Collaborative Research: PCK*Lex: Applying Computerized Lexical Analysis to Develop a Cost-Effective Measure of Science Teacher Pedagogical Content Knowledge
Collaborative Research: PCK*Lex: Applying Computerized Lexical Analysis to Develop a Cost-Effective Measure of Science Teacher Pedagogical Content Knowledge
批准号:
1438739
负责人:
Kevin Haudek
金额:
$26.67万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-10-01 至 2019-09-30
中文摘要
教学内容知识(PCK)是区分有效教学与无效教学的重要概念工具,但难以测量它导致了这一概念的最小应用,以提高实际的教学实践。本项目将应用计算机词汇分析技术开发一种有效、有效和可靠的科学教师PCK测量方法-教师知识类型,连接内容知识和如何在课堂上有效地教授内容。该项目将改变多个NSF STEM项目中使用的工具,但由于时间和资源密集而受到限制。词汇分析的最新发展的应用将允许测量PCK采取规模与快速反馈,并将是STEM研究人员,评估人员,PD提供者,教师教育者和教师本身的重要资源。这个合作研究项目汇集了两个具有独特但互补专业知识的团队。BSCS的研究人员在多个联邦项目中有测量PCK的经验,最近还领导了一个关于STEM PCK的国际峰会。密歇根州立大学的建构反应自动分析研究小组正在跨STEM学科进行工作,以改进将词法分析用于形成性教育目的的方法。该项目的更广泛的影响包括制定一项措施,这将是非常宝贵的多个利益相关者在评估和提高K-12科学教师的理解和能力。提高K-12教师的能力将有助于增加追求STEM职业的代表性不足的学生人数,以及扩大STEM劳动力和提高一般科学素养。
英文摘要
Pedagogical content knowledge (PCK) is a critical conceptual tool for distinguishing effective from ineffective teaching, but difficulty measuring it has resulted in minimal application of the concept to enhance actual teaching practice. This project will apply computerized lexical analysis techniques to develop an efficient, valid and reliable measure of science teacher PCK - the type of teacher knowledge that bridges content knowledge and how to effectively teach the content in classrooms. This project will transform an instrument used in multiple NSF STEM projects, but which is limited by being time and resource intensive to score. Application of recent developments in lexical analysis will allow measurement of PCK to be taken to scale with rapid feedback, and will be a vital resource for STEM researchers, evaluators, PD providers, teacher educators, and teachers themselves. This collaborative research project brings together two teams with unique yet complementary expertise. BSCS researchers have experience measuring PCK in multiple federal projects, and recently led an international summit on STEM PCK. The Michigan State University Automated Analysis of Constructed Response research group is working across STEM disciplines to refine approaches to using lexical analysis for formative educational purposes. Broader impacts of this project include developing a measure that will be invaluable to multiple stakeholders in evaluating and enhancing the understandings and abilities of K-12 science teachers. Enhancing the capacity of K-12 teachers will help increase the numbers of underrepresented students who pursue STEM careers, as well as expand the STEM workforce and increase general scientific literacy.
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依托单位:
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