Introductory description
The aim is to combine perspectives and methods of enquiry drawn from disciplines such as Psychology and Sociology with the tools, techniques and technologies of Computer Science to create an approach to of digital systems' design and innovation that is both relevant and practical.
Module aims
The aim is to combine perspectives and methods of enquiry drawn from disciplines such as Psychology and Sociology with the tools, techniques and technologies of Computer Science to create an approach to of digital systems' design and innovation that is both relevant and practical.
Outline syllabus
This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.
- Background: development and scope of social informatics; practical goals.
- Understanding individual behaviour: perception, memory and action.
- Modelling human interaction with digital systems.
- Design methodologies and notations.
- Techniques and technologies: dialogue styles, information visualisation.
- Designer-user relations: iteration, prototyping.
- Evaluation: formative and summative; performance and learnability.
- Mobile computing and devices: novel interfaces; ubiquitous computing.
- Organisational factors: understanding the workplace; resistance; dependability.
- Innovation processes at scale: social shaping of IT, actor-network theory, co-production.
Learning outcomes
By the end of the module, students should be able to:
- 1. Demonstrate, in writing, knowledge of issues and problems in social informatics.
- 2. Demonstrate understanding of issues impacting on uptake of digital systems and innovations by diagnosing problems in relations between technologies and use in a range of application domains.
- 3. Apply appropriate principles and methodologies to address challenges in the design and deployment of novel digital systems.
- 4. Demonstrate understanding of different disciplinary perspectives on social informatics and ability to apply them to solve design and deployment challenges.
- 5. Devise, plan and execute requirements investigations and system evaluation studies from a social informatics perspective, and present findings in a clear and effective manner.
- 6. Demonstrate awareness of current areas of research in social informatics by locating and summarising examples of recent controversies and progress.
Indicative reading list
Please see Talis Aspire link for most up to date list.
View reading list on Talis Aspire
Research element
Awareness of current research in the field
Interdisciplinary
Using insights from Psychology and Sociology to understand usability issues, human behaviour, requirements gathering and innovation processes
Subject specific skills
- knowledge of issues and problems in social informatics.
- understanding of issues impacting on uptake of digital technologies in a range of application domains.
- understanding of different disciplinary perspectives and ability to apply them to solve design and deployment challenges.
- devise, plan and execute requirements investigations and system evaluation, and present findings in a clear and effective manner.
- awareness of current areas of research by locating and summarising examples of recent controversies and progress.
Transferable skills
- Identify literature relevant to a solving problem and critically review it.
- Understanding of basic statistical tests.
-Familiarity with a range of methodologies for IT project management and how to match them to project-specific factors.
-Understanding of non-technical factors that influence success of IT projects - Competence in multi-disciplinary research
Study time
Type |
Required |
Lectures |
20 sessions of 1 hour (13%)
|
Seminars |
10 sessions of 1 hour (7%)
|
Practical classes |
8 sessions of 1 hour (5%)
|
Private study |
112 hours (75%)
|
Total |
150 hours |
Private study description
Background reading.
Organising and planning group work in the lab.
Revision.
Costs
No further costs have been identified for this module.
You do not need to pass all assessment components to pass the module.
Students can register for this module without taking any assessment.
Assessment group D3
|
Weighting |
Study time |
Eligible for self-certification |
Group-based exercise
|
12%
|
|
Yes (extension)
|
By default, each group member will receive the same mark, but the group may request a separate mark for each member if it can provide a weighting for each member's contribution that has been agreed by all members of the group. This assignment is group work and is not, therefore, eligible for self-certification.
|
Group-based exercise
|
18%
|
|
Yes (extension)
|
By default, each group member will receive the same mark, but the group may request a separate mark for each member if it can provide a weighting for each member's contribution that has been agreed by all members of the group. This assignment is group work and is not, therefore, eligible for self-certification.
|
In-person Examination
|
70%
|
|
No
|
CS916 exam
- Answerbook Pink (12 page)
- Students may use a calculator
|
Assessment group R2
|
Weighting |
Study time |
Eligible for self-certification |
In-person Examination - Resit
|
100%
|
|
No
|
CS916 resit exam
- Answerbook Pink (12 page)
- Students may use a calculator
|
Feedback on assessment
Written feedback on the assignment
Past exam papers for CS916
Anti-requisite modules
If you take this module, you cannot also take:
-
CS348-15 Social Informatics
Courses
This module is Optional for:
-
Year 2 of
TIMS-L990 Postgraduate Big Data and Digital Futures
-
TCSA-G5PD Postgraduate Taught Computer Science
-
Year 1 of
G5PD Computer Science
-
Year 1 of
G5PD Computer Science
-
Year 1 of
TCSA-G5PA Postgraduate Taught Data Analytics
-
TIMA-L995 Postgraduate Taught Data Visualisation
-
Year 1 of
L995 Data Visualisation
-
Year 2 of
L995 Data Visualisation
-
TIMA-L99A Postgraduate Taught Digital Media and Culture
-
Year 1 of
L99A Digital Media and Culture
-
Year 2 of
L99A Digital Media and Culture
-
Year 1 of
TIMA-L99D Postgraduate Taught Urban Analytics and Visualisation
This module is Core option list A for:
-
Year 1 of
TPSS-C803 Postgraduate Taught Behavioural and Data Science
This module is Core option list C for:
-
Year 1 of
TPSS-C803 Postgraduate Taught Behavioural and Data Science
This module is Option list A for:
-
Year 1 of
TIMS-L990 Postgraduate Big Data and Digital Futures