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Related Concept Videos

Data Collection by Survey01:07

Data Collection by Survey

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...
Nursing Evaluation01:15

Nursing Evaluation

The evaluation stage signals the end of the nursing process. The nurse gathers evaluative data to assess whether or not the patient has attained the expected results. Whereas the nurse collects data in the nursing assessment to identify the patient's health concerns, the evaluation stage data determines if the indicated health issues are resolved. Evaluative data collection includes two sections: the data acquired to evaluate patient outcomes and the time criteria for data collection.
Section...
Group Design02:01

Group Design

The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between the two are due to...
Data Validation01:03

Data Validation

Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs01:15

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs

Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...
Case Studies01:22

Case Studies

There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it.

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Related Experiment Video

Updated: May 12, 2026

Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios
06:02

Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios

Published on: October 6, 2020

Design and evaluation: end users, user datasets and personas.

Russell Marshall1, Sharon Cook1, Val Mitchell1

  • 1Loughborough Design School, Loughborough University, United Kingdom.

Applied Ergonomics
|April 13, 2013
PubMed
Summary

Personas, archetypal user models from research, help designers understand user needs efficiently. Data-rich personas, unlike assumption-based ones, offer superior insights in product design, including inclusive design applications.

Keywords:
Inclusive designPersonasUser-datasets

Related Experiment Videos

Last Updated: May 12, 2026

Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios
06:02

Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios

Published on: October 6, 2020

Area of Science:

  • Human-Computer Interaction
  • Product Design
  • User Research

Background:

  • Understanding user needs is crucial but challenging in product design.
  • Traditional methods like ethnographic studies are time-consuming and costly.
  • Design consultancies face time pressures limiting the use of in-depth research.

Purpose of the Study:

  • To discuss the utility of 'personas' as a method to address challenges in user research for product design.
  • To explore the application of personas in automotive design and inclusive design.
  • To highlight the advantages of data-rich personas over assumption-based personas.

Main Methods:

  • Literature review and discussion on the concept and application of personas.
  • Case study analysis of personas in car design.
  • Case study analysis of personas in inclusive design using the HADRIAN system.

Main Results:

  • Personas, as descriptive models of archetypal users, can streamline the understanding of user needs.
  • Data-rich personas, grounded in user research, provide more valuable insights than assumption-based personas.
  • The application of personas is demonstrated effectively in both automotive and inclusive design contexts.

Conclusions:

  • Personas offer a practical solution to the difficulties of incorporating user understanding into the design process.
  • The effectiveness of personas is significantly enhanced when they are data-rich and derived from thorough user research.
  • Personas are a valuable tool for designers, particularly in fields requiring deep user empathy like inclusive design.