SBIR Phase II: Artificial Intelligence Tutoring and Assessment for Teacher Development

SBIR 第二阶段：促进教师发展的人工智能辅导和评估

• 批准号: 0822696
• 负责人: Benny Johnson
• 金额: $ 50万
• 依托单位: Quantum Simulations Incorporated
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-07-15 至 2010-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0822696&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Artificial; Intelligence

This Small Business Innovation Research (SBIR) Phase II research project focuses on bringing the power and benefits of artificial intelligence tutoring technology to the arena of teacher professional development (PD). The proposed innovation is a teacher professional development system built on the principles of artificial intelligence, and delivered via the Internet. Similar to a flight simulator, this technology will offer a realistic but benign opportunity to test and expand a teacher's preparedness through practice with realistic classroom situations. A key objective is the creation of a classroom simulator which incorporates a virtual master teacher, to help teachers deepen their content understanding, learn to respond to student questions more effectively, practice proven pedagogical techniques for improving student understanding and conduct self-monitoring and assessment before getting in front of a live class. An increasing number of schools are forced to rely on new or out-of-field teachers to fill the gap for teaching science and mathematics, often resulting in a substantial decline in quality, depth and individual attention students receive. Because of the well-documented problems of teachers teaching out of their content areas, and low-performing schools having greater percentages of lesser-qualified teachers, states have established stronger criteria for in-service teachers and newly qualifying pre-service teachers. Middle and high school science and mathematics are the areas where most out-of-area teaching is occurring. In the National Center for Education Statistics (NCES) report, 'The Condition of Education', a key finding is that high school students in high-poverty, high-minority schools were more often taught science, mathematics and English courses by out-of-field teachers than their peers in low-poverty, low-minority schools. This research is expected to impact these issues and in addition address the goals of the American Competitiveness Initiative and the requirements for highly qualified teachers identified in the 'No Child Left Behind' initiative.

这个小企业创新研究 (SBIR) 第二阶段研究项目的重点是将人工智能辅导技术的力量和优势带入教师专业发展 (PD) 领域。拟议的创新是建立在人工智能原理基础上并通过互联网提供的教师专业发展系统。与飞行模拟器类似，这项技术将提供一个现实但良性的机会，通过现实课堂情境的练习来测试和扩大教师的准备情况。一个关键目标是创建一个包含虚拟主教师的课堂模拟器，以帮助教师加深对内容的理解，学会更有效地回答学生的问题，练习经过验证的教学技术以提高学生的理解，并在进入现场课堂之前进行自我监控和评估。越来越多的学校被迫依靠新教师或外聘教师来填补科学和数学教学的空白，这往往导致学生的质量、深度和个人关注度大幅下降。由于教师超出其教学内容领域进行教学的问题已得到充分记录，而且表现不佳的学校中资质较差的教师所占比例较高，各州对在职教师和新合格的职前教师制定了更严格的标准。初中和高中的科学和数学是大多数区外教学发生的领域。在国家教育统计中心 (NCES) 的报告《教育状况》中，一项重要发现是，与低贫困、少数族裔学校的同龄人相比，高贫困、高少数族裔学校的高中生更多地由外地教师教授科学、数学和英语课程。这项研究预计将影响这些问题，并解决美国竞争力倡议的目标以及“不让一个孩子掉队”倡议中确定的高素质教师的要求。