Module: Digital Business Tools

Module Specifications.

Current Academic Year 2024 - 2025

All Module information is indicative, and this portal is an interim interface pending the full upgrade of Coursebuilder and subsequent integration to the new DCU Student Information System (DCU Key).

As such, this is a point in time view of data which will be refreshed periodically. Some fields/data may not yet be available pending the completion of the full Coursebuilder upgrade and integration project. We will post status updates as they become available. Thank you for your patience and understanding.

Date posted: September 2024

Module Title	Digital Business Tools
Module Code	SB106 (ITS) / BAA1043 (Banner)
Faculty	DCU Business School	School	DCU Business School
Module Co-ordinator	Babu Veeresh Thummadi
Module Teachers	Cliona Mcparland, Louise Kirke
NFQ level	6	Credit Rating	10
Pre-requisite	Not Available
Co-requisite	Not Available
Compatibles	Not Available
Incompatibles	Not Available

None

Description

This is a blended learning, applied module co-created and co-delivered with DCU Futures industry partners. The module serves to provide students with exposure to key tools and language of digital business. The module will focus on experiential learning so students can appreciate the breadth of technology including, but not limited to, coding approaches and tools, traditional web technologies, cloud based technologies, mobile internet technologies, Internet of things, artificial intelligence, robotics, augmented reality and machine-learning. The module will be underpinned by curated learning and reflection points.

Learning Outcomes

1. appreciate the scope of digital business tools
2. explore and experiment with chosen technologies
3. reflect on the use and potential of digital business tools
4. design, conduct and reflect on a curated digital learning journey

*Type*	*Hours*	*Description*
Workload	Full-time hours per semester
Workshop	20	No Description
Group work	60	No Description
Directed learning	60	curated learning journey
Assignment Completion	65	No Description
Online activity	45	Exercises and Digital badges
Total Workload: 250

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Introduction via Gamification
Learning with and from technology (DCU Futures Partner co-created introduction)

Experimentation via engagement
Opportunity and challenges (DCU Futures Partner experiential exercise) e.g. machine learning, virtual reality

Introduction to coding via practice
Coding languages, techniques and developments

Applied digital tools via reflection
Curated learning journey experiencing and gaining understanding in select technology. Discover what it is and how it could be applied in organisations.

Foresight via scenarios and road mapping
Implications of technology for the future of business and ways of doing business. Technology Road mapping

Assessment Breakdown
Continuous Assessment	100%	Examination Weight	0%

Type	Description	% of total	Assessment Date
Course Work Breakdown
Performance evaluation	Digital tool in action performance evaluation	10%	n/a
Completion of online activity	Digital badge completion of on-line curated journey	10%	n/a
Participation	Gamification experience	10%	n/a
Reflective journal	Reflection of key observations, learnings, and challenges	30%	n/a
Group assignment	Forecast and foresight project. Exploring the role and potential of a digital tool in the context of a specific business problem/challenge	40%	n/a

Reassessment Requirement Type
Resit arrangements are explained by the following categories: Resit category 1: A resit is available for both* components of the module. Resit category 2: No resit is available for a 100% continuous assessment module. Resit category 3: No resit is available for the continuous assessment component where there is a continuous assessment and examination element.
* ‘Both’ is used in the context of the module having a Continuous Assessment/Examination split; where the module is 100% continuous assessment, there will also be a resit of the assessment
This module is category 1

Indicative Reading List

Global Centre for Public Service: 2018, Foresight Manual - Empowered Futures for the 2030 Agenda, UNDPO Singapore,
Agrawal, A., Gans, J., & Goldfarb, A.: 2018, Prediction Machines: The Simple Economics of Artificial Intelligence, Harvard Business Review.,

Other Resources

44120, Website, Microsoft, 0, AI, https://docs.microsoft.com/en-us/learn/topics/ai-business-school,