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MIS30150

Academic Year 2024/2025

Strategic Decision Making in the Digital World (MIS30150)

Subject:
Management Information Systems
College:
Business
School:
Business
Level:
3 (Degree)
Credits:
5
Module Coordinator:
Mr Matthias Glowatz
Trimester:
Autumn
Mode of Delivery:
Blended
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

Managers are faced with the challenge of crafting and implementing timely and accurate strategic decisions helping organisations to gain competitive advantage in the marketplace. In doing so, it is essential to make optimal use Digital Business applications for data collection, analysis, and decision making.

This applied, project-based module heavily utilising Bloomberg terminals, will allow students to gain important insights into several industry sectors in order to draft strategic investment ideas and recommendations.

Students will participate and compete in the annual Bloomberg global trading challenge and engage in several interactive in-class exercises utilising Artificial Intelligence (AI) tools for strategic decision making.

About this Module

Learning Outcomes:

On successfully completion of the module, students should be able to

(i) Demonstrate a deep understanding of key issues surrounding strategic management decision making.

(iii) Evaluate and discuss organisations’ market performance utilising Bloomberg’s infrastructure.

(iv) Explore and evaluate the role and potential of Artificial Intelligence (AI) tools and prompt engineering for decision making.

Indicative Module Content:

Strategic Decision Making in the context of implementing an organisation's Digital Business strategy
Bloomberg Infrastructure
Bloomberg Global Trading Challenge Competition
Artificial Intelligence (AI) tools for decision making
AI prompt engineering

Student Effort Hours:
Student Effort Type Hours
Specified Learning Activities

36
Autonomous Student Learning

60
Seminar (or Webinar)

7
Computer Aided Lab

5
Online Learning

5
Total

113

Approaches to Teaching and Learning:
Mixture of synchronous online and Face-to-face lectures, Bloomberg lab sessions.
Students will be able to follow an interactive study guide utilising Augmented Reality-driven study and learning content.

Referencing: Harvard Style Referencing is required for all assignment submissions. (https://libguides.ucd.ie/harvardstyle)

Generative Artificial Intelligence (GenAI): Allowed for in-class and async student activities set by the module coordinator. However, GenAI is not permitted for assignment preparation activities.

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Group Work Assignment: Bloomberg Global Trading Challenge Report Week 12 Standard conversion grade scale 40% No
50
 No
Individual Project: Artificial Intelligence (AI) for decision making and prompt engineering Week 4 Standard conversion grade scale 40% No
30
 No
Group Work Assignment: Bloomberg Global Trading Challenge Presentation (online) Week 12 Standard conversion grade scale 40% No
20
 No

Carry forward of passed components
No
 

Resit In Terminal Exam
Spring No
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, on an activity or draft prior to summative assessment
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Miss Niamh McDonagh Tutor

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Autumn Lecture Offering 1 Week(s) - 1, 2, 3, 12 Tues 11:00 - 12:50
Autumn Computer Aided Lab Offering 1 Week(s) - 4, 5, 6, 7, 8, 9, 10, 11 Tues 11:00 - 11:50
Autumn Computer Aided Lab Offering 2 Week(s) - 4, 5, 6, 7, 8, 9, 10, 11 Tues 12:00 - 12:50
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