Contribute meaningful work to multiple fields of psychology while you explore and apply scientific methods to human development, social interactions, and behavioral relationships in a degree targeted towards your career aspirations.
In the experimental psychology masters degree, students are trained to apply scientific methods to basic psychological processes in perception, brain and behavior relationships, thinking, memory, learning, social interactions, human development and related areas. It is a broad and flexible program that provides a solid stepping-stone into careers or further study in psychology. A choice of tracks – in experimental psychology or engineering psychology – allows students to specialize their degree toward their career goals and aspirations.
The MS program in experimental psychology builds on the strengths of faculty research and student interests in experimental psychology broadly defined. The program as a whole provides a foundation for further advanced academic study in human factors and/or experimental psychology.
Plan of study
The program includes 30 credit hours of core courses, elective courses, and a thesis. It also offers students two tracks to choose from: experimental psychology and engineering psychology.
The experimental psychology track embraces the application of the scientific method to the study of behavior. Faculty are experts in a variety of fields including addiction, attention, cognition, development, evolutionary psychology, forensic psychology, perception, psychopathology, and social psychology, among others.
The engineering psychology track examines human capabilities to sense, perceive, store, and process information and how these human factors impact interactions with technology. This knowledge is applied to the design, use, and maintenance of human-machine systems. Courses emphasize the role of human behavior and performance in both simple and complex human-machine systems. Students are trained in both research methods of experimental psychology and application of the results to contemporary problems in industry. This track prepares students to function as effective engineering psychologists in industrial, governmental, or consulting organizations.
Students in the engineering psychology track must select two electives (students should check for course prerequisites or if permission of the instructor is required). Any graduate course at RIT can be taken as an elective, assuming prerequisites are met.
The program includes an optional cooperative education component. Co-op is generally completed in the summer after the first year of the program. The co-op experience provides experiential learning that integrates with classroom education and allows students to apply psychological principles to problems in a variety of work environments. Co-op may be completed in any business or industrial setting.
Students select a thesis adviser during the first year. Selection of an adviser, thesis topic, and research proposal must be completed in the second semester of the first year of the program. Ongoing research activity is expected through the summer term of the program. At the completion of the thesis, students will publicly present their findings and defend their research before a thesis committee.
Government (Local, State, Federal)
Typical Job Titles
Experimental psychology, MS degree, typical course sequence
Sem. Cr. Hrs.
This course reviews descriptive and inferential statistics. Basic and advanced conceptual material will be presented to assist students in their understanding of diverse data analytic methods, their appropriate application, and how to interpret statistical analyses. Topics include one- and two-sample inferential procedures, interval estimation, correlation, nonparametric tests, linear regression, and analysis of variance. Students will learn to integrate concepts with computer applications. Course content will be taught through lectures, discussion, and applied data analysis exercises. Student mastery of the material will be evaluated through small group discussion of data set analyses, written results of the analyses following APA style, and two exams.
In this course the students will learn to recognize the integrated (systems) nature of Engineering Psychology, the centrality of human beings in systems design, and to use the topics covered and the available knowledge base to adapt the environment to people. This course will cover several fundamental models of human information processing in the context of human-system interactions. The models may include but are not limited to Signal Detection Theory, Information Theory, theories of attention, both normative and naturalistic decision-making models, Control Theory, and the Lens Model of Brunswick, as well as models of the human as a physical engine, that is, anthropometry, biomechanics, and work physiology. Most topics include readings in addition to the course text as well as a lab exercise with a detailed lab report.
PSYC Elective (Experimental track)
Graduate Research Seminar
The guiding principle of Graduate Research Seminar is that it provides students the opportunity to begin examining potential thesis topics during the student's first semester in the program. The course will involve faculty presentations of their research offered weekly through the semester.
Graduate Research Methods
This course provides students with sufficient background in the skills and knowledge necessary to be able to conduct psychological research on a wide variety of problems. In addition to introducing students to numerous research methods used in the discipline, the course will also assist students in planning their thesis research proposal. In parallel with covering core topics in research methodology (such as varieties of data, the role of theory and models in science, psychophysiological methods, subjective methods, and experimental design) the course is designed to guide students through the process of creating a feasible research proposal. Students will also use data to test their designs and practice their analyses.
The Thesis courses will vary widely but will fulfill the work plan agreed by the student and the adviser. The guiding principles of the Thesis Proposal course are to initiate thesis research including selecting a thesis advisor, choosing and defining a topic, surveying relevant research literature, and planning the research. To complete the course, the student will successfully submit and defend a thesis proposal, which is a detailed and complete plan of the thesis research. The thesis proposal should include exhaustive review of relevant literature, statement of the student's thesis, formulation of hypotheses, operational definitions of independent and dependent variables, and a detailed procedure for carrying out the research. The proposal may also include a section on anticipated results with a detailed plan for analysis of data.
The Thesis courses will vary widely but will fulfill the work plan agreed by the student and the thesis adviser. The guiding principle of the Thesis course is to complete the thesis research proposed in Thesis Proposal. The Thesis course consists of carrying out the thesis research, including collection and analysis of data, and completion and public defense of the thesis document for partial fulfillment of the requirements of the degree.
Choose one of the following:
Total Semester Credit Hours
This course provides students with an introduction to the practical application of various research methods that can be used in human computer interaction. The course provides an overview of the research process and the literature review, and provides experience with qualitative, survey, and experimental research methods. Students will study existing research and design and conduct studies. Students will need to have taken a statistics course before registering for this class.
Foundations of HCI
Human-computer interaction (HCI) is a field of study concerned with the design, evaluation and implementation of interactive computing systems for human use and with the study of major phenomena surrounding them. This course surveys the scope of issues and foundations of the HCI field: cognitive psychology, human factors, interaction styles, user analysis, task analysis, interaction design methods and techniques, and evaluation. This course will focus on the users and their tasks.
Information and Interaction Design
Designing meaningful relationships among people and the products they use is both an art and a science. This course will focus on the unique design practice of: representing and organizing information in such a way as to facilitate perception and understanding (information architecture); and, specifying the appropriate mechanisms for accessing and manipulating task information (interaction design). This course will also explore the various design patterns (design solutions to particular problems) that are appropriate for the HCI professional. Students will need prior knowledge of an interface prototyping tool.
This project-based course will focus on the formal evaluation of products. Topics include usability test goal setting, recruitment of appropriate users, design of test tasks, design of the test environment, test plan development and implementation, analysis and interpretation of the results, and documentation and presentation of results and recommendations.
Current Topics in HCI
Human-Computer Interaction (HCI) is an evolving field. This course is designed to study the current themes and advanced issues of HCI. Topics will vary depending upon current research and developments in the field.
Topics in HCI for Biomedical Informatics
This course will provide a theoretical and case-based study of several areas of HCI, all considered within the application domain of biomedical informatics. Course topics include a scientific approach to UI design (usability engineering), domain-specific user analysis and user profiles, social and cultural influences, general and domain-specific design issues, information visualization, data integration, mobile devices, security, privacy, and ethics.
Agent-based and Cognitive Modeling
This course is intended as an introduction to the emerging areas of agent-based modeling and cognitive modeling. Both modeling approaches are at the intersection of research (theory development and confirmation) and computational simulation. This course will be an introduction to these topics, focusing on the research aspects of agent-based modeling and the development and testing of cognitive models. The role of visualization in modeling development and analysis is presented. Students will analyze the social science literature for current models and theories and will develop computational models incorporating these theories.
Designing User Experiences for Web-enabled Devices
Wearable computers and Internet of Things devices involve both hardware and software. In order to design user experiences for these systems, professionals must understand how they are built. Students will learn how to rapidly prototype and evaluate wearable and IoT devices combining hardware and software. Experience in programming is helpful but not a prerequisite.
User-Centered Design Methods
This course will focus on the major user centered design methodologies used in the development of applications and environments. Topics include: evolution of software design methods, emergence of user-centered design, and key concepts, attributes and process of the major design methodologies. Software design projects will be required.
Collaboration, Technology, and the Human Experience
Students will examine the role of technology and group collaboration in organizations. An overview of relevant theory, current and emergent technologies, and trends in collaborative science will provide the context for strategic implementation and development of collaborative environments. Group projects using collaborative technologies will be required.
Students collect data in the lab and conduct the data analysis using MATLAB software. Topics include skeletal anatomy and mechanics, muscle anatomy and mechanics, theory and application of electromyography, motion and force measuring equipment and techniques, human locomotion, balance and falls, inverse dynamics modeling of the human body, and current topics in musculoskeletal biomechanics research
Advanced Topics in Ergonomics and Human Factors
Advanced topics are selected based on current ergonomic and human factors issues and interests of students. Course is taught using a seminar format. Students are required to select, read, and discuss scientific literature relevant to the fields of human factors and ergonomics.
Systems Safety Engineering
Acquaints students with practical aspects of safety engineering. Students acquire a working knowledge of legal and technical aspects of safety. Focuses on a systems approach to safety engineering. Topics include Workers Compensation, OSHA, Consumer Product Safety Commission, NIOSH Guidelines and various hazard analysis and utilization techniques. Students also are exposed to various theories of accident causation, research methodology and ways of evaluating safety programs and related research.
Applied Psychology Methods
This course explores various types of applied research methods as well as important methodological issues and concepts in areas of applied psychology. Methodologies studied include experimentation, quasi-experimentation, content analysis, surveys, and interviews. Methodological issues cover research ethics, reliability, threats to internal and external validity, demand characteristics, volunteer participant problems, and issues in sampling.
A graduate level introduction to the field of behavioral neuroscience, the study of neurobiological basis of cognition and behavior. Topics include neuroanatomy and physiology, localization of function, brain injury, research methods in behavioral neuroscience, and biological basis of learning, language, memory, emotion, conscious states, sexual behavior, etc.
This course will survey theoretical and empirical approaches to understanding the nature of the mental processes involved in attention, object recognition, learning and memory, reasoning, problem solving, decision-making, and language. The course presents a balance between historically significant findings and current state of-the-art research. Readings that have structured the nature and direction of scientific debate in these fields will be discussed. The course also includes discussions of methodology and practical applications. Students will have opportunities to develop their research skills and critical thinking by designing research studies in cognitive psychology.
This course is designed to enhance students' knowledge and skills with regard to infant, child, and adolescent development. We will examine a variety of topics that relate to the physical, cognitive, and social-emotional development of children and adolescents in the context of classic and current theory. We will also explore issues such as attachment, resiliency, and policy issues that pertain to positive child and adolescent development. Students will gain an enhanced knowledge of the sequence of child development and the processes that underlie it by studying child development from a chronological approach. Theories that discuss the various domains of development will be examined through each age period. This course will emphasize the interdependence of all domains of development and contribute to an appreciation of the interrelatedness of theory, research, and applications.
The course is designed to provide students with a deeper understanding of topics in perception. This course will be organized such that students will work in groups on various projects as well as covering topics through readings and classroom discussion. The topics may include, but are not limited to: spatial frequency perception; aftereffects, visual illusions and their relationship to cortical function and pattern perception; color perception; depth and motion perception; higher order perception such as face and object recognition; and music and speech perception. The goal is to cover current research and theories in perception, looking at current developments and their antecedents. The course will be divided into various modules. Students will be assigned readings relevant to each section of the course, and will be expected to master the major concepts. Group discussion of the readings will complement lectures where the instructor will present relevant background material. There will also be laboratory time for the students, where they will examine empirical findings in perception, and develop their research skills in the field.
Graduate Social Psychology
This course explores topics related to understanding individuals in a social context. Topics may include, but are not limited to: Social Perception and Social Cognition; Attitudes; Social Identity; Prejudice and Discrimination; Interpersonal Attraction; Close Relationships; Social Influence; Prosocial Behavior; Aggression; Group Behavior; Artifacts and Methodological Issues in Social Psychology. Course format is seminar focused on reading assigned texts each week, writing reaction papers, and participating in discussion. Students will also conduct a study on the topic of their choice and present their findings both in an oral and written format.
Advanced Graduate Statistics
This course introduces students to more advanced inferential parametric and non-parametric data-analysis techniques commonly used in psychological research, but not covered (or not covered in depth) in the Graduate Statistics course. These techniques may include, but are not limited to: Reliability Analysis, Multiple Regression, Discriminant Analysis, Logistic Regression, Factor Analysis, Analysis of Covariance, Multivariate Analysis of Variance, Contrast Analysis, Mediator and Moderator Variable Analysis, Non-Parametric Tests, and Multi-level Modeling. The focus is on the conceptual understanding of these statistics, how different statistical procedures are applied in different research methods, how to perform analyses, how to interpret the results in the context of the research question, and how to communicate these results.
Hold a baccalaureate degree (or equivalent) from an accredited university or college.
Submit official transcripts (in English) of all previously completed undergraduate and graduate course work.
Have a minimum cumulative GPA of 3.0 (or equivalent)
Have a minimum of 15 semester hours of course work in undergraduate psychology or a related field (e.g., engineering, computer science, information technology), including one course in experimental psychology and one course in statistics.
Submit scores from the GRE.
Submit a personal statement describing the applicant’s goals for the program, focusing on their research interests and possible thesis research (including possible thesis mentors).
Submit two letters of recommendation from academic or professional sources.
International applicants whose native language is not English must submit scores from the TOEFL, IELTS, or PTE. A minimum TOEFL score of 79 (internet-based) is required. A minimum IELTS score of 6.5 is required. The English language test score requirement is waived for native speakers of English or for those submitting transcripts from degrees earned at American institutions.