DIGIT 430: Simulations of Human Behavior

Textbook Information

Course readings are available in digital formats from Penn State Libraries and are linked within the course.

Published Remarks

None

Hardware Requirements

None

Software Requirements

You do not need to purchase software for this course. See inside the course for information about how you can access necessary course tools.

Proctored Exams

None

Course Description

In Modeling and Simulation, students will develop an understanding of the systems, processes, tools, and implications of the field.

Pre-requisite: 3 credits of programming; 3 credits of mathematics

Learning Objectives

By the end of this course:

Objective 1: Understanding Modeling and Simulation

Students will be able to define agent-based modeling (ABM) and simulation, differentiate between different types of models, and recognize the applications and limitations of ABM modeling and simulation to data analytics and similar data questions.

Objective 2: Model Specification

Students will be able to create the key components of an ABM based on data, specify the model parameters, and describe how the model simulates behavior in the real world.

Objective 3: Model Analysis

Students will analyze various types of ABMs based on data and explain how models predict real outcomes.

Objective 4: Model Selection and Evaluation

Students will evaluate the appropriateness of different ABM model configurations to address for specific data problems, explain the concepts of under and overspecification of an ABM model, and select the most suitable ABM model for a given simulation.

Objective 5: Simulation and Prediction

Students will be able to use ABM simulation techniques to predict outcomes, explain the strengths and limitations, and apply the simulation to various domains.

Course Structure

All course activities are contained in modules, where you will find:

  • An overview page, which serves as your guide to the module
  • Lesson materials and resource pages
  • Activities and assessments

This course consists of an orientation module, 14 learning modules, and a finals week module.

Course Requirements and Grading

Course Assignments

“Before You Read: Cracking the Concepts” Quizzes (Do not count toward final grade)

Modules 1 through 14 begin with a “Before You Read” quiz designed to help you feel more prepared and confident before diving into our module concepts. Reading assignments in this course can be challenging, and each “Before You Read” quiz can help. Any scores earned on these assignments are for your information only and do not count toward your final grade in this course. You may take the quiz as often as you wish, but it is not necessary. Simply give the questions your best guess, then be sure to read the feedback that explains each concept so that you are ready when you encounter those ideas in the module reading. 

Note that the “Before You Read” quizzes must be completed to unlock the rest of the module content. Canvas may take a few minutes to register the quiz completed and thus release additional content. Refresh the Modules page until it appears, and thank you for your patience with this mechanism.

Other Assignments (Counted toward final grade)

This course contains the following  assignments:

  • Discussions: Asynchronous discussions in this course shall take place using the Perusall platform. You can access Perusall using the link in our Course Navigation menu or by clicking on the discussion assignments on the Modules page. We will discuss excerpts from one or more of the readings for the week. You are not required to respond to every prompt. Please see instructions in Perusall.
  • Quizzes: Quizzes are your opportunity to demonstrate what you have learned in the module. Each quiz has no time limit, but you can submit the quiz only once. Please complete the quiz on your own, without the use of external resources such as web searches, AI tools, or notes. 
  • Assignments: Assignments in this course are applications of the lessons. Assignments are available until 1 week after the deadline.
  • Final Project: Built on many of the assignments in this course, the final project is your own model. You will submit a paper about your model (building the model is optional) and a screencast video describing your model.

Course Grading

The final course grade is determined as follows:

Course Grade Distribution
Assignment Percent of Final Grade
 Discussions (Perusall)  30%
 Quizzes  10%
Assignments   50%
Final Project 10%
TOTAL  100%

You are responsible for checking your grades on Canvas and reporting any discrepancy to the instructor immediately. Any concern regarding the grading should be addressed directly to the instructor, no later than one week after the grade was released on Canvas and before the final day of the course.

Letter grades will be based on the following scale:

Grading Scale
Letter Grade Range
A  93 – 100%
  A- 90 – 92.9%
  B+ 87 – 89.9%
B 83 – 86.9%
  B- 80 – 82.9%
  C+ 77 – 79.9%
C 70 – 76.9%
D 60 – 69.9%
F Below 60%