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MIS10050

Academic Year 2025/2026

Digital Technologies in Business (MIS10050)

Subject:
Management Information Systems
College:
Business
School:
Business
Level:
1 (Introductory)
Credits:
5
Module Coordinator:
Dr Matthias Glowatz
Trimester:
Spring
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

Digital Technologies, applications, and initiatives have become an integral part of all business activities. Throughout this applied, hands-on module, you will gain insights into both the opportunities and challenges posed by conducting business in an increasingly digital domain.

Students will research how innovative digital technologies have transformed a real organisation and design a working mobile application prototype for an organisation of their choice.

MIS10050 provides students with essential Artificial Intelligence (AI) literacy, practical AI prompt engineering skills, and the ability to evaluate AI outputs critically. Students will explore how AI and Generative AI (GenAI) are transforming industries, enhance business problem-solving using structured AI workflows, and learn responsible and ethical AI usage in both academic and organisational settings.

Students will also, during the first few weeks of the module, research, present, and reflect on how innovative digital technologies have transformed a real organisation to gain and sustain a competitive advantage in the marketplace.

About this Module

Learning Outcomes:

On completion of this module, students will be able to :

• Understand how businesses are using digital platforms and initiatives for operational efficiency and to be competitive.
• Be aware of emerging digital technologies.
• Explain core concepts underpinning AI and GenAI.
• Apply structured AI prompt engineering techniques to generate high‑quality outputs.
• Design and implement a mobile application prototype.

Indicative Module Content:

Gathering business intelligence and financial data using the Financial Times (ft.com)
Review of the principles of Artificial Intelligence (AI) and opportunities to deploy AI solutions
AI Development of a prototype AI application using current tools
AI Prompt Engineering
Mobile Application Protytpe Development

Student Effort Hours:
Student Effort Type Hours
Specified Learning Activities

36
Autonomous Student Learning

56
Practical

24
Total

116

Approaches to Teaching and Learning:
This module is based largely on practical work, building skills using current business technology tools.
Also, students will research technology trends and events using readings assigned, mainly from UCD's Financial Times online subscription.
Students will gain AI prompt engineering skills and develop a mobile application prototype.
Assessment is based on in-class activities and a variety of different assignment submissions, such as MCQ, presentation, learning journal creation, or poster submission.

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Incompatibles:
MIS10020 - Intro to Computers & Info Sys, MIS10070 - ICT for Decision Support, SMGT10030 - Information Technology


 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Individual Project: Project Poster and Video Week 12 Standard conversion grade scale 40% No
50
 No
Quizzes/Short Exercises: Online MCQ quiz to be completed in class Week 9 Alternative linear conversion grade scale 40% No
20
 No
Group Work Assignment: Group project presentation and learing journal Week 6 Standard conversion grade scale 40% No
30
 No

Carry forward of passed components
No
 

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

Feedback Strategy/Strategies

• Feedback individually to students, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Dr Matthias Glowatz Lecturer / Co-Lecturer
Mr Tyler Crow Tutor

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Spring Small Group Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Thurs 10:00 - 11:50
Spring Small Group Offering 2 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 31, 32, 33 Fri 09:00 - 10:50
Spring Small Group Offering 3 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Wed 09:00 - 10:50
Spring Small Group Offering 4 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Wed 16:00 - 17:50
Spring Small Group Offering 5 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 31, 32, 33 Fri 11:00 - 12:50
Spring Small Group Offering 6 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Thurs 10:00 - 11:50
Spring Small Group Offering 7 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 31, 32, 33 Fri 09:00 - 10:50
Spring Small Group Offering 8 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Tues 16:00 - 17:50
Spring Small Group Offering 9 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Tues 12:00 - 13:50
Spring Small Group Offering 10 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Wed 12:00 - 13:50
Spring Small Group Offering 11 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Wed 14:00 - 15:50
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