FW-HTF: The future of classroom work: Automated Teaching Assistants

人类技术前沿的未来工作（FW-HTF）是NSF宣布的10个未来投资新想法之一。FW-HTF跨董事会计划旨在通过支持融合研究来应对不断变化的就业和工作环境的挑战和机遇。这个奖项实现了这个目标的一部分。 专家教师通过个人、小组和全班活动，有效地协调课堂上复杂的思想和产品流。为了支持教师今后的工作，该项目将通过开发一个智能教学助理，作为一个基于平板电脑的仪表板，促进课堂协调过程。这将允许教师将与课堂活动相关的认知要求较高的编排任务委托给智能助理，使他/她能够专注于其他任务以支持学生学习。 在现有的中学数学教师共享文件系统的基础上，拟议的系统将有助于教师监测学生的工作，评估它，并作出结论（例如，指出学生的进步、错误和误解），同时允许它们在单独工作或小组工作的学生中传播。 最终，该系统将表现得像一个自动化的教学助手，使教师能够更有效地帮助最需要帮助的学生，从而提高他们的工作满意度。 在团队的形成性评估与计算技术（FACT）系统的基础上，智能教学助理的开发将提高教师对课堂上发生的事情的认识，并促进协调课堂活动的认知密集型任务。在第一个六个月的阶段，该项目将采用知识工程过程来揭示教师在管理课堂活动流程时用于决策的隐性知识。 在第二阶段，在两年半的时间里，将进行一系列的十次综合试验，通过数据收集和优化工作流程和想法，仔细考虑教师的输入，迭代开发系统的认知策略。 这些知识将被编码在基于规则的人工智能中，智能教学助理可以执行一些决策。 在老师的授权下，它将在特定情况下直接向学生发送信息-有些是反馈，有些是提示，有些是访问其他学生的请求，有些只是重新引导注意力回到任务上。 自动化教学助理还将优先考虑教师的任务;例如，在教室里参观哪些学生。 作为这一过程的一部分，新的传感器将被添加到FACT，将监测教师的讲话和位置。潜在的更广泛的影响包括促进教师进行更复杂的教学和有效的教训，提高教师的工作满意度，同时提高学生的learning.This奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。

The Future of Work at the Human-Technology Frontier (FW-HTF) is one of 10 new Big Ideas for Future Investment announced by NSF. The FW-HTF cross-directorate program aims to respond to the challenges and opportunities of the changing landscape of jobs and work by supporting convergent research. This award fulfills part of that aim. Expert teachers effectively orchestrate the complex flow of ideas and products in the classroom through individual, small group, and whole class activities. In supporting the future work of teachers, this project will facilitate the classroom orchestration process through the development of an intelligent teaching assistant, implemented as a tablet-based dashboard. This will allow the teacher to delegate cognitively-demanding orchestration tasks related to classroom activities to the intelligent assistant, enabling him/her to focus on other tasks to support student learning. Building on an existing shared-document system for middle school mathematics teachers, the proposed system will facilitate teachers in monitoring student work, assessing it, and making conclusions (e.g., indicating student progress, errors, and misconceptions) while allowing them to circulate among students who are working individually or in small groups. Ultimately, the system will behave like an automated teaching assistant and allow teachers to be more effective and increase their job satisfaction by allowing them to concentrate on assisting learners who most need help. Building on the team's Formative Assessment with Computational Technologies (FACT) system, the development of an intelligent teaching assistant will enhance teachers' awareness of what is going on in the classroom and facilitate the cognitively-intensive tasks of orchestrating classroom activities. In the first six-month phase, the project will employ a knowledge engineering process to uncover the tacit knowledge teachers use for decision-making in managing the flow of classroom activities. In the second phase, over two and one-half years, a series of ten comprehensive trials will be conducted to iteratively develop the cognitive policies of the system through data collection and optimizing the flow of work and ideas, carefully considering teacher input. This knowledge will be encoded in a rule-based Artificial Intelligence where the intelligent teaching assistant can perform some of the decision-making. Authorized by the teacher, it will send messages directly to students in specific situations - some will be feedback, some will be hints, some will be requests to visit other students and some will just be to redirect attention to get back on task. The automated teaching assistant will also prioritize tasks for the teacher; e.g., which students to visit in the classroom. As part of this process, new sensors will be added to FACT that will monitor the teacher's speech and location. The potential broader impact includes facilitating teachers in conducting more pedagogically complex and effective lessons and increasing teacher job satisfaction while improving student learning.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.