User Experience Evaluation
User Experience Evaluation - Related Videos
01:28
Users of Accounting Data
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2025
Accounting data is vital for various stakeholders who rely on financial information for decision-making. These users can be classified into internal and external users.Internal UsersBusiness owners and executives use accounting data to assess profitability, manage operational costs, and guide strategic decision-making. For instance, the Chief Executive Officer (CEO) may analyze income statements to determine the feasibility of launching a new product line. Human resources departments also rely...
01:27
Internal and External Users
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2024
Financial information is used by different groups of people, both inside and outside an organization. Internal users are people within the organization, like managers, employees, and executives. They use financial data to make decisions about how to run the business. For example, department managers look at budget reports to make sure their departments are staying within financial limits and using resources efficiently. Internal auditors check financial data to make sure everything is accurate...
10:56
A User-friendly and Powerful R Analysis of Large-scale Datasets
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2025
This report describes a method involving an R script in the open-source software RStudio to analyze large-scale datasets obtained from time series experiments.
06:58
The Factorial Experiment
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2023
Source: Laboratories of Gary Lewandowski, Dave Strohmetz, and Natalie Ciarocco—Monmouth University A factorial design is a common type of experiment where there are two or more independent variables. This video demonstrates a 2 x 2 factorial design used to explore how self-awareness and self-esteem may influence the ability to decipher nonverbal signals. This video leads students through the basics of a factorial design including, the nature of a factorial design and what distinguishes it from...
07:35
The Multi-group Experiment
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2023
Source: Laboratories of Gary Lewandowski, Dave Strohmetz, and Natalie Ciarocco—Monmouth University A multi-group design is an experimental design that has 3 or more conditions/groups of the same independent variable. This video demonstrates a multi-group experiment that examines how different interethnic ideologies (multiculturalism and color-blind) influence feelings about diversity and actions toward and out-group member. In providing an overview of how a researcher conducts a multi-group...
FAQs
Representative users perform clinical tasks while researchers observe their interactions with the technology. This approach can expose navigation problems, unclear information, workflow barriers, and potential safety risks that may not be apparent during development. Including the people expected to use a system helps evaluation findings reflect practical patient and healthcare professional needs before implementation.
The assessment can examine usability, accessibility, efficiency, and overall satisfaction. Usability indicates whether people can interact with the system effectively, while accessibility addresses whether the design meets varied user needs. Efficiency concerns how well the system supports tasks, and satisfaction captures users’ perceptions. Together, these dimensions provide a broader view than task completion alone.
Each method gathers a different type of information. Usability testing shows how representative users handle clinical tasks, while interviews and questionnaires collect their reported feedback, perceptions, and satisfaction. Heuristic review examines the system against usability considerations. Using these approaches can reveal both observable interaction problems and concerns users may describe directly.
A typical evaluation begins by selecting representative users and relevant clinical tasks. Researchers then observe interactions with the health technology and collect feedback through interviews, questionnaires, usability testing, or heuristic review. They analyze findings for navigation problems, unclear information, workflow barriers, and safety risks. Results can guide improvements before the system reaches wider implementation.
The approach applies to electronic health records, mobile health applications, diagnostic tools, and patient portals. In each case, evaluation can identify whether the technology supports the intended interactions and fits users’ needs. Examining these systems before implementation helps developers address design problems that could otherwise reduce acceptance or interfere with clinical and patient workflows.
Medical technologies must align with the needs of both patients and healthcare professionals. Evaluating their experiences can uncover barriers that affect navigation, information clarity, workflow, or perceived safety. Addressing these findings supports more effective design and can improve acceptance of the technology, making the resulting system better suited to its intended medical setting.