探索教育心理学中的认知行为:对可靠性和有效性措施的严格分析》。

IF 2.5 4区 医学 Q3 BIOCHEMICAL RESEARCH METHODS
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引用次数: 0

摘要

本研究旨在验证教育心理学量表的信度和效度,采用文献资料法、访谈法、问卷调查法和数理统计法等方法对其进行了探讨。研究对象为地方本科院校本科生的教育心理数据,通过量表对数据进行收集和分析。结果显示,教育心理量表包含自我效能感、学习动机、希望特质、心理弹性、生理自尊和情绪管理六个维度,共27个项目。量表的抽样适宜度 kmo 为 0.800。总量表中六个维度的负荷在 0.58 至 0.73 之间。结构模型各项目拟合系数在 0.45-0.73 之间,各维度与总量表的相关系数在 0.24-0.52 之间。量表的克朗巴赫 α 系数为 0.83,重测信度为 0.90。量表的内容效度介于 0.554 和 0.775 之间。该量表具有良好的信度和效度,可用于评价本科生的教育心理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploring cognitive behavioral aspects in educational psychology: A rigorous analysis of reliability and validity measures

The purpose of this study is to verify the reliability and effectiveness of an educational psychology scale, which is explored by using the methods of literature, interview, questionnaire survey and mathematical statistics. The research object is the education psychology data of undergraduate students in local undergraduate colleges and universities.The data are collected and analyzed through the scale. The results show that the educational psychology scale contains six dimensions, including self-efficacy, learning motivation, hope trait, psychological resilience, physical self-esteem and emotional management, with a total of 27 items. The kmo sampling appropriateness of the scale is 0.800. The load of six dimensions in the total amount table is between 0.58 and 0.73. The fitting coefficient of each item of the structural model is between 0.45–0.73, and the correlation between each dimension and the total table is between 0.24–0.52. Scale cronbach's α The coefficient was 0.83 and the test-retest reliability was 0.90. The content validity of the scale ranged from 0.554 to 0.775. The scale has good reliability and validity, and can be used to evaluate undergraduate students' educational psychology.

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来源期刊
SLAS Technology
SLAS Technology Computer Science-Computer Science Applications
CiteScore
6.30
自引率
7.40%
发文量
47
审稿时长
106 days
期刊介绍: SLAS Technology emphasizes scientific and technical advances that enable and improve life sciences research and development; drug-delivery; diagnostics; biomedical and molecular imaging; and personalized and precision medicine. This includes high-throughput and other laboratory automation technologies; micro/nanotechnologies; analytical, separation and quantitative techniques; synthetic chemistry and biology; informatics (data analysis, statistics, bio, genomic and chemoinformatics); and more.
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