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相关概念视频

Design Consideration01:22

Design Consideration

531
Designing a structure involves a series of considerations, primarily the material's ultimate strength, calculated through tests that measure changes under increased force until the material reaches its breaking point or limit. The ultimate load, where the material breaks, is divided by its original cross-sectional area, resulting in the ultimate normal stress or strength. The ultimate shearing stress is another significant factor taken into account.
The factor of safety is another key...
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Scaling01:26

Scaling

545
In designing and analyzing filters, resonant circuits, or circuit analysis at large, working with standard element values like 1 ohm, 1 henry, or 1 farad can be convenient before scaling these values to more realistic figures. This approach is widely utilized by not employing realistic element values in numerous examples and problems; it simplifies mastering circuit analysis through convenient component values. The complexity of calculations is thereby reduced, with the understanding that...
545
Self-Report Tests of Personality01:22

Self-Report Tests of Personality

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Self-report inventories are objective personality assessments that use multiple-choice items or numbered scales, typically ranging from 1 (strongly disagree) to 5 (strongly agree). They are often called Likert scales after Rensis Likert. These inventories are widely used due to their ease of administration and cost-effectiveness. One of the most prominent examples is the Minnesota Multiphasic Personality Inventory (MMPI), initially developed in the 1940s to assess abnormal personality traits.
752
Ordinal Level of Measurement00:55

Ordinal Level of Measurement

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The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks...
31.9K
Surveys02:16

Surveys

16.6K
Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
16.6K
Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

278
Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
278

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相关实验视频

Updated: Jan 12, 2026

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
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利克特尺度:设计,建造和使用的实用指南.

Pere J Ferrando1, Fabia Morales-Vives1, José M Casas1

  • 1Universitat Rovira i Virgili, Departament de Psicologia, Research Center for Behavior Assessment (Spain).

Psicothema
|November 4, 2025
PubMed
概括

本研究回顾了利克特类型的尺度,确定了其构建和应用的改进关键领域. 它提出了实际指导方针,以优化在研究中使用这些广泛应用的评估工具.

科学领域:

  • 心理测量 心理测量 心理测量
  • 调查方法 调查方法
  • 统计分析 统计分析

背景情况:

  • 1932年开发的利克特类型秤是各种科学和专业领域广泛使用的评估工具.
  • 它们的简单性和有效性导致了广泛采用.
  • 然而,它们的最佳构建,分析和应用需要进行批判性审查.

研究的目的:

  • 批判性地审查目前使用利克特类型秤的情况.
  • 为优化利克特尺度的设计,分析和应用提出实际指导方针.
  • 提高使用这些尺度收集的数据的可靠性和有效性.

主要方法:

  • 进行了系统的文献审查.
  • 审查的重点是关于利克特尺度的开发,分析,评分,使用和解释的现有指南.
  • 这种方法综合了当前的最佳实践,并确定了需要改进的领域.

主要成果:

  • 确定了提高利克特尺度构建和使用的关键领域.
  • 关键领域包括构造的操作定义,项目制定和响应类别选择.
  • 在响应分析,有效性证据收集,项目校准和分数解释方面也需要改进.

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结论:

  • 提出了一份实用指南,其中包含15个建议.
  • 十项建议重点关注利克特尺度的适当设计,构建和分析.
  • 五个建议指导研究人员和从业人员适当使用先前存在的利克特等级.