field study in ux research

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UX Research Field Study: A Complete Guide

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Understanding users’ needs, preferences, and pain points has never been more crucial for businesses aiming to create successful and impactful products and services. UX research, includes user interviews , usability testing , persona creation , data analysis , and the integration of emerging technologies.

As technology continues to advance, so does the complexity of users’ needs and expectations, making it essential to adapt and refine our research methodologies to meet these demands effectively. In this article, we’ll have a look at a complete guide to understand and get the latest insights, methodologies, and best practices in the field of UX research. 

What is UX Research?

The goal of UX (User Experience) research is to understand users’ behaviors, wants, and preferences when dealing with goods, services, or digital interfaces . It is a systematic and multidisciplinary approach. By providing information to the design and development process, its main objective is to enhance the overall user experience.

UX researchers learn important information about users , including their motivations, problems , and objectives, through a combination of qualitative and quantitative methodologies. User interviews, surveys, usability testing, card sorting, and data analysis are a few of these techniques.

After a quick understanding of What UX research is , let’s now move toward understanding what is user research and user observation. 

User Research & User Observation 

Both user research and user observation are separate concepts, which are carried out based on the context of the problem designer or researchers are trying to solve.

1. User Research: Understanding Users for Better Design

A key component of the user experience design process is user research, which focuses on learning about the needs, wants, and preferences of the target audience. It entails gathering information using a range of qualitative and quantitative techniques to guide the creation of products, services, or digital user interfaces.

Methods of User Research:

• User Interviews: Conducting one-on-one interviews with users helps researchers gain in-depth insights into their thoughts, motivations, and pain points. It allows for a personalized understanding of individual experiences and preferences.
• Surveys and Questionnaires: Surveys are useful for collecting data from a large number of users quickly. They provide quantitative data that can reveal trends and patterns.
• Usability Testing: This involves observing users as they interact with a prototype or an existing product. Researchers can identify usability issues and areas for improvement based on users’ actions and feedback.
• Persona Creation: Personas are fictional representations of target users based on research data. They help designers and developers better empathize with users and make informed decisions.
• Card Sorting: Card sorting is a method where users categorize information or features to help designers understand how users mentally organize content.
• Data Analysis: Analyzing the collected data helps researchers identify patterns, trends, and key insights that inform design decisions.

2. User Observation: Observing Users to know how they perform a certain action

A qualitative research technique called “ user observation ” allows researchers to watch users as they engage with a product or service in real time. In contrast to surveys and interviews, which rely on self-reported information, observation offers more unbiased and behavior-based insights. 

Key Aspects of User Observation:

• Natural Context: Observing users in their natural environment provides a better understanding of their real-world interactions and challenges.
• Behaviour Patterns: Observations reveal patterns in user behavior, highlighting pain points, difficulties, and moments of delight.
• Non-Verbal Cues: Users may not always articulate their experiences accurately, but non-verbal cues like facial expressions and body language can offer valuable clues.
• User Empathy: Directly observing users fosters empathy, helping designers connect with users on a deeper level.
• Real-Time Feedback: Observations provide immediate feedback, allowing designers to make quick adjustments and iterate designs rapidly.

In order to produce products and services that actually resonate with users, increase satisfaction, and promote economic success, user research and observation are essential parts of the UX design process.

Data Gathering Method in UX Research

In order to obtain important data regarding users’ behaviors, preferences, and experiences, data gathering methods in UX research use a variety of methodologies and approaches. By using these techniques, researchers can develop user-centric designs by gaining insights into the wants, problems, and motivations of users. 

There are 3 dimensions of data gathering methods, using which designer or researchers conduct research sessions. 

• Direct & Indirect data gathering methods
• Individual & Group data gathering methods
• Performance & Discussion data gathering methods

Let’s have a detailed look at each of the dimensions of data gathering methods.

1. Direct & Indirect Data Gathering Methods

The two primary categories of data collection techniques used in UX research are direct and indirect techniques. Both strategies have different goals and provide distinctive insights on user actions and experiences. Let’s examine each in more depth:

Direct Data Gathering Methods:

• User Interviews: User interviews are one of the most popular direct approaches and involve in-person or virtual encounters with people. To acquire a thorough understanding of consumers’ thoughts, feelings, motives, and pain spots, researchers pose open-ended questions.
• Usability Testing: Usability testing involves watching actual consumers as they engage with a product or prototype. Researchers can spot usability problems, examine navigational patterns, and gather user experience input.
• Focus Groups: Focus groups involve gathering a small group of users to talk about particular subjects or ideas connected to a product. The dynamics of the group can encourage conversation and idea creation while offering insightful information about shared viewpoints and group dynamics. 
• Field Studies and Contextual Inquiry: Field studies entail monitoring people while they utilize a product or service in their natural contexts. This approach gives users context from the real world and reveals user behaviors that may not be seen in a controlled lab environment.

Indirect Data Gathering Methods:

• Surveys and Questionnaires: One of the popular indirect methods for gathering information from a bigger population of people. Surveys are important for determining user demographics, sentiments, and preferences.
• Analytics and Clickstream Analysis: Examining a website’s or an app’s analytics can provide you hints about how users behave by measuring things like time spent on a page, click-through rates , and conversion rates .
• A/B Testing: Following conversations and emotions about a product or brand on social media can provide indirect feedback from a larger audience. The public’s impressions and user sentiment can be better understood with this strategy.
• Social Media Listening: Comparing two or more iterations of a design to see which performs better is known as A/B testing. Researchers can decide on design changes using data-driven decisions by gathering information on user interactions with various versions.
• Heat-maps and Eye Tracking: These tools provide us a hazy understanding of how users interact with our products and what they are paying attention to. Eye tracking shows where users’ attention is focused on a screen, whereas heat maps show areas of strong user interaction.

Both direct and indirect data collection techniques have advantages and disadvantages. Direct techniques may take more time and only work with a smaller number of users, but they offer deep qualitative insights and a greater knowledge of user emotions and motives. On the other hand, indirect methods enable data collecting from a bigger audience and provide quantifiable data, but they could not provide the same level of knowledge as direct contacts.

2. Individual & Group Data Gathering Methods

Based on the number of participants, data collection techniques can be divided into two broad categories: individual and group data collection techniques. Each strategy has unique benefits and is appropriate for various research goals. Let’s examine each type in greater detail:

2.1. Individual Data Gathering Methods

Focuses on Depth of insights, Privacy and Personalisation.

Note: Individual methods might not capture the influence of group dynamics on user behavior.

• Diary Studies: In a diary study, participants maintain a journal or diary detailing their interactions with a good or service over time. This longitudinal approach offers deep insights into the experiences and behaviors of people in everyday life.
• Contextual Inquiry: Contextual inquiry entails observing and speaking with specific users while they carry out specific tasks associated with a product or service in their natural surroundings.

2.2. Group Data Gathering Methods

Focuses on Efficiency, Interaction insights and Stimulating Discussion. 

Note: Due to the dynamics of the group, some members may dominate conversations while others sit back and listen.

• Workshops and Design Sprints: During workshops and design sprints, participants collaborate to brainstorm, rank features, or give input on design concepts.
• Card Sorting (Group-Based): Group-based card sorting entails several individuals cooperating to classify data or qualities, offering insights into societal mental models and organizational preferences.
• Online Discussion Forums and Communities: Online forums and communities allow researchers to gather insights from a larger group of users asynchronously. Participants can share experiences, discuss ideas, and provide feedback at their convenience.

It would be right to say that both individual and group data collection techniques are essential because they provide distinctive insights into user experiences and preferences.

3. Performance & Discussion Data Gathering Methods

3.1. performance data gathering methods.

Focus on observing users’ actions and interactions to measure their task success, efficiency, and effectiveness. These methods provide quantitative data, allowing researchers to identify usability issues and assess the overall performance of a product or interface. 

Note: Performance data might not reveal the “why” behind users’ actions, requiring additional discussion data to gain a comprehensive understanding.

• Usability Testing
• Clickstream Analysis
• Eye Tracking
• Analytics and Heatmaps
• Objective Metrics: Performance data offers objective metrics to evaluate product usability and efficiency.
• Identifying Usability Issues: Performance data helps identify pain points and areas for improvement in the user experience.
• Data-driven Design Decisions: Quantitative data supports data-driven design decisions and can be useful for justifying design changes to stakeholders.

3.2. Discussion Data Gathering Methods

Focus on gathering qualitative data through interactions and discussions with users. These methods provide insights into users’ opinions, perceptions, and subjective experiences, offering a deeper understanding of their motivations and preferences. 

Note: Social desirability bias, where participants may give responses they think researchers want to hear, can have an impact on discussion data.

• User Interviews
• Focus Groups
• Online Discussion Forums and Surveys
• Contextual Inquiry
• User Perspectives: Discussion data provides rich qualitative insights into users’ perspectives, motivations, and emotional responses.
• Understanding Context: Discussion methods offer contextual information and provide a deeper understanding of user needs in real-life settings.
• Ideation and Innovation: Focus groups and discussions foster idea generation and encourage participants to suggest innovative solutions.

It is always a great idea to combine both quantitative performance data and qualitative discussion data to lead to a more comprehensive and informed understanding of users and their interactions with products and services.

Must Check: UX Design Process: A Complete Guide UX Design | Key Process, Flow and Principles 7 Tips to Create an Impressive UX Design

In this detailed article we explored what field studies are, the diverse data gathering techniques employed. We also had a look at the ethical considerations in conducting field studies, ensuring that users’ privacy and consent are respected throughout the research process. Field studies help researchers to find unexpected insights and validate assumptions by stepping outside of the boundaries of controlled lab settings, paving the way for user-centric design decisions. Field studies provide the rich qualitative data that supports the quantitative results from conventional usability testing, whether it be through anthropological observations, contextual queries, or user shadowing. In the end I hope this article serves the purpose as a complete guide to field study for beginners. 

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The Complete Guide to UX Research Methods

UX research provides invaluable insight into product users and what they need and value. Not only will research reduce the risk of a miscalculated guess, it will uncover new opportunities for innovation.

By Miklos Philips

Miklos is a UX designer, product design strategist, author, and speaker with more than 18 years of experience in the design field.

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“Empathy is at the heart of design. Without the understanding of what others see, feel, and experience, design is a pointless task.” —Tim Brown, CEO of the innovation and design firm IDEO

User experience (UX) design is the process of designing products that are useful, easy to use, and a pleasure to engage. It’s about enhancing the entire experience people have while interacting with a product and making sure they find value, satisfaction, and delight. If a mountain peak represents that goal, employing various types of UX research is the path UX designers use to get to the top of the mountain.

User experience research is one of the most misunderstood yet critical steps in UX design. Sometimes treated as an afterthought or an unaffordable luxury, UX research, and user testing should inform every design decision.

Every product, service, or user interface designers create in the safety and comfort of their workplaces has to survive and prosper in the real world. Countless people will engage our creations in an unpredictable environment over which designers have no control. UX research is the key to grounding ideas in reality and improving the odds of success, but research can be a scary word. It may sound like money we don’t have, time we can’t spare, and expertise we have to seek.

In order to do UX research effectively—to get a clear picture of what users think and why they do what they do—e.g., to “walk a mile in the user’s shoes” as a favorite UX maxim goes, it is essential that user experience designers and product teams conduct user research often and regularly. Contingent upon time, resources, and budget, the deeper they can dive the better.

What Is UX Research?

There is a long, comprehensive list of UX design research methods employed by user researchers , but at its center is the user and how they think and behave —their needs and motivations. Typically, UX research does this through observation techniques, task analysis, and other feedback methodologies.

There are two main types of user research: quantitative (statistics: can be calculated and computed; focuses on numbers and mathematical calculations) and qualitative (insights: concerned with descriptions, which can be observed but cannot be computed).

Quantitative research is primarily exploratory research and is used to quantify the problem by way of generating numerical data or data that can be transformed into usable statistics. Some common data collection methods include various forms of surveys – online surveys , paper surveys , mobile surveys and kiosk surveys , longitudinal studies, website interceptors, online polls, and systematic observations.

This user research method may also include analytics, such as Google Analytics .

Google Analytics is part of a suite of interconnected tools that help interpret data on your site’s visitors including Data Studio , a powerful data-visualization tool, and Google Optimize, for running and analyzing dynamic A/B testing.

Quantitative data from analytics platforms should ideally be balanced with qualitative insights gathered from other UX testing methods , such as focus groups or usability testing. The analytical data will show patterns that may be useful for deciding what assumptions to test further.

Qualitative user research is a direct assessment of behavior based on observation. It’s about understanding people’s beliefs and practices on their terms. It can involve several different methods including contextual observation, ethnographic studies, interviews, field studies, and moderated usability tests.

Jakob Nielsen of the Nielsen Norman Group feels that in the case of UX research, it is better to emphasize insights (qualitative research) and that although quant has some advantages, qualitative research breaks down complicated information so it’s easy to understand, and overall delivers better results more cost effectively—in other words, it is much cheaper to find and fix problems during the design phase before you start to build. Often the most important information is not quantifiable, and he goes on to suggest that “quantitative studies are often too narrow to be useful and are sometimes directly misleading.”

Not everything that can be counted counts, and not everything that counts can be counted. William Bruce Cameron

Design research is not typical of traditional science with ethnography being its closest equivalent—effective usability is contextual and depends on a broad understanding of human behavior if it is going to work.

Nevertheless, the types of user research you can or should perform will depend on the type of site, system or app you are developing, your timeline, and your environment.

Top UX Research Methods and When to Use Them

Here are some examples of the types of user research performed at each phase of a project.

Card Sorting : Allows users to group and sort a site’s information into a logical structure that will typically drive navigation and the site’s information architecture. This helps ensure that the site structure matches the way users think.

Contextual Interviews : Enables the observation of users in their natural environment, giving you a better understanding of the way users work.

First Click Testing : A testing method focused on navigation, which can be performed on a functioning website, a prototype, or a wireframe.

Focus Groups : Moderated discussion with a group of users, allowing insight into user attitudes, ideas, and desires.

Heuristic Evaluation/Expert Review : A group of usability experts evaluating a website against a list of established guidelines .

Interviews : One-on-one discussions with users show how a particular user works. They enable you to get detailed information about a user’s attitudes, desires, and experiences.

Parallel Design : A design methodology that involves several designers pursuing the same effort simultaneously but independently, with the intention to combine the best aspects of each for the ultimate solution.

Personas : The creation of a representative user based on available data and user interviews. Though the personal details of the persona may be fictional, the information used to create the user type is not.

Prototyping : Allows the design team to explore ideas before implementing them by creating a mock-up of the site. A prototype can range from a paper mock-up to interactive HTML pages.

Surveys : A series of questions asked to multiple users of your website that help you learn about the people who visit your site.

System Usability Scale (SUS) : SUS is a technology-independent ten-item scale for subjective evaluation of the usability.

Task Analysis : Involves learning about user goals, including what users want to do on your website, and helps you understand the tasks that users will perform on your site.

Usability Testing : Identifies user frustrations and problems with a site through one-on-one sessions where a “real-life” user performs tasks on the site being studied.

Use Cases : Provide a description of how users use a particular feature of your website. They provide a detailed look at how users interact with the site, including the steps users take to accomplish each task.

You can do user research at all stages or whatever stage you are in currently. However, the Nielsen Norman Group advises that most of it be done during the earlier phases when it will have the biggest impact. They also suggest it’s a good idea to save some of your budget for additional research that may become necessary (or helpful) later in the project.

Here is a diagram listing recommended options that can be done as a project moves through the design stages. The process will vary, and may only include a few things on the list during each phase. The most frequently used methods are shown in bold.

Reasons for Doing UX Research

Here are three great reasons for doing user research :

To create a product that is truly relevant to users

• If you don’t have a clear understanding of your users and their mental models, you have no way of knowing whether your design will be relevant. A design that is not relevant to its target audience will never be a success.

To create a product that is easy and pleasurable to use

• A favorite quote from Steve Jobs: “ If the user is having a problem, it’s our problem .” If your user experience is not optimal, chances are that people will move on to another product.

To have the return on investment (ROI) of user experience design validated and be able to show:

• An improvement in performance and credibility
• Increased exposure and sales—growth in customer base
• A reduced burden on resources—more efficient work processes

Aside from the reasons mentioned above, doing user research gives insight into which features to prioritize, and in general, helps develop clarity around a project.

What Results Can I Expect from UX Research?

In the words of Mike Kuniaysky, user research is “ the process of understanding the impact of design on an audience. ”

User research has been essential to the success of behemoths like USAA and Amazon ; Joe Gebbia, CEO of Airbnb is an enthusiastic proponent, testifying that its implementation helped turn things around for the company when it was floundering as an early startup.

Some of the results generated through UX research confirm that improving the usability of a site or app will:

• Increase conversion rates
• Increase sign-ups
• Increase NPS (net promoter score)
• Increase customer satisfaction
• Increase purchase rates
• Boost loyalty to the brand
• Reduce customer service calls

Additionally, and aside from benefiting the overall user experience, the integration of UX research into the development process can:

• Minimize development time
• Reduce production costs
• Uncover valuable insights about your audience
• Give an in-depth view into users’ mental models, pain points, and goals

User research is at the core of every exceptional user experience. As the name suggests, UX is subjective—the experience that a person goes through while using a product. Therefore, it is necessary to understand the needs and goals of potential users, the context, and their tasks which are unique for each product. By selecting appropriate UX research methods and applying them rigorously, designers can shape a product’s design and can come up with products that serve both customers and businesses more effectively.

Further Reading on the Toptal Blog:

• How to Conduct Effective UX Research: A Guide
• The Value of User Research
• UX Research Methods and the Path to User Empathy
• Design Talks: Research in Action with UX Researcher Caitria O'Neill
• Swipe Right: 3 Ways to Boost Safety in Dating App Design
• How to Avoid 5 Types of Cognitive Bias in User Research

Understanding the basics

How do you do user research in ux.

UX research includes two main types: quantitative (statistical data) and qualitative (insights that can be observed but not computed), done through observation techniques, task analysis, and other feedback methodologies. The UX research methods used depend on the type of site, system, or app being developed.

What are UX methods?

There is a long list of methods employed by user research, but at its center is the user and how they think, behave—their needs and motivations. Typically, UX research does this through observation techniques, task analysis, and other UX methodologies.

What is the best research methodology for user experience design?

The type of UX methodology depends on the type of site, system or app being developed, its timeline, and environment. There are 2 main types: quantitative (statistics) and qualitative (insights).

What does a UX researcher do?

A user researcher removes the need for false assumptions and guesswork by using observation techniques, task analysis, and other feedback methodologies to understand a user’s motivation, behavior, and needs.

Why is UX research important?

UX research will help create a product that is relevant to users and is easy and pleasurable to use while boosting a product’s ROI. Aside from these reasons, user research gives insight into which features to prioritize, and in general, helps develop clarity around a project.

• UserResearch

Miklos Philips

London, United Kingdom

Member since May 20, 2016

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What is UX Research: The Ultimate Guide for UX Researchers

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User experience research is a crucial component of the human-centered design process and an essential part of creating solutions that meet user expectations and deliver value to customers. This comprehensive guide to UX research dives into the fundamentals of research and its various methods and includes tips and best practices from leading industry experts.

Make informed design decisions with user research

Validate ideas, test prototypes, assess usability, and deliver real, actionable insights to your product team.

UX research: Your ultimate guide to nailing user experience and exceeding expectation

User experience research, or UX research , is the process of gathering insights about users' behaviors, needs, and pain points through observation techniques and feedback methodologies. It’s a form of user research that looks at how users interact with your product, helping bridge the gaps between what you think users need, what users say they need—and what they actually need.

The goal of UX research is to understand your users and gain context and perspectives to help make informed decisions and build user-centered products. It’s an essential part of designing, developing, and launching a product that will be an instant hit—but it should also be used throughout the product’s lifecycle post-launch to keep updated, and ensure new features are relevant to your audience.

As Sinéad Davis Cochrane , UX Manager at Workday, explains: “UX research represents insights gathered directly from users and customers, that helps you make product decisions at every stage of the development process.”

Is UX research the same as user research?

The terms ‘user research’ and ‘UX research’ are often used interchangeably, but they do differ. User research is the parent of UX research; it’s a broader research effort that aims to understand the demographics, behaviors, and sentiments of your users and personas.

UX research, on the other hand, is a type of user research that’s specific to your product or platform. Where user research focuses on the user as a whole, UX research considers how they interact with, respond to, and feel about your product or concept itself.

In both cases, the overarching goal is to get to know your users, understand what they need from your product, gain context to help make informed decisions, and build human-centered experiences.

Involve your users at every stage of your design process

Create research projects with Maze using customizable templates, and start making data-informed product decisions

Why is conducting UX research important?

In an ideal world, users would find your product easy to navigate, your net promoter score (NPS) would be off the charts, and you’d see adoption and activation rates skyrocket. In reality, however, this can be a challenging dream to achieve—but it is possible. The only way to build a product that users really resonate with is by involving them throughout the development process and building with them.

UX research is more than just a single ‘step’ in the development process: it should happen continuously, throughout the product lifecycle—so whether you’re building new products or iterating on existing ones, every decision is informed by user insights.

Here’s what you can achieve with continuous UX research:

Make informed decisions based on data

Our 2023 Continuous Research Report shows that 74% of people who do research (PWDR) believe research is crucial to guiding product decisions. Plus, 60% of respondents find that user recommendations inspire new product ideas.

Getting stakeholder buy-in to product decisions can be challenging, but when you suggest changes based on UX research, you have data to back up your suggestions. Your users inform your product, becoming the decision-makers as well as the customer.

UX research helps reduce and mitigate the risk of building the wrong thing—or building the right thing in the wrong way.

Sinéad Davis Cochrane , UX Manager at Workday

Reduce bias in the UX design process

There are hundreds of cognitive biases identified by psychologists, many of which unknowingly influence our decisions and the products we build. But a key principle of great UX design is to put aside existing beliefs, and learn from your users.

“You have to be humble, optimistic, and open-minded,” says Bertrand Berlureau , Senior Product Designer at iMSA. Using effective UX research, you can root out bias or assumptions, and follow real human behavior to inform product decisions.

According to Sinéad, you should consider these questions early in the design process:

• “What are your assumptions?”
• “What are some of the assumptions you’ve been making about your end-users and product without any evidence?”
• “What are the anecdotes or coincidental pieces of information that you hold, and how can you challenge them?”

Biases can subconsciously affect research and UX design, and it can be tricky to identify them. The first step to overcoming cognitive biases is by being aware of them. Head to chapter three of our cognitive biases guide to discover how.

Test and validate concepts

The power of UX research is that it can prove you right or wrong—but either way, you’ll end up knowing more and creating a product that provides a better user experience. For Bertrand, an idea without a test is just an idea. So, before the design process, his team starts with these user research methods:

• Face-to-face and remote user interviews
• Focus groups
• Co-creativity sessions through design sprints, quick prototyping, and hypothesis concepts
• User testing

UX research is the only way to unequivocally confirm your product is solving the right problem, in the right way. By speaking directly to real users, you can pinpoint what ideas to focus on, then validate your proposed solution, before investing too much time or money into the wrong concept.

Work on solutions that bring real value to customers

Another main benefit of UX research is that it allows product teams to mitigate risk and come up with products users want to use. “One of the main risks we need to control is whether users actually want to use a solution we've implemented,” explains Luke Vella , Group Product Manager at Maze. “UX research helps us reduce this risk, allowing us to build solutions that our customers see as valuable and make sure that they know how to unlock that value.”

Luke works on pricing and packaging, an area that requires constant user research. On one hand, he and his team want to understand which problems their users are facing and come up with plans to satisfy those different needs. On the other hand, they need to make sure they can monetize in a sustainable way to further invest in the product. You can only get this perfect balance by speaking to users to inform each step of the decision.

Market your product internally and externally

UX research also plays a crucial role in helping product marketers understand the customer and effectively communicate a product's value to the market—after all, a product can only help those who know about it.

For example, Naomi Francis , Senior Product Marketing Manager at Maze, uses different research methods to inform marketing strategy. Naomi conducts user interviews to build personas, using user research to collect insights on messaging drafts, product naming, and running surveys to gather user feedback on beta products and onboarding.

Understanding how and why customers need and use our product pushes marketing launches to the next level—you can get a steer on everything from messaging to language and approach.

Naomi Francis , Senior Product Marketing Manager at Maze

Types of UX research

All UX research methods fit into broader UX research techniques that drive different goals, and provide different types of insight. You can skip to chapter seven for a rundown of the top 9 UX research methods , or keep reading for a deep dive on the main types of UX research:

• Moderated and unmoderated
• Remote and in-person
• Generate and evaluate
• Qualitative and quantitative
• Behavioral and attitudinal

Where moderated/unmoderated and remote/in-person refer to the way research is conducted , the other types of UX research reflect the type of data they gather.

The most powerful insights come from a mixture of testing types—e.g. attitudinal and behavioral, generative and evaluative, and quantitative and qualitative. You don’t need to run all types of research at all times, but you’ll benefit from gathering multiple types of data throughout different stages of product development.

Moderated research

Moderated research is any research conducted with a facilitator or researcher present. A moderator may observe research sessions and take notes, ask questions, or provide instruction to participants where needed.

Like all research, it’s crucial a moderator doesn’t overly guide participants or influence results. Due to certain types of cognitive biases , people may behave differently while being observed, so researchers often opt for unmoderated methods to avoid results being impacted.

UX research methods for moderated research

• User interviews to speak directly with your target user face-to-face
• Focus groups to gather feedback on a variety of topics
• Moderated usability testing to hear the thought process behind the actions

Unmoderated research

As the name suggests, unmoderated research refers to the lack of a moderator. Often used in tandem with remote research , users complete tasks independently, guided by pre-written instructions.

Unmoderated research is helpful to ensure users are acting entirely of their own volition, and it has a lower cost and quicker turnaround than moderated research—however it does require efficient planning and preparation, to ensure users can navigate the tasks unaided.

UX research methods for unmoderated research

• Unmoderated usability testing to see how easily users navigate your product
• Live website testing to witness users interacting with your product in real time
• Surveys to have users answer specific questions and rate design elements

Remote research

An incredibly flexible approach, remote research is often favored due to its time-to-results and cost savings. Remote research can be moderated or unmoderated, and is conducted using UX research tools which record user behavior, feedback, and screen recordings.

Another key benefit is its reach and accessibility—by moving research to a virtual platform, you can access users from anywhere in the world, and ensure research is inclusive of those with different abilities or requirements, who may otherwise be unable to take part in traditional in-person research.

UX research methods for remote research

• Usability testing to evaluate how accessible your product is
• Card sorting to understand how users categorize and group topics
• Concept testing to assess what ideas users are drawn to
• Wireframe or prototype testing to invite users to test a rough version of the design

In-person research

Research conducted in-person is typically more expensive, as it may require travel, accommodation, or equipment. Many traditionally in-person research methods can easily be performed remotely, so in-person research is often reserved for if there’s additional needs for accessibility, or if your product requires physical testing, safety considerations or supervision while being tested.

UX research methods for in-person research

• Guerrilla research to speak to random users and gather feedback
• User interviews to connect with users and read body language
• Field studies to gauge how your product fits into a real world environment

Generative research

Generative research provides a deep understanding of your target audience’s motivations, challenges, and behaviors. Broadly speaking, it pinpoints a problem statement, identifies the problem to be solved, and collects enough data to move forward.

It should happen before you even begin designing, as it helps you identify what to build, the types of problems your user is facing, and how you can solve them with your product or service.

UX research methods for generative research

• Field studies to get familiar with users in their authentic environment
• User interviews to ask open-ended questions about pain points
• Diary research to keep a log of users’ behaviors, activities, and beliefs over time
• Open card sorting to have users define and name their own categories

Evaluative research

Evaluative research focuses on evaluating a product or concept in order to collect data that will improve the solution. Evaluative research usually happens early on and is used in a continuous, iterative way throughout the design process and following launch. You can use this type of UX research to assess an idea, check navigation, or see if your prototype meets your user’s needs.

UX research methods for evaluative research

• Usability testing to see if your platform is easy and intuitive to use
• A/B testing two versions of a design to see which one works best
• Tree testing to assess if your website’s information architecture (IA) makes sense
• Five-second tests to collect first impressions

Behavioral research

This type of research refers to observation—it’s human nature that sometimes what we say, or what we think we’ll do doesn’t match up to what we actually do in a situation. Behavioral research is about observing how users interact with your product or how they behave in certain situations, without any intervention.

UX research methods for behavioral research

• Observation in labs or real environments to witness behavior in real time
• Tree testing to view which paths users take on a website
• Diary research to see how users interact with your product in real life

Attitudinal research

Attitudinal research is the companion to behavioral research—it’s about what people say, and how they feel. In attitudinal research, you ask users to share their own experiences and opinions; this may be about your product, a concept, or specific design element. With a mix of attitudinal and behavioral research, you can get a broader picture of what your user truly needs.

UX research methods for attitudinal research

• Focus groups to understand users’ perspectives on your product
• User interviews to ask people questions about your product directly
• Surveys to gather insights on user preferences and opinions

Quantitative research

Quantitative and qualitative research methods are two types of research that can be used in unison or separately. Quantitative research comes from data and statistics, and results in numerical data.

It allows you to identify patterns, make predictions, and generalize findings about a target audience or topic. “[At iMSA] We analyze a lot of metrics and specific data like traffic analytics, chatbot feedback, user surveys, user testing, etc. to make decisions,” explains Bertrand. “The convergence of all the data, our user’s needs, governs the choices we make.”

Types of quantitative results you can find through UX research include:

• Time spent on tasks
• Net promoter score (NPS)
• System usability score (SUS)
• Number of clicks taken to complete a task
• Preference percentage on A/B tests

UX research methods for quantitative research

• A/B testing to see which option your users likes best
• Tree testing to get data on which paths users follow on your website
• Usability testing to get a score on system usability
• Heatmaps to spot where users spend most of their session time

Qualitative research

Qualitative research is about understanding the why behind the data. It comes from comments, opinions, and observations—this type of research answers why and how users think or act in a certain way. Qualitative data helps you understand the underlying motivations, thoughts, and attitudes of target users. For this reason, attitudinal research is often qualitative (though not always).

UX research methods for qualitative research

• Interviews to discover your users’ motivations and frustrations
• Open question surveys to learn users’ pain points in their own words
• Focus groups to observe users’ interacting with your product
• Think aloud usability tests to hear commentary behind each user decision

💡 Product tip:

Maze allows you to record your participants' screen, audio, and video with Clips, so you can collect qualitative and quantitative insights simultaneously.

When should you conduct UX research?

The truth is, you should always be researching. When NASA wants to send a new shuttle into space, they don't build a rocket and launch it right away. They develop a design, test it in simulations and lab environments, and iterate between each stage. Only once they’ve run all the foreseeable scenarios do they put a person on the ship. Why should your product be any different?

With an overwhelming 83% of product professionals surveyed in our 2023 Continuous Research Report believing research should happen at all stages, it’s surprising that just 36% run tests after launch. While time and budget can make continuous research a challenge, testing at different stages gives you access to unique insights about your users and how they interact with your product.

That being said, if you can only afford to research a few times throughout the development process , here are some key moments to focus on:

Before developing the product

This is when you need to conduct the most extensive and detailed part of your research. During this phase, you’ll want to conduct generative research to get to know exactly:

• Who your user is
• The types of problems they’re facing (and what kind of product they want to solve them)
• What their expectations on a product or service like yours are
• What they like or dislike about your competitors
• Where they currently go to solve the mentioned problems
• What needs to happen for them to change companies (if they’re using a different product)

You can use a variety of UX research methods like focus groups and surveys to gather insights during this stage.

Remember: This step applies even if your product is already live, if you’re thinking of introducing a new feature. Validate your idea and investigate potential alternatives before you spend time and money developing and designing new functionality.

When you want to validate your decisions

This is the point where you’ll run through a few cycles of researching, building, and iterating, before launching your product. The Maze Product team does this through continuous product discovery, via a dual-track habit:

Conduct research regularly while developing and building your product to see if you’re headed in the right direction. Let the research findings feed your deliverables.

Gather qualitative insights on user sentiment through surveys or focus groups. Test your wireframe or sketches to get quantitative answers in the form of clicks, heatmaps, or SUS. Use card sorting to generate ideas, tree testing to assess IA, or prototype testing to assess the usability of a beta version. The options are endless, so there’s no reason to miss maximizing your research at this stage and gather insights to power product decisions.

To evaluate product accessibility

Your product will be used by a multitude of diverse, unique users. Your research participants should be representative of your real audience, which means including all usage scenarios and user personas. Usability testing is one form of UX research that can be used here to ensure your product works for all its users, regardless of ability or need.

There are many ways to ensure your design is inclusive and accessible , including:

• Testing alt-texts, screen-reading capabilities, and color combinations
• Avoiding screen flashes or sudden pop-ups that may be triggering for certain conditions
• Being intentional in what language and imagery is used

Once your product is live

Research doesn’t end once you push your platform to production. Conduct Live Website Testing to evaluate how well your product is meeting your users' expectations and needs. This type of research invites you to answer the question: did we nail it?

Testing your live website also allows you to see how your users interact with your design in a real environment, so you can identify and solve mistakes fast. Pay close attention to loading times, error messages, and other quantitative data that may indicate bugs. You can also conduct regular sentiment checks by embedding feedback surveys into your product itself, to assess user satisfaction and NPS in a few clicks.

TL;DR: Why, how, and when to conduct UX research

The more you understand your customers, the better you can create products that meet expectations, tailor your strategy to their specific needs, and increase your chances for success. Plus, UX research allows you to create unbiased products that put your customers at the center of your business.

To conduct UX research, you’ll need to mix the stage of your product lifecycle with the right research type and methods. Meaning, while you need to conduct UX research continuously, you should look for different types of insights depending on the development stage you’re at and what your current objective is.

For example, if you want to test your live product, you should conduct a mix of quantitative and qualitative evaluative research. That means you might want to perform:

• Usability tests
• Feedback surveys
• Five-second tests
• Prototype testing

Now we’ve covered the what and why of UX research, let’s get into the how. Continue to the next chapter to learn how to create a UX research strategy that blows your competitors away.

Frequently asked questions

What are some examples of UX research?

Some examples of UX research include:

• A/B testing
• Prototype or wireframe testing
• Card sorting
• User interviews
• Tree testing
• 5-second testing
• Usability testing

What are the basics of UX research?

The basics of UX research are simple: you just need a clear goal in mind and a mix of quantitative and qualitative tests. Then, it's a case of:

• Determining the right testing methods
• Testing on an audience that’s an accurate representation of your real users
• Doing continuous product discovery
• Performing unbiased research to build an unbiased design
• Iterating and building user-centric products

UX research gets easier when you use a product discovery platform like Maze. This tool allows you to run multiple types of product research such as usability, prototype, card sorting, and wireframe tests—and get answers within hours.

Is UX research hard?

UX research isn’t hard, especially when you use an intuitive tool for product discovery—like Maze. Maze allows you to build tests using its multiple available templates. It also lets you bring your own users or recruit from its panel and creates an automated, ready-to-share metrics report. Maze gives you answers to tests within hours so you can improve your UX based on real user feedback fast.

How to nail your UX research strategy

A Guide to Design System Field Studies

There is no shortage of guides published about how to build a design system . However, many of these guides do not pay enough attention to a crucial step in building a design system: user research. I’ll discuss why including user research in your design system process is an absolute must. I’ll also discuss one of my favorite methods for design system user research: the field study. We’ll take a leaf out of our elementary school curriculum and cover the “who, what, when, where, and why” of design system field studies. Plus, I’ll include some specific research questions to investigate when doing your field studies.

NEW RESEARCH: LEARN HOW DECISION-MAKERS ARE PRIORITIZING DIGITAL INITIATIVES IN 2024.

Why Companies Skip Design System Research

The usual reasons for skipping user research still apply to design systems — not enough time, not enough budget, can’t convince leadership, etc. However, design systems introduce some new reasons why people skip research.

Because design systems are internal products built for internal employees, teams discount the importance of user research to the system’s success. Essentially they think, “I work with these people every day — I know what they need and what problems they’re having.” In a worst case scenario, a team might not even think of their colleagues as people with problems and needs. Instead, they relegate them to cogs in a machine, with a job to do and a new tool they should be using.

First of all, design systems are inclusive tools — they serve more than just designers and developers. They’re a resource for marketing, copy writers, and even legal teams. So, unless you’re an expert in all of those things, slow your roll on assuming you know the exact pain points a design system can solve for your company’s employees. In fact, even if you are a genius lawyer-designer-author-developer hybrid-cyborg, you still haven’t lived the lives of the people you’re designing for . Each person will have different experiences, attitudes, expectations, skills, and abilities that will affect how they experience your design system. For example, maybe Jane Doe refers to a dropdown as a “select box” because that’s the verbiage her last company used. Have fun telling Jane she’ll never find a select-box in your design system because you never bothered to chat with her for a few minutes.

Your design system is only valuable if people use it. Imagine if Tim Berners-Lee launched the world wide web and hid it away in his basement. Without buy-in, your design system is nothing. Including multiple teams, partners, and stakeholders in your design process garners more buy-in throughout your organization. Think about it — which tool are you more likely to use?

• A tool that you actively helped create;
• A tool that a co-worker built for you, but it’s annoyingly useless because your co-worker never bothered to ask how you work;

The second approach is a fast track to making people feel invisible. The people you leave out will not only avoid your system, but they will become active detractors and undermine it.

The other main reason people skip design system research is because people still have a general misconception about what a design system is. Many think that a design system is just a library of reusable UI components. But it’s actually much more than that. A design system is more about the people who use it and how they interact than the components inside it. It must establish a governance process and design principles, among other things. However, because people think of a design system as just a component library, they think they can simply copy another public system. They look at material design or whatever the hottest new design system is and view it as a one-size fits-all solution.

However, your company is probably more unique than you think it is. Yes — there is probably a lot of overlap between each design system’s components. Every product is probably going to have buttons somewhere. But when it comes to things like the system’s governance process, different approaches are going to work better at different companies or for different products. Without doing user research, you won’t be able to make an informed decision about how to structure your governance process. For example, you’ll want to understand your team’s general outlook regarding design systems. If they feel that design systems tend to limit their creativity, then your governance process should be more inclusive and less authoritative.

The design system team’s structure is also an important part of the governance process. It defines who has the authority to make changes to the system. The team structure you decide to use will depend on several factors:

• How much time can people devote to the design system?
• How do people feel about being fully or partially dedicated to building and maintaining the design system? Are they interested in such a project?
• How well do your team member’s skills align to design system responsibilities?
• How much exposure does each team member have to different products throughout your organization?

Guess what? Unless you do user research, you can bet you won’t have accurate answers to the above questions.

So, now that we’ve established you’ll be doing user research for your design system (we have established that right? Nod your heads), let’s talk about how to actually do it. First, let’s talk about two different types of user research: generative research and evaluative research.

Generative research focuses on finding answers to your “known unknowns” as well as your “unknown unknowns.” In other words, through generative research you can answer your existing research questions, but you can also discover new insights and questions you didn’t even know you should be looking for .

Next we have evaluative research, which is a bit more straightforward. With evaluative research, your goal is to evaluate something (shocker). That something could be how well your solution solves the problems you set out to solve. Or, it could be evaluating the validity of a hypothesis or risky assumption. Most importantly, good evaluative research highlights why the solution is performing well or not.

So how does this apply to design systems? Your first instinct might be to follow a linear approach: do generative research first, then build the design system, then evaluate it. That approach would still be more valuable than doing no research at all, but it’s not the most optimal approach. To get the most out of your research, you want to do it continuously throughout the entire product development lifecycle. Everytime you release a new version of your design system or start to conceive a new feature, you should do user research.

There are a lot of user research methods out there that can be applied to your design system:

• Collaborative journey line exercises
• Field studies/contextual inquiry
• Participatory design
• Card sorting and tree testing

And the list goes on. For a great rundown of which methods to use when, I repeatedly refer back to this Neilsen Norman article . But today, I want to focus on one method in particular that works well with design systems user research: field studies.

What is a Field Study?

Think of a field study like your typical research interview, except it’s performed in context. Rather than asking someone to recount how they did something, you actually observe them perform the task in their natural environment and ask questions when necessary. The technical term for this method is “contextual inquiry.” However, I tend to use the term field study because it’s more relatable for participants and others.

Why Field Studies?

Memory is notoriously fallible. If you asked me to recount the exact steps I took to make my breakfast this morning, I wouldn’t be able to accurately tell you. I would leave steps out, recount them in a different order, or even add steps that never happened. This is the drawback of your traditional research interview: what people say they do is almost always different from what they actually do . With a field study, you see the action firsthand. You uncover much richer and more accurate data.

Field studies are my preferred method when doing design system research because users are completing very complex tasks. For example, when I design something, I’m making key decisions every few minutes. Meanwhile, the engineering side is so complex that I can’t even begin to fully understand it (another reason why user research is so important). The more complex the task is, the more likely that a participant will leave out details in a typical interview.

There are drawbacks to field studies as well. For example, you have to get the timing right. Field studies are only valuable if you observe your users in their natural environment, performing tasks as they would usually perform them. This means that your participants need to actually have the tasks you want to observe on their to do list. Artificially recreating a task will introduce issues, because then you move into the realm of what the user “typically” does, instead of what they actually do .

A field study can be more time consuming than your typical interview because you have to observe participants as they fully complete their tasks. Often, completing a task takes longer than explaining how to complete it. Similarly, because you collect richer and more data, the analysis process can take more time.

Lastly, it’s often more difficult to find participants willing to let you shadow them for an extended period of time. Many participants perceive an interview as lower effort than doing a field study. That’s because in a field study we ask the participant to take the lead. They explain everything they’re doing to the moderator, which requires thought and effort. However, unlike an interview, the participant completes their work tasks and remains productive . Be sure to stress this point when recruiting co-workers for field studies.

These challenges may seem tough to overcome, but they are minimized when working on an internal tool like a design system. For one, you’ll have more luck recruiting co-workers than consumers. You’re likely to have an existing relationship with many of your co-workers. Your co-workers also will have more motivation to participate. A consumer’s motivation is usually to receive compensation or to improve the tool they use. For your co-workers, it may actually be within their job duties to help you out.

Who to Research With

We’ve already covered the different teams that a design system can impact. But who within those teams should you observe? Not all engineers are the same and not all designers are the same. You should consider having sessions with senior engineers and junior engineers. Engineers with React skills and engineers with Angular skills. Designers who code and designers who don’t. There are a ton of ways to slice it. The point here is that, right off the bat, you might not know who exactly you should research with or how many people to do sessions with. There’s no hard and fast rule for this. As you start your research, you will start to identify different skills, goals, and personalities for each persona. The rigorous researcher side of me will tell you to continue researching until you hit saturation. In other words, research until you stop hearing new things and discovering new types of people.

Also, a word of caution here. Some design system teams structure their teams using a federated model. In this model, different “representatives” from your various product teams also contribute to the design system. In this case, you might be tempted to rely heavily on these representatives to give you insights on what they need from a design system or how well the design system is working. After all, they’ve set aside the time to specifically work on the design system. However, we need to cast a wider net than just these representatives. You’re looking for different perspectives from people across your company . Plus, the people who are on your design system team are most likely biased. Why? Well, they’re on the design system team, so they have inside knowledge and probably an affinity for the design system that others might not have.

Where to Do a Field Study

This might seem obvious, but you should perform your field studies in the field, or in other words, within the user’s natural environment. This means that if your designers typically work from the office at their desk, you should hold your session there. If your participants do any face-to-face collaboration with others during their work day, try to attend the session in person.

If you have a session with an engineer who is 100% remote, you can try doing the session remotely over screen share. Doing these sessions remotely is possible, but there are some technical challenges. For example, your colleagues might use multiple monitors and most screen share tools only share one monitor at a time. So you run the risk of missing important actions the participant might take, like sending a message to someone on another monitor. In this case, it can be helpful to have the user talk through all the steps they are taking to ensure nothing is missed.

How to Do a Field Study

Your first time running a field study might feel a little foregin, because it’s very different than most common UX research methods. Remember, it’s also probably unfamiliar for your participants. That’s why your first step when doing a field study is to make sure your participant is aware of what to expect. Send them an email ahead of time making sure they will have tasks ready to perform. Make it clear that you’re not doing a typical interview. Also make sure they know the session is an individual session, unless they always perform the tasks in question with other people. You’d be surprised how many people “bring a friend.” For design systems, this is a key point, because often designers and developers will collaborate for long periods of time. A design system can be a key resource during those collaboration sessions.

Before you go into the session, I also recommend creating an intro script to follow. This script can be as fleshed out as you need it to be. Personally, I write out every single word that I say to make sure everyone gets the exact same instructions. In this script, I explain what we’ll be doing during the session. There are a few key points to focus on here:

• Tell the participant it’s important to do their work as they naturally would.
• Assure the participants that they can be honest. Nothing they say or do will be held against them.
• Explain that the session will be different from a typical interview. Walk the participant through how the session will work.

On this last item, there are two different ways you can approach the session. In a more structured session, you will know exactly which tasks you would like to observe and should inform the participant beforehand to have those tasks ready. In a less structured session, you’ll start the session with a brief interview to understand the design system related tasks the participant will perform that day. Once you’ve created a list of tasks, ask your participant to complete them in a natural order. When it comes time for the participant to start their work, I make it clear that we are making a dramatic shift in how the session is run. I say something like:

“Okay, now we’re going to change gears and do something completely different. Up until now, I’ve been doing most of the talking and asking you questions. Now, I’m going to turn it over to you and ask you to walk me through your work tasks. I’d like you to think of this session as if you are a trainer and I’m your apprentice. Assume that I know nothing about the work you do, and you’re trying to teach me how you do it. This means don’t skip any of the details, even if you feel I might think they’re boring. I want to see absolutely everything.”

Even with this introduction, your participants will likely try to gloss over the “boring” details. In such cases, gently remind them you would like to see everything. In the case of a design system, the boring, repetitive tasks are actually the most important to observe. After all, a design system is meant to make design and development more efficient.

Tasks and Research Questions

As mentioned, the tasks that people at your company perform will be unique in certain ways. That being said, below I’ve included a set of tasks you can explore with your team members and research questions for each task. The questions you investigate might be slightly different depending on whether you have launched your design system or not.

Collaboration between Team Members

Design systems are meant to streamline collaboration between your team members by limiting disagreements about how components work and building a shared terminology. Here are some things to look out for when watching teams collaborate:

Design Concepting & Prototyping

Design systems play a big role in making prototyping more consistent and efficient. Similarly, they can introduce consistency into very early stages of the design process as well. Investigate these research questions to make sure your designers get the most out of your design system when using it to concept and prototype:

Design Review or Critique

Hopefully your design team performs regular design reviews to gather actionable feedback. Try to answer the following research questions when observing this task:

Translating Designs into Front-End UI

If your team has designers and developers, there’s a good chance that at some point your developers will reference a design artefact, such as a prototype or mockup, to begin building part of the product.

Updating Existing UI

One of a design system’s biggest benefits is that it makes changing your existing front-end UI much faster. Explore these research questions to understand how you can help your teams achieve this goal:

User Research and Analytics

This is going to get a bit meta, but just as you should perform user research for your design system, your product teams should also perform user research on their products. More broadly, your product teams should inform their decisions with data, including product analytics, to reduce risk.

Most people won’t think of a design system as affecting user research and analytics all that much. However, the design principles you evangelize through your design system can transform your entire design and development process. For example, if your company struggles to do user research but wants to improve, you might include a design principle like “Test early and often.” You could also include best practices for how to use data in the design process. That’s not something you typically see in a design system, but that’s the point — design system user research allows you to make your system your own.

With that in mind, here are some good research questions to explore when observing people perform user research.

Evolving the Design System

A design system is never done. Over time, your system should evolve to include new components, principles, and content. You should improve your processes over time. A good design system provides guidance on how this evolution should occur. Making changes to the system is one of the most complex challenges you will face, so here are some research questions to help you fully understand the challenge.

Wrapping It Up

In summary, performing user research for your design system is important because your organization has unique needs. Your organization employs people with different perspectives, skills, and experience. Tapping into this rich data can be challenging, but it will result in greater buy-in and engagement. With this article, you can arm yourself with some great questions to research at each step of the process. If you give it a shot, let us know how it goes in the comments.

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How to Conduct Field Studies for UX Research

Field studies are a crucial component of ux research, allowing designers to gain valuable insights into user behavior and preferences. to conduct an effective field study, start by defining clear research objectives and selecting a diverse group of participants. then, immerse yourself in their natural environment, observe their interactions, and engage in meaningful conversations to uncover valuable user insights that can inform your design decisions..

User experience (UX) research plays a crucial role in designing products and services that meet the needs and expectations of users. While there are various methods to gather user insights, conducting field studies is one of the most effective ways to understand user behavior in real-world contexts. In this blog post, we will explore the process of conducting field studies for UX research and provide you with practical tips to ensure successful outcomes.

What is a Field Study?

A field study, also known as contextual inquiry or ethnographic research, involves observing and interacting with users in their natural environments. Unlike lab-based studies, field studies provide researchers with a deeper understanding of how users engage with products or services in real-life situations. By immersing themselves in the users' context, researchers can uncover valuable insights that may not be apparent through other research methods.

Benefits of Field Studies for UX Research

Field studies offer several advantages over other research methods, making them an essential tool for UX researchers. Here are some key benefits:

Real-world insights : Field studies provide researchers with a firsthand understanding of how users interact with products or services in their natural environments. This allows for a more accurate assessment of user needs, behaviors, and pain points.

Contextual understanding : By observing users in their natural settings, researchers can gain insights into the broader context in which products or services are used. This includes factors such as physical environment, social dynamics, and cultural influences, which can significantly impact user behavior.

Uncovering hidden needs : Field studies often reveal user needs and expectations that users themselves may not be aware of or unable to articulate. By observing users in real-life situations, researchers can identify pain points and opportunities for improvement that may have been overlooked.

Validating assumptions : Field studies help validate or challenge assumptions made during the design process. By observing how users interact with a product or service, researchers can assess whether it meets their expectations and identify areas for improvement.

Steps to Conduct a Field Study

Now that we understand the benefits of field studies, let's dive into the step-by-step process of conducting one:

Step 1: Define Research Objectives

Before embarking on a field study, it's crucial to clearly define your research objectives. What specific questions do you want to answer? What insights are you hoping to gain? By setting clear goals, you can focus your research efforts and ensure that the study remains on track.

Step 2: Recruit Participants

Identify and recruit participants who represent your target user group. Consider factors such as demographics, usage patterns, and familiarity with the product or service. Aim for a diverse sample to capture a range of perspectives and experiences. You can reach out to potential participants through online communities, social media, or by partnering with relevant organizations.

Step 3: Plan the Study

Develop a detailed plan for your field study, including the research methods, data collection techniques, and timeline. Decide whether you will conduct interviews, observations, or a combination of both. Determine the number of sessions required and allocate sufficient time for each session. It's also essential to obtain any necessary permissions or consent from participants before the study begins.

Step 4: Conduct the Study

When conducting the field study, it's crucial to establish rapport and build trust with participants. Make them feel comfortable and encourage them to share their experiences openly. Use a combination of observation and interview techniques to gather data. Take detailed notes, capture audio or video recordings (with participants' consent), and document any artifacts or physical evidence that may be relevant.

Step 5: Analyze and Synthesize Data

Once the field study is complete, it's time to analyze and synthesize the data collected. Transcribe interviews, review observation notes, and organize artifacts. Look for patterns, themes, and insights that emerge from the data. Consider using qualitative analysis techniques such as affinity mapping or thematic coding to identify commonalities and outliers.

Step 6: Derive Insights and Recommendations

Based on the analysis of the data, derive meaningful insights and recommendations. Identify key pain points, opportunities for improvement, and potential design solutions. Use the insights gained from the field study to inform the design process and make data-driven decisions.

Step 7: Communicate Findings

Finally, communicate your findings effectively to stakeholders, designers, and other relevant team members. Use visual aids such as charts, graphs, or personas to present the insights in a compelling and easily understandable manner. Clearly articulate the implications of the findings and how they can be applied to improve the user experience.

Tips for Successful Field Studies

To ensure successful field studies, consider the following tips:

Prepare a research kit : Pack a research kit with essential items such as a notebook, pens, audio or video recording devices, consent forms, and any other tools you may need during the study.

Be adaptable : Field studies can be unpredictable, so be prepared to adapt your research plan as needed. Stay flexible and open to unexpected insights or changes in the research direction.

Build rapport : Establishing a good rapport with participants is crucial for obtaining honest and valuable insights. Be friendly, empathetic, and respectful throughout the study.

Observe non-verbal cues : Pay attention to participants' non-verbal cues, such as body language or facial expressions. These can provide valuable insights into their emotions, frustrations, or delight.

Take detailed notes : Capture detailed notes during the study to ensure accurate data collection. Use shorthand or symbols to record observations quickly without interrupting the flow of the session.

Triangulate data : Whenever possible, gather data from multiple sources or methods to validate findings. Triangulation helps ensure the reliability and validity of the insights derived from the field study.

Field studies are a powerful tool for UX researchers to gain deep insights into user behavior and needs. By immersing themselves in the users' natural environments, researchers can uncover valuable insights that inform the design process and lead to better user experiences. By following the steps outlined in this article and implementing the tips provided, you can conduct successful field studies that provide meaningful and actionable insights for your UX research.

Explore More

Nielsen Norman Group. (2021). Field Studies. Retrieved from https://www.nngroup.com/articles/field-studies/

Interaction Design Foundation. (2021). Field Studies - Contextual Inquiry. Retrieved from https://www.interaction-design.org/literature/topics/field-studies-contextual-inquiry

Usability.gov. (2021). Field Studies. Retrieved from https://www.usability.gov/how-to-and-tools/methods/field-studies.html

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7 Great, Tried and Tested UX Research Techniques

Thinking about conducting some user research ? Wondering which techniques are most likely to provide useful results? Then look no further. We’ve compiled a list of 7 excellent techniques which are tried and tested and have been proven to deliver real value in UX projects. Let’s take a look at each technique and see what it is and why it works:

Technique Number 1 – Card Sorting

Card sorting was originally a technique used in psychological research long before UX research was a “thing”. It’s a simple concept, you write words or phrases on cards, then you ask the user to categorize them. You might also ask them to label the categories. It’s a great way to determine whether your Information Architecture (IA) is heading in the right direction or to examine IA for new products.

There are all sorts of card sorting techniques and choosing the right one is important. Better still, there are a bunch of online tools that let you do card sorting remotely now – allowing you to use the technique globally and not just locally.

Why is card sorting a good technique?

It’s a very cheap form of research – particularly face-to-face, online tools may be more expensive.

It’s a very easy technique for users to understand and for clients to understand too.

It’s a very easy method to get user input (or even to get user validation) for ideas early on in a UX project.

It requires next to no effort to prepare a card sorting study.

Technique Number 2 – The Expert Review

Expert reviews involve a single “expert” walking through a product via the User Interface ( UI ) and looking for issues with the design, accessibility , and usability of the product. There’s no fixed process to follow and the expert review can vary from professional-to-professional as well from product-to-product. The more expertise the reviewer has in usability and UX design – the more valuable their input (in most cases).

Why is an Expert Review a Good Technique?

It’s quick, easy and cheap. This is doubly so when you compare it to more formal usability testing methods.

It only takes a single professional to conduct an expert review.

It is a great way to inform further UX research and caution should be used in taking an expert review at face value without further user testing .

Technique Number 3 – Eye Movement Tracking

It can be really useful to know where your users are looking when they’re using your system. It helps with UI design and it helps with knowing how to prioritize certain kinds of content. This technique was developed for academic research and has been used extensively in medical research and has now become popular and cost-effective enough to be deployed by the UX team too.

Why is Eye Movement Tracking a Good Technique?

Now that technology is advanced enough, eye movement tracking systems are no longer bulky and invasive and they do not interfere with the results of usability tests.

The technology is reasonably affordable now. It won’t suit every project budget but it often won’t break the bank either.

The technology is now reliable enough for results to be easy to reproduce and for researchers to be able to rely on the outputs.

Clients love eye movement tracking. It’s a great way to demonstrate why they might want to invest in further usability testing.

Technique Number 4 – Field Studies

This is actually a number of techniques under a broad heading. It’s all about going out and observing users “in the wild” so that behaviour can be measured in the context where a product will actually be used. It includes; ethnographic research , interviews and observations, plus contextual enquiry.

Why are Field Studies a Good Technique?

There’s no stronger form of research than observing users behaving as they will when they use your product. Researchers love these techniques and are often passionate about persuading their clients to take them on board.

When conducted well, the outputs of field studies provide the deepest insights into user issues and how they might be solved.

Technique Number 5 – Usability Testing

A firm favourite that has a long and prestigious history in UX research. Usability testing is the observation of users trying to carry out tasks with a product. They can focus on a single process or be much more wide ranging.

Why is Usability Testing a Good Technique?

Can you think of a better way to understand what users do than watching them do stuff? Of course, you have to pick the right users – they need to be a good representation of the user base as a whole but that’s pretty much the only constraint.

Usability tests produce specific results that lead to specific action. Better still, it’s very hard for people to contradict decisions based on these tests; it’s nearly impossible to refute evidence of user behaviour .

You can bring clients into usability testing easily as observers. This increases their enthusiasm for such testing and shows clearly why such testing adds value.

Technique Number 6 – Remote Usability Testing

This is usability testing but without the need to drag users into your laboratory environment. It was once complex and expensive but technology has moved on and now it’s fairly simple to set up and reasonable value for money too.

Why is Remote Usability Testing a Good Technique?

It often saves time and money when compared to lab testing and it allows for a wider range of participants when you complete your participant screening .

It is closer to field testing in some respects in that the tests are conducted in the user’s environment and not an artificial lab environment. This delivers better results in many cases than a lab environment.

Technique Number 7 – User Personas

User personas are a fictional representation of the ideal user. They focus on the goals of the user, the characteristics that they have and the attitudes that they display. They also examine what the user expects from the product.

User personas are created from other forms of user research and thus offer an in-depth real-life vivid portrait that is easy for the whole team to keep in mind when designing products. User personas have a name and a backstory. They inspire the imagination and keep focus on the user.

Why are User Personas a Good Technique?

They are a step above the old user profile and give a more in depth and specific look at a user.

They are easy for people to relate to and become part of the team as they are constantly spoken about during a project.

They are a lot of fun and they tend to be interesting, easy for people to engage with and more memorable than many other research outputs.

There are many user research techniques but these 7 have shown time and again to offer valuable input into UX projects. Which is your favourite?

Header Image: Author/Copyright holder: Zeke Franco. Copyright terms and licence: CC BY-NC-ND 2.0

Data-Driven Design: Quantitative Research for UX

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Researchers find oldest undisputed evidence of Earth’s magnetic field

A new study, led by the University of Oxford and MIT, has recovered a 3.7-billion-year-old record of Earth’s magnetic field, and found that it appears remarkably similar to the field surrounding Earth today. The findings have been published today in the Journal of Geophysical Research .

In the new study, the researchers examined an ancient sequence of iron-containing rocks from Isua, Greenland. Iron particles effectively act as tiny magnets that can record both magnetic field strength and direction when the process of crystallization locks them in place. The researchers found that rocks dating from 3.7 billion years ago captured a magnetic field strength of at least 15 microteslas comparable to the modern magnetic field (30 microteslas).

These results provide the oldest estimate of the strength of Earth’s magnetic field derived from whole rock samples, which provide a more accurate and reliable assessment than previous studies which used individual crystals.

Lead researcher Professor Claire Nichols (Department of Earth Sciences, University of Oxford) said: ‘Extracting reliable records from rocks this old is extremely challenging, and it was really exciting to see primary magnetic signals begin to emerge when we analysed these samples in the lab. This is a really important step forward as we try and determine the role of the ancient magnetic field when life on Earth was first emerging.’

Whilst the magnetic field strength appears to have remained relatively constant, the solar wind is known to have been significantly stronger in the past. This suggests that the protection of Earth’s surface from the solar wind has increased over time, which may have allowed life to move onto the continents and leave the protection of the oceans.

Understanding how Earth’s magnetic field strength has varied over time is also key for determining when Earth’s inner, solid core began to form. This will help us to understand how rapidly heat is escaping from Earth’s deep interior, which is key for understanding processes such as plate tectonics.

A significant challenge in reconstructing Earth’s magnetic field so far back in time is that any event which heats the rock can alter preserved signals. Rocks in the Earth’s crust often have long and complex geological histories which erase previous magnetic field information. However, the Isua Supracrustal Belt has a unique geology, sitting on top of thick continental crust which protects it from extensive tectonic activity and deformation. This allowed the researchers to build a clear body of evidence supporting the existence of the magnetic field 3.7 billion years ago.

Study co-author Professor Benjamin Weiss (Massachusetts Institute of Technology), said: ‘Northern Isua has the oldest known well-preserved rocks on Earth. Not only have they not been significantly heated since 3.7 billion years ago but they have also been scraped clean by the Greenland ice sheet.’

In the future, researchers hope to expand our knowledge of Earth’s magnetic field prior to the rise of oxygen in Earth’s atmosphere around 2.5 billion years ago by examining other ancient rock sequences in Canada, Australia, and South Africa. A better understanding of the ancient strength and variability of Earth’s magnetic field will help us to determine whether planetary magnetic fields are critical for hosting life on a planetary surface and their role in atmospheric evolution.

The study ‘Possible Eoarchean records of the geomagnetic field preserved in the Isua Supracrustal Belt, southern west Greenland’ has been published in the Journal of Geophysical Research: Solid Earth .

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• Published: 29 April 2024

Faculty members as academic knowledge brokers in Iran's health sector: a social network analysis study

• Khadijeh Shabankareh 1 ,
• Ali Hamidi 2 ,
• Mohammad Reza Soleymani 1 ,
• Haniye Sadat Sajadi 3 &
• Mousa Alavi 4  

Health Research Policy and Systems volume  22 , Article number:  53 ( 2024 ) Cite this article

Metrics details

Interaction between researchers and policymakers is an essential factor to facilitate the evidence-informed policymaking. One of the effective ways to establish this relationship and promote evidence-informed policymaking is to employ people or organizations that can play the role of knowledge brokers. This study aims to analyze the communication network and interactions between researchers and policymakers in Iran's health sector and identify key people serving as academic knowledge brokers.

This study was a survey research. Using a census approach, we administered a sociometric survey to faculty members in the health field in top ten Iranian medical universities to construct academic-policymaker network using social network analysis method. Network maps were generated using UCINET and NetDraw software. We used Indegree Centrality, Outdegree Centrality, and Betweenness Centrality indicators to determine knowledge brokers in the network.

The drawn network had a total of 188 nodes consisting of 94 university faculty members and 94 policymakers at three national, provincial, and university levels. The network comprised a total of 177 links, with 125 connecting to policymakers and 52 to peers. Of 56 faculty members, we identified four knowledge brokers. Six policymakers were identified as key policymakers in the network, too.

Conclusions

It seems that the flow of knowledge produced by research in the health field in Iran is not accomplished well from the producers of research evidence to the users of knowledge. Therefore, it seems necessary to consider incentive and support mechanisms to strengthen the interaction between researchers and policymakers in Iran's health sector.

Peer Review reports

Research in the health field, by knowledge production in terms of providing better technologies and improving people's lifestyle, can lead to social and economic development, in addition to improving the society's health [ 1 ]. However, the production of new knowledge will be effective when it is available to stakeholders and used in making decisions and policies. Evidence-informed policymaking (EIPM) helps policymakers use the best available evidence in their policy decisions systematically and transparently. It can lead to more informed decisions, strengthen health systems, and as a result, improve public health outcomes [ 2 ].

Activities aimed at using the results of health research in policymaking and practice are known as knowledge translation. knowledge translation experts highlight the importance of both EIPM and practice, and policy and practice-informed evidence generation [ 3 ]. However, the gap between knowledge production and its application is considered one of the fundamental challenges of health systems in developing countries, including Iran [ 4 ]. These countries face challenges such as the lack of high-quality evidence, limited capacity to evaluate and use evidence, investment policy problems, and structural barriers to evidence use [ 5 ]. Research results are not usually available to the policymakers, so, research does not have an objective and noticeable effect on important policies [ 6 ]. In such a situation, researchers and policymakers are considered separate communities whose few interactions and different priorities hinder the flow of evidence between them. This gap has been mentioned in various studies, and the interaction of researchers and policymakers has been emphasized as the most essential factor facilitating EIPM [ 7 , 8 , 9 ].

One of the effective ways to establish communication between researchers and policymakers is to employ people or organizations as knowledge brokers (KBs) to accelerate the process of knowledge flow by creating an active cooperation network among stakeholders [ 4 ]. A KB seeks to transfer knowledge and establish and facilitate communication and interaction between producers and users of knowledge [ 10 ]. These people may not be researchers or end users of knowledge. Recently, the notion of academic KB has emerged, highlighting the role of university faculty in facilitating information flow between researchers and policymakers. In addition to producing knowledge, these people can also play a role as mediators of knowledge [ 11 ].

In Iran's General Health Policies (GHPs), institutionalization of knowledge production and promotion of evidence-informed decision-making at different levels of policymaking have been emphasized [ 12 ]. Therefore, much attention has recently been paid to the concepts of knowledge translation, EIPM, and knowledge brokering in health field. Measures such as the establishment of the National Institute of Health Research, and the Health Policy Council are initiatives that have been presented to promote EIPM in Iran's health system [ 13 ]. However, the implementation of EIPM in Iran has faced obstacles, and the use of evidence has not been well institutionalized in the country's health system [ 14 ].

One of the most important sectors in modern healthcare systems is the health sector. The World Health Organization has always emphasized the principle that "prevention is better than cure" [ 15 ]. Similarly, Iran's health system's motto is “prevention comes before treatment” although it seems that this phrase has not been much considered in practice. In this context, faculty members and researchers at medical sciences universities, specializing in the health field, can take steps towards realizing this motto. These individuals can enhance community health by generating valid scientific evidence and influencing health policies [ 16 ]. It requires mutual communication and appropriate interactions between researchers and policymakers in the health field [ 17 ].

Individual relationships between researchers and policymakers in the health field for EIPM have been considered in some studies. These studies employed the Social Network Analysis (SNA) method to discern relationships within the scientific network, identifying key individuals or organizations. McAneney et al. drew the stakeholder network structure for academic and non-academic members of the Center of Excellence for Public Health in Northern Ireland using the SNA method. They assessed the quality and extent of these relationships, exploring their impact on research influencing policy and practice. Additionally, they delved into researchers' perspectives on knowledge brokering and knowledge translation [ 18 ]. Yousefi-Nooraei et al. depicted the information search network concerning the integration of research evidence into practice among staff in the Canadian public health department. They investigated the nature of connections between staff, network structure, key actors, and KBs and their characteristics [ 19 ]. The role of academic KBs was first discussed in Jessani's doctoral dissertation [ 11 ]. The author drew a communication network for the faculty members of public health schools and policymakers in Kenya and defined KBs and their characteristics [ 11 ]. In a separate study, Jessani et al. investigated the connections between faculty members at the Johns Hopkins Bloomberg School of Public Health and policymakers at the city, state, federal, and global levels [ 20 ].

Studies conducted in the field of EIPM in Iran have often evaluated the impact of health research [ 21 ], obstacles and challenges of EIPM [ 22 ], and strategies to strengthen EIPM [ 13 , 14 , 17 , 23 ]. All these studies have emphasized the lack of communication and mutual trust between researchers and policymakers and the need to strengthen the interaction between these two groups. To our knowledge, there is no specific research addressing the relationship between researchers and policymakers in Iran's health sector, with a particular emphasis on the role of faculty members as KBs. Therefore, the current study has sought to depict the current situation by analyzing the communication network and interactions between researchers and policymakers in Iran's health field and identify key people who can play a role as academic KBs.

Design and setting

This study was a survey, which is part of a wider research with the aim of explaining the role of academic KBs in Iran's health sector. We used the SNA method to draw the communication network between faculty members and policymakers in the health field in Iran [ 24 ]. SNA is a quantitative method for analyzing data in social networks that studies the relationships between actors, including individuals or organizations, and how they communicate to access intellectual, financial, social, and other resources [ 25 ]. Additionally, this method serves to identify influential individuals, organizations, and KBs within the network [ 20 , 26 ]. SNA reveals the fine interpersonal and interdepartmental communication structure, which cannot be visualized using conventional surveys [ 19 ].

Participants and sampling

The research population involved the faculty members specializing in the health field in top ten medical universities in Iran, under the MOHME, including Tehran UMS, Shahid Beheshti UMS, Mashahd UMS, Tabriz UMS, Iran UMS, Shiraz UMS, Isfahan UMS, Ahvaz Jundishapur UMS, Mazandaran UMS, and Kerman UMS. The faculty members' names were extracted from the Iranian Scientometrics Information Database. Footnote 1 Accordingly, 302 people with degrees in health education and promotion, public health, occupational health, environmental health engineering, and epidemiology who had at least one article in the Scopus, regardless of the faculty or research center where they worked, were included in the study. Therefore, the sampling method was non-probability, purposeful and total population sampling.

Data collection

For data collection, a sociometric questionnaire, commonly employed in studies focused on social relations, was utilized [ 27 ]. Data collection was done January to August 2020 by visiting in person or sending an online questionnaire via email. In order to increase the response rate to online questionnaires, reminder e-mails were sent to people several times at ten-day intervals. In addition to providing demographic information, this questionnaire provided the necessary data to draw the communication network. In the questionnaire, the respondents were asked to name the people with whom they interacted in order to apply research evidence in health policies. According to previous studies, in the sociometric survey, the maximum number of people introduced by the respondents in a network varied between 5 and 7 people [ 19 , 28 ]. Therefore, in the present study, the respondents were asked to introduce a maximum of 7 people in each of the three categories determined in the questionnaire. The three categories of relationships between researchers and policymakers were: (1) direct relationship with policymakers, (2) relationship with policymakers through peers, and (3) researchers as intermediaries between policymakers and peers.

Data analysis

UCINET, version 6.716, and NetDraw 2.173 software were used for network visualization. To achieve this, initially, data from the sociometric questionnaire were input into Excel. Then, the reported connections between each respondent and their alters were recorded in a relational matrix in UCINET. Subsequently, the data file was saved and analyzed. For simplicity and to maintain the confidentiality of the respondents, the names of people were replaced with unique IDs in the matrix. Each row or column in the matrix represents one of the nodes (i.e., the network members). In the matrix, the numerical value of the relationship between nodes was entered. In this way, if there is a connection between two nodes, the number 1 is entered, and if there is no connection, the number 0 is entered. In order to reduce the possibility of data loss, those groups of the research population who did not complete the questionnaire, provided that another member of the network introduced them as peers, were also included in the network.

After drawing the network, KBs were selected based on the following three factors:

Number of links with policymakers;

Number of links with academic peers;

Individuals' positions in the network, serving as links between other nodes, were assessed using the Betweenness Centrality index in the UCINET. In other words, in this research, Indegree Centrality, Outdegree Centrality, and Betweenness Centrality indicators were used to determine key actors or KBs in the network.

A high Indegree index indicates the person's reputation, which shows that many people pay attention and refer to this node. A high Outdegree index suggests authority, signifying that nodes of this kind can disseminate information more rapidly [ 29 ]. The Betweenness Centrality index of a node expresses the importance of that node in the flow of information passing from one part to other parts of the network. Thus, it can show the ability of a node to create connections between the other nodes [ 30 ]. In order to determine KBs, people were first ranked based on the indicators of Indegree Centrality (number of connections with peers), Outdegree Centrality (number of connections with policymakers and number of connections with peers), and Betweenness Centrality, and then the scores were normalized. Due to the limited number of qualified people, people who were in the top 50% in all four indicators were selected as KBs. The reason for choosing these indices was that the academic KBs did not gain this position only as a channel to control the flow of information (which is determined using the Betweenness Centrality index). However, their position could also be due to their reputation and popularity among their peers and their effect on policymakers through direct or indirect communication [ 28 ].

In order to determine the key policymakers in the network, the frequency of repeating the names of the policymakers introduced by the faculty members, according to the information from the sociometric questionnaire, was considered. Since this frequency varied from 1 to 5, the Median number was considered an indicator for determining key policymakers. As a result, policymakers mentioned three times or more were chosen as key policymakers in the network. These policymakers had the highest interaction with faculty members, as reported by respondents. After drawing the network, the structural characteristics of the network, including prevalence, depth, and effective density, were also calculated.

The prevalence of connections between network members has been calculated in two ways: (1) absolute prevalence, which includes the number of faculty members participating in the research who have had contact with at least one policymaker, and (2) Relative prevalence, which is the ratio of faculty members who have had contact with at least one policymaker to all faculty members participating in the research [ 20 ].

The depth of communication indicates the degree of overlapping of communication between faculty members and policymakers, and peers. In other words, it is the ratio of joint members with more than one connection with academic faculty members of the research population to all policymakers and peers introduced in the network [ 28 ].

Network density is defined as the ratio of the number of all existing links to all possible links [ 31 ]. This index, which represents the degree of network correlation, can provide insight into the speed of information dissemination among nodes and the amount of social capital or social restrictions of actors [ 32 ]. Usually, the higher the density of the network, the more direct relationships there are between members, [ 29 ] and the more likely knowledge is to flow in the network [ 33 ]. Because, in the present study, the respondents were limited to introducing seven people in each of the three categories of communication, the concept of effective density has been used.

One hundred fifty-two people (50.33%) of the research population answered the sociometric questionnaire, whose demographic information is presented in Table  1 .

Individual network

Fifty-six (36.84%) of the respondents, asserted their interaction with at least one policymaker. This interaction aimed to share the results of their research. Thirty-six (23.68%) of the respondents, indicated having experience as decision-makers. The communication network of faculty members and policymakers in Iran's health sector is shown in Fig.  1 . This network has 188 nodes consisting of 94 university faculty members and 94 policymakers at three national, provincial, and university levels. One of the faculty members with the code FT05, who completed the sociometric questionnaire as a researcher, also has a policymaking role at the national level. Due to the fact that he was introduced as a policymaker by some members of the research population, he is considered as a policymaker here.

Academic-policymaker network for top ten Iranian universities of medical sciences

In the drawn network, faculty members are represented as squares, and policymakers as circles. The connection between the members of the network is also shown with directional lines, so that the connection between faculty members and policymakers is shown as one-way lines (from faculty members to policymakers) and the connection between faculty members and peers is shown as one-way or two-way lines (Fig.  1 ).

In the drawn network, 114 nodes, connected through 119 links, formed the main component. A component is defined as the largest connected subgraph. Other nodes were outside the main component and separated into small subgraphs. The network drawn based on the existing subgraphs is shown in Fig.  2 .

Subgraphs of academic-policymaker network

In the network, there were a total of 177 links. Specifically, 125 links were established with policymakers. Moreover, 52 links were established with peers. Of these, nine links were two-way links. It should be noted that all policymakers and peers (regardless of employment status, field of study, and university of employment) who were introduced by the faculty members were retained in the network for complete analysis. However, 96 respondents had no connection with the policymakers or their peers to share the results of their research with the policymakers, were considered isolated nodes and were not displayed in the network.

Organizational network

Faculty members were linked with policymakers from nine organizations at the national level. Furthermore, connections were established with policymakers from 21 organizations at the provincial level. Thirty-three relationships were also established with policymakers at the level of medical sciences universities, including presidents and vice-chancellors of universities. The highest number of connections at the national level was with policymakers from the MOHME (42 connections), so faculty members in all ten surveyed universities had connections with policymakers from this organization. Most of the connections at the provincial level were established with provincial health centers (7 connections) and the Department of Environment (5 connections). Respondents from all universities in the survey were linked with at least one organization at the national level. Notably, Tehran University of Medical Sciences held the largest share among these connections, establishing links with six organizations. However, at the provincial level, the faculty members of 4 universities had no connection with the policymakers. Regarding the variety of organizational connections at the provincial level, Ahvaz Jundishapur University of Medical Sciences had the best situation. It was the only university whose faculty members had connections with policymakers from other provinces (Fig.  3 ).

Organizational network at national and provincial level

Network characteristics

The structural characteristics of the network, and their associated formulas are given in Table  2 . Information on interactive features is also provided in Fig.  4 .

Interactive features of academic-policymaker network

The findings of the investigation of the structural characteristics of the network indicated the limited direct relationships between the members and the low correlation of the network, so the effective density of the network was about 0.15. In other words, 56 respondents, considering the limit of 7 connections in each category (connections with policymakers and peers), were potentially able to establish 1176 connections. However, the total number of links in the network was 177 links (Table  2 ).

The findings related to the network interactive features showed that the request for interaction was often made by policy makers (54.29%). The primary communication between researchers and policy makers has been done mostly in face-to-face meetings (65.72% (. The interaction was mostly aimed to provide advice to policymakers about technical issues (26.07%), sharing research results (22.28%), and requesting research or collaboration in a project (18.96%. ( The researchers acquaintance with policymakers was mostly due to the organizational position of the policymaker (49.52%), being a colleague (22.86%), and working in an advisory committee (20%. ( In 48.57% of cases, researchers had contact with policy makers at least once a year (Fig.  4 ).

Key actors in the network

Academic kbs.

Among the 56 faculty members who had relationships with policymakers or peers, 24 individuals met the criteria established in the research and were eligible to be selected as KBs, Subsequently, four individuals were chosen as academic KBs, as outlined in Table  3 . One was female. Regarding academic position, three were professors, and one was an associate professor. Two had a PhD degree in environmental health engineering, one had a PhD degree in public health, and one had a PhD degree in health education and promotion. They had been at their respective organization between 6 and 28 years. All four KBs had acknowledged that they have been or are currently playing a role as policymakers in the health field at the national or provincial level.

Key policymakers

A total of 94 policymakers at three national, provincial, and university levels were nominated by the respondents. Specifically, the names of 75 policymakers were mentioned once. Furthermore, the names of 19 policymakers were cited multiple times. This included 11 at the national level, five at the provincial level, and three at the university level. The highest frequency of repeating the name of a policymaker in the network was five times, which was related to two policymakers at the national level. Based on the criteria considered, four policymakers at the national level and two policymakers at the university level were selected as key policymakers (Table  4 ).

In this study, using the SNA method, the current state of personal communication between researchers and policymakers in the health field in Iran was depicted. The results show that there are several faculty members in communication network who can play a role as academic KBs in Iran's health sector.

The findings showed a low interaction between researchers and policymakers in the health field in Iran. The low effective density of the network also confirmed that there are not many direct relationships between the network members. So, the possibility of the flow of knowledge obtained from research in the network is low. It indicates that the researchers have little influence on decision-making process in Iran's health sector. Yousefi-Nooraei et al. also showed the existence of a local communication network with low density and limited connections between public health workers in Canada [ 19 ]. However, based on Jessani et al., the frequency of relationships and the degree of influence of public health schools of the Johns Hopkins University in the United States on decisions were evaluated as appropriate [ 20 ]. In another study, Jessani et al. also reported that the level of interaction between faculty members of public health schools and policymakers in Kenya is favorable [ 28 ].

The factors such as lack of mutual trust between researchers and policymakers, lack of attention to long-term research programs and need-based research, and the existence of inappropriate criteria for evaluating the performance of policymakers and academic members in Iran can be considered as reasons for their lack of interest in engaging in EIPM [ 22 ]. In addition, the lack of appropriate incentives for researchers to participate in activities related to the knowledge translation and application of research results can cause researchers to be reluctant. As a result, they are often content only with the production and dissemination of knowledge in the form of articles. McAneney et al. also showed that academic members were less concerned with knowledge transfer as a personal goal than non-academic members of the UKCRC Center of Excellence for Public Health in Northern Ireland. They mainly expected this center to generate new knowledge and had fewer expectations about health interventions and influence on health policies [ 18 ]. Changing the incentive structure based on the publication of research in journals with a high impact factor towards publication in specialized media that have a greater chance of influencing policy and practice can make academic researchers more willing to engage in activities related to EIPM [ 34 ].

Examining the degree of overlapping of communication between faculty members and policymakers, and peers, which is referred to as the depth of communication, indicated the low depth of individual and organizational communication in the network. It shows that most of the communication in the network relies on interpersonal relationships, and probably, there is no clear organizational structure to communicate between health professionals and policymakers. Jessani et al. showed that despite the breadth of connections amang the faculty members at the Johns Hopkins Bloomberg School of Public Health in the United States, the depth of the relationships was generally low, which, together with the heterogeneity of the communication between the faculty members/policymakers, shows that most of the communication relies on interpersonal connections. The diversity of relationships and the creation of stable institutional structures for interaction with policymakers can increase the flexibility of networks at the organizational level and overcome the challenge of dependence on individuals. At the same time, the failure to achieve this can cause the network to disintegrate [ 20 ].

The organizational network analysis also demonstrated the low level of organizational communication between universities of medical sciences and decision-making organizations in Iran's health sector. According to Doshmangir et al., to ensure the successful implementation of EIPM, knowledge-generating organizations should pay special attention to knowledge management and organizational communication management, and increase their communication with their audience, including decision-makers and policymakers. In this regard, removing institutional barriers and using mechanisms and networks for effective interaction between producers and users of knowledge at macro and intermediate (organizational) levels will be effective for individual and institutional capacity building [ 23 ]. Accordingly, creating opportunities for formal and informal interaction, encouraging researchers and policymakers in organizations, and giving organizational support to faculty members willing to interact with policymakers can increase the role of universities of medical sciences and, consequently health research in EIPM. Since, based on the results, the initial communication between researchers and policymakers has mostly been done in face-to-face meetings; it is recommended to hold regular meetings to strengthen the interaction and exchange of information between researchers and policymakers in the health field, by the MOHME as well as other policymaking authorities at the national and provincial levels, and the universities and research centers.

In addition to the need for organizational support, prior acquaintance between researchers and policymakers seems to be an essential factor in forming communication and interaction in the direction of EIPM. The results of the research showed that prior acquaintance between the faculty members and the policymakers was mainly due to personal familiarity, and more than half of the connections were expressed and channeled through being a colleague, having a history of working together in an advisory committee, professor-student relationship, friendship and classmate relationship. As Kotim et al. also showed, actors are more likely to cooperate in the network when they have already cooperated [ 35 ]. Jessani et al. also showed that policymakers prefer to get the experts' opinions through personal and trusted contacts. However, they acknowledge that a delicate balance between using individual relationships and creating more stable organizational partnerships is required [ 36 ]. The results showed that a low rate of these communications was made by a third party who could potentially play the role of a KB. It indicates the existence of a gap in the role of knowledge brokerage in Iran's health sector. According to McAneney et al., academic members attached less importance to the role of KBs and interdisciplinary collaboration [ 18 ].

Additionally, it seems that researchers with executive backgrounds or current executive positions as decision-makers can interact more with policymakers in the direction of EIPM. All four KBs identified in this research admitted that they have played or are playing a role as policymakers in the health field at the national or provincial level in the past or at present. On the other hand, two of the policymakers who had the most connections with the researchers in the network were themselves faculty members of the health educational departments of the studied universities, which can be a justification for their more excellent communication with the faculty members of the research population. Therefore, having the dual role of researcher/policymaker can help to facilitate EIPM and interaction.

A noteworthy point in the drawn network was the presence of some academic faculty members in the network who had a relatively large number of direct connections with policymakers, especially at the national level, but had no or few connections with their peers in order to share research results with policymakers. For example, node FT01 had the most relationship with policymakers. However, it did not play a role in facilitating communication between peers and policymakers. So, it lacked the conditions of knowledge brokering in this research. Jessani et al. showed that although people with strong relationships with policymakers are less likely to contact their peers to access policymakers, they are more likely to receive more requests from their peers to help and connect them with policymakers [ 28 ]. Since these people can provide potential opportunities to involve research in policymaking through connection with policymakers, by identifying these people and training them to acquire the necessary skills, their influence can be used at the service of knowledge brokering to facilitate communication between researchers and policymakers.

Research limitations

Because, about half of the members of the research population did not answer the sociometric questionnaire and some of the respondents refused to mention the names of policymakers and their peers (and therefore were excluded from the study), the drawn network cannot give a complete picture of the existing relationships between faculty members and policymakers in Iran's health sector. Besides, since the sociometric questionnaire was completed only by the faculty members of the research community and no survey of policymakers and peers was conducted, we cannot confirm the bidirectionality of relationships.

Based on the results, it seems that the flow of knowledge produced by research in the health field in Iran is not realized well from the producers of research evidence to the users of knowledge. Accordingly, it seems necessary to consider incentives and support mechanisms to strengthen the interaction between researchers and policymakers in Iran's health sector. In this context, measures such as creating and strengthening individual and organizational incentives to produce valid and effective scientific evidence, increasing research cooperation between researchers and policymakers, revising the regulations for the scientific promotion of the academic community, providing educational programs to promote the culture of using research evidence in policymaking, and providing formal and informal interactions between researchers and policymakers to encourage their participation in activities related to EIPM are recommended. Formulating strategies to institutionalize the culture of knowledge translation and EIPM in the strategic planning of universities and research institutes can help structure this process.

Moreover, by examining the communication network of faculty members in different universities, it is possible to identify people who can play the role of KB. By organizing these people in the form of knowledge brokerage groups, their capabilities can be used to facilitate communication between researchers and policymakers and to apply the results of research in the health field. To achieve this goal, the MOHME and Iranian medical sciences universities should establish formal and structured knowledge brokering activities. One way to accomplish this is by establishing a knowledge translation committees. To discover and benefit from existing relationships between researchers and policymakers, SNA studies should be conducted regularly by universities. This will help identify and utilize the individual and organizational capacities needed to realize this goal. Identifying the existing gaps in the communication network helps in the necessary planning to solve these gaps and to create and develop targeted networks. It is suggested to study the communication network status of researchers and policymakers in other fields related to Iran's health system.

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https://isid.research.ac.ir [Accessed Jan 2020].

Abbreviations

• Evidence-informed policymaking

Knowledge Brokers

Ministry of Health and Medical Education

Social Network Analysis

University of Medical Sciences

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Acknowledgements

The authors wish to acknowledge the contribution of all participants who took part in the study.

This article is an excerpt from a doctoral dissertation in the field of medical library and information sciences, which is done with the support of the Research and Technology Vice-Chancellor of Isfahan University of Medical Sciences, under the scientific code 398401.

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Minimal criteria for reporting mesenchymal stem cells in veterinary regenerative medicine

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The widespread application of mesenchymal stem cells (MSCs) in veterinary regenerative medicine highlights their promising therapeutic potential. However, the lack of standardized characterization and reporting practices across studies poses a significant challenge, compromising the assessment of their safety and efficacy. While criteria established for human MSCs serve as a foundation, the unique characteristics of animal-derived MSCs warrant updated guidelines tailored to veterinary medicine. A recent position statement outlining minimal reporting criteria for MSCs in veterinary research reflects efforts to address this need, aiming to enhance research quality and reproducibility. Standardized reporting criteria ensure transparency, facilitate evidence synthesis, and promote best practices adoption in MSC isolation, characterization, and administration. Adherence to minimal reporting criteria is crucial for maintaining scientific rigor and advancing the field of veterinary regenerative medicine. Ongoing collaboration among stakeholders is essential for effective implementation and adherence to updated guidelines, fostering excellence and innovation in MSC-based therapies for animal patients.

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The authors thank the Director, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, India, and the All-India Network Program on Diagnostic Imaging and Management of Surgical Conditions in Animals (AINP-DIMSCA) for providing the necessary facilities to carry out this work.

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Ux research methods: glossary.

September 10, 2023 2023-09-10

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UX research requires knowledge and understanding of many jargon terms. Use this glossary as a reference as you delve into research.

Jump to a definition in the table or review the complete glossary.

Attitudinal Methods

A class of research methods that collects self-reported data about users’ perceptions and attitudes. Attitudinal data is based on “what users say.” Surveys, user interviews, and focus groups are attitudinal methods. Attitudinal methods are often contrasted with behavioral methods, which collect data about user actions and behaviors.

• See also: behavioral methods

A/B test (A/B testing)

An analytics method that involves randomly deploying two different versions of a product to two different user groups in order to identify which works best. The winning version is usually selected based on metrics such as conversion rate or click-through rate. To conduct an A/B test, you will need to install specialized analytics software.

• Related article: Putting A/B Testing in Its Place
• See also: analytics , multivariate testing

A class of research methods that involve collecting real-time usage data for a product. Examples of collected metrics include the number of user visits, the number of clicks on a particular element, percentage of users who took a particular action (e.g., checkout, scroll) on a web page. Analytics research methods are not controlled: the data collected reflects users’ behaviors in their natural environment. Using such methods requires that the product is instrumented with analytics software such as Adobe Analytics or Google Analytics.

• Related article: Three Uses for Analytics in User-Experience Practice
• See also: A/B testing , multivariate testing , clickstream analytics

Behavioral Methods

A class of research methods that collect data reflecting users’ actions and behaviors. Unlike attitudinal methods, which are based on “what users say,” behavioral methods are based on “what users do.” Examples of behavioral methods include usability testing and analytics methods.

• See also: attitudinal methods

Card Sorting

A research method in which study participants group individual labels according to criteria that make sense to them. This method helps designers to group items into categories and create an information architecture of a site or application. Card sorting can be “open” (if the categories are not defined in advance of the study and participants group similar items into clusters) or “closed” (if a predefined set of categories is given to participants and they are asked to assign items to these categories).

• Related article: Card Sorting: Uncover Users' Mental Models for Better Information Architecture
• See also: tree testing

Clickstream Analytics 

An analytics method that involves analyzing the sequence of pages that users visit as they use a site or application. It can provide insights about potential issues, typical navigation routes, and the content that users interact with right before completing key actions on a site or in an application.

• Related article: Understanding User Pathways in Analytics
• See also: analytics

Concept Testing

An attitudinal research method that involves collecting users’ thoughts and attitudes about a product idea (“concept”) in its incipient stages, usually through a qualitative survey. It is used very early in the discovery phase of the design process to understand whether a specific product idea meets users’ needs and expectations.

• See also: survey

Context Methods

A class of research methods that involves capturing the context in which users naturally engage in a specific behavior. The context can be captured directly, by observing users in their natural environment (field studies), or indirectly, by asking them to log context details whenever that behavior occurs (diary studies).

• Related article: Context Methods: Study Guide
• See also: diary study , field study

Contextual Inquiry

A type of field study in which the researcher watches the user as they naturally perform their task in their normal environment (e.g., home, office) and asks for information to understand how and why the user did what they did. Contextual inquiry is a combination of in-depth observation and interview and aims to gain a robust understanding of work practices and behaviors. Contextual inquiry is typically conducted in the early discovery stages of a project.

• Related article: Contextual Inquiry
• See also: field study , context methods

Desirability Study

A research method that involves exposing participants to a product and then asking them to select a few words that describe their reaction to that product out of a list of possible options. This type of method can be done qualitatively or quantitatively, to assess the aesthetic properties of an image and whether they are consistent with a desired brand image.

• Related article: Using the Microsoft Desirability Toolkit to Test Visual Appeal
• See also: five-second test

Diary Study

A research method used to collect self-reported data about user behaviors, activities, and experiences over an extended period that can range from a few days to months. During that period, study participants are asked to keep a diary and log specific information about the activities of interest.

• Related article: Diary Studies
• See also: context methods

Ethnographic Study

A class of qualitative research methods that involves observing users in their natural habitat. In UX, the term is used as a synonym for “field study.” However, in social sciences, ethnographic studies involve immersion in a particular culture or community, to observe the behaviors and rules of that community.

• Related article: Field Studies

Eyetracking

A behavioral research method that involves tracking users’ eye movements as they interact with a product or perform a specific activity, to determine where they focus their attention. Eyetracking studies require special equipment to capture participants’ eye movements. Eyetracking data can be used to understand which design elements attract users’ attention and which are ignored.

• Related article: Text Scanning Patterns: Eyetracking Evidence
• See also: retrospective think aloud

Field Study

A research method that involves observing the users in their natural context. Field studies are a type of context method. Field studies vary in the amount of interaction between the researcher and the participant. Some field studies are purely observational, while others involve active participation from the researcher in the form of interviews or tasks given to the user.

• See also: context methods , diary study , ethnographic study

First-Click Test

A behavioral, task-based research method in which participants are given a specific task before they are exposed to a design and then stopped immediately after their first click on the corresponding screen. This test works best when users have a specific goal in mind the first time they encounter the site. The first-click test is similar to the five-second test in that they are both very quick; however, in the first-click test, participants are likely to ignore most page elements that are not directly related to their goal.

• Related article: How to Test Visual Design

Five-Second Test

An attitudinal research method in which a study participant is shown a design for five seconds and then asked to describe what they saw. A five-second test is meant to gather users’ first reactions to the aesthetic qualities of a design.

• Related video: 5-Second Usability Test
• See also: desirability test

Focus Group

A qualitative, attitudinal research method in which a facilitator conducts a meeting with a group of 6–9 people to discuss their experiences with a product or service. The term “focus” relates to the role of the facilitator, who maintains the group’s focus on certain topics during discussions. Focus groups are used in the early discovery stages of product development to gauge users’ mental models and expectations.

• Related article: Focus Groups
• See also: attitudinal methods , qualitative methods

Formative Method

Any method that focuses on determining which aspects of the design work well or not, and why. Formative evaluations occur throughout a design or redesign and provide information to incrementally improve the interface. Formative methods are often contrasted with summative methods, which are used after a design has been finalized to provide an overall assessment of its usability.

• Related article: Formative vs. Summative Evaluations
• See also: summative method

Moderated Usability Testing

The traditional type of usability testing which involves a facilitator (moderator) and a participant interacting synchronously. The facilitator gives participants tasks to do one at a time and may probe with further questions and clarifications; they can also ask the participant to stop when they consider it necessary.

• Related article: Moderated (Usability) Testing
• See also: usability testing , unmoderated usability testing

Multivariate Test

A design-optimization method in which multiple variants of specified design elements are tested in a user interface, with the goal of maximizing an analytics metric such as conversion. This method determines which combination of the variants results in the highest-performing design. For example, a multivariate test could be used to determine whether a button should be labeled Place Order or Submit and whether it should be blue or red.

• Related article: Multivariate vs. A/B Testing: Incremental vs. Radical Changes
• See also: A/B testing , analytics

Participatory Design

A research method in which one or several users are invited to offer their own solution to a particular design problem. Participants may be provided with some basic building blocks that they could use to create their designs. The resulting designs are not usually implemented, but rather used to get an understanding of users’ needs and expectations.

Paper Prototyping

A type of usability testing that is related to the Wizard of Oz method and in which an early-stage design is shown to the participant on paper. The piece of paper schematically represents the prototype of a specific page. The participant indicates to the facilitator which action(s) they would take on that page in order to complete the assigned task. The facilitator (or another person present in the room who plays the role of the computer) then changes the page to reflect the new state of the system. Paper prototyping is a type of prototype testing.

• Related article: Paper Prototyping: A Cutout Kit
• See also: usability testing, prototype testing , Wizard of Oz

Prototype Testing

A type of usability testing in which the interface being tested is a design prototype rather than a live product. The prototype can be presented to the participant on paper (paper prototyping) or using interactive prototyping software. Prototype testing is used before a design is implemented to identify potential usability issues and fix them, or to explore how alternative design solutions fare with users.

• See also: paper prototyping , usability testing

Qualitative Method

A type of research method that aims to collect observational data about users’ behaviors and interactions. Such data may identify whether particular aspects of the interface are easy or hard to use. Focus groups and user interviews are examples of qualitative methods. Usability testing can also be qualitative when used to uncover issues in a design.

• Related article: Quantitative vs. Qualitative Usability Tests
• See also: qualitative method

Qualitative Usability Testing

A type of usability testing that aims to collect observational data about user behaviors and interactions and that is often used to identify problems in an interface. Qualitative usability testing can be moderated or unmoderated.

• See also: usability testing , qualitative method , quantitative usability testing

Quantitative Method

A type of research method that collects metrics such as success, satisfaction, conversion, task time, or number of user visits. Quantitative methods focus on numbers. Examples of quantitative methods include analytics-based methods and quantitative usability testing. In quantitative usability testing, metrics such as task time and success are gathered in order to assess whether particular tasks are easy to perform.

• See also: quantitative method

Quantitative Usability Testing

A type of usability testing that collects metrics such as task success, user satisfaction, and time on task to understand whether particular tasks were easy to perform. Quantitative usability testing is usually used to assess the overall experience of a product and make inferences about user behavior in the target user population.

• See also: usability testing , quantitative method , qualitative usability testing

Remote Research Method

Any type of research method that involves a facilitator and one or more participants and in which the participant is in a different location than the facilitator. Usability testing, focus groups, user interviews, and contextual inquiries can be done remotely, with various degrees of success.

• See also: usability testing , moderated usability testing , remote moderated usability testing

Remote Moderated Usability Testing

A type of user testing in which the facilitator and the participant are not in the same room and interact through video-conferencing software.

• Related article: Remote Moderated Usability Tests: How to Do Them
• See also: usability testing , moderated usability testing , remote research method

Retrospective Think-Aloud Protocol

A variation of the think-aloud protocol in which participants are asked to explain their behavior immediately after they interact with a product. In a variation of the protocol, participants may be shown a replay of their interaction and asked to explain out loud what they were thinking when they were doing those actions. Retrospective think-aloud is used in situations where thinking out loud would be too distracting for participants (e.g., during complex activities) or would contaminate data (e.g., in eyetracking or quantitative usability testing).

• See also: think aloud , usability testing , eyetracking

Summative Method

A research method that focuses on evaluating the user experience of a product, usually by comparing it with that of a competitor or of one of its own prior versions. Quantitative usability testing is usually used as a summative method.

• See also: formative method

A research method in which a participant responds to multiple-choice or open-ended questions that are presented to them online, on paper, or by phone. Surveys are an attitudinal research method that collects participants’ self-reported perceptions and attitudes. Surveys can be used to collect qualitative or quantitative data.

• Related article: 10 Survey Challenges and How to Avoid Them

Task Analysis

A research method that studies how users perform a specific task: their goals, the different steps they take, the order in which they do them, when and where they do it, and what information they need during the task. Task analysis often involves a mix of interviews and context methods such as contextual inquiry, field studies, or diary studies. It is used to inform the design of complex workflows for a product.

• Related article: Task Analysis: Support Users in Achieving Their Goals
• See also: contextual inquiry , user interview ,  field study , ethnographic study , context methods

Think-Aloud Protocol

The practice of asking a usability-testing participant to “think out loud” as they are interacting with an interface – in other words, to verbalize their actions and thoughts. It is widely used in qualitative usability testing to supplement the behavioral data provided by the participant’s actions.

• Related article: Thinking Aloud: The #1 Usability Tool
• See also: retrospective think-aloud protocol , usability testing

Tree Testing

A task-based research method that evaluates a hierarchical category structure (or tree) by having users find the locations in the tree where specific resources or features can be found. It is an information-architecture method used to assess how well the navigational hierarchy of a site matches users’ expectations.

• Related article: Tree Testing
• See also: card sorting

Unmoderated Usability Testing

A type of usability testing in which there is no facilitator (moderator) and in which the tasks are presented to the participant by special software. Unmoderated testing is usually remote, with the participant testing the software at their location of choice, through an Internet connection. However, it is possible to run unmoderated usability tests in person, by having the participant interact by themselves with the interface of interest.

• Related article: Unmoderated User Tests: How and Why to Do Them
• See also: usability testing , remote moderated usability testing , remote research method

Usability (UX) Benchmarking

A type of summative research method that involves evaluating a product’s user experience by comparing its performance against a competitor or a previous version of the same product. Many UX benchmarking studies are quantitative usability-testing studies in which participants perform a set of top tasks; metrics such as task success, task time, and satisfaction are collected and compared across product versions or competitors.

• Related article: Benchmarking UX: Tracking Metrics
• See also: quantitative usability testing ,  quantitative method , summative method

User Interview

A one-on-one attitudinal research method in which an interviewer asks a participant questions about a topic, listens to their responses, and follows up with further questions to learn more details. User interviews can be used by themselves in discoveries to inform the early stages of product design or can be combined with other methods such as contextual inquiry and usability testing.

• Related article: User Interviews: How, When, and Why to Conduct Them

User Testing

See usability testing

Usability (User) Testing

A research method in which a researcher (called a “facilitator” or a “moderator”) asks a participant to perform tasks, usually using one or more specific user interfaces. While the participant completes each task, the researcher observes the participant’s behavior and listens for feedback. Usability testing can be qualitative or quantitative. Qualitative usability testing is used to identify problems in an interface, whereas quantitative usability testing focuses on collecting metrics that help assess the overall user experience of the product.

• Related article: Usability Testing
• See also: qualitative usability testing , quantitative usability testing , think-aloud protocol , unmoderated usability testing , moderated usability testing

Wizard of Oz

A moderated research method in which a participant interacts with a prototype manned by a human who controls the system responses. This method is used to test early stages of the design, before investing resources in developing it. It is also used to understand users’ expectations, mental models, and vocabularies.

• Related article: The Wizard of Oz Method in UX
• See also: paper prototyping

Is there a method that you think is missing? Please send suggestions at [email protected] and we will consider them for further versions of this glossary.

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