PLA Course Subjects

Prior Learning Assessment Course Subjects

math

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Courses 1-10 of 47 matches.
Business Mathematics   (BUS-161)   3.00 s.h.  

Course Description
With a growing need for record keeping, establishing budgets, and understanding finance, taxation, and investment opportunities, mathematics has become a greater part of our daily lives. Business Mathematics attempts to apply mathematics to daily business experiences. Success in business relies more than ever upon the ability of managers to keep careful records, establish budgets, and understand finance, taxation, and investment opportunities. This course will help you use mathematics to your advantage in your daily business practices.

Learning Outcomes
Through the Portfolio Assessment process, students will demonstrate that they can appropriately address the following outcomes:

  • Fractions, decimals, and percents
  • Basic equations and formulas
  • Balancing a checkbook and filling out a simple tax return
  • Business insurance and personal insurance
  • Business discounts, pricing, and inventory control
  • Simple interest, compound interest, notes, and bank discounts
  • Credit and credit purchases
  • Annuities, amortization, and depreciation
  • Financial statements, cash flow, and ratios
  • Stocks and bonds
  • Some basic ideas of statistics.

Available by DSST exam. 
Math for Young Children   (CDS-211)   3.00 s.h.  
This course will help prospective teachers prepare materials to develop basic mathematical concepts with conservation, seriation, and geometry. Emphasis will be placed upon the development of materials and language skills necessary for presentation of lessons. 
Introduction to Child Development and Early Childhood Curriculum   (CDS-251)   3.00 s.h.  

Course Description
An examination of contemporary curriculum practices that facilitate learning in all areas: affective, psychomotor and cognitive. Emphasis on the teacher as reflective practitioner who employs culturally responsive teaching strategies and demonstrates sensitivity to special needs learners.

Learning Outcomes
Through the Portfolio Assessment process, students will demonstrate that they can appropriately address the following outcomes:

  • Discuss how knowledge of child development theory informs principles of learning and guides "best practice" in curriculum planning.
  • Explain the role of the learning environment in regard to planning developmentally appropriate curriculum.
  • Discuss how curriculum and teaching strategies are differentiated for a diverse learner population (ELL and Special Education).
  • Describe the process of how children "emerge" into literacy in areas of speaking, listening, and writing.
  • Determine the process of assessment in reference to children's knowledge, skills, and abilities.
  • Summarize how the content areas (language, creative arts, math, ad science) enhance and support a child's cognitive growth and development.

 
Math and Science For Child   (CDS-271)   3.00 s.h.  

Course Description
This course identifies and classifies the major mathematical and science concepts and topics considered in teaching the young child. Emphasis is placed on planning Math and Science activities that encourage thinking, exploring, discovering and problem solving. Each concept is exemplified by hands-on experience.

Learning Outcomes
Through the Portfolio Assessment process, students will demonstrate that they can appropriately address the following outcomes:

  • Discuss the cognitive and developmental capabilities of early childhood students in the areas of math and science.
  • Address various philosophical approaches to the teaching of math and science.
  • Indicate instructional activities that support both critical thinking and problem-solving.
  • Give examples of hands-on experiences in both the math and science content areas.
  • Discuss the challenges in planning developmentally appropriate math and science lessons/activities.
  • You may address math and science together or as separate content-areas in the narrative paper.

 
Introduction to Information Systems and Applications   (CIS-101)   3.00 s.h.  
A survey of the basic concepts, principles and problems IN INFORMATION processing. In addition, students will discuss current paradigms through the use of newspapers, magazines, WEBSITES AND OTHER hands-on applications. The major topics to be covered include the history of computers, basic computer mathematics, introduction to mainframes, minicomputers, PCs and networking, operating systems, software, hardware, secondary storage, programming languages, and introduction to spreadsheets/word processing/databases.  
Information Systems Design   (CIS-322)   3.00 s.h.  

Course Description
Business information systems design, installation and implementation as part of the systems development life cycle, with emphasis on structured design methodology.

Learning Outcomes
Through the Portfolio Assessment process, students will demonstrate that they can appropriately address the following outcomes:

  • An ability to apply knowledge of computing and mathematics appropriate to the discipline
  • Demonstrated ability to analyze a problem, and identify and define the computing requirements appropriate to its solution
  • Demonstrated ability to design, implement, and evaluate a computer-based system, process, component, or program to meet desired needs
  • Demonstrated ability to function effectively on teams to accomplish a common goal
  • Articulate an understanding of professional, ethical, legal, security and social issues and responsibilities
  • Communicate effectively with a range of audiences of varied technical sophistication
  • Analyze the local and global impact of computing on individuals, organizations, and society
  • Articulate the ongoing need to engage in continuing professional development
  • Utilize current techniques, skills, and tools necessary for computing practice
  • Demonstrated understanding of processes that support the delivery and management of information systems within a specific application environment

 
Clinical Instrumentation   (CLB-331)   3.00 s.h.  

Course Description
Theory and principles of operation of clinical laboratory instruments, quality control, preventive maintenance. Laboratory mathematics. Hand-on experience with clinical instruments; spectrophotometers, flame photometers, atomic absorption spectrophotometer, ion-selective electrodes, PH/blood gas analyzer, chloridometer, gas chromatograph osmometer, Auto Analyzer, Gemini centrifugal analyzer. Emphasis on understanding the capabilities and limitations of each instrument; calibration and preventive maintenance procedures.

Learning Outcomes
Through the Portfolio Assessment process, students will demonstrate that they can appropriately address the following outcomes:

  • Knowledge of the theory and principles of operation of clinical laboratory instruments, spectrophotometers, flame photometers, ion-selective electrodes, pH/blood gas analyzers, chloridometers, gas chromatographs, osmometers, Auto analyzers, and Gemini centrifugal analyzers.
  • An understanding of the capabilities and limitations of each instrument.
  • Instrument calibration and preventive maintenance procedures.

 
Artificial Intelligence   (COS-451)   3.00 s.h.  

Course Description
Artificial Intelligence is an introduction to how Artificial Intelligence (AI) methods solve problems that are difficult or impractical to solve with other methods. The focus of the course is on learning how to determine when an AI approach is appropriate for a given situation, being able to select an AI method, and implementing it. AI methods will be chosen from heuristic search and planning algorithms, formalisms for knowledge representation, and reasoning techniques and methods applicable to expert systems and games. Advisory: Students should be familiar with computer hardware and software as provided in an introductory computer science course and they should have the sophistication of understanding material as demonstrated by successfully completing courses such as discrete math, discrete structures, or computer architecture or having similar practical experience. It is recommended, but not required, to have taken a course in computer programming. However, the course will not require programming.

Learning Outcomes
Through the Portfolio Assessment process, students will demonstrate that they can appropriately address the following outcomes:

  • Explain the possibilities and limitations of Artificial Intelligence by using famous thought experiments and paradigms, strong methods and weak methods in the context of strong AI and weak AI, and knowledge representation methods.
  • Develop basic search methods, and compare and contrast search methods providing examples that include game-playing techniques.
  • Illustrate how AI uses search methods to explore, define, and implement AI problem-solving systems.
  • Build expert systems and discuss the practicalities of implementing such systems.
  • Explain the properties of logical systems and their use in theorem proving, language processing, and logic interplays.
  • Demonstrate AI's use of knowledge representation (logic and proof) and automated reasoning to deal with AI problems

 
Heat Transfer   (EGM-323)   3.00 s.h.  

Course Description
Heat transfer by modes of conduction, convection and radiation. Fundamental principles of heat transfer and radiation. Heat transfer and application to the solution of industrial heat transfer problems.

Learning Outcomes
Through the Portfolio Assessment process, students will demonstrate that they can appropriately address the following outcomes:

  • Ability to apply mathematics, science and engineering principles.
  • The broad education necessary to understand the impact of engineering solutions in a global and societal context.
  • Ability to identify, formulate and solve engineering problems.
  • Ability to use the techniques, skills and modern engineering tools necessary for engineering practice.
  • Articulate an understanding of the concepts and applications by providing evidence of applied knowledge of the fundamentals of heat transfer and radiation to include the following:
    • Steady-state conduction
    • Transient conduction
    • Lumped and distributed systems
    • Thermal and hydrodynamic boundary layer concepts
    • Forced convection (external and internal)
    • Free convection
    • Heat exchangers
    • Radiation properties
    • Radiation heat transfer
    • Combined mode heat transfer
    • Numerical solution techniques

     
    Digital Signal Processing   (ELC-454)   3.00 s.h.  

    Course Description
    This course covers principles and knowledge required to successfully develop cost-effective digital signal processing solutions to problems related to such areas as controls, telecommunications, speech/audio, instrumentation, image processing, and biomedicine.

    Learning Outcomes
    Through the Portfolio Assessment process, students will demonstrate that they can appropriately address the following outcomes:

    • Discuss principles of mathematical theorems used in digital signal processing
    • Describe applications of digital signal processing to communications
    • Describe applications of digital signal processing to control problems
    • Provide evidence of programming for digital signal processors
    • Identify hardware vs. software solutions for digital signal processing

     
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