An introduction to human information processing and learning; topics include the nature of mental representation and processing; the architecture of memory; pattern recognition; attention; imagery and mental codes; concepts and prototypes; reasoning and problem solving.

Explores the theory and research related to information processing, focusing on attention, perception, memory storage and information retrieval. Also highlights work in artificial intelligence and cognitive neuroscience which serves to describe and explain cognitive processes.

This course will introduce you to cognitive psychology. Memory, along with attention, perception, language, and decision making, are among the most prominent topics within this broad and diverse field. Upon successful completion of this course, students will be able to: Identify underlying theoretical considerations in the field of cognitive psychology; Describe the historical context in which cognitive psychology emerged as a field; Define cognitive psychology as is was historically defined and is now defined; Identify the main academic fields and other subdisciplines of psychology to which cognitive psychology is tied; Describe the main findings in the primary areas of scientific research within cognitive psychology; Compare and contrast the theories associated within the primary areas of scientific research in cognitive psychology (e.g., models of memory, attention, etc.). (Psychology 206)

Cognitive Psychology is a psychological science which is interested in various mind and brain related subfields such as cognition, the mental processes that underlie behavior, reasoning and decision making.

This is a class about applying autonomy to real-world systems. The overarching theme uniting the many different topics in this course will center around programming a cognitive robotic. This class takes the approach of introducing new reasoning techniques and ideas incrementally. We start with the current paradigm of programming you're likely familiar with, and evolve it over the semester—continually adding in new features and reasoning capabilities—ending with a robust, intelligent system. These techniques and topics will include algorithms for allowing a robot to: Monitor itself for potential problems (both observable and hidden), scheduling tasks in time, coming up with novel plans to achieve desired goals over time, dealing with the continuous world, collaborating with other (autonomous) agents, dealing with risk, and more.

How genetics can add to our understanding of cognition, language, emotion, personality, and behavior. Use of gene mapping to estimate risk factors for psychological disorders and variation in behavioral and personality traits. Mendelian genetics, genetic mapping techniques, and statistical analysis of large populations and their application to particular studies in behavioral genetics. Topics also include environmental influence on genetic programs, evolutionary genetics, and the larger scientific, social, ethical, and philosophical implications.

" This seminar examines the history and legacy of the Cold War on American science. It explores scientist's new political roles after World War II, ranging from elite policy makers in the nuclear age to victims of domestic anti Communism. It also examines the changing institutions in which the physical sciences and social sciences were conducted during the postwar decades, investigating possible epistemic effects on forms of knowledge. The subject closes by considering the place of science in the post-Cold War era."

How do individuals and families interface with larger systems, and how do therapists intervene collaboratively? How do larger systems structure the lives of individuals and families? Relationally-trained practitioners are attempting to answer these questions through collaborative and interdisciplinary, team-focused projects in mental health, education, the law, and business, among other fields. Similarly, scholars and researchers are developing specific culturally responsive models: outreach family therapy, collaborative health care, multi-systemic school interventions, social-justice-oriented and spiritual approaches, organizational coaching, and consulting, among others. This course explores these developments and aims at developing a clinical and consulting knowledge that contributes to families, organizations, and communities within a collaborative and social-justice-oriented vision.

Learn how to collect and import spatial features from the field, use web-based map tools to engage citizens, and incorporate the best available spatial data from public domain sources.

This e-book provides interactive lessons and hands-on exercises for anyone interested in applying GIS and related tools to conservation and environmental applications. The lessons in this book assume users have a basic proficiency in GIS. Through these lessons and exercises, you will explore and use applications of GIS particularly related to landscape assessment, suitability modeling, and design of alternative strategies. By engaging with the activities in this book, you will:

Know how to collect and work with spatial data from the field and public domain;
-Learn to frame and practice solving spatial environmental questions;
-Proficiently apply spatial thinking and analytical tools toward conservation and adaptation solutions
-Confidently apply spatial analyst and spatial statistics tools to compare and evaluate landscape change
-Model and synthesize potential environmental scenarios
-Design and plan strategies for adaptation to landscape change

This College Algebra text will cover a combination of classical algebra and analytic geometry, with an introduction to the transcendental exponential and logarithmic
functions. If mathematics is the language of science, then algebra is the grammar of that language. Like grammar, algebra provides a structure to mathematical notation, in addition to its uses in problem solving and its ability to change the appearance of an expression without changing the value.

College Algebra is an introductory text for a college algebra survey course. The material is presented at a level intended to prepare students for Calculus while also giving them relevant mathematical skills that can be used in other classes. The authors describe their approach as "Functions First," believing introducing functions first will help students understand new concepts more completely. Each section includes homework exercises, and the answers to most computational questions are included in the text (discussion questions are open-ended).

Table of Contents
1 Relations and Functions
2 Linear and Quadratic Functions
3 Polynomial Functions
4 Rational Functions
5 Further Topics in Functions
6 Exponential and Logarithmic Functions
7 Hooked on Conics
8 Systems of Equations and Matrices
9 Sequences and the Binomial Theorem

This course covers relations and functions, specifically, linear, polynomial, exponential, logarithmic, and rational functions. Additionally, sections on conics, systems of equations and matrices and sequences are also available.

It is often said that mathematics is the language of science. If this is true, then the language of mathematics is numbers. The earliest use of numbers occurred 100 centuries ago in the Middle East to count, or enumerate items. Farmers, cattlemen, and tradesmen used tokens, stones, or markers to signify a single quantity—a sheaf of grain, a head of livestock, or a fixed length of cloth, for example. Doing so made commerce possible, leading to improved communications and the spread of civilization.

College Algebra is an introductory text for a college algebra survey course. The material is presented at a level intended to prepare students for Calculus while also giving them relevant mathematical skills that can be used in other classes. The authors describe their approach as "Functions First," believing introducing functions first will help students understand new concepts more completely. Each section includes homework exercises, and the answers to most computational questions are included in the text (discussion questions are open-ended).

College Algebra provides a comprehensive exploration of algebraic principles and meets scope and sequence requirements for a typical introductory algebra course. The modular approach and richness of content ensure that the book meets the needs of a variety of courses. College Algebra offers a wealth of examples with detailed, conceptual explanations, building a strong foundation in the material before asking students to apply what they’ve learned.

College Algebra provides a comprehensive and multi-layered exploration of algebraic principles. The text is suitable for a typical introductory Algebra course, and was developed to be used flexibly. The modular approach and the richness of content ensures that the book meets the needs of a variety of programs.College Algebraguides and supports students with differing levels of preparation and experience with mathematics. Ideas are presented as clearly as possible, and progress to more complex understandings with considerable reinforcement along the way. A wealth of examples – usually several dozen per chapter – offer detailed, conceptual explanations, in order to build in students a strong, cumulative foundation in the material before asking them to apply what they've learned.

OpenStax College has compiled many resources for faculty and students, from faculty-only content to interactive homework and study guides.

Access also available here: https://openstax.org/details/books/college-algebra

Table of Contents
1 Prerequisites
2 Equations and Inequalities
3 Functions
4 Linear Functions
5 Polynomial and Rational Functions
6 Exponential and Logarithmic Functions
7 Systems of Equations and Inequalities
8 Analytic Geometry
9 Sequences, Probability, and Counting Theory

Table of Contents:

Chapter 1 Prerequisites
Introduction to Chapter 1 Prerequisites
1.1 Real Numbers: Algebra Essentials
1.2 Exponents and Scientific Notation
1.3 Radicals and Rational Exponents
1.4 Polynomials
1.5 Factoring Polynomials
1.6 Rational Expressions
Chapter 1 Review Exercises
Chapter 1 Practice Test

Chapter 2 Equations and Inequalities
Introduction to Chapter 2 Equations and Inequalities
2.1 Linear Equations in One Variable
2.2 Models and Applications
2.3 Complex Numbers
2.4 Quadratic Equations
2.5 Other Types of Equations
2.6 Linear Inequalities and Absolute Value Inequalities
Chapter 2 Review Exercises
Chapter 2 Practice Test

Chapter 3 Functions
Introduction to Chapter 3 Functions
3.1 The Rectangular Coordinate Systems and Graphs
3.2 Functions and Function Notation
3.3 Domain and Range
3.4 Rates of Change and Behavior of Graphs
3.5 Composition of Functions
3.6 Transformation of Functions
3.7 Absolute Value Functions
3.8 Inverse Functions
Chapter 3 Review Exercises
Chapter 3 Practice Test

Chapter 4 Linear Functions
Introduction to Chapter 4 Linear Functions
4.1 Linear Equations in Two Variables
4.2 Linear Functions
4.3 Modeling with Linear Functions
4.4 Systems of Linear Equations: Two Variables
Chapter 4 Review Exercises
Chapter 4 Practice Test

Chapter 5 Polynomial and Rational Functions
Introduction to Chapter 5 Polynomial and Rational Functions
5.1 Quadratic Functions
5.2 Power Functions and Polynomial Functions
5.3 Graphs of Polynomial Functions
5.4 Dividing Polynomials
5.5 Zeros of Polynomial Functions
5.6 Rational Functions
Chapter 5 Review Exercises
Chapter 5 Practice Test

Chapter 6 Exponential and Logarithmic Functions
Introduction to Chapter 6 Exponential and Logarithmic Functions
6.1 Exponential Functions
6.2 Graphs of Exponential Functions
6.3 Logarithmic Functions
6.4 Graphs of Logarithmic Functions
6.5 Logarithmic Properties
6.6 Exponential and Logarithmic Equations
6.7 Exponential and Logarithmic Models
Chapter 6 Review Exercises
Chapter 6 Practice Test

This textbook was created through Connecting the Pipeline: Libraries, OER, and Dual Enrollment from Secondary to Postsecondary, a $1.3 million project funded by LOUIS: The Louisiana Library Network and the Institute of Library and Museum Services. This project supports the extension of access to high-quality post-secondary opportunities to high school students across Louisiana and beyond by creating materials that can be adopted for dual enrollment environments. Dual enrollment is the opportunity for a student to be enrolled in high school and college at the same time.

The cohort-developed OER course materials are released under a license that permits their free use, reuse, modification and sharing with others. This includes a corresponding course available in Moodle and Canvas that can be imported to other platforms.

This course is designed to take the concepts you learn in developmental math to expand your knowledge of algebra. This course will focus on two major algebraic concepts to learn - how to SOLVE equations and how to GRAPH equations. Throughout this course you will be challenged to recall ALL of your prior knowledge of operations of real numbers as well as your knowledge related to solving and graphing linear equations (which you should have already mastered from developmental algebra). You will use this prior knowledge to expand on learning the following objectives: solving linear & rational equations. operations of complex numbers, solving quadratic equations, solving radical & polynomial equations, solving equations with rational exponents, solving linear and compound inequalities, solving absolute value equations and inequalities, graphing linear equations & slope, understanding concepts of domain, range and function notation, finding compositions of functions, finding inverses of functions, solving and graphing exponential and logarithmic equations, solving and graphing systems of equations and inequalities, and graphing conics.

*Open Campus courses are non-credit tutorials and cannot, in and of themselves, be used to satisfy degree requirements at Bossier Parish Community College (BPCC). (College Algebra Course by Bossier Parish Community College is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. Based on a work at http://bpcc.edu/opencampus/index.html.)

The goal of this course is to offer a fundamental understanding of algebraic concepts which form an important component of an undergraduate education and to enhance the algebraic skills and knowledge necessary for upper-level mathematics courses and for courses in many other disciplines. The Department of Mathematics is offering Math 1111 College Algebra course designed around the Emporium Model. The underlying principle of this model is very simple:

“Students learn math by doing math not by listening to someone talk about doing math.”

The students enrolled in Math 1111 spend one hour a week at a fixed time with their professor and then a minimum of three flexible hours a week in the Math Emporium lab which is staffed with professors and undergraduate learning assistants (ULA’s).

During the meeting at the fixed time, professors guide the students through their responsibilities, connect concepts, work examples, and point out common student misconceptions. In the Math Emporium lab, professors and ULA’s offer immediate and personalized help with math concepts.

This College Algebra text will cover a combination of classical algebra and analytic geometry, with an introduction to the transcendental exponential and logarithmic functions. If mathematics is the language of science, then algebra is the grammar of that language. Like grammar, algebra provides a structure to mathematical notation, in addition to its uses in problem solving and its ability to change the appearance of an expression without changing the value.

Table of Contents
1 Algebra Review
2 Polynomial and Rational Functions
3 Exponents and Logarithms
4 Functions
5 Conic Sections - Circle and Parabola
6 Sequences and Series
7 Combinatorics
8 Right Triangle Trigonometry
9 Graphing the Trigonometric Functions
10 Trigonometric Identities and Equations
11 The Law of Sines The Law of Cosines