These problem collections are available for authorized instructors only. Instructors can request access through Customer Support or their assigned Customer Success Engineer or Account Representative.

## Calculus I:

Collection of 10 problems on concepts taught in Calculus I.

• Intended for use in Calculus I courses and courses that require corequisite knowledge of concepts taught in Calculus I.
• The problems use MATLAB to enhance conceptual and practical understanding of the use of Calculus to solve engineering and scientific problems by focusing on visualization, manipulation, and algorithms.
• Concepts covered: Limits, Rates of Change, Differentiation Rules, Inverse Functions, Applications of Differentiation, and Integrals.

Prerequisites:

• Problems assume prerequisite mathematics knowledge up to and including pre-Calculus.
• Beginner-level programming experience is recommended, which can be achieved by taking the MATLAB Onramp or an Introduction to Programming course.
• The problems use MATLAB Symbolic Toolbox. Consider supplementing them with problems from the Symbolic Math Toolbox collection to build and assess student proficiency.

## Calculus II:

Collection of 10 problems on concepts taught in Calculus II.

• Intended for use in Calculus II courses and courses that require corequisite knowledge of concepts taught in Calculus II.
• The problems use MATLAB to enhance conceptual and practical understanding of the use of Calculus to solve engineering and scientific problems by focusing on visualization, manipulation, and algorithms.
• Concepts covered: Applications of Integration, Techniques of Integration, Sequences and Series, and Parametric and Polar Coordinates.

Prerequisites:

• Problems assume prerequisite mathematics knowledge up to and including Calculus I.
• Beginner-level programming experience is recommended, which can be achieved by taking the MATLAB Onramp or an Introduction to Programming course.
• Certain problems use MATLAB Symbolic Toolbox. Consider supplementing them with problems from the Symbolic Math Toolbox collection to assess student proficiency.

## Dynamics:

Collection of 10 problems on concepts taught in introductory courses on dynamics of mechanical systems.

• Intended for use in Dynamics courses in undergraduate engineering programs. The problems can also be used in courses that require corequisite knowledge of dynamics of mechanical systems.
• Concepts covered: Kinematics and Kinetics of Particles, Kinematics and Kinetics of a Rigid Body in Plane Motion, Kinematics of a Rigid Body in Three-Dimensional Motion, and Kinetics of a Rigid Body in General Motion.

Prerequisites:

• Problems assume prerequisite knowledge of Classical Mechanics and Multi-variate Calculus.
• Beginner-level programming experience is recommended, which can be achieved by taking the MATLAB Onramp or an Introduction to Programming course.

## Introduction to Programming:

Collection of 111 problems on introductory programming using MATLAB.

• Intended for use in Introduction to Programming courses and courses that require prerequisite knowledge of introductory programming concepts.
• Problems draw from a variety of applications including physics, engineering, and finance, but do not require prerequisite knowledge in these fields.
• Concepts covered: Introduction to variables and data types, Matrices & Operators, Input/Output, Flow Control and Loops, Functions, and Graphing.

Prerequisites:

• Problems assume prerequisite mathematics knowledge up to and including pre-calculus.
• No prior computer programming experience is required.

## Numerical Methods:

Collection of 10 problems on concepts taught in courses on numerical methods.

• Intended for use in Numerical Methods and Analysis courses. The problems can also be used in courses that require corequisite knowledge of numerical methods.
• Concepts covered: modeling, computers and error analysis, equation solving, linear algebraic functions, curve fitting/approximation, numerical quadrature, numerical differentiation, and ordinary differential equations.

Prerequisites:

• Problems assume prerequisite knowledge of calculus, linear algebra, and differential equations.
• Beginner-level programming experience is recommended, which can be achieved by taking MATLAB Onramp or an Introduction to Programming course.

## Symbolic Math Toolbox:

Collection of 10 problems as a supplementary resource for courses using the Symbolic Math Toolbox

• Intended to assess introductory skills for using Symbolic Math Toolbox features and functions.
• Concepts covered: Creating symbolic variables and expressions, Evaluating symbolic expressions and functions, Creating symbolic equations and relations, Solving equations symbolically, and Converting symbolic functions to numeric functions.

Collections that use Symbolic Math Toolbox:

• Calculus I
• Calculus II

## System Dynamics and Control:

Collection of 10 problems on concepts taught in undergraduate System Dynamics and Control courses.

• Intended for use in System Dynamics and Control courses and courses that require corequisite knowledge of concepts taught in this course.
• The problems use MATLAB to enhance conceptual and practical understanding of different controls concepts in modeling, systems analysis and controller design.
• Concepts covered: System identification, time and frequency domain system response, system stability, Root-locus design technique, and PID control.
• Relevant background reading for problem formulation using automated assessment in a System Dynamics and Control curriculum

R. C. Hill and Y. Parvini, "Automated Grading with a Software-Checking Program in the System Dynamics and Control Curriculum," 2018 Annual American Control Conference (ACC), Milwaukee, WI, 2018, pp. 345-351.

Prerequisites:

• Problems assume prerequisite mathematics knowledge up to and including Calculus, Linear Algebra and Differential Equations.
• Beginner-level programming experience is recommended, which can be achieved by taking the MATLAB Onramp or an Introduction to Programming course.

## Contributors:

• Eric Davishahl, Whatcom Community College
• David Manuel, Texas A&M University
• Marc Smith, Georgia Institute of Technology
• Mark Gockenbach, Michigan Technological University
• Navid Nakhjiri, California State Polytechnic University
• Richard Hill, University of Detroit Mercy