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)是区分有效和无效教学的重要概念工具,但测量它的难度导致了这一概念在提高实际教学实践中的最小应用。这个项目将应用计算机词汇分析技术来开发一种有效、有效和可靠的科学教师PCK衡量标准--连接教学知识和如何在课堂上有效教授内容的教师知识类型。这个项目将改变一个在多个NSF STEM项目中使用的工具,但这是有限的时间和资源密集型得分。词汇分析的最新发展应用将使PCK的测量具有快速反馈的规模,并将成为STEM研究人员、评价者、PD提供者、教师教育工作者和教师自身的重要资源。这一合作研究项目将两个拥有独特但互补专业知识的团队聚集在一起。BSCS研究人员有在多个联邦项目中测量PCK的经验,最近领导了一次关于STEM PCK的国际峰会。密歇根州立大学构建反应的自动化分析研究小组正在跨STEM学科努力改进将词汇分析用于形成性教育目的的方法。该项目的更广泛影响包括制定一项措施,该措施将在评估和提高K-12科学教师的理解和能力方面对多个利益攸关方具有无价的价值。加强K-12教师的能力将有助于增加从事STEM职业的人数不足的学生的数量,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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