user research masters

User Experience, Master of Science

User Experience

Master of Science

Course Delivery

Total Credits

Credit Hour

Minimum Duration

• Program Details

Course Information

Admissions requirements.

• Tuition & Fees

Program Overview

The Department of Information and Media offers a fully online, asynchronous masters-level program in User Experience (UX) to accelerate career prospects of early and mid-career professionals for leadership roles. UX focuses on humans interacting with technologies, as well as business goals, during the design process to create user-centered and socially responsive interactive technologies, applications, and information systems. The program enables students to earn a masters from one of the world’s leading programs without the expense and overall challenges associated with leaving their home or job. The 30-credit program emphasizes a “user-first” perspective, meaning it integrates knowledge of human-computer interaction with industry-relevant methods and social responsibility to prepare students for real-world experiences in the workplace, including technical and/or management careers in user-first experience design and human-centered research.

Program Outcomes

This premier online graduate user experience program combines user-first theoretical and practical knowledge of experience design that will help students build their skills and expertise to become champions of change, drivers of innovation, and creators of sustainable user experiences and engagements. With a Master of Science in User Experience from MSU, graduates will be prepared to:

• Become a UX leader, driving the technology behind product design and marketing
• Qualify for UX job roles such as designer, researcher, or project manager
• Design more usable and accessible websites, software, and products for diverse audiences
• Collect, analyze, and interpret user experience data to inform decision making
• Advance dynamic IT developments in the 21st century global workplace

Career Outlook

The User Experience program will position students for rewarding, well-paying careers in human-computer interaction, user experience design, and human-centered research. Graduates will have job titles that reflect the major UX areas:

• UX Design: UX designer, experience designer, interaction designer, or information architect
• UX Strategist: UX strategist, UX architect, UX product manager, or UX analyst
• Visual Design: Visual information designer, user interface (UI) designer, UI artist, or digital designer
• Research and Usability: UX researcher or usability researcher/specialist/analyst
• Content: Content strategist or UX copywriter

A Top-Ranked Education

• 31st among Best Public Universities in America — U.S. News & World Report, 2022
• A Top 100 Global University — Times Higher Education and U.S. News & World Report

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Jeff  Siarto

Interim program director of ux, ms.

Jeff is a UI/UX designer, author, and technologist with over 15 years of experience building web and software user interfaces. Since 2013 he’s been working with NASA and other organizations to help make remote sensing and Earth Science data more usable and actionable for scientists, engineers, and the general public.

UX 800 - User Research and Design, 3 credits

UX 802 - Current Topics in UX, 3 credits

UX 805 - Quantitative Analysis and Insights in UX, 3 credits

UX 810 - Social Science for Design, 3 credits

UX 815 - Programming Fundamentals for UX, 3 credits

UX 820 - Usability Evaluation, 3 credits

UX 825 - Visual Design Fundamentals, 3 credits

UX 830 - Design for Interactivity, 3 credits

UX 835 - Accessibility and Design, 3 credits

UX 840 - UX and Society, 3 credits

UX 898 - User Experience Capstone/Practicum, 3 credits

To be accepted to this program, you must have:

• A bachelor's degreefrom a recognized, accredited educational institution (Minimum of 3.0 undergraduate GPA). No GRE required.
• Previous work experience preferred (Résumé/CV, portfolio is optional)
• TOEFL/IELTS scores if English is not your native language
• A written personal statement detailing your professional interests and goals
• Letter of recommendation
• Official transcripts from all previous schools

To apply to this program:

• Complete a departmental and university graduate application 
• Submit all official transcripts

Fall Semester

Application Deadline

Spring Semester

December 10th

Tuition & Fees per credit

The university reserves the right to make changes in the types, structures, rates for fees, and tuition. Every effort will be made to give as much advance notice as possible.

The MSU Value Promise

You can be ensured a return on your investment at Michigan State University.

As one of the top research universities in the world, Michigan State University has advanced the common good with uncommon will for more than 160 years. MSU pushes the boundaries of discovery and forges enduring partnerships to solve the most pressing global challenges while providing life-changing opportunities to a diverse and inclusive academic community.

MSU has been offering online degree programs for over 20 years. Our maturity is evident in the high quality of the learning experience enjoyed by our online students.

MSU provides programs and initiatives that support and enhance diversity. We will expand our campus and external partnerships to put in place inclusive recruitment and retention practices. We nurture and promote individuals’ varied experiences and perspectives, ensuring structures and processes make possible full participation by all members of our community.

MSU’s nationally recognized online programs foster student growth and well-being throughout their academic career. We will expand inclusive mentoring practices and accelerate improvement across units to implement evidence-based practices to ensure our students complete successfully.

Continuing education  can be one of the most exciting, challenging, and rewarding experiences you undertake in your life. We hope you consider becoming a Spartan, to learn online and reach your career goals.  With highly ranked online programs and exceptional professors, we educate students who advance the common good with uncommon will.

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The School of Information is UC Berkeley’s newest professional school. Located in the center of campus, the I School is a graduate research and education community committed to expanding access to information and to improving its usability, reliability, and credibility while preserving security and privacy.

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The School of Information offers four degrees:

The Master of Information Management and Systems (MIMS) program educates information professionals to provide leadership for an information-driven world.

The Master of Information and Data Science (MIDS) is an online degree preparing data science professionals to solve real-world problems. The 5th Year MIDS program is a streamlined path to a MIDS degree for Cal undergraduates.

The Master of Information and Cybersecurity (MICS) is an online degree preparing cybersecurity leaders for complex cybersecurity challenges.

Our Ph.D. in Information Science is a research program for next-generation scholars of the information age.

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The School of Information's courses bridge the disciplines of information and computer science, design, social sciences, management, law, and policy. We welcome interest in our graduate-level Information classes from current UC Berkeley graduate and undergraduate students and community members.  More information about signing up for classes.

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Research by faculty members and doctoral students keeps the I School on the vanguard of contemporary information needs and solutions.

The I School is also home to several active centers and labs, including the Center for Long-Term Cybersecurity (CLTC) , the Center for Technology, Society & Policy , and the BioSENSE Lab .

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The Goldman School of Public Policy, the CITRIS Policy Lab, and the School of Information hosted the inaugural UC...

Dr. Diag Davenport has been appointed as an assistant professor at UC Berkeley as part of a joint search in...

At the Women in Data Science conference held at UC Berkeley this past week, four educators affiliated with the...

At the UC Berkeley School of Information, two educators have taken the initiative to begin incorporating data...

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Morgan Ames

Jenna Burrell

Kimiko Ryokai

Recent publications.

When you go to a new healthcare clinic in the United States, doctors and nurses pull up your patient record based on your name and birthdate.  Sometimes it’s not your chart they pull up.  This is not only a healthcare problem; it’s a data science problem.

In The Charisma Machine , Morgan Ames chronicles the life and legacy of the One Laptop per Child project and explains why — despite its failures — the same utopian visions that inspired OLPC still motivate other projects trying to use technology to “disrupt” education and development.

User Experience Research news

A group of researchers, including the I School’s own Professor Kimiko Ryokai, recently received a grant of $1.29M from the National Science Foundation (NSF) to tackle this challenge.

Would you prefer a chart or text when being presented with information? Ph.D. student Chase Stokes has dedicated his studies to answering this question.

ScholarPhi is an augmented reading interface that makes scientific papers more understandable and contextually rich

Professors Hany Farid and Joshua Blumenstock have been awarded seed funding for their projects designed to mitigate the COVID-19 crisis by CITRIS and the Banatao Institute.

Prof. Farid: “Coronavirus misinformation is going to get a lot of people killed.”

I School researchers have developed a custom-fit earpiece that that can capture “passthoughts” through brainwave signals from the ear canal, and for the first time demonstrated one-step three-factor authentication.

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The Best Masters in UX Design Programs: 2024 Guide

Time, money, and a whole lot of hard work. Enrolling in a UX design program is a huge commitment — so you want to make sure you make the most informed choice. 

In this article, we’ll explore our 10 best masters in UX design programs. 

We’ll then answer the question of whether you should do a masters in UX design or whether an online UX certification or other bootcamp may be a better option for you.

To skip ahead to a section, simply use this clickable menu:

• Carnegie Mellon University
• Stanford University
• Georgia Tech
• New York University
• University of Washington
• UC Berkeley
• California College of the Arts
• Parsons School of Design
• DePaul University
• Rochester Institute of Technology

Should you do a masters in UX design?

Top 10 masters in ux design programs.

Masters in UX design often have very different official course titles, despite covering the same material. For the purpose of assessing a wide range of masters programs in this article, we have included those with titles other than UX design.

Let’s explore some of the best masters programs out there!

1. Carnegie Mellon University:

Master of human-computer interaction.

Length: 1 year Total tuition: $77,784 Location: Pittsburgh, PA Class size: 60 students/year Attendance: Full-time preferred; part-time possible Format : Campus Founded: 1997 Application fee: $100

ADMISSION REQUIREMENTS

GPA: No min SOP: Required Resume: Required Recommendation: 3 letters TOEFL: 100 (25 per subsection) IELTS: Not required GRE: Required Portfolio: Optional

The Master of Human-Computer Interaction (MHCI) at Carnegie Mellon University is one of the best UX design masters.

Self-described as “the first program in the world dedicated to preparing professionals for careers related to human-computer interaction, user experience design, and user-centered research,” the program draws students from a huge range of backgrounds.

Students with varying degrees of industry experience—and backgrounds in design, social science, business and computer science, and more—attend the (generally full-time) one-year program on campus in Pittsburgh, PA.

One factor behind its strong reputation is that Carnegie Mellon University is known for its tough admission criteria. Graduates are respected not only in the design space but also in the broader world of tech.

Their comprehensive Post-Graduation Outcomes Dashboard highlighted the number of their graduates who find employment with the likes of Google, Amazon, Facebook, Microsoft, and Apple:

Source: Carnegie Mellon University

2. Stanford University: M.S. in Design Impact 

Length: 2 years Total tuition: $75,240 Location: Stanford, CA Class size: 13 students/year Attendance: Full-time Format : Campus Founded: 2018 Application fee: $125

GPA: No minimum SOP: Required Resume: Required Recommendation: 3 letters TOEFL: 100 IELTS: Not required GRE: Not required Portfolio: Required

Regularly ranked in the top two or three US colleges, and in the top three or four worldwide, Stanford University is a globally acclaimed institution.

Its M.S. in Design Impact (DI), a full-time, two-year program established in 2018, shares that reputation. 

Founded on the idea that design is broader than products, experiences, and systems, the program explores “the technologies and data that power the above” as well as “the implications and consequences of all of our work in the world in the short and long term.”

With the objective of grounding students in the full problem space of this interconnected landscape, the M.S. in Design Impact has three focus areas:

Design Core: I ncluding Project-Based Design Work, Human Factors, Design Ethics, Leadership, and Visualization

Methods: A choice of three focus areas that enable students to effectively implement their design abilities with methods such as analysis, describing phenomena, and design problem application.

Domain: A domain focus area from appropriate courses to gain added knowledge in a field of interest to them.

3. Georgia Tech:

Master of human computer interaction.

Length: 2 years Total tuition: $70,816/2 years (out-of-state); $32,128/2 years (in-state) Location: Atlanta, GA Class size: 52 students/year Attendance: Full-time Format : Campus Founded: 1998 Application fee: $85

GPA: 3.0 SOP: Required Resume: Required Recommendation: Asked letters TOEFL: 100 IELTS: Not required GRE: Required Portfolio: Optional

Established in 1998, Georgia Tech’s Master of Human Computer Interaction (MS-HCI) is something of a veteran among the programs we look at. It has both a very strong US reputation and a growing global one.

Like many of the masters in UX design and HCI, Georgia tech’s program is an interdisciplinary offering. Four schools offer the program collaboratively:

• Industrial Design
• Interactive Computing
• Literature, Media, and Communication (LMC)

Its aim is to equip students with the practical skills and theoretical understandings they need to develop into “leaders in the design, implementation, and evaluation of the next generation of human-computer interfaces”.

4. New York University: Integrated Design & Media, M.S.

Length: 2 years Total tuition: $115,680 Location: New York, NY Class size: 110 students/year Attendance: Full-time Format : Campus or online Founded: 1979 Application fee: $65

GPA: No minimum SOP: Required Resume: Required Recommendation: 2 letters TOEFL: Not required IELTS: Not required GRE: Required Portfolio: Required

New York University’s MS in Integrated Digital Media has built its reputation as one of the best UX masters programs because of its emphasis on art and aesthetics. It combines art and technology in a unique, challenging, and fluid way.

Only the second program on our list to offer students the chance to learn online or with a blended mix of campus and online, the Integrated Design & Media, M.S. is set up to cater to all career levels.

And—whatever career stage you’re at— you’ll get to experience new ways of understanding culture, technology, and society and how these inform technological design.

If “The Big Apple” holds the same mystique for you as it does for most of us, you can tap into an unparalleled cultural and technological experience right at its core.

5. University of Washington:

Master of human-computer interaction and design.

Length: 1 year Attendance: Full-time Total tuition: $$55,430 (2023-24) Location: Seattle, WA Class size: 30 students/year Format : Campus Founded: 2013 Application fee: $85

GPA: 3.2 SOP: Required Resume: Required Recommendation: 3 letters TOEFL: 106 (26 speaking) IELTS: Not required GRE: Not required Portfolio: Optional

Taught on campus in Seattle, the University of Washington’s Master of Human-Computer Interaction and Design (MHCID) is undoubtedly one of the finest masters in UX design out there.

It’s a multidisciplinary program, with course content provided collaboratively by four departments:

• Computer Science & Engineering
• Human-Centered Design & Engineering
• The Information School
• Division of Design in the School of Art + Art History + Design

The program’s unique, cross-disciplinary approach is designed to cultivate “a new generation of designers, engineers, and researchers” with an education that enables them to “successfully combine the creative aspects of design and the study of human behavior with the analytical techniques of engineering”. 

And—judging by their strong graduate outcomes—they’re doing something right.

95% of the program graduates are employed within six months (70% within three months and the majority join large enterprises (5,000+ employees) in tech. This infographic from the course website shows where their graduates land:

Source: University of Washington

6. UC Berkeley: Master of Design  

Length: 1.5 years Total tuition: $73,130 Location: Berkeley, CA Class size: 23 students/year Attendance: Full-time Format : Campus or online Founded: 2020 Application fee: $140

GPA: 3 SOP: Required Resume: Required Recommendation: 3 letters TOEFL: 90 IELTS: 7 GRE: Not required Portfolio: Required

UC Berkeley’s reputation is global, and it won’t surprise many to see its Master of Design (MDes) feature in our list. 

Based on three pillars—technical rigor, design theory, and social practice—the program is aimed at early to mid-career professionals who want to pursue work “at the intersection of design and technology”.

With this in mind, UC Berkeley students are offered the chance to work in fields such as artistic production, technological innovations, product design, and design interventions in cities.

Students are also pushed to develop intelligent new approaches and design toolkits to respond to the changing dynamics of technologies like artificial intelligence, augmented and virtual reality, sensing, and the internet of things. 

At the same time, they’re encouraged to take a wider perspective and understand the underlying ethical concerns and questions about their possible, often unforeseen, impacts. 

7. California College of the Arts:

Mdes in interaction design.

Length: 1 year Total tuition: $63,900 Location: San Francisco, CA Class size: 45-60 students/year Attendance: Full-time Format : Campus or online Founded: 2016 Application fee: $70

GPA: No minimum SOP: Required Resume: Required Recommendation: 2 letters TOEFL (or IELTS): 100 IELTS (or TOEFL): 7.5 GRE: Not required Portfolio: Required

Staying on the west coast—the heart of Silicon Valley to be precise—the MDes in Interaction Design at California College of the Arts is the next masters on our list.

Promising aspiring designers the chance to “build the most in-demand design toolkit in the world today” this is a program focused on cultivating systems thinking, design leadership development, and iteration and collaboration skills.

Priding itself on creating skills that can have “measurable social impact”, this MDes is centered on designing for the environment, public health, transportation, education, and other major industries. 

8. Parsons School of Design:

M.f.a. in design and technology .

Length: 2 years Total tuition: $103,500 Location: New York, NY Class size: 80 students/year Attendance: Full-time Format : Campus or online Founded: 1997 Application fee: $50

GPA: No minimum SOP: Required Resume: Required Recommendation: 2 letters TOEFL (or IELTS): 92 IELTS (or TOEFL): 7 GRE: Not required Portfolio: Required

Another New York-based option, Parsons School of Design offers an M.F.A. in Design and Technology (DT) which takes a broad and critical approach to tech. Students at Parsons will enter a dynamic, challenging, idea-driven environment that pushes them to think about the “ever-present impact that computational technologies have on our lives”. 

With a wider scope than some other masters programs in the field, students at Parsons can focus on areas of practice including wearable technology, game design, new media art, digital fabrication, physical computing, interaction design, data visualization, and critical design.

9. DePaul University:

M.s. in human-computer interaction.

Length: 2.5 years Total tuition: $44,980 (2022-23) Location: Chicago, IL Class size: 100 students/year Attendance: Full-time, part-time Format : Campus and online Founded: Unknown Application fee: $25

GPA: 2.5 SOP: Not required Resume: Required Recommendation: Optional letters TOEFL (or IELTS): 80 (17 each subsection) IELTS (or TOEFL): 6.5 GRE: Not required Portfolio: Not required

Part of DePaul University’s Jarvis College of Computing and Digital Media, the Master of Science in Human-Computer Interaction (HCI) program teaches students how to “ideate, design, implement, and evaluate computer-based technologies so they are useful and usable for end users.”

An interdisciplinary degree, the program draws on concepts and methods from computer science, graphic design, and the social sciences to offer a well-rounded education.

Students are encouraged to pursue user-centered and participatory design approaches in creating dynamic websites, mobile apps, desktop applications, and more.

DePaul’s program has a good reputation with employers and graduates have found well-remunerated employment with a range of major corporations, as this graphic from the course website illustrates:

Source: DePaul

10. Rochester Institute of Technology:

Length: 2 years Total tuition: $100,272 Location: Rochester, NY Class size: 25 students/year Attendance: Full-time, part-time Format : Campus or online Founded: 2004 Application fee: $65

GPA: 3 SOP: Required Resume: Required Recommendation: 2 letters TOEFL (or IELTS): 88 IELTS (or TOEFL): 6.5 GRE: Required Portfolio: Not required

Based in Rochester, NY, a small city (by US standards) on the shore of Lake Ontario, Rochester Institute of Technology (RIT) boasts an acclaimed M.S. in Human-Computer Interaction (HCI) .

Students explore “the design methods, evaluation, and implementation of interactive computing systems for human use” to build the skills needed for a career in UX design or research. They focus on creating professionals who understand the shift away from the desktop user and know how evolving tech can be designed to be intuitive, effective, and even compelling.

Perhaps unsurprisingly—with program hiring partners including the likes of Cisco, HubSpot, HP, Bose Corporation, and many more—graduates from RIT tend to fare well in their careers. Graduates report job titles such as UI/UX Designer, Interaction Designer, Usability Specialist, Product Designer, and User Experience Researcher.

Now that we’ve looked at ten of the best masters in UX design out there, let’s quickly wrap up with some final thoughts.

There is no easy answer to this, other than: “it depends”.

There are many factors that you’ll need to weigh up before deciding whether to do a UX design master.

Ultimately, it will hinge on your unique personal situation, so think about things like: 

• How much time you can invest (and whether you can study full-time or part-time)
• How much money you can invest
• Whether you can relocate for campus study if required or would rather go online 
• Whether you need an accredited program (if you’re an expat or soon-to-be expat for example)
• How much the prestige (or otherwise) of the institution matters to you
• Your learning style
• Your career goals

We realize this is a lot to think about. So—to help you get started with your decision—here are three win pros and cons of UX design masters, as opposed to UX design certifications.

Pros of masters in UX design

• Prestige: Some masters in UX Design (or HCI) carry more prestige than other types of certification. This will vary from employer to employer though, and UX teams at the best employers are often made up of designers with masters degrees, online certifications, and even self-taught skills.
• Career prospects: Related to the prestige factor, some employers will look more favorably on candidates with a UX design masters over a certification. Bear in mind that this generally applies less and less the further along in your career you get, as your experience and portfolio—and ability to explain them both—become key drivers of your career path.
• Formal and structured: Masters in UX design are typically more formal than other UX certifications and often require in-person attendance at lectures or seminars. 

Cons of masters in UX design

• Long: Doing a masters in UX design will take you a minimum of one year of full-time study, often going to two years or even longer. Meanwhile, online UX certifications can be completed much more quickly ( CareerFoundry: 5-10 months, UX Design Institute UX Design Diploma : 6 months or less, General Assembly UX Design Immersive : 12 weeks full-time)
• Expensive: Unless you can secure a scholarship or other subsidies, a masters in UX design can be incredibly expensive. The masters we look at in this article range from $44,980 to $115,680, and that’s for the tuition fees alone, without factoring in your living expenses and so on.
• Geographical limitations: Some masters require, or strongly prefer campus study. This can be limiting for those not able or willing to relocate to study. Online UX certifications, on the other hand, are available to you regardless of geography.

If you’d like to explore online certifications more, we recommend checking out Emily Steven’s The Best UX Design Certification Programs: A Complete Guide .

Alternatively, if you’d like to read more on the pros and cons of accredited courses (masters degrees) and non-accredited (most online certifications), our article on The 7 Best UX Design Schools will be right up your alley.

Before you apply for any UX design course, be it a masters or an online certification, do your research and figure out if the course is suited to your unique personal situation, learning preferences, and career goals.

Whether or not you apply to do a masters will ultimately depend on whether you can make and justify the time, logistical, and financial commitments required.

And remember: in the medium to long term, when you’re three or four years into your career, where you studied will be far less important to prospective employers than your work experience and portfolio. 

How persuasively and logically you can explain your design decisions, and how well you can collaborate and engage stakeholders or clients will count for a lot more than whether you studied at Stanford or completed an online certification.

If you’re interested in reading more about UX design, try the following articles:

• The Ultimate Guide to UX Research Bootcamps
• Can You Teach Yourself UX Design?
• A Day in the Life of a UX Designer

Master’s in Innovation with User Experience

Grounded in technology, design, and business disciplines, the  online Master’s in Innovation with User Experience (IUX) program is designed to deliver a highly qualified and competitive workforce for the IT industry. The WPI Business School has world-class expertise and resources in UX and is ideally positioned to prepare students as UX professionals and set them on a path to take on leaderships positions such as chief experience officers (CXO). 

UX-driven innovations are no longer a luxury, but a must for maintaining competitive advantage in the marketplace. The continual demand for innovative technologies in our daily lives, both at personal and organizational level, is intensified by the continually increasing pace of our digital economy. Tech companies must ensure that their products are successfully embraced and effectively used by their intended users at home and at work. To achieve this goal, competition in the IT industry has shifted toward developing an outstanding user experience (UX). 

Innovative companies know UX is key to gaining and retaining customers. Become a UX specialist and meet the growing demand for professionals who work with product designers, game designers, and technology designers to deliver exceptional user experiences. Get there by joining our online Master's in Innovation with User Experience graduate program, one of the first such programs in the nation with faculty with UX expertise who provide IUX skills and experiences to professionals with a variety of backgrounds.

A Premier STEM Business Degree, More Affordable Tuition

There is a pressing need for engineers, scientists, and coders with business acumen and management skills. WPI is committed to making STEM education more attainable, and The Business School is doing its part by reducing its  tuition for graduate programs . Today, a premier degree from WPI’s business school is more affordable than ever—meaning you can see a high return on investment from your degree even sooner.

The Business School , established at a premier technology-focused university, has world-class expertise and educational resources in technology and business, and thus is suitably poised to offer valuable graduate-level programs that prepare students to apply entrepreneurial thinking and transform into leadership roles.  

Learning Outcomes

The online Masters in Innovation with User Experience prepares students for working in advanced technological environments where they apply the UX driven innovation (UXDI) framework to help their companies develop competitive products and services. Gain skills for careers in product design, user experience design, user experience engineering, interaction design, human factors in computing, and web and mobile app design.

In our project-based, asynchronous online learning environment, students will:  

Gain needed skills for designing competitive human-centered technologies.

Gain foundational knowledge in design thinking, design science, and the UX-driven innovation (UXDI) framework for developing technological innovations (e.g., smart and connected systems, robots, AR/VR applications) for homes and work environments. 

Develop and execute plans for gaining a deep understanding about user needs. 

Develop and execute plans for discovering opportunities for creating business and social value with UX driven innovations. 

Develop and execute plans for designing and evaluating the discovered UX-driven innovation opportunities. 

Develop advanced skills in focused area(s) of interest through the specialties offered in this program such as Applied Analytics, Understanding User for Developing and Delivering IUX, Managing and Organizing Innovation, IUX Research, System Design for IUX, and others. 

Capstone experience enables students to revise, integrate, and apply their knowledge and skills through a large project.  

Admissions Qualifications for Master’s in Innovation with User Experience

• BS or BA degree from an accredited school, in any discipline, with a GPA of > 3.0  
• GMAT/GRE’s are not required for this program  

For specific application requirements, visit  our admissions for online programs  page.

If you do not have a bachelor's degree, please view our list of  undergraduate programs .

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The UI UX master’s online is a 33-credit program, designed as a stackable, professional master’s degree. As such, it involves a realistic capstone project. The MS IUX also serves as an entry to the PhD program in the WPI Business School, and thus allows for research credits (with permission of the IUX program director).  

Students will gain specialized knowledge in the following areas/specialties:

• System Design. Prepares students for designing advanced technologies that utilize data science approaches such as business intelligence and machine learning.
• Applied Analytics. Prepares students for careers involving information retrieval, data curation, and data analysis.
• Marketing. Prepares students for developing product management strategies that take advantage of consumer analytics.

Subject to change based on availability.    View academic term start dates for online courses.   

Students must complete the three-course core as follows: 

• MIS 583 . User Experience Applications 
• MIS 585 . User Experience Design 
• MIS 586 . User Experience Methods 

Students must complete two three-course specialties, selected from the following specialties: 

Brands, Products and Consumers   

• MKT 500 . Marketing Strategy 
• MKT 561 . Consumer Behavior and Analytics 
• MKT 569 . Product and Brand Management 

System Design (Select any 3; The first three are online; the others, which are not FBS courses, may not be available online)

• MIS 500 . Innovating with Information Systems 
• MIS 571 . Database Applications Design and Development 
• MIS 582 . Information Security Design and Management 
• IMGD 5000 . Game Design Studio  
• IMGD 5300 . Design of Interactive Experiences 
• RBE/CS 526 . Human-Robot Interaction 
• RBE 595 . Synergy of Human and Robot Systems 
• WR 593 . Robot Futures: Design, Ethics, Communication 

Applied Analytics (Select any 3) 

• MIS 502 . Data Management for Analytics 
• MIS 584 . Business Intelligence 
• MIS 587 . Business Applications in Machine Learning 
• OIE 559 . Optimization for Business Analytics 
• DS 501.  Introduction to Data Science 
•  or,  MA 511 . Applied Statistics for Engineers and Scientists 

Organizing and Managing Innovation (Select any 3) 

• FIN 500 . Financial Management 
• ETR 500 . Entrepreneurship and Innovation 
• ETR 593 . Technology Commercialization 
• MIS 576 . Project Management 
• OBC 533 . Negotiations 
• OBC 537 . Leading Change 

Students must complete a two-course capstone project experience   

• OBC 505 . Teaming and Organizing for Innovation 
• Capstone project for IUX and IT students

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Master of Human-Computer Interaction

The longest-running and most impactful Master of Human-Computer Interaction in the world.

The Master of Human-Computer Interaction (MHCI) program at Carnegie Mellon University is the first program in the world dedicated to preparing professionals for careers related to human-computer interaction, user experience design and user-centered research.

The MHCI program integrates service and design thinking into a rigorous HCI curriculum that prepares our students to design and guide the future of human and technology interactions.  

About the MHCI Program

• The MHCI program is a three-semester program completed over the course of a full calendar year (August-August).
• It is a professional degree that prepares students for industry and a career related to user experience, human-computer interaction and beyond.
• Our program is interdisciplinary to its core. Each year, cohorts are made up of richly diverse student groups with varying degrees of industry experience and backgrounds in design, social science, business and computer science among many others.
• MHCI is led by faculty who are driving and defining the world of HCI. They bring together expertise in computer science, cognitive psychology, behavioral science, design and many are experts coming directly from industry. Our diverse range of faculty powers the interdisciplinary culture in the HCII.
• The flagship course of the MHCI program is the seven-month Capstone course, a research and design team project with an external industry client.
• MHCI is currently designated a STEM program.  

The MHCI Experience

During the first semester, students learn core HCI methodologies and techniques in the required classes, while customizing their academic experience from the immense selection of electives across all of the schools at Carnegie Mellon University.

While completing the second and third semesters, students continue their diverse electives and complete a substantial industry capstone project with an external client. Our alumni praise the capstone course as being one of the most instrumental courses in their academic career.

Since our first graduating class in 1997, we have graduated more than 1,200 MHCI students who are now defining the ways humans interact with technology. They are user researchers, experience designers, product managers, entrepreneurs and business owners, and software developers. More importantly, they are strategizing and defining the future of technology in companies around the world. Take a look at where our grads go after graduation on the Post-Graduation Outcomes Dashboard .

Application

The application for the next MHCI program cohort (2024-25) is now closed.

Please check back in Fall of 2024 when our next application season will begin.

Capstone Project

  Electives

  Sample Study Plans

  Handbooks

Tuition & Aid

Alumni Board

MHCI Alumni

Nicole Willis MHCI Director of Student Affairs

Human-Computer Interaction Institute Carnegie Mellon University 300 S. Craig Street, Suite 209 Pittsburgh, PA 15213

[email protected] Phone: 412-268-7971 Fax: 412-268-9433

Future Students

Master of science.

The University of Washington's Master of Science in Human Centered Design & Engineering (HCDE) prepares its graduates for leadership roles in user experience research and design, interface design, interaction design, product design, and human-computer interaction.

HCDE Master's students solve real-world problems with our award-winning interdisciplinary faculty and students from diverse professional backgrounds. A flexible schedule allows students to attend part time or full time. Courses are offered in-person and cannot be completed online.

HCDE is an inclusive, interdisciplinary academic community. Graduates of HCDE receive engineering degrees and find jobs as user experience (UX) researchers and designers, systems analysts, design researchers, usability evaluators, web and information developers, and more. The University of Washington is located on a beautiful campus in the city of Seattle, and our students have access to the many prominent corporations that call the Pacific Northwest home. 

• Faculty & Research

Our Students

The Master's program in HCDE attracts students who are interested in researching, designing, and engineering technological interactions from a human perspective. Our students have a variety of academic and professional backgrounds, with an approximate breakdown of one-third from technical and engineering backgrounds, one-third from social sciences backgrounds, and one-third from design backgrounds. About half of our students are working professionals, studying as part-time students; the other half of our students study full-time. 

• Student profiles

Curriculum & Program Objectives

Students in the HCDE Master's program take a minimum of 50 credits, 24 of which are required core courses. The remaining 26 credits include elective courses, seminars and Directed Research Groups. Upon completion of the HCDE Master's degree, students assume leadership roles in human centered design and engineering in academia, industry, government, and non-profits. 

• Program Objectives
• Degree Requirements
• Course Descriptions
• Directed Research Groups

The online application is first made available no later than September each year through the UW Graduate School's application portal . The annual application deadline for the HCDE Master's program is on January 15 (except in years when that date coincides with a holiday or weekend, in which case it is slightly adjusted). Students begin the program in the following autumn quarter only. Unfortunately, we cannot accommodate deferment requests to any quarter/year beyond this time for accepted applicants.   View admission requirements »

• Majors & Careers
• Online Grad School
• Preparing For Grad School
• Student Life

Top 10 Best UX Design Graduate Programs in 2024

A UX or user experience design degree is one of the most highly sought-after programs today. This is an interdisciplinary field involving studies of human-computer interaction, industrial design, computer science , psychology, and anthropology. Businesses are increasingly focusing on improving user experience for maximum high conversion rates. This means expert UX design technologists are currently in high demand, and this demand is only set to increase in the future.

Therefore, it will not be hard to find a lucrative UX design job  once you complete one of the best UX design graduate programs from a reputable school.

Wondering which are the best UX design schools to get your UX designer degree? Let’s dive into our list!

Table of Contents

Best UX Design Graduate Programs

Each school on this list makes an excellent UX design university. Compare and contrast to find the best fit for you!

Carnegie Mellon University, Human-Computer Interaction Institute

Master of Human-Computer Interaction

Carnegie Mellon University is a private research university with locations on six continents. Its Human-Computer Interaction Institute is one of the top UX schools in the US, and this master’s program was the world’s first-ever user experience program. It is known for its diverse, multidisciplinary student cohorts. As part of this program, you get the opportunity to complete your capstone project with a top industry client.

• Courses : Communications in HCI, interaction design studio, and programming usable interfaces.
• Duration : 3 semesters (1 year)
• Delivery : On-campus
• Tuition : $77,784
• Financial aid :  Grants, fellowships
• Acceptance rate : 17.3%
• Location : Pittsburg, PA

DePaul University, College of Computing and Digital Media

Master of Science – Human-Computer Interaction

DePaul is the largest Catholic university in the country and has a strong anti-discrimination policy, welcoming students from all backgrounds. It also offers one of the best UX design programs around, with an emphasis on ICT evaluation, prototype development, information architecture, and exploratory user research.

• Courses : Prototyping & implementation, usability evaluation methods, and design ethnography.
• Credits : 52
• Tuition : $46,800
• Financial aid : Scholarships, grants, graduate assistantships, employer tuition deferral, and military benefits.
• Delivery : On-campus, online
• Acceptance rate : 70.2%
• Location : Chicago, IL

University of Washington, Graduate School

Master of Human-Computer Interaction and Design (MHCI+D)

The University of Washington is one of the oldest universities on the West Coast, with one of the largest library systems in the world. This interdisciplinary UX program is offered by the university’s award-winning research group known as DUB (Design: Use: Build). The group encompasses four departments: Computer Science & Engineering, the Information School, Human-Centered Design & Engineering, and the Division of Design from the School of Art + Art History + Design.

• Courses : Immersion studio, design of interactive systems, and data visualization.
• Duration : 11 months (intensive)
• Credits : 46+
• Tuition : $53,038
• Financial aid : Grants, loans, and work-study
• Acceptance rate : 55.9%
• Location : Seattle, Washington

The University of California Irvine, Donald Bren School of Information & Computer Sciences

Master of Human-Computer Interaction & Design (MHCID)

The University of California Irvine was ranked one of the top ten public universities  in the nation by the US News & World Report. Its MHCID is the only low residency, one-year, hybrid master’s program in the world. Thanks to its hybrid format combining some campus visits with online study, you’ll have enough flexibility to complete the program while continuing with your work.

• Courses : Design & prototyping, interactive technology studio, and user needs analysis.
• Duration : 1 year
• Delivery : Hybrid
• Tuition : $49,500
• Financial aid : Scholarships
• Acceptance rate:  29.9%
• Location : Irvine, CA

Georgia Institute of Technology

MS in Human-Computer Interaction

Georgia Tech is globally renowned in the IT sector, ranked 13 th  and 12 th  in computer science and engineering, respectively, in the World University Rankings. Four schools jointly offer this interdisciplinary MS program: the schools of Interactive Computing, Industrial Design, Literature, Media, and Communication (LMC), and Psychology.

• Courses : Human-robot interaction, human-centered computing, and web design accessibility.
• Credits : 36
• Duration : 4 semesters (18 months)
• Tuition : $24,120
• Financial aid : Graduate Research Assistantships (GRA) and Graduate Teaching Assistantships (GTA)
• Acceptance rate: 21.3%
• Location : Atlanta, GA

The University of Baltimore, Yale Gordon College of Arts and Sciences

MS in Interaction Design and Information Architecture

The University of Baltimore is one of the most prestigious universities around and was named among the top performers for social mobility  by the US News & World Report, 2022. This MS program is one of the best interaction design programs that allow you to study under a faculty whose members are conducting research in specialized fields. You can complete the program with a thesis option or a project option.

• Courses : Interaction & interface design, information architecture, and interactive multimedia.
• Delivery : On-campus, Online
• Tuition : $28,368
• Financial aid:  Scholarships, grants, loans, and federal work-study
• Acceptance rate : 80%
• Location : Baltimore, MD

Purdue University, Department of Computer Graphics & Technology

MS in Computer Graphics Technology – UX Design

Purdue University is a reputable public research university with hundreds of programs across various disciplines and academic levels. This MS program is flexible, allowing you to pursue it either within the Department of Computer Graphics and Technology (CGT) or across other available programs. If you don’t already have a bachelor’s degree, you can opt for a combined BS and MS, which will take five years to complete.

• Courses : Foundational readings of user experience design, UXD graduate studio, and interaction design evaluation.
• Duration : 2 years
• Tuition : $19,984
• Acceptance rate : 67.2%
• Location : West Lafayette, IN

Drexel University, College of Computing & Informatics

MS in Information – Human-Computer Interaction (HCI) & User Experience (UX)

Drexel University is a well-known R1 private research university. With this interdisciplinary MS program, you study in a reputed UX design university under a diverse faculty from a range of backgrounds, including engineering and human factors, multimedia design, education, social sciences, and healthcare.

• Courses : Prototyping the user experience, designing with data, and human-computer interaction.
• Credits : 45
• Tuition : $60,975
• Financial aid : Grants, loans, scholarships
• Acceptance rate : 77.2%
• Location : Philadelphia, PA

Pratt Institute

Information Experience Design (MS)

The Pratt Institute, founded in 1887, is known globally for its art, design, and architecture programs. This MS program aims to develop not only competent UX designers, but excellent researchers, strategists, and communicators. You can choose between two concentrations: research & evaluation or design.

• Courses : Conversational user experience design, sustainable interaction design, and advanced usability & UX evaluation
• Tuition : $55,908
• Financial aid : Scholarships, loans, grants, student employment
• Acceptance rate : 65.9%
• Location : Brooklyn, New York

California College of the Arts

MDes Interaction Design

California College of the Arts is one of the top arts and design colleges in the world. It was also ranked #1  on Payscale.com’s list of the best value art colleges. With this program, you’ll get to study under quality faculty that includes practicing designers connected with some of the world’s largest digital brands, such as Microsoft, Apple, Facebook, and Google. Our opinion? CCA is one of the best schools for UX design.

• Courses : Studio: design-people, communication by design, and studio: form.
• Duration : 1 year (3 semesters)
• Tuition : $68,112
• Financial aid : Scholarships, grants, work-study, and loans
• Acceptance rate : 78%
• Location : San Francisco, CA

How to Choose the Best UX Design Degree

With so many strong UX design programs available, it can be difficult to wade through the options to choose the right one for you. Here are a few factors that will help you make the right decision:

• Investment vs. job prospects:  You should first get a basic idea of how much you’ll spend on the program and compare this to your expected earnings as a UX designer. Essentially, this is about the ROI         (return on investment), as well as the program you can afford.
• Curriculum:  Though many UX programs share courses in common, there are certain differences. Pick curriculums that appeal to your interests and career goals. Additionally, certain programs offer special concentrations and specializations.
• Duration:  Most UX design graduate programs last two years. However, some schools offer one-year programs, and others that you can complete in as little as 11 months in an intensive format.
• School reputation:  A degree from a school with a strong reputation can make a         huge difference in securing the job you want.
• Location:  You’ll want to look for a conveniently located school or one with online options.

Why Choose a UX Design Program?

The major reason to choose a UX design program is that it will qualify you for lucrative roles in one of the most in-demand fields right now. With businesses becoming more and more user-oriented, there is an increasing demand for technologists that can create innovative designs to provide better user experiences.

Additionally, salary prospects in this field are excellent. According to Glassdoor.com, the average base pay for UX designers is currently more than $115,000 .

UX Design Graduate Program FAQs

Which degree is the best for ux design.

If you want to pursue a career in UX design, you can choose between a few different degrees. Any course covering human-computer interaction, information architecture/design, psychology, interaction design, industrial design, and computer science will be useful.

Though these topics may also be covered in programs like computer science  and psychology , a master’s in UX Design will give you in-depth knowledge across all these fields, making it arguably the best option.

Is a Master’s in UX Design Worth It?

Graduates with a master’s in UX Design are in high demand today. UX designers enjoy an average annual salary of over $115,000 . Additionally, with so much demand in the field, with a master’s in UX Design from a reputable university and excellent grades, you’ll find it relatively easy to secure an excellent role.

What Master’s Degree Should I Get for UX Research?

If you want to work in UX research, a master’s in UX Design is a strong asset. However, some UX research roles require a PhD in UX design. To pursue this type of doctorate, you’ll need a degree in UX design or a related field, such as interaction design, communication design, or industrial design.

Key Takeaways

With so many UI design schools offering UX design master’s programs today, it’s important to do your research and choose the right program for you. If you have a multidisciplinary approach to problem-solving, a UX design program could be the perfect fit for you. These programs involve diverse fields of study, including digital, industrial, scientific, and humanities subjects.

Once you’ve chosen from the best UX design graduate programs, take a look at our posts and guides  for advice on putting together a strong application.

Lisa Marlin

Lisa is a full-time writer specializing in career advice, further education, and personal development. She works from all over the world, and when not writing you'll find her hiking, practicing yoga, or enjoying a glass of Malbec.

• Lisa Marlin https://blog.thegradcafe.com/author/lisa-marlin/ ACBSP Vs AACSB: Which Business Program Accreditations is Better?
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• Lisa Marlin https://blog.thegradcafe.com/author/lisa-marlin/ 25 Best Gifts for Law Students for 2024

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• Berkeley Boot Camps

How to Become a UX Researcher — No Experience Needed

If you have a knack for understanding people and figuring out what makes them tick, a career in user experience (UX) research might just be the right fit for you. In this article, we’ll show you how to become a UX researcher and give you a few insights into what career training opportunities and job prospects are available in the field. 

7 Qualifications and Skills Needed to Become a UX Researcher:

• UX/Design Thinking
• User-Centered Design Research
• Persona Creation
• User Testing
• Soft Skills

Interested in not only learning these skills, but also putting them into practice? Berkeley UX/UI Boot Camp offers the hands-on experience you need to take the next step in your career. 

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Why UX Researchers Are in High Demand

UX researchers give businesses, designers and developers valuable insights into user behaviors and psychology; these detective-techies tease apart the rationales that drive people to think, feel and act in specific ways when encountering a website or an app or even a piece of software. It’s an exciting gig for the right person — so if you think you might be a good fit, keep reading.

User experience research has become crucial to running a successful modern business. As designer Jacob Gube explains in an article for Smashing Magazine , “Websites and Web applications have become progressively more complex as our industry’s technologies and methodologies advance […] but regardless of how much has changed in the production process, a website’s success still hinges on just one thing: how users perceive it.”

UX describes how people feel when they interact with a system or service and encompasses several factors including usability, design, marketing, accessibility, performance, comfort and utility. A person’s experience when they visit a website can dramatically impact and even change their perception of a company or a service — for better, and for worse. 

Think of a banking website. Consumers expect their virtual financial experiences to be crisp, intuitive and as formal as any in-person interactions would be at a physical branch. How odd and off-putting would it be to expect that level of professionalism and instead find the casual  quirkiness of a gaming website? What works for one audience and intent certainly won’t work for all!

As UX guru Don Norman once shared in an interview , “Everything has a personality; everything sends an emotional signal. Even where this was not the intention of the designer, the people who view the website infer personalities and experience emotions. Bad websites have horrible personalities and instill horrid emotional states in their users, usually unwittingly. We need to design things — products, websites, services — to convey whatever personality and emotions are desired.” 

This isn’t just theory; it’s backed up by facts. When companies invest in UX research and design, they tend to see higher levels of customer acquisition and retention as well as reduced support costs because their products and services are more intuitive and easy to use. These companies also tend to enjoy a higher share of the market for their industry. In 2018, researchers for McKinsey’s report on the business case for good design found that companies that scored in the top quartiles of the research firm’s Design Index outperformed industry benchmarks by two-to-one. As the report’s authors write, “Top-quartile MDI scorers increased their revenues and total returns to shareholders (TRS) substantially faster than their industry counterparts did over a five-year period — 32 percentage points higher revenue growth and 56 percentage points higher TRS growth for the period as a whole.”

Let’s talk about how you can become a UX researcher and kickstart your career in this high-potential field. 

What Do UX Researchers Do?

It’s a no-brainer: all businesses want to appeal to their customers. Their survival depends on doing so — and given this, companies have long tried to craft an experience that their customers find pleasant. With the meteoric rise of e-commerce and consumers’ increasing interest in living more of their lives online, UX research has become a specialized profession in its own right. In 2017, a research initiative that sought to investigate the business benefits of user research found that 49 percent of surveyed executives believed that UX research made their company more efficient, while 56 percent believed that it improved the quality of their products or services. 

These benefits are the result of UX researchers’ work to gather insights and information about what customers need, what they prefer and how they react. UX researchers use both quantitative and qualitative methods to examine and improve the user experience. These research methods encompass everything from simple online surveys to full-scale prototype designs. 

For example, UX researchers might use observation to determine user behaviors and feelings or understand consumers’ mental models (i.e., what they believe about the website or software). They might send out impersonal surveys to user groups, run face-to-face interviews with users of a site or product or carry out hands-on usability tests to assess customer preferences. Then, after the information-gathering phase is complete, UX researchers can analyze the collected data to identify patterns and trends that will then guide design and development decisions for digital products, software or websites. 

Qualifications and Skills Needed to Become a UX Researcher (That Employers Look For)

If you want to know how to become a user experience researcher, there are certain skills, qualifications and experience levels that are essential to this field. While clients, products and research goals vary widely across roles, all UX professionals need to master the fundamentals. Below, we’ve listed a few of the most important qualifications and skills to develop when considering how to become a user experience researcher.

1. UX/Design Thinking

Design thinking might have been developed in 1969, but it hasn’t faded with the times. If anything, our growing reliance on digital experiences has made the organizational framework more critical. A design thinking approach helps designers handle complex problems and keep the user in mind at all times. It forces a UX researcher to step into their target users’ metaphorical shoes and, in doing so, empowers them to predict, define and solve the issues users may face. UX research skills are a significant part of design thinking and are invaluable in analyzing user response throughout the process.

2. User-Centered Design Research

User-centered design aims to put a product’s end user at the center of all design plans. Rather than attempting to cast a wide net, this design philosophy homes in on a target user and allows developers to create a project with that ideal user’s needs, goals and preferences in mind. 

UX research is, as you might expect, a crucial part of this process. Without it, this type of design becomes mostly guesswork. Eventually, it devolves into an exploration of what the project’s developers think they would want as users — a dangerous shift, given that what appeals to the site developers might not align with the target user’s needs and preferences. The application of UX research skills is thus essential to the success of user-centered design plans. 

3. Persona Creation

Basic descriptions are all well and good, but when a researcher needs to define an ideal user, understanding how to apply their UX research skills to develop and use a persona is critical. A persona describes an imagined ideal or typical user of a website or product and empowers UX researchers to make sense of the information gathered through user research. A persona reflects the needs and wants of broad user groups by collating the attitudes, skills, technical background, patterns and environment of typical users. UX researchers for a banking app, for example, might build a persona that incorporates their customers’ likely financial knowledge or probable tech-savviness. A UX researcher may even opt to include direct user information, such as specific quotes obtained through user research, into their persona.

Keeping that persona in mind, UX researchers and developers can build empathy with their users and better understand their expectations and needs. Personas allow researchers to go beyond vague imaginations of what users might and might not like and narrow in on a user’s actual experience. When applied, these personas respond to the specific context of a site or piece of software, reflecting the real users of that product and giving designers more accurate insights into what does and doesn’t work well. 

4. UX Mapping

What does a user do, and when? If a UX designer doesn’t have a clear understanding of how consumers progress through a given app or website, they won’t know how to optimize the user’s journey. Mapping is a critical skill for UX researchers, as it allows them to use their collected observations to create an annotated timeline of a user’s journey. A UX map provides an expansive overview of user touchpoints. It demonstrates how decisions made at these touchpoints can create diverging decision “branches” and lead to positive or — depending on the “branch” — negative experiences. Having a visual representation of the highs and lows of a user’s journey can help UX professionals identify and address the touchpoints and decisions that spark poor experiences. 

5. User Testing

Every UX researcher needs to know how to conduct usability testing . While it can be tempting for companies to avoid spending the time — and the money — that proper user testing requires, investing in the process can help project developers avoid severe pitfalls and tailor the end product to user preferences. 

Put simply, user testing tells developers whether they’ve hit or missed the mark. The testing process gauges whether users can successfully navigate the site or app, complete essential tasks and receive the information they need. It flags common user errors and notes any features that, while intuitive for developers, routinely mystify end users. As a UX researcher, you might even test competitor products alongside your own to find out how users’ experiences differ between the two. When initiated early during the development process and repeated regularly, this type of UX research can help designers and developers produce a successful, user-intuitive product.

6. InVision

As in any specialized field, aspiring UX professionals must know the tools of their trade. Of particular note, the popular prototyping, workflow and collaboration app called InVision is a must-know skill for UX researchers . Imagine being able to create a prototype of your incomplete app, and having the ability to conduct user tests as if your users were working with the real, fully functioning website or app. The prototypes allow instant feedback, commenting and other specialized features that feed into an overall UX analysis. This interactive platform enables researchers to test the interactive parts of a site, rather than relying on screenshots, images or PDFs that do not fully replicate the final experience. InVision isn’t just a collaboration tool; it also provides fully featured design software and integrates with other popular products in Adobe’s Creative Cloud suite.

7. Soft Skills

Software skills and research aptitude will only ever get you so far in the job market. Soft skills — those concerned with being a good team member and professional — are just as vital as any niche technical capability. Given that learning from and listening to users is at the heart of UX, developing your empathy and ability to communicate is a must. If you can’t communicate well or maintain an open mind, you’ll never manage to see beyond your own opinions and identify what matters to your user. As odd as it might sound, learning how to be an empathetic, thoughtful and perceptive person may serve you better as a UX researcher than any technical guide. 

How to Acquire the Skills to Become a UX Researcher

When it comes to education, aspiring UX researchers have options. You don’t need to have years of experience in tech. Those in the social sciences, for example, are well-suited to UX research because the core competencies in both sectors overlap — though they often need to step up their working pace and alter their research methods to suit the tech sector’s fast pace. Similarly, professionals in marketing and communications fields often already have the user response and interaction training necessary to segue into UX research. 

As researcher Nikki Anderson shared in an article for UX Collective , “One of the number one questions I get every week are people asking me how to break into the field of user research from another role or right after graduating. I speak with people from all different disciplines, some closer to user research, such as marketing, psychology or design, and others further away, such as accountants or writers […] Getting into user research was one of the least straight-forward paths I have taken, and that is often the case for most people breaking into this field.”

Regardless of whether you’re just starting out or want to change your professional path, expanding your knowledge and skill set is essential to kickstarting a new career in UX research. Let’s dive into a few options that may help you gain the knowledge and experience you need to become a UX researcher. Ultimately it’s up to you to decide which ones works best for you.

While career interest in UX has grown, there are still relatively few undergraduate degree programs explicitly dedicated to UX research. There are master’s programs for the profession — but even those rarely require any background training in the discipline . That said, if you want to become a UX researcher and are planning on enrolling in a four-year undergraduate program, there are a few majors that will prepare you for the field. These include standby options from computer science and information systems to design, psychology and even anthropology. 

Of course, this is a better option for people who have never received a four-year degree or who have the time and money to go back to school full-time. People who have already graduated and want to stay in the workforce may look for other, faster options to explore this exciting career path.

UX/UI Boot Camps

Boot camps are another option that can help you complete a successful career transition into UX research. These short programs are designed to provide an intensive educational experience and quick entry into tech hiring pools. They are well-suited to learners who have either already left university or don’t have the time to enroll in a four-year degree program. Because boot camps offer a variety of full-time, part-time and online options, they tend to also be more flexible for those who need to juggle working or family responsibilities during their academic journey. Such programs have seen a meteoric rise over the last several years; between 2018 and 2019 alone, Course Report found that boot camps grew an incredible 49 percent.  

While boot camps are most often associated with coding or software development, there are also specific programs for those interested in UX research. Explore your options to see if an intensive UX/UI boot camp could suit your situation and career interests. 

Self-Guided Resources

Who says that learning has to happen in person? If you’re ambitious and self-directed, you may want to use self-guided resources to structure your foray into UX research. An abundance of learning opportunities is available online, from tutorials and discussion forums to virtual courses . These offer price-conscious or time-constrained learners a chance to take their education into their own hands — and even once you enter your career, these sites can be an essential part of lifelong learning and job advancement.

Keep in mind, however, that free online self-guided resources often lack the support and structure that degree programs or boot camps provide. Do your research before you commit to an educational path.

How to Get Hired

Once you gain the education and skills you need, it’ll be time to look for a job in the UX field. Your boot camp or university may have a career assistance office that can help you land internships and interviews with leading technology companies, which can, in turn, evolve into valuable full-time career opportunities.

Do your research; make sure to check out job boards, especially the specialized ones provided by your boot camp or university career center. Networking, attending conferences and actively participating in the UX research community can all put you in good stead to find a great job. When you get the interview you want, prepare in advance to make the best impression possible, and show off your ability to communicate and listen effectively.

User experience research is a rapidly growing profession at the heart of today’s tech industry. With tremendous upward potential and opportunities for people with a wide range of skills and backgrounds, UX research can be an exciting and rewarding career. Will online learning, a  UX/UI boot camp or a university degree be the right option for you? Explore your training options and forge a path that will allow you to become a UX researcher according to your own timeline and educational preferences.

UX Degrees – A Global List of UX-related Bachelor & Master Degrees

User Experience as a discipline is not yet well-established in many universities. There are, however, degrees in related fields that you can study at a tertiary level. These include: Interaction Design , HCI , Information Architecture, Digital Design, and others.

For more information on the pros and cons of university degrees (especially when it comes to landing a job in UX) read the chapter “Step 1: Get Educated” in our eBook,  Get Started in UX .

The List of UX Degrees

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User Research

What is user research.

User research is the methodic study of target users—including their needs and pain points—so designers have the sharpest possible insights to make the best designs. User researchers use various methods to expose problems and design opportunities and find crucial information to use in their design process.

Discover why user research is a crucial part of the design process.

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User Research – Get to know your Users, and What They want

To call user research a crucial part of an interaction design process might seem overly obvious. Indeed, it’s the only way to discover exactly what these users need, having first found out precisely who they are. To set out to generate these facts, you must gather data from your users through a structured approach . First, you must choose methods that 1) suit your research’s purpose and 2) will yield the clearest information. Afterwards—to get the insights you want—you’ll need to interpret your findings from all that data, which can be tricky . You can apply user research anytime during the design process. Typically, researchers begin with qualitative measures, to discover users’ needs and motivations . They might later test their results by using quantitative measures .

“Research is creating new knowledge.” – Neil Armstrong, the First person to walk on the Moon

User research essentially splits into two subsets:

Qualitative research – Ethnographic field studies and interviews are examples of methods that can help you build a deep understanding of why users behave the way they do (e.g., why they leave a website so quickly). For instance, you can interview a small number of users and get sharp insights into their shopping habits by asking them open-ended questions. Usability testing is another dimension of this type of research (e.g., examining users’ stress levels when they use a certain design). Qualitative research requires great care. As it involves collecting non-numerical data (e.g., opinions), your own opinions might influence findings.

Quantitative research – With more-structured methods such as surveys, you gather measurable data about what users do and test assumptions you developed from qualitative research. An example is to use an online survey to ask users questions about their shopping habits (e.g., “Approximately how many items of clothing do you buy online per year?”). You can use this data to find patterns within a large user group. In fact, the larger the sample of representative test users is, the more likely you’ll have a statistically reliable way of assessing the target user population. Regardless of the method, with careful research you can gather objective and unbiased data. Nevertheless, quantitative data alone cannot expose deeper human insights.

We can also split user research into two approaches:

Attitudinal – you listen to users’ words (e.g., in interviews).

Behavioral – you watch their actions through observational studies.

Usually, you can get the sharpest view of a design problem when you apply a mixture of both quantitative and qualitative research as well as a mixture of attitudinal and behavioral approaches.

© Interaction Design Foundation, CC BY-SA 4.0

Leverage User Research Methods throughout Development

Industry-leading user experience consulting organization the Nielsen Norman Group names appropriate user research methods for you to use during your project’s four stages . Here are key methods:

Discover – Determine what’s relevant for users.

Diary studies – Have users log their performance of activities or record their daily interactions with a design.

Contextual inquiries – Interview suitable users in their own environment to find out how they perform the task/s in question.

Explore – See how to address all users’ needs.

Card sorting – On cards, write words and phrases and then let participants organize these in the most meaningful way and label categories to ensure your design is logically structured.

Customer journey maps – Create user journeys to reveal potential pitfalls and crucial moments.

Test – Evaluate your designs.

Usability testing – Make sure your design is easy to use.

Accessibility evaluations – Test your design to ensure everyone can use it.

Listen – Put issues in perspective, uncover any new problems and spot trends.

Analytics – Gather analytics/metrics to chart (e.g.) website traffic and generate reports.

Surveys/Questionnaires – Track how users’ feel about your product/design via these.

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However you approach user research, always consider the pros and cons of each technique . Card sorting is cheap and easy, for example, but may prove time-consuming when you proceed to analysis. Moreover, it might not provide in-depth contextual meaning. The resources available to you are another constraint. These will decide when, how much and which type of user research you can actually do. Therefore, carefully choose only the most relevant method/s for your research . Also, get stakeholders from your organization involved early on . They can reveal precious insights and help keep your research on track regarding business goals. Overall, user research is a valuable way to validate the assumptions the design team makes concerning users in the field , cut the expense of the best deliverables and keep your product’s demand high and ahead of competitors’ in the marketplace.

User research methods have various pros and cons and involve activities ranging from observations of users in context to controlled experiments in lab settings.

Learn More about User Research

For a fuller grasp of user research, take our course here .

See the Nielsen Norman Group’s list of user research tips .

Find an extensive range of user research considerations , discussed in Smashing Magazine.

Here’s a convenient and example-rich catalogue of user research tools.

Questions related to User Research

User Research is a fulfilling career for individuals driven to comprehend user behaviors and work collaboratively with teams. As a User Researcher, you're instrumental in steering teams towards crafting user-centric solutions. If you're intrigued by a career that combines both analytical and creative insights, consider delving into this field. For a comprehensive understanding, explore the User Researcher Learning Path on our platform.

User Researchers are seeing competitive pay in the industry. On average, they can earn from $92,000 to $146,000 annually. In some smaller firms, user research duties might be combined with a broader UX role. To understand how salaries can differ by region or delve into a broader perspective on UX-related pay, check out this detailed guide on UI UX Designer Salaries for 2023 or Glassdoor's breakdown of User Experience Researcher salaries .

While both are integral to the user experience, User Research and UX Design serve different purposes. User Research delves deep into understanding user preferences and needs, paving the way for informed design strategies. In contrast, UX Design is about sculpting a product based on that insight, ensuring it's both user-centric and aesthetically pleasing. 

Sometimes, especially in compact teams, the roles might blur with a designer handling research. Want a comprehensive insight? Dive into User Experience: The Beginner's Guide to explore their interconnected dynamics.

Yes, there is! Think of UX research as a subset of user research. While both focus on understanding users, user research casts a broader net, examining topics like pricing or delivery preferences. UX research, meanwhile, zeroes in on how users interact with a product and their experience doing so. In short, user research looks at broader interactions, while UX research specifically studies product use. To dive deeper, check out our course on User Research Methods and Best Practices .

User research utilizes varied techniques such as usability testing, A/B tests, surveys, card sorting, interviews, analytics analysis, and ethnographic studies. Every approach brings unique insights and is ideal for specific situations. It's essential to choose the proper technique based on your research goals and your audience. Discover these techniques further in 7 Great, Tried and Tested UX Research Techniques . 

For a comprehensive understanding of usability testing, a popular user research method, check out our course on User Research Methods and Best Practices .

While a related degree can be beneficial, it's not strictly required to become a user researcher. Many successful user researchers have degrees in diverse fields like psychology, design, anthropology, statistics, or human-computer interaction. What's crucial is a mix of relevant education, hands-on experience, and continuous learning. Even if some employers might favor candidates with a bachelor's degree, it can be in something other than a UX-focused area. Only some degrees specifically target user research. To strengthen your knowledge, consider courses like Data-Driven Design: Quantitative Research for UX or User Research Methods and Best Practices .

While each user research project is unique, some standard steps guide most endeavors:

Determine the research question.

Choose the proper research technique.

Find participants.

Execute the research.

Evaluate the gathered data.

Share the results.

For a thorough understanding of these steps and more, check out User Research – Methods and Best Practices .

There's a wide array of user research tools to pick from, tailored to your research goals, organizational size, and project specifics. Some popular choices include:

For surveys: Typeform or Google Forms.

Card sorting: Tools like Optimal Workshop, Maze or Trello.

Analyzing user activity: HotJar or CrazyEgg for heatmaps.

Usability evaluations: Platforms like Userlytics or Lookback.

Analyzing qualitative data: Miro or Lucidchart for affinity diagramming.

Crunching numbers: Google Sheets or Microsoft Excel for quantitative insights.

Usability testing on prototypes: Tools like Adobe XD or Figma.

Presenting findings: Use Google Slides, PowerPoint, or Prezi.

These tools often boast extra features to amplify your research.

Dive deeper into their applications with User Research – Methods and Best Practices .

User research is paramount in creating products that align with users' genuine needs and preferences. Instead of basing designs on assumptions, it provides factual insights into how users feel and interact with products. By engaging in user research, designers can spot usability challenges, collect feedback on design ideas, and validate their design decisions. For businesses, this not only refines product offerings but also strengthens brand loyalty and reputation. A standout user experience gives a company a competitive edge and lowers the chances of product setbacks. Dive deeper into the significance of user research in design with Data-Driven Design: Quantitative Research for UX and User Experience: The Beginner’s Guide .

Literature on User Research

Here’s the entire UX literature on User Research by the Interaction Design Foundation, collated in one place:

Learn more about User Research

Take a deep dive into User Research with our course User Research – Methods and Best Practices .

How do you plan to design a product or service that your users will love , if you don't know what they want in the first place? As a user experience designer, you shouldn't leave it to chance to design something outstanding; you should make the effort to understand your users and build on that knowledge from the outset. User research is the way to do this, and it can therefore be thought of as the largest part of user experience design .

In fact, user research is often the first step of a UX design process—after all, you cannot begin to design a product or service without first understanding what your users want! As you gain the skills required, and learn about the best practices in user research, you’ll get first-hand knowledge of your users and be able to design the optimal product—one that’s truly relevant for your users and, subsequently, outperforms your competitors’ .

This course will give you insights into the most essential qualitative research methods around and will teach you how to put them into practice in your design work. You’ll also have the opportunity to embark on three practical projects where you can apply what you’ve learned to carry out user research in the real world . You’ll learn details about how to plan user research projects and fit them into your own work processes in a way that maximizes the impact your research can have on your designs. On top of that, you’ll gain practice with different methods that will help you analyze the results of your research and communicate your findings to your clients and stakeholders—workshops, user journeys and personas, just to name a few!

By the end of the course, you’ll have not only a Course Certificate but also three case studies to add to your portfolio. And remember, a portfolio with engaging case studies is invaluable if you are looking to break into a career in UX design or user research!

We believe you should learn from the best, so we’ve gathered a team of experts to help teach this course alongside our own course instructors. That means you’ll meet a new instructor in each of the lessons on research methods who is an expert in their field—we hope you enjoy what they have in store for you!

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Original research article, a novel approach toward cyberbullying with intelligent recommendations using deep learning based blockchain solution.

• 1 Faculty of Computing and Information Technology, King Abdulaziz University, Department of Information Technology, Rabigh, Saudi Arabia
• 2 Faculty of Computing and Information Technology, King Abdulaziz University, Department of Information Systems, Rabigh, Saudi Arabia

Integrating healthcare into traffic accident prevention through predictive modeling holds immense potential. Decentralized Defense presents a transformative vision for combating cyberbullying, prioritizing user privacy, fostering a safer online environment, and offering valuable insights for both healthcare and predictive modeling applications. As cyberbullying proliferates in social media, a pressing need exists for a robust and innovative solution that ensures user safety in the cyberspace. This paper aims toward introducing the approach of merging Blockchain and Federated Learning (FL), to create a decentralized AI solutions for cyberbullying. It has also used Alloy Language for formal modeling of social connections using specific declarations that are defined by the novel algorithm in the paper on two different datasets on Cyberbullying and are available online. The proposed novel method uses DBN to run established relation tests amongst the features in two phases, the first is LSTM to run tests to develop established features for the DBN layer and second is that these are run on various blocks of information of the blockchain. The performance of our proposed research is compared with the previous research and are evaluated using several metrics on creating the standard benchmarks for real world applications.

1 Introduction

Within the dynamic sphere of social media, the persistent issue of cyberbullying demands inventive and robust solutions to ensure user safety and cultivate a secure digital environment. Recent insights from the “Cyberbullying Statistics, Facts, and Trends (2023) with Charts” ( 1 ) underscore concerning statistics, revealing that over 61% of teens on social media have encountered online bullying related to their appearance, while 41% of adults have personally confronted harassment on social media. A thorough examination of cyberbullying rates among adolescents further underscores the gravity of the issue, with a study in England revealing an incidence of 17.9%, and research in Saudi Arabia reporting a prevalence of 20.97% ( 2 ). Despite recognized correlations between socio-economic factors, environmental influences, mental health, and cyberbullying tendencies, there remains an unexplored dimension—the creation of an online self-sufficient system to address cyberbullying and offer necessary guidance to identified victims and bullies.

As our digital interconnectedness expands, so too does the urgency to confront the challenges posed by malicious online behaviors. This paper proposes a novel approach to combat cyberbullying by integrating findings from cyberbullying statistics with innovative solutions. Our approach involves the fusion of two cutting-edge technologies: Blockchain and Federated Learning (FL) ( 3 ). Blockchain, known for its decentralized nature and transaction integrity, serves as the foundation of our solution, while Federated Learning facilitates collaborative machine learning without compromising individual data privacy. Alloy Language is utilized for the formal modeling of social connections, with specific declarations defined by our novel algorithm shaping the foundation of our proposed methodology. The incorporation of Long Short-Term Memory (LSTM) and Deep Belief Networks (DBN) into our system architecture enables established relational checks as well as feature detection within the DBN layer. Recognizing the importance of user accessibility, we augment our approach with an eXplainable Artificial Intelligence (XAI) layer, which sits atop our integration of Deep Learning and Blockchain technologies, making the solution more understandable to users in real-world circumstances. In the dynamic scenario of online interactions, natural language processing with AI capabilities emerges as an important aspect in the study of Cyberbullying, this plays an important role in developing useful features textual data. With the growth in usage of social media communication and utilization of day to day activities, prevalence of NLP with AI capabilities to study and analyze human interactions, innate sentiments, and discourse patterns has become increasingly relevant. The availability of vast amounts of data and the development of NLP and AI capabilities are the main drivers which cause the surge in the field of Sentiment Analysis, Tone detection etc. ( 4 ). The same is also used in fields such as information retrieval, topic modeling, sentiment analysis, and more. Cyberbullying has developed as a major issue in today’s socially connected generation, with reference to the purposeful and repetitive use of digital communication by miscreants to harass, intimidate, or hurt individuals. Cyberbullying includes a wide range of damaging activities such as spreading rumors, publishing sexual or slanderous content, sending abusive communications, and participating in online hate speech. Individuals’ mental health, social interactions, and overall well-being are all negatively impacted by cyberbullying ( 5 ).

The design is kept such that the proposed solution can be deployed using existing packaging and MLOps processes. The work explored in this document aims to contribute to the existing studies on detection and prevention of cyberbullying by proposing a novel approach and make online spaces safer. It combines three powerful technologies: federated learning, blockchain, and deep learning with natural language processing (NLP). Federated learning protects user privacy by training the cyberbullying detection model on individual devices without sharing the data itself. Blockchain ensures the security and tamper-proof nature of the training process. Deep learning and NLP enable the model to accurately identify cyberbullying content.

Through this Blackbox model powered by federated learning and NLP techniques, we develop a model that works primarily on two factors – Preservation of Social Media User Privacy and increasing the accuracy of Cyberbullying detection. The work done in this paper works in line with objective of creating safer online spaces by detecting cyberbullying and hence giving a boost to the mental health of individuals in the digital era. Our study follows a well-defined federated training sequence of various blocks, that has been developed to implement both user privacy and high-speed block chain based deep learning methods, toward cyberbullying detection.

In this paper, we have made the following contributions:

• To propose a novel framework using Blockchain and Federated Learning based Cybersecurity Solution (BFL-CS) to handle cyberbullying in social media space.

• To develop novel algorithms which works as a Hybrid Block Chain & Federated Learning model for the prevention Cyber bullying solution.

• To evaluate the proposed method with other deep learning-based methods, by using a dual layer deep learning architecture using LSTM and DBN techniques.

• To assess the effectiveness of the work using metrics and visualization tools.

The paper has been organized as follows: Section 1 discusses the Introduction and contributions made, Section 2 highlights the previous researches done in the field. Section 3 mentions the detailed proposed framework and methodology. Section 4 presents the evaluation and discussion of the results and last section concludes with some future directions.

2 Literature review

Muniyal el al. ( 3 ) introduced Federated Learning [FL] as a procedure to secure sensitive user data across the process pipeline. The authors emphasize more toward the possibility of a security breach on a Cyberbully detection and prevention system when the same is based on a Central Server. In addition to this, the performance parameters of the proposed solution is shown only on a IID (Independent and Identically Distributed) dataset only. The solution developed is named as “FedBully,” which used NLP techniques such as sentence-embedding based classifier, Sentence-BERT (Bidirectional Encoder Representations from Transformers) to detect cyberbullying, incorporating the training procedure from federated learning. Iwendi et al. ( 6 ) proposes a pure Deep Learning based solution for detection of Cyberbullying in Social Media. Advanced techniques like Bidirectional Long Short-Term Memory (BLSTM), Gated Recurrent Units (GRU), Long Short-Term Memory (LSTM), and Recurrent Neural Network (RNN) are used in ensemble to generate a higher accuracy – AOC (Area Under the Curve) for the proposed solution. In addition to that, the solution also does a significant amount of text cleaning and tokenization efforts. The paper also explores a comparative analysis of various other deep learning methods and provides a qualitative result of each method with respective accuracies and process performances. Samee et al. ( 2 ) showed detection of cyberbullying with federated learning. The work improved the identification of cyberbullying cases by offering a richer knowledge of the emotional context within communications by developing eight novel emotional elements retrieved from textual tweets. The use of privacy-preserving federated learning enabled collaborative cyberbullying detection, maintaining data privacy while encouraging collaboration across varied groups for a more scalable and successful method. Furthermore, similar to Iwendi et al. ( 2 ) where the analysis done in the paper used a client selection strategy for overall model ensemble preparation which was purely based on statistical performance of the model, the output was desired to be more accurate. The paper showed that the BERT model used in Gohal et al. ( 2 ) outperforms other traditional models such as CNN, DNN, and LSTM, that too with such low number of epochs, i.e., 200.

2.1 Research gap

Based on the literature review, we see that in previous research works on cyber-bullying detection and mitigation, a drawback that we constantly notice is the centralization of sensitive user data compared to social media for deep learning model training, highlighting a major privacy concern ( 12 ). This disadvantage may also make the adoption of such systems problematic when applied to real-world applications, as consumers will be hesitant to provide data with systems that take no precautions to safeguard their data ( 13 ). Furthermore, we show that traditional approaches frequently struggle to perform effectively due to a lack of different user behavior data and linguistic patterns. In our research, we effectively solve the above mentioned issues by combining federated learning with a secure block chain-based backend and alloy data modeling techniques. Federated learning uses a decentralized strategy to ensure that user data is handled and stored ensuring user privacy. Furthermore, the basic working of primary deep learning methods provides us with opportunity of continuous model tweaking, which, combined with other data security measures helps us in achieving our goal without giving away the third-party data security ( 7 ). Our paper uses features of federated learning to handle these shortcomings of earlier methodologies, resulting in a ground-breaking approach to cyberbully identification that maintains the highest level of user information privacy and data security.

2.2 Comparative study of systems proposed in earlier works

3 Proposed design methodology

This paper envisages novel method named Blockchain based Federated Learning based Cybersecurity Solution (BFL-CS) methodology to handle cyberbullying in social media space and its prevention ( 14 ). In the approach defined in this study, a Federated Learning methodology is employed with methods such as a modified LSTM in tandem traditional DBN to improve on the statistical parameters of the model and the privacy security of the model. The LSTM has traditional parameters such as batch size, timesteps and input feature vectors. It is to be noted that the DBN model is used as per its usual implementation without any modifications.

The proposed methodology works on two layers of memory:

1. A short-term memory (LSTM) that helps in generating blocks and federated learning nodes.

2. A long term memory (DBN) that keeps the learning from federated learning nodes and propagates it across the model during future epochs.

In this way, the model achieves faster run time due to actively forgetting information that does not value the model in the long run. And also generates highly accurate results from its long memory model implementation.

In a classical Ensemble implementation, the accuracy of two or models is combined to get a unified result. However, in our model, we have two DL models working together on the same data but at different stages to generate a result.

The architecture given below shows the complete data flow and working of the proposed design ( Figure 1 ).

Figure 1 . Overall structure of the BFL-CS model.

The framework model is listed and explained in the following steps.

3.1 Data warehousing

In our system architecture, the data is mainly collected from Social media platforms using Web Scrapping APIs. This scrapping is running on a preset scheduler to collect information at regular intervals of time and new data is added to the existing information set ( 15 ). In our model, data is stored in PostgreSQL. Currently the solution is hosted locally, however, as the complexity and size of data increases, we plan on scaling the solution toward AWS S3 with 3 AZs.

3.2 Data pre-processing

At this stage the data is made ready for ingesting into the model for obtaining desired performance. In the signal, it clears unnecessary effects, prevents issues, and improves accuracy. In this stage dataset namely the “BFL-CS dataset” and operations such as data cleaning, normalization and development of data stream is done.

3.3 Data cleaning and normalization

All the blank value fields and social media comments which clean word stems are not established are deleted from the database to prevent any kind of influence on the model due to high level outliers. Also, in order to eliminate the influences presented in the dissimilar scale features is executed in this process which reduces the model’s run time.

In many cases in the data science space, data scientist use the method of min-max normalization process. However, this method has its own problems, since this is rather a feature scaling method – this normalization significantly lowers the biasness of the model. While a lot of cases see biasness as a vice, in our case the biasness of the model actually points us toward the habitual bullies ( 16 ). Therefore, in our model we apply a rather lesser known normalization process which creates a correlation between the dataset and the standard deviation of the dataset.

3.4 Data stream for real time data publication to base database

This step involves a sophisticated integration of advanced data streaming and storage methodologies, as this step is very crucial in sensing repeated offenders and sensing their patterns. The various concepts incorporated in the model are as follows:

Event-Driven Architecture is a process that enables real-time processing by triggering and responding to events as they occur via web hooks, making it instrumental in capturing and handling data streams in real time. Kafka facilitates the building of real-time data pipelines and streaming applications. The process of collecting and importing real-time data streams into the base database for immediate storage and analysis. Utilizing messaging protocols (such as AMQP and XMPP) that minimize the time it takes for data to travel from source to destination, ensuring low-latency data delivery.

3.5 API Integration

Representational State Transfer APIs follow a set of architectural principles for designing networked applications, providing a standardized way for systems to communicate ( 17 ). Webhooks enable real-time communication between systems by triggering events in one system based on actions or updates in another, enhancing the responsiveness of API integrations. OAuth is a protocol for secure API authorization, allowing applications to access resources on behalf of a user with limited permissions. A centralized entry point that manages and optimizes API requests, ensuring scalability, security, and efficient data flow between systems. The entire design is parametric in nature without any hardcoded values. These parameters will be controlled by API driven microservices.

3.6 Data broadcaster to blockchain

At this stage a data broadcaster is developed which pushed the information to the blockchain, marrying the real-time dissemination of information with the immutable, decentralized characteristics of blockchain technology.

Key Components and Technical Processes involved at this stage. The deployment of a specialized protocol, such as DBP (hybrid ICMP & POP3), facilitates the secure and efficient real-time broadcasting of diverse data types onto a blockchain network. Decentralized Ledger Technology ensures a decentralized and distributed ledger, eliminating single points of failure and fortifying data availability across a network of nodes. The integration of a sophisticated execution engine ensures the seamless automation and enforcement of predefined rules embedded within smart contracts associated with the broadcasted data. The utilization of cryptographic hash functions, which is SHA-512 (specialized for our application), safeguards the immutability of data on the blockchain, rendering each block impervious to unauthorized modifications. The consensus algorithm, like Proof of Work (PoW) or Proof of Stake (PoS), orchestrates the agreement among network nodes, validating transactions and solidifying the security of the data broadcasting process. Blockchain’s inherent transparency provides an audit trail that allows participants to scrutinize the origin, journey, and modifications (if any) made to the broadcasted data, fostering accountability and trust. The comprehensive security architecture ensures the resilience of the data during transmission and storage, encompassing encryption, public-key infrastructure (PKI), and other robust security measures.

3.7 Blockchain administration system

This system tracks that individual changes are meticulously recorded within blocks, contributing to a transparent and tamper-resistant ledger with time & pseudo random number based identification module. The system allows for individual data entries to be added to the blockchain, with each piece of information forming a block in the distributed ledger. This decentralization eliminates the need for a central authority, enhancing transparency and reducing the risk of single points of failure ( 18 ). The heart of blockchain’s power lies in its unchangeability. Information in a block, once added, is cryptographically secured, making it virtually impossible to modify or erase. This feature guarantees the integrity of the recorded data throughout its entire existence. Every block in the blockchain is timestamped, providing an accurate record of when each data addition occurred. This temporal dimension adds another layer of transparency and traceability to the administration system. Smart contracts, self-executing contracts with predefined rules, can be incorporated to automate specific administrative functions. This enhances efficiency and reduces the need for manual intervention in routine processes. The administration of the blockchain is distributed across network nodes, eliminating the need for a centralized administrator. This decentralized governance model aligns with the principles of autonomy and inclusivity.

3.8 Deep learning engine

The deep learning engine that we are using in our architecture has two methods built in it. We first run classifications using LSTM and then we run another classification using Deep Belief Networks which then throws out the result.

Long Short-Term Memory (LSTM) is modified process of recurrent neural network (RNN) architecture designed to address the diminishing gradient situations in usual RNNs, enabling more effective modeling of sequential data. The key innovation of LSTMs lies in their memory cells, which allow them to capture and store information over long sequences.

Mathematically, as per theory, the following is to be noted in terms of LSTM model:

The base model contains of three units—the input unit i p , forget unit f , and output unit o p .

In addition to that, data state is stored in – cell state c s .

The input unit handles the process flow of new information into the cell,

The forget unit controls the retention of existing information,

and the output unit handles the knowledge to be output from the cell.

In addition to LSTMs, the model proposed in the paper also used Deep Belief Networks (DBNs) in tandem.

Here, α is a weighting parameter that determines the influence of each component on the final output. This hybrid approach aims to exploit the complementary strengths of LSTM and DBN, providing a more robust and expressive model for tasks such as sequence generation, where capturing both short-term and long-term dependencies is crucial. The choice of α allows for flexible adjustment of the contribution of each component, enabling fine-tuning based on specific task requirements and data characteristics.

3.9 Mathematical model

From the above mathematical model, we define a base algorithm on directions of which the entire architecture is built, the algorithm is as follows:

ALGORITHM 1 : Deep learning engine of BFL-CS.

3.10 Federated learning node

In the context of the proposed model on combating cyberbullying through a decentralized defense system, Federated Learning (FL) emerges as a main technology backbone of the solution. By distributing the model training process across individual devices, FL ensures that sensitive user data, integral to understanding and mitigating cyberbullying, remains localized. The use of Federated learning is used to handle separate learning activities across the data. This step has actually made the system faster by running complex algorithms across small scale datasets with limited features.

This decentralized approach mitigates privacy concerns associated with centralization, a critical consideration in the realm of cyberbullying detection. Moreover, FL’s iterative model refinement, conducted collaboratively while preserving individual data, holds significant promise in enhancing the system’s understanding of evolving cyberbullying patterns. The incorporation of FL in the proposed system aligns with the broader goal of empowering users and institutions to actively contribute to the development of robust cyberbullying detection models, fostering a collective defense against online harassment while respecting individual privacy. The Algorithms 1 , 2 for the complete model is given below:

ALGORITHM 2 : Complete BFL-CS Model.

This code implements a secure federated learning system for training a combined LSTM and DBN model. In each round, clients are chosen to participate. They receive a global model, train their local versions on their own data, and calculate updates. To protect privacy, these updates can be masked with noise or securely combined before being sent back to a central server. The server aggregates the updates and improves the global model. Finally, for tamper-proof tracking, each improved model is recorded on a blockchain ledger. This process repeats for multiple rounds, resulting in a collaboratively trained model without ever sharing the raw data from individual clients.

3.11 Result node, feedback loop: to deep learning engine and corrective data loop: to social media

In the proposed system, the culmination of federated learning, LSTM, DBN, data collection, preprocessing, and blockchain management converges at the result node ( 21 ).

This node serves as the repository for the outcomes of the intricate processes conducted during each communication round. Subsequently, these results are broadcasted into the system feedback loop, initiating a sequence of actions for system parameter optimization. The system feedback loop strategically utilizes the obtained results to refine global model parameters, enhancing the overall effectiveness of the cyberbullying detection system. Simultaneously, the results are channeled into the social media loop, triggering actions against systemic bullies. This dynamic loop interfaces with social media platforms to deploy measures aimed at curtailing cyberbullying activities. The feedback-driven optimization process and decisive actions against online aggressors collectively contribute to the robustness and adaptability of the decentralized defense system, fostering a safer and more secure online environment.

3.12 Alloy modeling

In this paper, Alloy language helps in formalizing and modeling the intricate social connections within the context of cyberbullying detection ( 22 ). Alloy, a declarative modeling language, provides a robust framework for expressing and analyzing complex relationships between entities in a system. Specifically, we employ Alloy language to create formalized declarations and constraints that define the features and dynamics of social interactions within the cyber realm ( 23 , 24 ). We construct a formal model that captures the essential features and constraints relevant to cyberbullying scenarios. This model helps in shaping the foundation of our proposed methodology, influencing the design of our novel algorithm. Alloy’s ability to articulate intricate relationships and constraints enhances the precision of our modeling efforts, contributing to the overall effectiveness of the decentralized defense system against cyberbullying.

4 Experimental results and discussions

The working of the BFL-CS method for detection and prevention of Cyberbullying in social media is tested with the Federated Deep Learning Processes which employ various methods.

The method is tested against various measures such as Recall, F1, Accuracy etc., and the results are compared with existing methods such as Vanilla RNN (v-RNN), Deep Reinforcement Learning (DRL), Residual Networks (ResNet) and Capsule Networks (CapNets). It is to be noted that the design is specifically made for English language analysis, it is seen that with appropriate data training, the results on various regional languages also show same results as shown by Pawar et al. ( 25 ) and Haider et al. ( 26 ).

4.1 Experimental setup

In this paper, the proposed methodology is implemented using Python and R. Pre-built packages are used for the implementation ( 27 ).

4.2 Programming setup parameters

In this research, Mean Squared Error (MSE) serves as the error function, while the RELU activation function is employed.

The rate of learning is set to 0.001, with a bundle size of 300 and a dropout rate of 0.1. To enhance the performance of the BFL-CS method, a Gradient-based target optimizer is applied, as illustrated in Eqs. 12– 14 , for hyperparameter optimization in this study ( 28 ). Another important aspect is that the data is purely textual in nature ( 29 ).

4.3 Dataset description

In the paper, we have utilized the dataset of Cyberbullying which is available on Kaggle by Sahane et al. ( 30 ) & KLEJ ( Kompleksowa Lista Ewaluacji Językowych ) ( 31 ) to implement the BFL-CS method for detection of Cyberbullying.

4.4 Evaluation measures

The performance of the proposed method for Cyber bullying is evaluated through evaluation statistics such as Recall, Accuracy, Specificity, F1-score, etc. ( 32 ). The performance evaluation of these metrics is based on the mathematical expressions mentioned below.

Accuracy: This is the measure that measures the efficacy of the model with respect to correct classification of data-points on Cyberbullying scope.

Precision: This is the measure that shows the overall consistency of the model and shows how many instances does the model provide accurate classifications ( 12 ).

Recall: This measure shows the number of positive values that are measured on a random basis from the total number of positive classifications feedback ( 13 ).

F1-score: This is a derived value which is the mixture of Recall and Precision – basically the Harmonic mean of both these functions ( 33 ).

Specificity: This is again a very simple measure which sort of is the opposite of precision. This is the total negative hits of the model out of the total negative values ( 34 ).

4.5 Performance analysis

The statistical performance evaluation of the proposed model for detection and prevention of Cyberbullying in social media is tested with the Federated Deep Learning Processes which employ various methods.

The BFL-CS method is evaluated with various evaluation measures against existing methods such as Vanilla RNN (v-RNN), Deep Reinforcement Learning (DRL), Residual Networks (ResNet) and Capsule Networks (CapNets) ( 27 , 35 ). From Figures 2 – 6 , the performance of various methods as mentioned above are compared with respect to the BFL-CS. It is pertinent to note that the results are with respect to the overall accuracy of detection ( 36 ).

Figure 2 . Comparison of accuracy.

Figure 3 . Comparison of precision.

Figure 4 . Comparison of recall measure.

Figure 5 . Comparison of F1-score.

Figure 6 . Graphical representation of specificity analysis.

The plot shown in Figures 2 , 3 illustrates the accuracy and precision of the BFLCS method in comparison to other known models. Impressively, BFLCS method has managed a remarkable accuracy of 98.92%. In contrast, established methods like v-RNN, DRL, ResNet, and CapNet demonstrated lower accuracies, recording values of 93.21, 96.43, 95.38, and 97.20%, respectively. Furthermore, examining precision, the BFL-CS method excels with a notable precision score of 97.91%.

We see that the system shows that it has achieved a high recall of 97.61% while the existing methods show much less recalls.

Figure 5 represents the graphical analysis to illustrate the F1-score of the BFL-CS method and the existing methods and again the superiority of the proposed solution.

The proposed methodology achieved high specificity of 97.55% while the existing methods obtained low specificity of 96.37, 95.61, 94.53, and 94.16%, respectively ( Figures 7 , 8 ).

Figure 7 . AUC-ROC plots.

Figure 8 . Comparison of run time.

In above plot shows the area under curve of the proposed methodology. The proposed solution method showed a higher ROC of 0.9812 while the existing models such as vRNN, DRL, ResNet, and CapNet obtained a low AUC-ROC of 0.9691, 0.9592, 0.9494 and 0.9576, respectively.

We have tabulated the comparison of various statistical parameters of the proposed solution and the existing models such as vRNN, DRL, ResNet and CapNet. The details of our analysis are given ( Table 1 ).

Table 1 . Tabulation of statistical performance measure of various laid down processes against the proposed methodology.

BFL-CS achieved the highest accuracy (98.92%) and AUC-ROC (0.9812), indicating that it correctly classified the most data points and has the best ability to distinguish between positive and negative classes. However, it also has the second highest computational time (16 s).

v-RNN, DRL, and ResNet all have similar performance in terms of accuracy (around 95–96%) and computational time (around 20 s). They also have good precision, recall, and F1-score, which means they are good at identifying both positive and negative cases correctly. CapNet has a slightly lower accuracy (97.2%) and AUC-ROC (0.9526) compared to the other methods, but it has the highest computational time (33 s). This suggests that CapNet may be less efficient than the other methods, even though it has a good overall performance. In addition to comparison of BFL-CS with respect to other Deep Learning models, we also compared the accuracy of other implemented solutions ( Table 2 ).

Table 2 . Comparison of technique, dataset & accuracy of previous work done on the subject.

The table suggests that models using sentence encoders (SBERT, DAN) perform well on publicly available data (Kaggle, Youtube, Twitter) and achieve high accuracy (above 97%). The model using a multi-technique approach (SVM, CNN, XGBoost) shows competitive performance on a specific dataset (VISR) ( 37 , 38 ). The BFL-CS model, which combines blockchain, federated learning, and deep learning (LSTM & DBN), achieves the highest accuracy but the data source is not specified.

5 Conclusion

The study done on the paper is a novel approach named Blockchain & Federated Learning based Cybersecurity Solution (BFL-CS) Algorithm for detection and prevention of Cyberbullying in social media. In this study, LSTM-DBN in-tandem is utilized along with block chain based federated learning. We see from our design that a major roadblock of the proposed methodology is the usage of multiple technologies in the model, therefore making it very complex for implementation, particularly in implementation of Federated Learning where two complex deep learning methods are already running, while FL is being carried out across the blocks of a real time updated ledger. This level of interconnectedness with various cutting edge technologies will required significant computational resources and strong network data transfer capabilities, however, we have tried to solve this problem by keeping only one epoch of Block-chain updation post training of data, when we increase the frequency of block updations, this approach may prove to very computationally expensive, as each updation will need a hashing process and consensus building. In the future, we should explore in making the blockchain and vanilla federated learning processes more effective. At this point of time, we have high efficacy with respect to the Deep Learning engine, however, this only contributes to only a fraction of what this approach is all about. However, handling the federated learning layer is very crucial when the size of data increases. While there has been attempts in the past at making this process more efficient, however, all of these have created compromises in the security part of it. Therefore, the future scope of work will play out in this direction. In the future scope of work, we try in developing an in-line module in one of the social networks to do a real time reporting and correction of cyberbullying online.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Author contributions

AA: Conceptualization, Formal analysis, Funding acquisition, Methodology, Project administration, Writing – original draft. AM: Conceptualization, Formal analysis, Data curation, Validation, Visualization, Writing – review & editing.

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research work was funded by Institutional Fund Projects under grant no. (IFPIP: 55-865-1442). Therefore, authors gratefully acknowledge technical and financial support from the Ministry of Education and King Abdulaziz university, DSR, Jeddah, Saudi Arabia.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: public health, prediction, health monitoring, blockchain, cyberbullying, federated learning, decision making

Citation: Alabdali AM and Mashat A (2024) A novel approach toward cyberbullying with intelligent recommendations using deep learning based blockchain solution. Front. Med . 11:1379211. doi: 10.3389/fmed.2024.1379211

Received: 30 January 2024; Accepted: 15 March 2024; Published: 02 April 2024.

Reviewed by:

Copyright © 2024 Alabdali and Mashat. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Arwa Mashat, [email protected]

This article is part of the Research Topic

Cluster-based Intelligent Recommendation System for Hybrid Healthcare Units