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SBIR Phase II: Online Game to Assess and Improve Behavioral Readiness and Social Emotional Skills for Students in Kindergarten and First Grades

SBIR Phase II: Online Game to Assess and Improve Behavioral Readiness and Social Emotional Skills for Students in Kindergarten and First Grades
SBIR 第二阶段:评估和提高幼儿园和一年级学生行为准备度和社交情感技能的在线游戏
批准号:
1853055
负责人:
James Thomas
金额:
$74.99万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-04-01 至 2022-03-31
关键词:

项目摘要

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中文摘要
翻译
这个SBIR第二期项目旨在创建和测试一个基于游戏的智能辅导系统,评估和改善幼儿园和一年级学生的行为准备和社交情感技能。研究表明,对社交技能缺陷的儿童进行早期干预对于在课堂上取得成功和在生活中取得成功至关重要。来自弱势、服务不足的社会小众群体的儿童尤其有可能“更不准备”上学,包括那些经历了贫困、家庭不稳定和创伤的儿童,这些都对来自种族和少数民族群体的儿童产生了不成比例的影响。该项目正在开发的游戏使教育工作者能够为他们的年轻学生提供亟需的社交情感学习支持。首先,它提供了一种负担得起的、可行的和可扩展的手段,用于确定年轻学生在过渡到正规学校时的社会情感需求。其次,它使教育工作者能够迅速将这种形成性评估数据转化为个性化的数字干预,与传统的面对面服务相比,这种干预可以在更广泛的范围内应用于K1学生。最后,由于这一创新是基于游戏和乐趣的,学生更有可能充分参与并充分受益于嵌入式教学。这个项目将促进对如何有效地使用智能辅导系统(ITS)来帮助教育工作者向所有学生提供社交情感指导的理解。在科学和数学等学术领域,许多成功的ITS实现都采用了学习模型,其中问题的答案和被评估的知识可以很容易地表示出来。然而,传统的ITS技术在社交情感学习等领域并不那么有效,在这些领域,学生的所作所为与学生所知之间的联系不那么明确。这个项目将为ITS开发几个重要的创新,适用于社交和情感学习,但也可能在其他定义较不明确的学习领域有用。这些创新的代表是我们的适应性学生模型和辅导管理器,它们通过个性化、步调和参与度共同提高学生的学习能力。随着收集的学生数据越来越多,学生模型将变得越来越准确,从而使辅导经理做出更智能的选择,以更好地增强我们创新的社交辅导,从而促进学生的学习。除了解决重大的社会和市场需求外,这项SBIR的研究成果将被公布,以更广泛地为ITS社区的努力提供信息。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
This SBIR Phase II project aims to create and test a game-based intelligent tutoring system that both assesses and improves the behavioral readiness and social emotional skills of Kindergarten and 1st grade students. Research has shown that early intervention for children with social skill deficiencies is critical for success in the classroom and success in life. Children from vulnerable, underserved social niches are particularly likely to be 'less ready' for school, including those who experience poverty, family instability, and trauma, each of which disproportionately impact children from racial and ethnic minority groups. The game being developed by this project empowers educators to provide that much needed social emotional learning support for their young students. First, it provides an affordable, feasible, and scaleable means for identifying the social emotional needs of young students as they transition to formal schooling. Second, it enables educators to quickly translate this formative assessment data into personalized, digital intervention that can be applied with K1 students on a much broader scale than is possible with traditional, in-person services. And lastly, because this innovation is game-based and fun, students are more likely to fully engage and fully benefit from the embedded instruction. This project will advance understanding of how an Intelligent Tutoring System (ITS) can be used effectively to help educators provide social emotional instruction to all students. Within academic domains such as science and mathematics, many successful ITS implementations have employed learning models where answers to problems and the knowledge being evaluated can be easily represented. However, traditional ITS techniques have not been as effective in domains like social emotional learning, where the connection between what a student does and what the student knows is less well-defined. This project will develop several significant innovations for ITS that apply to social and emotional learning, but may also be useful in other, less well-defined learning domains. These innovations are represented by our adaptive Student Model and Tutorial Manager which collectively enhance student learning via personalization, pacing, and engagement. As more student data is collected, the student model will become increasingly accurate, leading to more intelligent choices from the tutorial manager to better enhance the social tutoring of our innovation and thereby, student learning. In addition to addressing significant societal and market needs, research findings from this SBIR will be published to more broadly inform the efforts of the ITS community.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.
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