BCSER: Using Computational Language Processing Techniques to Determine if Parental STEM Language Varies By Child Gender

该STEM教育研究能力建设项目结合了一个调查家长是否在日常对话中向学龄前儿童传播关于STEM的性别陈规定型观念的研究项目，以及一个详细的专业发展计划，使首席调查员能够培养计算研究方法方面的能力，指导初级同事的技能，以及关于妇女在STEM中代表性不足的研究知识。这项研究将考察父母是否比女孩更多地使用STEM词汇和话题，从而提供证据表明，父母的语言可能导致女孩在STEM中的代表性不足。该项目还将开发和测试一种新的研究方法，使用一种新的定量方法--计算文本分析。研究项目和专业发展计划将支持一项研究轨迹，旨在使用计算文本分析来检验父母言语的差异如何影响孩子的下游结果，例如使用纵向研究设计的科学思维和STEM参与。该项目将使研究人员探索与STEM结果中的性别差异相关的潜在可塑性因素，目标是提出有针对性的干预措施，以扩大所有学习者在STEM中的代表性。该项目将以学习和发展的社会文化理论、性别图式理论和期望理论为指导，以解释父母信念和行为的性别差异如何影响儿童未来的STEM动机和坚持性。研究者将考察三个研究问题：(1)父母对STEM语言的使用是否基于父母是与他们的儿子或女儿互动而存在差异？(2)哪些家庭特征在父母的STEM语言与孩子性别之间存在适度的联系？(3)与人工编码方法相比，计算文本分析在识别父母STEM语言方面的可靠性如何？将收集80个家庭的人口结构、科学态度和性别图式的录像带和调查数据。这两个来源的成绩单将汇编成一个语料库进行分析。计算文本分析将被用来确定父母在与儿子和女儿交谈时使用与STEM相关的单词和话题是否有所不同。调查员将使用开源的R统计建模语言来执行整个文本分析工作流程。这些研究成果将促进关于STEM陈规定型观念如何从父母传递给幼儿的过程的核心知识。本项目得到EHR核心研究(ECR)计划的ECR：STEM教育研究竞赛中的能力建设的支持。ECR资助专注于STEM学习和学习环境、STEM领域的能力建设和STEM劳动力发展的基础研究。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。

This STEM education research capacity building project combines a research project that investigates whether parents transmit gender stereotypes about STEM to pre-school children in everyday conversations and a detailed professional development plan that enables the principal investigator to develop competencies in computational research methodologies, skill in mentoring junior colleagues, and knowledge of research on the underrepresentation of women in STEM. The research will examine whether parents use more STEM words and topics with boys than girls, providing evidence that parental language may contribute to girls’ underrepresentation in STEM. The project also will develop and test a new research method by using a novel quantitative methodology, computational text analysis. The research project and professional development plan will support a research trajectory aimed at using computational text analysis to examine how variations in parents’ speech impact children’s downstream outcomes, such as scientific thinking and STEM participation using longitudinal research designs. The project will position the investigator to explore potential malleable factors associated with gender differences in STEM outcomes, with the goal of proposing targeted interventions to broaden representation in STEM for all learners.The project will be guided by the sociocultural theory of learning and development, gender schema theory to contextualize why parents may communicate about STEM differently with boys versus girls, and expectancy theory to explain how gender differences in parents’ beliefs and behaviors may impact children’s future STEM motivation and persistence. The investigator will examine three research questions: (1) Are there differences in parents’ use of STEM language based on whether the parent is interacting with their son or daughter? (2) What family characteristics moderate associations between parents’ STEM language and child gender? and (3) How reliable is computational text analysis compared to manual coding approaches for identifying parental STEM language? Videotapes and survey data of demographic constructs, science attitudes, and gender schemas will be collected for 80 families. Transcripts from both sources will be compiled into one corpus for analysis. Computational text analysis will be used to determine whether parents’ use of STEM-related words and topics differ when speaking to their sons versus daughters. The investigator will use the open-source R statistical modeling language to perform the entire text analysis workflow. The research findings will advance core knowledge about the processes underlying how STEM stereotypes are transmitted from parents to young children. This project is supported by the ECR: Building Capacity in STEM Education Research competition of the EHR Core Research (ECR) Program. ECR funds fundamental research focused on STEM learning and learning environments, building capacity in STEM fields, and STEM workforce development.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.