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Curricular information is subject to change
On completion of this module, the learner will be able to
1. Demonstrate an understanding of human visual perception & how it can be exploited to design effective visualisations
2. Identify visualisation approaches suitable for specific data types (including tabular data, spatial data, and network data).
3. Critically evaluate different visualisation approaches as applied to particular tasks
4. Implement interactive visualisation approaches using a programming language
5. Design experiments to test the effectiveness of a specific visualisation approach
Student Effort Type | Hours |
---|---|
Laboratories | 16 |
Autonomous Student Learning | 75 |
Online Learning | 22 |
Total | 113 |
Prior knowledge of a specific programming language is not required. However all students must be comfortable programming in some language (e.g. R/Python/Java/C). Students should also be able to use a text editor to edit code.
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Assignment: Information visualisation assignment | Unspecified | n/a | Graded | No | 60 |
Examination: In person exam (on paper). This will contain MCQs, Short Answer Questions, and some longer form questions. |
1 hour End of Trimester Exam | No | Graded | No | 40 |
Resit In | Terminal Exam |
---|---|
Autumn | No |
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
Not yet recorded.
Name | Role |
---|---|
Diptasree Debnath | Tutor |
Narod Kebabci | Tutor |
Crisron Rudolf Lucas | Tutor |
Mr Anjan Venkatesh | Tutor |
Laboratory | Offering 1 | Week(s) - 21, 22, 23, 24, 25, 26, 30, 31, 32 | Thurs 10:00 - 11:50 |
Laboratory | Offering 1 | Week(s) - 29 | Thurs 10:00 - 11:50 |
External & School Exams | Offering 1 | Week(s) - 33 | Thurs 10:00 - 11:50 |