Module manager: Costas Loizou
Email: C.Loizou@leeds.ac.uk
Taught: Semester 1 Jul to 31 Aug View Timetable
Year running 2024/25
GPA of 2.5 (US) or equivalent and enrolled at a university
This module is not approved as a discovery module
This module transcends computer science, cultivating problem-solving expertise across diverse domains, from business to biology. In the global innovation landscape, computational thinking serves as a universal language. Students will equip themselves to think like a computer scientist, mastering concepts like decomposition, pattern recognition, and abstraction. Students will develop crucial skills in logical thinking and algorithm design, tackling real-world problems with confidence. Students will enhance both their spoken and written scientific communication abilities.
The module aims to enable the students to:
Develop a creative way of thinking that would be useful for scientific problem solving and programming in various disciplines.
Introduce an approach to computational thinking and demonstrate a broad understanding of its concepts and techniques.
Develop scientific communication skills
On successful completion of the module students will have demonstrated the following learning outcomes relevant to the subject:
1. Express physical problems in a computational setting.
2. Implement core principles of computational thinking to obtain appropriate solutions of problems in a well-defined context.
3. Explain the background and solution of a given problem to an audience of non-specialists effectively in English.
On successful completion of the module students will have demonstrated the following skills learning outcomes:
a) Understand and communicate the key concepts of Computational Thinking effectively in English (Work-Ready, Academic, Digital).
b) Develop a logical approach towards problem solving (Academic, Work-Ready, Sustainability).
c) Move towards an autonomous learning style with an ability to work independently and in a group situation (Work-Ready, Sustainability, Enterprise).
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Fieldwork | 1 | 8 | 8 |
| Fieldwork | 1 | 10 | 10 |
| Seminar | 8 | 3 | 24 |
| Independent online learning hours | 15 | ||
| Private study hours | 43 | ||
| Total Contact hours | 42 | ||
| Total hours (100hr per 10 credits) | 100 | ||
Student progress will be monitored through:
Observation of student participation in seminar discussions and in-class group tasks
One-to-one discussion with the tutor during the tutor’s office hours.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Presentation | Group presentation | |
| Assignment | Written Assignment | |
| Total percentage (Assessment Coursework) | 0 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
There is no reading list for this module
Last updated: 4/29/2024
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