COLLABORATIVE RESEARCH: Social-Emotional Analysis of the Language Environment (SEAL): Key Word & Phrase Spotting in Early Childhood Care Settings

O该项目由发展科学计划和既定的激励竞争性研究计划(EPSCoR)共同资助。儿童在学校和生活中的成功取决于他们在幼年是否学习了某些社交和情感技能。为了培养教师促进社交情绪学习的能力，需要有工具向教师提供基于数据的反馈，以关注社交情绪学习。该项目创建了这样一个工具--语言环境的社会情感分析(SEAL)。Seal使用先进的语音处理算法来自动捕捉幼儿教育课堂中支持社交情感学习的教师实践的一个关键元素：他们对语言的使用，特别是日常互动中利用社交情感学习的单词和短语。这种从幼儿教室的录音中自动测量教师的社交情绪谈话的方法可以代表一种变革性的方法，帮助教师更好地支持儿童的社交情绪发展(例如，理解、管理和表达情绪)。反过来，这样的工具可以更好地确保幼儿获得技能，确保他们为学校、人际关系和生活做好准备。为证明SEAL的概念验证而开展的项目活动包括：(1)开发一个社会和情感词汇和词组，其信息来自一项国家调查和一个幼儿专业人员和专家咨询小组的重点小组；(2)探索教师音频数据，以改进现有的语音处理算法，以检测课堂成人社会情感关键词和短语；以及(3)通过将人类转录与自动检测语音数据的基线算法进行比较，检查单词和短语库的初步有效性。这项探索性研究旨在创造证据，证明未来的完全制定的海豹突击队解决方案可以产生易于访问和解释的数据，并可被个别教师、教练和儿童早期项目用来改进旨在促进儿童社交情绪结果的实践。最终，就像计算步数的自动监测器一样，我们设想SEAL可以被教师自己用来监控课堂上的社交情绪谈话，并培养提高幼儿社交情绪能力的能力。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。

o This project is jointly funded by the Developmental Science Program and the Established Program to Stimulate Competitive Research (EPSCoR).Children’s success in school and in life depends on whether they have learned certain social and emotional skills in their early years. To build teachers’ capacity to promote social emotional learning, there is a need for tools that provide data-based feedback to teachers on talk that focuses on social-emotional learning. This project creates such a tool, the Social Emotional Analysis of the Language Environment (SEAL). SEAL uses advanced speech processing algorithms to automatically capture a key element of teacher practice in early childhood education classrooms known to support social emotional learning: their use of language, and specifically, words and phrases within everyday interactions that tap into social emotional learning. This automatic measurement of teachers’ social-emotional talk from audio recordings in toddler classrooms could represent a transformative approach to help teachers better support children’s social-emotional development (e.g., understanding, managing, and expressing emotions). In turn, such a tool could better ensure young children gain the skills that ensure they are ready for school, relationships, and life. Project activities to demonstrate proof-of-concept for SEAL include: (1) developing a social and emotional word and phrase bank, informed by a national survey and focus groups with early childhood professionals and input from an expert advisory panel; (2) exploring teacher audio data to refine existing speech processing algorithms to detect classroom adult social emotional key words and phrases; and (3) examining initial validity of the word and phrase bank by comparing human transcription to a baseline algorithm to automatically detected speech data. This probe study serves to create evidence that a future fully formulated SEAL solution could yield data that will be easy to access and interpret and can be used by individual teachers, coaches, and early childhood programs to improve practices aimed at promoting child social emotional outcomes. Eventually, like an automated monitor for counting steps, we envision SEAL could be used by teachers themselves to monitor classroom social emotional talk and build capacity to improve social emotional competence in young children.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.