. I will conclude with the outcomes of deploying a portion of our platform on algebra challenges conducted on two US states and the country of Norway. Zoran Popovic is a Director of Center for Game Science at University of Washington and founder of Enlearn. Trained as a computer scientist his research focus is on creating interactive engaging environments for learning and scientific discovery. His laboratory created Foldit, a biochemistry game that produced three Nature publications in just two years, an award-winning math learning games played by over five million learners worldwide. He is currently focusing on engaging methods that can rapidly develop experts in arbitrary domains with particular focus on revolutionizing K-12 math education. His Algebra Challenges conducted in Washington, Minnesota, and Norway, have shown that 96% of children even in elementary school can learn key algebra concepts in 1.5 hours. He has recently founded Enlearn to apply his work on generative adaptation to any curricula towards the goal of achieving full mastery by 95% of students. His contributions to the field of interactive computer graphics have been recognized by a number of awards including the NSF CAREER Award, Alfred P. Sloan Fellowship and ACM SIGGRAPH Significant New Researcher Award.
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