Course Syllabus

Contact Information

This table includes information about how to contact your instructor and other important details about your class

Office Hours:  🚩🚩 day/time Central hyperlink to Zoom link 🚩🚩

Email: alex@ou.edu 

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Office Hours:  🚩🚩 day/time Central hyperlink to Zoom link 🚩🚩

Phone: 🚩

Email: www-1@ou.edu 

Zoom Meeting ID: 🚩

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Dr. Alex Durcikova

Professor of Management Information Systems

John Mertes Presidential Professor

Division Director of Management
Information Systems

Dr. Wilfred Wu

Assistant Professor

Management Information Systems

 

 

Course Details

For a list of course activities, scroll to the bottom of this page.

Course Delivery

  • Asynchronous Online: Learning takes place online and asynchronously within a course site, typically hosted in a learning management system (LMS).

Course Prerequisites 

None

Course Materials

Program Learning Outcomes (PLO) 

  1. Analyze data and provide valuable business insights
  2. Solve problems in relation to IT concerns and applications
  3. Communicate technical information to non-technical business professionals
  4. Demonstrate an understanding of the business, organizational, and regulatory context of information technology and organizational information systems
  5. Demonstrate an understanding of how information technology and systems can be leveraged to provide business value

Course Learning Outcomes (CLO) Alignment

Course Learning Outcomes
CLO Description PLO
A Understanding Digital Transformation: Explain the key drivers of digital transformation and how organizations can leverage digital capabilities to innovate and compete in the modern business landscape. 5
B Strategic Importance of Technology: Analyze how digital technologies can be strategically aligned with business goals to create value and achieve competitive advantage. 2
C Operating Models for Digital: Identify and differentiate between various digital operating models, such as coordination, unification, and diversification, and understand how these models impact organizational strategy. 4, 5
D Building Digital Platforms: Describe the importance of digital platforms, ecosystems, and APIs, and explain how they enable organizations to scale and enhance customer value. 1
E Leadership in a Digital Age: Develop an understanding of the role of leadership in driving digital initiatives and how leaders can foster a culture that embraces digital innovation and agility. 4, 5
F Managing Digital Risks: Identify and evaluate the risks associated with digital transformations, including cybersecurity threats, and propose strategies for mitigating these risks to ensure sustainable digital growth. 2
G Analyze a business’s IT Strategy in terms of Digital: Demonstrate the ability to analyze an organization’s current digital strategy, identify gaps in alignment with digital transformation principles, and recommend actionable steps to enhance its digital capabilities, operating models, and leadership approach in order to position the organization for success in a digital economy. 4
H Making the invisible IT work visible: Understand and apply the principles of DevOps, particularly how collaboration between development, operations, and business teams can improve efficiency, reduce bottlenecks, and enhance the overall delivery of IT services in an organization. 2
I Basics of Data Storage: Analyze an Entity-Relationship Diagram (ERD) and data dictionary to determine what data types exist in the database and how to utilize the ERD and data dictionary to retrieve data. 3
J Data Extractions from an SQL Database: Effectively extract data from one or more tables in a relational database by utilizing the SELECT statement utilizing inner JOINS 1

Grades

Breakdown

Course activities and grades listed for each activity
Activity Description Percentage
Quizzes Autograded assessments covering module content 25%
Practice Exercises SQL practice and quiz questions designed to further concepts introduced in module lectures 25%
Homework Assignments Strategic Analysis and SQL homework aligning with module content and course concepts 25%
Weekly Reflection Summary reflection on the module learning outcomes 25%
Total  100%

Scale

Grade Scale
Percentage Letter Grade
90–100% A
80–89% B
70–79% C
60–69% D
Below 60% F

Course Components

Quizzes

This assessment is a short quiz used as a learning tool to assess students’ grasp of the basic concepts covered in the week’s resources (readings, media, and recorded lectures). 

Practice Exercises

These exercises challenge students to utilize the SQL skills they have learned in class by requiring them to write SQL statements to answer questions based on the data.  In addition, there are multiple-choice, true/false, and short essay questions that further test the concepts introduced in the week’s lecture. The goals of these exercises are to put the theory from the weekly lectures into practice and prepare to complete the Homework assignments.

Homework Assignments: Strategic Analysis & SQL

The homework assignment format is similar to that of the Practice Exercises.  These assessments require students to write SQL code and answer questions based on the SQL code results. In addition, these assessments may ask students to answer multiple-choice, true/false, and short essay questions that further test the concepts introduced in the week’s recorded lecture and in-class exercises. 

Weekly Reflection

The Reflection should summarize the student’s weekly learning experience (engagement with materials, quiz, practice exercises) in two paragraphs with a minimum of 10 lines per paragraph. There are 3 parts to the reflection:  

  1. Summarize the week’s learning materials (readings, media, and recorded lectures) and how they relate to the module learning objectives.
  2. List two topics of interest from the week’s content using the following questions as guidance:
    1. What are the topics that are most interesting to you?
    2. What are the topics that can be utilized immediately at your work?  
  3. What is a question that you still have about this week’s learning topics? 

Course Policies

Communication 

You can address the instructors as Dr. Durcikova or Dr. Wu. The best way to contact them is through email. They will generally respond within 24 hours M-F. They will do my best to respond to you within 24 hours, but it may take them longer (up to 48 hours) over the weekend. They am open for appointments to discuss issues via Zoom. Please contact me about setting up Zoom appointments if needed.

For general questions about the course, feel free to use the Course Help Board. For anything private (grades, special accommodation, group issues), please contact your instructors directly. They are most accessible via e-mail, as they check their e-mail throughout the day. Please put MIT-5602 in the email subject line. 

Feedback 

Course Quizzes are automatically graded and will provide you with automatic feedback. Course assignments will typically receive feedback within one week of the assignment deadline.

Late Policy

With the exception of university-excused absences, late work is not accepted. Due dates are automatically enforced. When juggling competing priorities, remember: It is always better to submit something for this class rather than nothing at all. I usually give partial credit. 

Plagiarism 

Plagiarism is the most common form of academic misconduct at OU. There is no college-level assignment that can be satisfactorily completed by copying. OU's basic assumption about writing is that all written assignments show the student's own understanding in the student's own words. That means all writing assignments, in class or out, are assumed to be composed entirely of words generated (not simply found) by the student, except where words written by someone else are specifically marked as such with proper citation. Including other people's words in your paper is helpful when you do it honestly and correctly. When you don't, it's plagiarism. 

For more information about plagiarism, watch this video and then take this short course offered by University Libraries. 

Use of Generative AI

Generative AI is one of the most exciting developments in business analytics. It is important that you know how to use generative AI tools. First attempts on assignments must be your own work. However, you are allowed to use generative AI tools in revising code, proofing text, and sharpening analysis. Such use must be clearly disclosed in the submission. 

When using generative AI tools, keep a couple of things in mind: 

  1. These tools make mistakes, and you are responsible for what you submit. When questioning low marks, I don't want to hear "But that is what ChatGPT said..."
  2. This class is an opportunity to learn and deepen your capabilities. If everything you produce during this class can be done by AI, you will be immediately replaceable.   

AI Policy for Written Assignments

While you are permitted to use large language models (LLMs), such as ChatGPT, to help refine or improve your answer (e.g., enhancing clarity, structure, or grammar), you may not use them to generate the entire response. LLMs are still prone to hallucinations, producing incorrect or misleading information that appears credible. If your submission reflects unverified or fabricated content generated by an LLM, or if it appears fully AI-written, you will receive a zero on the assignment.

It is your responsibility to ensure the accuracy, originality, and academic integrity of your work.


University Academic Policies and Student Support

Access the University Academic Policies Document.

Course Summary:

Course Summary
Date Details Due