克朗巴赫阿尔法
持久性(不连续性)
验证性因素分析
心理学
度量(数据仓库)
测量数据收集
回归分析
数据科学
心理测量学
计算机科学
临床心理学
结构方程建模
统计
数学
数据挖掘
工程类
机器学习
岩土工程
作者
David I. Hanauer,Mark Graham,Graham F. Hatfull
标识
DOI:10.1187/cbe.15-09-0185
摘要
Curricular changes that promote undergraduate persistence in science, technology, engineering, and mathematics (STEM) disciplines are likely associated with particular student psychological outcomes, and tools are needed that effectively assess these developments. Here, we describe the theoretical basis, psychometric properties, and predictive abilities of the Persistence in the Sciences (PITS) assessment survey designed to measure these in course-based research experiences (CREs). The survey is constructed from existing psychological assessment instruments, incorporating a six-factor structure consisting of project ownership (emotion and content), self-efficacy, science identity, scientific community values, and networking, and is supported by a partial confirmatory factor analysis. The survey has strong internal consistency (Cronbach's alpha: α = 0.96) and was validated using standard simple and multiple regression analyses. The regression analyses demonstrated that the factors of the PITS survey were significant predictors of the intent to become a research scientist and, as such, potentially valid for the measurement of persistence in the sciences. The PITS survey provides an effective method for measuring the psychological outcomes of undergraduate research experiences relevant to persistence in STEM and offers an approach to the development and validation of more sophisticated assessment tools that recognize the specificities of the type of educational opportunities embedded in a CRE.
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