利克特量表
比例(比率)
心理学
数学教育
多元方法论
定性研究
教师教育
半结构化面试
编码(社会科学)
定性性质
医学教育
教育学
计算机科学
医学
发展心理学
物理
量子力学
社会科学
统计
数学
机器学习
社会学
作者
Jianlan Wang,Yuanhua Wang,Shahin Shawn Kashef
标识
DOI:10.1080/09500693.2024.2439141
摘要
In pre-service teacher (PST) education, developing effective instructional practices like questioning is a crucial learning objective. Assessing PSTs' questioning competencies is essential, yet traditional qualitative methods (e.g., discourse analysis) limit large-scale analysis within PST preparation programs. Previously, we addressed this challenge by designing and validating instruments, including a video-coding scheme and free-response questions, to assess novice teachers' competencies in asking effective guiding questions to address student difficulties. We established a link between their questioning practices and performance on free-response questions. Building upon these efforts, this study aims to further enhance assessment efficiency by transforming pre-validated free-response questions into Likert-scale questions. In this approach, respondents rate provided options that represent various levels of questioning competencies, rather than providing their answers. Over two semesters, we administered Likert-scale questions to more than 100 PSTs each term to evaluate the feasibility and validity of this method. We identified five categories of options for Likert-scale questions and developed empirical equations to derive Pedagogical Content Knowledge in Questioning (PCK-Q) from the collected ratings. The findings support the use of Likert-scale questions as a promising tool for large-scale assessment of PCK-Q in PST education. We also discussed the application of Likert-scale questions in PST preparation.
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