Module Details
| Module Code: |
COMP9095 |
| Title: |
Advanced Info Design & Develop
|
|
Long Title:
|
Advanced Info Design & Development
|
| NFQ Level: |
Expert |
| Valid From: |
Semester 1 - 2022/23 ( September 2022 ) |
| Field of Study: |
4811 - Computer Science
|
| Module Description: |
As a key area of technical communications, this module focuses on information design and development concepts and skills to enable information developers to design and deliver effective information for advanced systems, including connected and intelligent systems. The module aims to impart theory and practices of designing and developing information for systems governed by Artificial Intelligence, with a particular focus on Natural Language Processing (NLP), in order to deliver information that is personalised to user contexts.
|
| Learning Outcomes |
| On successful completion of this module the learner will be able to: |
| # |
Learning Outcome Description |
| LO1 |
Investigate the impact of emerging technologies and machine language processing on information design and delivery |
| LO2 |
Determine the impact of automated and Artificial Intelligence systems on information development strategies |
| LO3 |
Appraise user context scenarios and multi-dimensional context models |
| LO4 |
Design and develop information for multi-dimensional contexts |
| LO5 |
Understand conversation design, and develop information using automated systems |
| LO6 |
Identify potential ethical and privacy issues related to delivering information via automated machine interfaces |
| Dependencies |
Module Recommendations
This is prior learning (or a practical skill) that is strongly recommended before enrolment in this module. You may enrol in this module if you have not acquired the recommended learning but you will have considerable difficulty in passing (i.e. achieving the learning outcomes of) the module. While the prior learning is expressed as named MTU module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
|
|
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module. You may not earn additional credit for the same learning and therefore you may not enrol in this module if you have successfully completed any modules in the incompatible list.
|
| No incompatible modules listed |
Co-requisite Modules
|
| No Co-requisite modules listed |
Requirements
This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed. You may not enrol on this module if you have not acquired the learning specified in this section.
|
| No requirements listed |
| Indicative Content |
|
Impact of emerging technologies
Explain Industry 4.0 and Information 4.0 concepts and impact of artificial intelligence, IoT, automated systems and machine language processing on information design and development.
|
|
Machine language processing
Define natural language processing (NLP), natural language understanding (NLU), and natural language generation (NLG). Develop high-level understanding of how NLP and neural networks work. Explain how NLP impacts information design. Identify challenges of NLP and natural human language.
|
|
User context and prediction
Define user context and identify examples. Explain the relationship between information and user context. Understand current research into sentiment analysis and prediction methods. Understand how prediction may be used to drive personalised user information.
|
|
Multi-dimensional contexts and information modelling
Define multi-dimensional context. Explain context models. Create strategy for multi-dimensional context models. Build multi-dimensional context models. Map information to user context.
|
|
Writing molecular content (micro content)
Understand how molecular content functions in multi-dimensional contexts and user contexts. Design and develop molecular content for user context.
|
|
Conversation design
Understand role of conversation design in emerging technologies. Examine rule-based and artificial intelligence systems for conversation design. Provide practical application using automated systems.
|
|
Ethics and Privacy
Examine ethical and privacy issues raised by use of automated systems, Artificial Intelligence, IoT, and other emerging technologies. Understand the impact of GDPR and similar regulations on automated systems, including IoT and voice and chatbot technologies.
|
|
Module Content & Assessment
|
| Assessment Breakdown | % |
|---|
| Coursework | 100.00% |
Assessments
| No End of Module Formal Examination |
| Reassessment Requirement |
Coursework Only
This module is reassessed solely on the basis of re-submitted coursework. There is no repeat written examination.
|
The University reserves the right to alter the nature and timings of assessment
Module Workload
| Workload: Full Time |
| Workload Type |
Contact Type |
Workload Description |
Frequency |
Average Weekly Learner Workload |
Hours |
| Lecture |
Contact |
Lecture delivering theory underpinning learning outcomes. |
Every Week |
3.00 |
3 |
| Tutorial |
Contact |
Tutorial to support learning outcomes. |
Every Week |
2.00 |
2 |
| Independent & Directed Learning (Non-contact) |
Non Contact |
Independent study. |
Every Week |
9.00 |
9 |
| Total Hours |
14.00 |
| Total Weekly Learner Workload |
14.00 |
| Total Weekly Contact Hours |
5.00 |
| Workload: Part Time |
| Workload Type |
Contact Type |
Workload Description |
Frequency |
Average Weekly Learner Workload |
Hours |
| Lecture |
Contact |
Lecture delivering theory underpinning learning outcomes. |
Every Week |
3.00 |
3 |
| Tutorial |
Contact |
Tutorial to support learning outcomes. |
Every Week |
2.00 |
2 |
| Independent & Directed Learning (Non-contact) |
Non Contact |
Independent study. |
Every Week |
9.00 |
9 |
| Total Hours |
14.00 |
| Total Weekly Learner Workload |
14.00 |
| Total Weekly Contact Hours |
5.00 |
|
Module Resources
|
| Recommended Book Resources |
|---|
-
Schwab, K.. (2017), The Fourth Industrial Revolution., Penguin Group, [ISBN: 978-024130075].
-
Nass, C., Brave, S.. (2007), How Voice Activates and Advances the Human-Computer Relationship, The MIT Press, [ISBN: 978-026264065].
| | Supplementary Book Resources |
|---|
-
Budinski, Kenneth G.. (2001), Engineers Guide to Technical Writing, ASM International, [ISBN: 9780871706935].
-
Rude, Carolyn D., Eaton, Angela.. (2014), Technical editing., Pearson, [ISBN: 9780205786718].
-
Markel, M., Selber, Stuart A.. (2018), Technical Communication., Macmilan, [ISBN: 9781319058616].
| | This module does not have any article/paper resources |
|---|
| Other Resources |
|---|
-
Website, (2020), IEEE Style Manual., IEEE Publishing Operations,
-
Website, Christiansen S, Iverson C, Flanagin A,
et al.. (2020), AMA Manual of Style: A Guide for Authors
and Editors. 11th ed., Oxford University Press,
-
Website, (2021), Microsoft Style Guide., Microsoft,
|
|
