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MBA2003: Decision Science

MBA2003: Decision Science

MBA2003: Decision Science Syllabus

Course Title: Decision Science

Credit Units: 3

Course Number: MBA2003 Term Offered: Winter 2024 Modality: Online

Section: 4

Office Hours: By Appointment

Course Start/End Dates: 01.08.23 – 03.18.24

Time and Location: Sofia University Canvas System

Course Clock: Pacific Time

Prerequisites: none

Course Description

This course covers the practical ways to develop, strengthen, and balance human and organizational capacities for better decision making. It integrates quantitative, behavioral, interpersonal, transpersonal, and organizational perspectives in strategic global decision making. Topics include decision theory and decision analytics, design thinking, cognitive science, organizational behavior, and transpersonal psychology. The course emphasizes dialogue processes for effective inquiry, balanced with contemplation and reflection, to clarify values, surface assumptions, and develop an appropriate frame. It integrates mathematical decision modeling, data analytics, and data science processes that can be applied to generate valuable insights by focusing further inquiry on essential variables and facilitating deep collaborative reasoning. The course presents myriad case studies to emphasize key strategic decision principles based on reason and data analysis.

Course Learning Outcomes

Upon successful completion of this course, students will be able to:

  • Explain different theories of reasoning and decision-making.
  • Describe significant principles of decision-making.
  • Apply decision-making principles to analyze real-world events.
  • Assess how a broader understanding of physical and mental sensations caused by analysis of the cost and benefit with a decision-making.

Required Textbook(s)

There are no required textbooks for students to purchase. All required readings will be supplied in the module in which they are required.

Graded-Activity Weighting

Assignment Type Weight Schedule
Discussions 51% Modules 1-10
Knowledge Exercises 22.5% Modules 2, 5, & 8
Signature Assignment 26.5% Modules 3 & 10

Letter Grade Conversion Scale

Grade Range
A 100 % to 93.0%
A- < 93.0 % to 90.0%
B+ < 90.0 % to 87.0%
B < 87.0 % to 83.0%
B- < 83.0 % to 80.0%
C+ < 80.0 % to 77.0%
C < 77.0 % to 73.0%
C- < 73.0 % to 70.0%
D+ < 70.0 % to 67.0%
D < 67.0 % to 65.0%
F < 65.0 % to 0.0%

Course Schedule

Module Module Name/Topic Readings & Media Assignments
1 What is Reasoning? Decision Making? 2 Articles Introduction DiscussionWeekly Discussion
2 Cognition: Information Processing 2 Textbook Chapters (linked) Weekly DiscussionKnowledge Exercise 1
3 Theory Review: Rational Choice Theory, Exchange Theory, Utility Theory Decision-making Questionnaire Weekly DiscussionSignature Assignment Part 1
4 Heuristics and Biases of Economic and Financial Decisions 2 Textbook Chapters (linked) Weekly Discussion
5 Normative Analysis, Moral Judgement, and Decision Making Article Weekly DiscussionKnowledge Exercise 2
6 Humanistic Rational Choice Theory (Societal Cooperation) Article Weekly Discussion
7 Game Theory for Decision Making 2 Videos Weekly Discussion
8 Game Theory Applications for Finance Video Weekly DiscussionKnowledge Exercise 3
9 Sensitivity Analysis: What if analysis 2 Videos Weekly Discussion
10 Cost Benefit Analysis, Emotions and Sensations 2 Videos Weekly DiscussionSignature Assignment Part 2

Attendance Policy

Attendance is represented (and taken each week by your professor) by active engagement over the course of the week in the weekly Discussion, unless otherwise specified.

Late Work Policy

The policy on late work varies from professor to professor and should be specified here. Your policy should specify under what conditions late work will be accepted (or not) and what the grade consequences are for late work.

Technology Requirements, Learner Support, and Academic Policies

See the Getting Started Module in the Canvas LMS course for Technology Requirements, Learner Support, and Academic Policies. Each of these topics has its own page in the module.

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