Bachelor of Science in Cognitive Engineering (B.S.C.E.)
About the Program
The Bachelor of Science in Cognitive Engineering is crafted for students interested in the scientific and experimental study of thought processes, perception, and decision-making mechanisms. This program provides a robust, data-driven approach to understanding cognition, incorporating psychometric methodologies, cognitive modeling, and neurobehavioral research.Program Overview
The B.S. in Cognitive Engineering integrates advanced scientific principles with practical applications to examine and enhance cognitive functions. Students will gain in-depth knowledge of how cognitive processes are structured and can be engineered or modified. This program emphasizes the development of quantitative and analytical skills necessary for creating and implementing cognitive models that simulate human thinking and decision-making processes. Through a curriculum that includes quantum cognition, psychodynamic processing units (PPUs), cognitive wave interference, and applied cognitive reinforcement strategies, students will learn to assess and influence cognitive behaviors effectively. These studies prepare them for critical roles in behavioral research, AI cognitive structuring, and psychometric modeling, enabling them to contribute to advancements in cognitive technologies and therapies.Key Areas of Study
- Psychometric Methodologies and Cognitive Assessment
- Quantum Cognition and Non-Linear Thinking Models
- Cognitive Modeling and Neurobehavioral Research
- Psychodynamic Processing Units (PPUs) and Cognitive Wave Interference
- Applied Cognitive Reinforcement Strategies
Program Courses: 120 credits
Degree Requirements
Total Credits Required: 120 credits
Core Major Courses: 40 credits
Electives & Research Focus: 30 credits
General Education & Interdisciplinary Studies: 50 credits
Year One – Foundations of Cognitive Engineering
Fall Semester 1
CEN 101 – Introduction to Cognitive Science (3 credits)
An introduction to cognitive science, covering fundamental concepts of perception, attention, memory, and reasoning.
CEN 102 – Cognitive Intent & Thought Structuring (3 credits)
Examines how intention directs cognition and the structuring of conscious thought.
CEN 103 – Neural Mechanisms of Decision-Making (3 credits)
Explores the neural substrates of decision-making processes and their implications for behavior.
General Education Elective (3 credits)
Research & Writing Foundations (3 credits)
Spring Semester 2
CEN 104 – Psychodynamic Dimensions in Cognitive Systems (3 credits)
Investigates the role of psychodynamic processes in cognition and behavioral outcomes.
CEN 105 – Cognitive Measurement & Psychometric Evaluation (3 credits)
Focuses on psychometric methods for assessing cognitive abilities and thought processes.
CEN 106 – Pattern Recognition & Cognitive Context Processing (3 credits)
Explores how the brain identifies patterns and contextualizes information.
General Education Elective (3 credits)
Mathematical Logic & Systems Thinking (3 credits)
Year Two – Intermediate Cognitive Systems & Research Methodologies
Fall Semester 3
CEN 201 – Experimental Methods in Cognitive Research (3 credits)
Introduces scientific research methods used to investigate cognitive processes.
CEN 202 – Cognitive Wave Function Analysis (3 credits)
Examines quantum cognition principles and their role in probabilistic thinking.
CEN 203 – Neural Plasticity & Cognitive Adaptation (3 credits)
Studies how the brain adapts and restructures cognitive functions over time.
Research Elective (3 credits)
General Education Elective (3 credits)
Spring Semester 4
CEN 204 – Quantum Psychodynamics & Non-Linear Thought Processing (3 credits)
Explores how quantum cognition and psychodynamic principles shape complex thought.
CEN 205 – AI and Cognitive Modeling (3 credits)
Introduces computational models of cognition and their applications in AI.
CEN 206 – Applied Cognitive Enhancement Strategies (3 credits)
Examines interventions and techniques for optimizing cognitive performance.
General Education Elective (3 credits)
Data Science & Statistical Analysis for Cognition (3 credits)
Year Three – Specialized Cognitive Research & Application
Falll Semester 5
ONT 301 – Advanced Theories of Cognitive Optimization (3 credits)
Investigates advanced cognitive optimization models and ontological applications.
ONT 302 – Perception Structuring & Thought Mechanics (3 credits)
Examines how perception is structured through ontological frameworks.
ONT 303 – Psychodynamic Collapse & Thought Stability (3 credits)
Studies how cognitive structures collapse into stable ontological models.
Research Elective (3 credits)
General Education Elective (3 credits)
Spring Semester 6
ONT 304 – Non-Ordinary States of Awareness & Consciousness Evolution (3 credits)
Explores altered states of awareness and their role in ontological evolution.
ONT 305 – Ontological Philosophy & Theoretical Constructs (3 credits)
Analyzes historical and contemporary ontological philosophies.
ONT 306 – Experimental Methods in Thought Construction (3 credits)
Investigates experimental methodologies for cognitive and ontological analysis.
Elective in Applied Cognitive Structuring (3 credits)
General Education Elective (3 credits)
Year Four – Capstone Research & Independent Inquiry
Fall Semester 7
CEN 401 – Independent Research in Cognitive Structuring (3 credits)
Students conduct an independent research project focused on cognitive structuring.
CEN 402 – Cognitive Complexity & Multi-Layered Decision Networks (3 credits)
Examines how cognition operates across hierarchical decision-making layers.
CEN 403 – Senior Seminar: Cognitive Structuring in Decision Systems (3 credits)
A capstone seminar discussing theoretical and applied perspectives in cognitive engineering.
Research Elective in Neurocognition (3 credits)
General Education Elective (3 credits)
Spring Semester 8
CEN 404 – Capstone Thesis & Cognitive Research Presentation (6 credits)
A culminating thesis project where students conduct original research and present their findings.
CEN 405 – Computational Cognitive Analysis in AI and Human Systems (3 credits)
Examines applications of computational cognition in artificial intelligence and human decision-making.