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Related Concept Videos

Surveys02:16

Surveys

16.2K
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.
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Types of Surveys01:27

Types of Surveys

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Surveys are essential for marking property boundaries near water bodies. Different types of surveys are defined, each with its own function. Land surveys mark the property boundaries, while route surveys determine the position of properties on nearby highways. Topographic surveys create maps by capturing the three-dimensional features of the land. Hydrographic surveys focus on the shapes of underwater areas and the movement of streams through the properties. Mine surveys determine the relative...
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Data Collection by Survey01:07

Data Collection by Survey

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The systematic method of obtaining and analyzing accurate information of a population is called data collection. A survey is a standard method of data collection that involves collecting information from a target human population about their experience, opinion, or knowledge of a product, service, or process. The responses are recorded and interpreted. The most common survey examples are written questionnaires, face-to-face or telephonic conversations, focus groups, and electronic (e-mail or...
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Nursing Process for Patient and Caregiver Teaching III: Evaluation and Documentation01:20

Nursing Process for Patient and Caregiver Teaching III: Evaluation and Documentation

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Evaluation of the teaching process enables the nurse to determine if the patient's learning needs were met and if training was effective. If the expected outcomes are not met, the care plan is revised, and additional education or reinforcement is provided. Nurses can ask questions after the session or obtain feedback to assess the patient's understanding of the topic.
Nurses can use several methods to evaluate patient outcomes. For example, oral questions can assess cognitive learning,...
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Survey Safety01:28

Survey Safety

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Surveying near highways, rough terrain, or power lines involves significant risks. Working along highways is particularly dangerous and requires the use of warning signs and flagmen. It is safest to avoid working directly on roads and use offsets whenever possible. When highway work is unavoidable, it must follow all safety guidelines. Surveyors should wear bright clothing, such as orange reflective vests, to ensure visibility to motorists, coworkers, and hunters. In construction zones, wearing...
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Study Design in Statistics01:15

Study Design in Statistics

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A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research problem. Statistics is commonly for effective study design and more robust experiments,
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
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Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques
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A Survey on Curriculum Learning.

Xin Wang, Yudong Chen, Wenwu Zhu

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    |March 31, 2021
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    Summary
    This summary is machine-generated.

    Curriculum learning (CL) trains machine learning models using a staged approach, starting with easier data and progressing to harder data. This survey reviews CL strategies, their applications, and future research directions.

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    Area of Science:

    • Machine Learning
    • Artificial Intelligence
    • Computer Science

    Background:

    • Curriculum learning (CL) is a training strategy that mimics human learning by starting with easier data and progressing to more complex data.
    • CL has proven effective in enhancing generalization and convergence rates for models in computer vision and natural language processing.

    Purpose of the Study:

    • This survey provides a comprehensive review of curriculum learning.
    • It covers motivations, definitions, theories, applications, and design methodologies for both manual and automatic curricula.

    Main Methods:

    • The review categorizes automatic CL methodologies into Self-paced Learning, Transfer Teacher, RL Teacher, and Other Automatic CL.
    • It summarizes existing CL designs within a Difficulty Measurer + Training Scheduler framework.

    Main Results:

    • The article analyzes principles for selecting appropriate CL designs for practical applications.
    • It explores the connections between CL and other machine learning concepts like transfer learning, meta-learning, continual learning, and active learning.

    Conclusions:

    • The survey identifies current challenges in curriculum learning and suggests potential future research directions.
    • It offers insights into the effective application and integration of CL strategies.