The graduate program in Kinesiology is an integrated study of movement encompassing the physiological, mechanical, and behavioral aspects of physical activity. The curriculum includes lectures and laboratory courses, seminars, independent study, and mentored research.
The curriculum consists of a set of 6 required core courses (30 credits) and either a thesis (for the research track) or a capstone project (for the capplied track). The remaining 18 credits may be taken from the list of electives provided below. The program may be completed in two years by taking classes during the Fall, Winter, and Spring quarters. Please note: some electives offered outside of the department may only be available in the Summer quarter.
The thesis option is designed to provide the fundamental framework for understanding and conducting research in kinesiology. In addition to course work, students complete a research project as part of the thesis requirement under the supervision of a faculty mentor. Through a rigorous research experience, students will demonstrate their mastery of the material and to contribute to the body of knowledge in the field of kinesiology. Graduates within the thesis track often pursue further graduate training such as advanced study at the doctoral level, admission to allied health professional programs, or medical school. Those students not continuing on with further graduate studies typically pursue careers in research, educational, or industrial settings.
The applied data science track will teach students the latest advancements in data science for application within the field of Kinesiology. Students will have the opportunity to gain the analytical skills needed to work with complex sport and human performance data and contribute to important advancements in the field for improving both athletic performance and general health and well-being. In the applied data science track, students will learn how to apply evidence to practice through a 600-hour applied capstone experience in their second year of the program. An interdisciplinary approach will guide students to greater data science and analytics skills that are applied within Kinesiology and are highly transferable to other fields as well. Graduates within the applied data science track often pursue careers in performance analytics, sport technology, data science, consulting, recruitment analytics, or applied sport science for sports organizations. technology providers, sport analytic providers, or allied health care systems.
The purpose of this course is for students to become familiar and proficient with exercise-specific research designs that informs evidence-based practice for human performance and health.
The purpose of the Graduate Seminar is to enhance awareness of crucial matters that influence the shape and viability of scholarship, professional practice, and performance centered on physical activity and examining and analyzing current problems and issues facing our field. The Graduate Seminar has two major components: (1) scholarly presentations by graduate students; and (2) examination and analysis of current problems and issues facing people engaged in scholarly study, professional practice, and/or performance centered on physical activity. Graduate Seminar meetings will typically consist of discussions based on preparatory readings, other assigned preparatory work, or results of work in small break-out groups occurring during the meeting.
The purpose of this course is engage graduate students in scholarly discussions with professionals whose work relates to the disciplines of movement science. The format of the course will include a 2h research panel, occurring bi-weekly. During the first hour (open to the general public), themed experts across the exercise disciplines will briefly present relevant information based on that week’s theme (e.g. obesity), with follow-up panel discussion. The second hour (closed to enrolled students) will be a break-out session where the visiting researchers speak in more intimate groups to directly encourage student enquiry. The speakers for the seminar will include both internal and external professionals who will present their scholarly work, and the topics will vary for each panel. Graduate students enrolled in this course will be expected to complete readings to prepare for each seminar, and will have the opportunity to meet with the speaker after the seminar in a more intimate setting. This format encourages the development of professional conduct and networking skills, and has the potential to foster interdisciplinary collaborations both inside and outside of Seattle University’s campus. This course will also serve to build the department’s sense of community as all members of the Department of Kinesiology will be encouraged to attend the weekly seminar.
The purpose of this course is to advance students’ understanding of the concepts, terms, and methods of investigating biomechanics, neuroscience/neuromechanics, motor control, and movement disorders in the human movement system. These topics will be addressed using examples from clinical rehabilitation, sporting and workplace environments.
The purpose of this course is to explore special topics in the development, maintenance, and adaptation of skeletal muscle to short-term and long-term exercise, as it relates to health and disease.
The course is designed to give students an evidence-based approach to the role of physical activity in improving health outcomes in diseased and non-diseased states.
Completion of a thesis that serves as the culminating experience for graduates of the M.S. Program in Movement Science. Students will complete a substantive project, allowing them to demonstrate their mastery of the material and to contribute to the body of knowledge in the field of Movement Science.
The Capstone Project is designed to demonstrate your accumulated training in Movement Science in a single original portfolio of your experiences within the clinical setting.
Movement and locomotion are fundamentally important to every aspect of animal biology. The purpose of this a lecture and tutorial-based course is to advance students’ understanding of the mechanics and physiology of locomotion. The course will be focused on terrestrial bipedal locomotion and address the following areas: 1) theories of bipedal locomotion, 2) kinematics and kinetics of locomotion, 3) energy utilization and transfer during the gait cycle, and 4) factors influencing locomotion.
The purpose of this course is to critically apply skills and methods necessary for assessment, acquisition, interpretation, and application of knowledge for evaluating health and human performance.
This course is designed from a holistic and combined research approach to give students practical tools for analyzing sport performance. Students will learn appropriate methods of disseminating, displaying, and communicating athletic performance information.
Objective of course is for students to develop statistical reasoning skills and to choose appropriate quantitative techniques for analyzing research questions in criminal justice. Topics include the examination of the basic concepts and measures in statistical analysis, probability theory, statistical inference, and bivariate and multivariate analyses, correlational relationships, t-tests, ANOVA, and regression.
Provides an overview of quantitative, qualitative, and mixed-methods research. Emphasizes paradigms, designs, methods, skills, and dispositions required for planning and conducting doctoral-level research. Equips students to access scholarly literature in databases, critique research studies, write literature reviews, propose future research, and defend its significance.
Develops knowledge and skills to understand and apply quantitative methodologies; focuses on surveys and statistics for analyzing, interpreting, and displaying quantitative data; provides a foundation and framework for quantitative inquiry and design.
Develops knowledge and skills to understand and apply qualitative methodologies; focuses on collecting, analyzing, interpreting, and displaying interview, narrative, and observational data; provides a foundation and framework for qualitative inquiry and design.
Ethical and legal issues in technology and the use of data. Problems, controversies, policies and best practices. Topics include data dignity, data set bias, intellectual property protection of data, technology’s compatibility with social justice values, and ethical technology implementation. Leadership models for data scientists.
Statistical inference and experimental design. Parameter estimation, resampling methods, and statistical modeling. Applied linear regression and logistic regression. Selecting appropriate models and interpreting model results. Topics also include causal inference and study designs. Statistical software will be used for computation, simulation, and visualization.
Principles of effective design in data visualization. Psychological underpinnings of data visualization methods. Data wrangling skills to appropriately format and transform data before using visualization tools. How to use visualizations to efficiently communicate information to specific audiences. Accessibility in data visualization.
Methods in statistical learning and modeling. Topics will include multiple regression, logistic regression, non-linear models. Dummy variables and interaction effects. Model selection and model assessment.
