Masters Degrees in Human-Computer Interaction, USA

Program overview

Human-computer interaction (HCI) addresses the design, evaluation, and implementation of interactive computing and computing-based systems for the benefit of human use. HCI research is driven by technological advances and the increasing pervasiveness of computing devices in our society. With an emphasis on making computing technologies more user-friendly, HCI has emerged as a dynamic, multifaceted area of study that merges theory from science, engineering, and design––as well as concepts and methodologies from psychology, anthropology, sociology, and industrial design––with the technical concerns of computing.

The master of science degree in human-computer interaction provides the knowledge and skills necessary for conceptualizing, designing, implementing, and evaluating software applications and computing technologies for the benefit of the user, whether the user is an individual, a group, an organization, or a society. Human, technological, and organizational concerns are interwoven throughout the curriculum and addressed in team- and project-based learning experiences.

Plan of study

The program is comprised of four required core courses, up to three program electives (depending upon capstone option chosen), two application domain courses, and a capstone project or thesis.

Core courses

The core courses provide knowledge and skills in the conceptual and methodological frameworks of HCI and HCI research. Emphasis is on understanding human cognition as it applies to information systems plus interaction design, interface prototyping, and usability evaluation.

Electives

Student choose up to three electives, depending on which capstone option they choose to complete.

Program electives

Students will select two courses from the program electives list. In select cases, students can petition for approval to include a course complementray to the degree program as a program elective. See website for further details of available electives: https://www.rit.edu/programs/human-computer-interaction-ms

Application domain courses

To gain breadth in a technical area to which HCI concepts can be applied, students complete two courses in any of the following application domain areas. A special topics option is also available, with faculty approval, for individuals with interest in other HCI-related areas. See website for further details of available domain courses: https://www.rit.edu/programs/human-computer-interaction-ms

Thesis/Capstone project

Students may complete a thesis or capstone project. (Student who choose the capstone will complete one additional elective.) This experience is meant to be an empirical study of a HCI problem, which can be the development of a software product through user-centered design processes. The results are either published in a peer-reviewed journal or publicly disseminated in an appropriate professional venue.

Curriculum

Course sequence differs according to selected thesis/project option, see website for further details of a particular option's modules and electives: https://www.rit.edu/programs/human-computer-interaction-ms

Other admission requirements

-Have a minimum cumulative GPA of 3.0* (B average).
-Submit official transcripts (in English) of all previously completed undergraduate and graduate course work.
-Have prior study or professional experience in computing; however, study in other disciplines will be given consideration.
-Complete a graduate application.
-International applicants whose native language is not English must submit scores from the Test of English as a Foreign Language. Minimum scores of 570 (paper-based) or 88 (Internet-based) are required.
-Applicants with undergraduate degrees from foreign universities are required to submit GRE scores.

*Applicants with a GPA below 3.0 may be considered, but are required to submit standard Graduate Record Exam (GRE) scores.

Additional information

Prerequisites:
The program requires strong technical and social science skills. Knowledge of quantitative statistical methodologies is important since students review research studies as well as analyze the results of their own usability evaluations. Students are also expected to have a solid background in computer programming. These competencies may be demonstrated by previous course work, technical certifications, or comparable work experience. Bridge courses are available to fulfill any gaps in an applicant's qualifications. Applicants will be made aware of any areas where additional course work may be necessary.

Maximum time limit:
University policy requires that graduate programs be completed within seven years of the student's initial registration for courses in the program. Bridge courses are excluded.

Online option:
The program can be completed on campus or online.

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The Duke University Master in Interdisciplinary Data Science (MIDS) is home for creative problem-solvers who want to use data strategically to advance society. We are cultivating a new type of quantitative thought leader who uses disruptive computational strategies to generate innovation and new insights.

MIDS combines rigorous computational and technical training with field knowledge and repeated practice in critical thinking, teamwork, communication, and collaborative leadership to generate data scientists who can add value to any field.

Program Overview

Duke MIDS is a two-year program designed to help meet the need for knowledgeable data scientists who can answer important questions with data-backed insights. All MIDS students complete a set of eight core courses that cover critical topics in statistics, machine learning, database management, data wrangling, data communication, analytical thinking, team management, and ethics. The core courses are designed to fit together as a cohesive set of learning experiences, and ensure that students have repeated practice interpreting and reporting the results of analyses on real data sets. Accompanying these core courses, students choose a set of approximately eight electives that deepen their expertise in a methodological or domain area. Students culminate their experience with a capstone project that will be completed over the course of at least one year with mentoring from Duke’s world-class faculty.

Why Duke MIDS?

• World-renowned faculty
• Personalized pathways
• Diver student body
• Comprehensive training
• Collaboration across disciplines
• Critical thinking about real problems

For more information on the syllabus visit the "courses" section: https://mids.duke.edu/

Who Should Apply?

MIDS is open to all applicants who demonstrate a passion for data analysis, a mastery of analytical reasoning, an aptitude for learning quantitative and technical skills, and compelling academic or professional achievement.

We welcome applicants of any age and background, including (but not limited to) recent college graduates with quantitative majors, database engineers who have been in the IT field for years, government professionals who want to integrate data science into federal or local offices, and journalists who want to incorporate data mining into their investigative skills.

Due to our comprehensive approach, our application process requires applicants with primarily quantitative backgrounds to demonstrate their commitment to excelling in the problem-solving, communication, and team-building aspects of data science. Likewise, applicants without quantitative backgrounds are asked to demonstrate their commitment to learning quantitative concepts and skills quickly through mechanisms like online classes or recommendations from colleagues with strong quantitative track records.

We provide resources for students to review and learn critical concepts and skills before beginning the core courses, so that all students can begin the core courses on a level playing ground.

Financial Support

For more information on the financial support, funding and scholarships that are available please visit: https://gradschool.duke.edu/financial-support

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