Toyhouse Crowd Cognitive Learning Lab

TOYHOUSE Manifesto

THE CHALLENGE

The human race has never before been in such dire need of independent thinkers and cooperative problem solvers. Two formidable countervailing forces have driven this need. These are to sustain its insatiable demand for natural resources whilst preserving the balan¬ce in global ecology so that quality human life is sustainable into the future.

Our discipline-centered and exam-based educational system has guided people to focus on individual achievement to the detriment of humanity and the expertise to solve this is scattered. We have forgotten that the real purpose of accumulating expertise is to foster the collaboration which will enrich our lives, whilst helping mankind to tackle global threats. To break out of the downward spiral, we must do more than just move along the curve of development, we must jump to the next curve. Educational institutions need to nurture trustworthy, compassionate people with pragmatic expertise. They must adopt social networking tools to situate us within interdisciplinary experts who come together to solve humanity’s big problems.

To meet these challenges, we must learn to develop existing industrial systems which are safe for the environment and its inhabitants by drawing on expertise wherever we can find it. Secondly, we must learn to produce dynamic, lively services and wholesome products, which supply our needs and inspire us. To balance the two competing forces of safety and liveliness, all industrial systems should be envisioned, created, and perfected by qualified and humble learners who can masterfully tame these two forces in reality. A new type of learning environment is needed to promote this new educational paradigm. We therefore introduce our proposition – spaces for “Learning by Playing” – Toyhouse.

OUR SOLUTION

Toyhouse is a combination of physical and virtual spaces supporting safe, yet lively learning activities. Toyhouse serves as a safe environment for incubating ideas as well as creating content, services or products. Toyhouse supports collaborative individuals as they tackle interesting challenges in the real world, possibly learning through body/mind engaging games or new toys to empower themselves to improve their individual and collective abilities in many fields of human endeavor. Learners may then create new games to build mastery.

In Toyhouse learners organize themselves according to their mission rather than by age or subject expertise. Games will often include learners of all ages, so that players have authentic experiences of the diversity and range of talents typical of the world they will emerge into.

Toyhouse is a learning space with no boundaries and each Toyhouse is part of a wider network. Learners are encouraged to use technology to expand the scale and capacity of intellectual/physical realms. Each Toyhouse will have features which are specialized in a way which is sensitive to its local needs whilst retaining its global cultural perspective.

The Toyhouse model is adaptable, working harmoniously with existing facilities and systems, capitalizing on existing intellectual and physical resources. It may also help revise learning activities and infrastructures of existing schools to better fit the “Learning by Playing” model. Toyhouse developers can also collaborate in developing suitable purpose-built facilities and share their vision that all educational institutions are knowledge conservatories, empowering their learners to move into the global collaborative web. Based on such firm foundations, young people can participate in conserving our planet and co-creating the future of our civilization.

• 众学理论逻辑模型：
  • 目标： 奠定众学理论基础
  • 效果： 16年3月份众学理论学术讨论，在此之前出1-2篇论文，完善基于理论的学习工具整合和开发。
  • 输出： 学术论文（集）、群体认知基础著作、XLP操作手册（基于网络性数字化工作流的群体自主学习的设计原则和测量方法）
  • 过程： 认知基础课、研讨、录音整理、学术会议发表论文、翻译著作、整理分析众学实践反馈数据、著书
  • 输入： 开源知识、专家资源、众学实践产生的数据

• 众学实践逻辑模型：
  • 目标： 培养符合未来需求的学习者
  • 效果： 可灵活重组的人才团队和知识结构
  • 输出： 宏观、中观、微观三类学习者的三层次数据资产、人才团队
  • 过程： XLP-Based Courses（包括前期筛选、认知基础课、专业课、集成挑战）
  • 输入： 基于众学理论和工具的课程设计方法、教学执行团队、工具开发团队

• 众学产业逻辑模型：
  • 目标： 众学成为以群体认知、社会协作的底层结构
  • 效果： 产学融合一体，没有界限
  • 输出： 形成基于众学数据基础与协议的企业及产业集群
  • 过程： 产业的科技和工具应用于众学实践、在众学实践中测试和展示产业科技和工具；将产业实际需求引入众学实践，通过众学实践输出可灵活重组的人才团队；将众学数据基础与协议应用于具体企业。
  • 输入： 基于众学理论的工具和方法