The MS in Human Factors and Cognition prepares you to design smarter, safer, and more intuitive systems by understanding how people think, perceive, and interact with technology. Whether your background is in psychology, design, engineering, or computer science, this program empowers you to bridge the gap between human behavior and technological innovation.
Learn to apply cognitive and behavioral science to real-world challenges, evaluating how humans interact with complex systems and creating products, technologies, and environments that truly serve their users.
At LTU, you’ll have the opportunity to engage in hands-on research and human-centered design projects that integrate science, creativity, and technology.
Earn two degrees in just five years. This master’s program can be combined with the following undergraduate degrees:
If you are interested in earning a 4+1 degree but your degree is not listed here, contact your academic advisor.
Course Name
Course #
Credits
This course provides a comprehensive survey of the field of human factors, emphasizing the theoretical foundations, empirical methods, and applied challenges involved in optimizing human performance and well-being in complex sociotechnical systems. Students will critically examine topics including perception and cognition, decision making, human error, workload, user-centered design, human-computer interaction, and system safety. Through an integration of classic literature, contemporary research, and real-world case studies, the course prepares students to evaluate and contribute to cutting-edge research in human factors across diverse domains such as healthcare, aviation, transportation, and automation. Emphasis is placed on rigorous methodological training, interdisciplinary synthesis, and scholarly communication through presentations, research proposals, and peer-reviewed writing.
PSY5XX3
3
Research Design and Statistics
XXX3
3
Elective
XXX3
3
Total Credits:
9
Course Name
Course #
Credits
This course provides a comprehensive examination of the core domains of cognitive psychology, including perception, attention, memory, language, decision making, problem solving, and learning. The course emphasizes theoretical frameworks that characterize cognition in terms of knowledge representation and information processing, drawing on both classical models and contemporary developments in computational and neural approaches. Students will critically engage with foundational and current research to understand how cognitive functions are instantiated, measured, and modeled. Attention is also given to the application of cognitive principles in real-world contexts, including human-machine interaction, applied cognition, and the integration of human cognition with artificial systems. Through readings, discussions, written critiques, and independent projects, students will gain the theoretical and methodological expertise necessary to contribute to the advancement of cognitive science.
PSY5XX3
3
This course explores the interdependent processes through which organisms acquire, interpret, and respond to information from the environment. Covering key topics in visual, auditory, tactile, and proprioceptive perception, the course examines how sensory information guides motor planning, coordination, and control. Emphasis is placed on theoretical models that link perceptual processing to action, including ecological, computational, and embodied cognition perspectives. Students will engage with current empirical research addressing topics such as sensorimotor integration, perception-action coupling, affordances, and motor learning, as well as applications in robotics, virtual environments, rehabilitation, and human-machine interaction. Through critical analysis, research proposals, and interdisciplinary synthesis, students will develop a deep understanding of how perception and action are jointly organized in adaptive behavior.
PSY5XX3
3
Elective
XXX3
3
Total Credits:
9
Course Name
Course #
Credits
Research Project I
XXX3
3
Elective
XXX3
3
Total Credits:
6
Course Name
Course #
Credits
Research Project II
XXX3
3
Elective
XXX3
3
Total Credits:
6
Course Name
Course #
Credits
Course not found.
PSY3732/5XXX
2
Course not found.
PSY3713/5XX3
3
This course focuses on leadership skills specific to the allied disciplines of design within the College of Architecture and Design. Students will engage models of leadership relevant to a dynamic and evolving professional context. Course content will include typologies of leadership organization, principles of successful teamwork and collaboration, viable economic frameworks, ethics and design entrepreneurship.
DES5112
2
Course not found.
DES5113
3
Course not found.
DES5413
3
Covers a new or specialized topic in Mechanical Engineering for which there is strong faculty and student interest, but is not covered in other courses. Credit hour is indicated by the last digit of the course number.
EME5983
3
This course introduces a machine learning technique called deep learning and its Electrical Engineering applications, as well as core machine learning concepts such as data set, evaluation, overfitting, regularization and more. Topics in: Real-time decisions in autonomous vehicles, warning systems, radar, LiDAR sensor fusion. Covers neural network building blocks: linear and logistic regression, followed by shallow artificial neural networks and a variety of deep networks algorithms and their derivations. Including interactive programming with industrial automation hardware and software.
EEE5253
3
This course focuses on writing maintainable and extensible engineering systems code development. Topics include: smart software encryption and cybersecurity development in autonomous vehicles, physical systems semantic networks, frames, pattern matching, deductive inference rules, case-based reasoning, and discrimination trees. Project-driven. Substantial programming assignments. Including interactive programming with industrial automation hardware and software.
EEE5513
3
This course focus on Sampling theory and sampling hardware, Z-transform, Discrete Time Fourier Transform, architecture of VLSI digital signal processors. Design and implementation of real time polynomial, FIR, IIR, and adaptive filters, spectral analysis with DTFT will be dealt. Filter realization techniques, Direct I, Direct II, Canonical, Parallel form. Design of DSP application in communication and digital control. Substantial programming assignments. Including interactive programming with industrial automation hardware and software.
EEE5653
3
The objective of the course is to study, understand, and practice the concepts of machine learning and pattern recognition. The course will cover the basic aspects of pattern recognition and machine learning such as different approaches to feature selection, classification methods, interpolation methods, and techniques of machine learning performance evaluation. In the end of the course the students will be able to implement all aspects of pattern recognition to create a working machine learning system that will solve a real-life pattern recognition problem.
MCS5623
3
An introduction to computational scene understanding focused on computer vision. Students will study the acquisition and processing of camera data to describe the surrounding environment, using tools and methods now being deployed in industry. Included topics to range from basic image processing techniques such as camera models, object detection, and filtering to higher level scene understanding methods using neural networks to perform multi-view reconstruction, motion/tracking, and recognition.
MCS5623
3
Security measures are associated with various types of computing systems. An introduction to network security fundamentals, including compliance and operational security; threats and vulnerabilities; application, data, and host security; access control and identity management; and cryptography. New topics in network security, including psychological approaches to social engineering attacks, web application attacks, penetration testing, data loss prevention, cloud computing security, and application programming security. It is recommended, but not required, that MCS3663, MCS4613, and MCS4653 is taken prior to taking MCS5813.
MCS5813
3
As networks continue to grow and as computing becomes more and more ubiquitous, today’s IT Managers need to have a thorough understanding of security and the risks associated when inappropriate security exists. Students will explore basic security concepts, principles and strategy, how to develop and manage IT security program and how to strategize and plan an IT architecture. Students will also discuss other IT security issues as it relates to current market trends.
INT7223
3
Minimum requirements for admission to the MS in Human Factors and Cognition program are as follows:
Use Your Cell Phone as a Document Camera in Zoom
From Computer
Log in and start your Zoom session with participants
From Phone
To use your cell phone as a makeshift document camera
