Academic Handbook Course Descriptors and Programme Specifications
LCSCI4212 Discrete Structures Course Descriptor
Last modified on December 19th, 2024 at 4:11 pm
Course code | LCSCI4212 | Discipline | Computer & Data Science |
UK credit | 15 | US credit | 4 |
FHEQ level | 4 | Date approved | November 2022 |
Core attributes | Conducting Formal and Quantitative Reasoning (FQ) | ||
Pre-requisites | None | ||
Co-requisites | None |
Course Overview
This course introduces discrete structures that form the foundation of computer science. Learning starts with an understanding of mathematical notation, logic, and sets. Students then study proof techniques, combinatorics (counting), probability, asymptotic notation, recurrences, and an introduction to graph theory. By the end of this course, students will have become familiar with a number of discrete structures that are used throughout computer and data science.
Learning Outcomes
On successful completion of the course, students will be able to:
Knowledge and Understanding
K1a | Demonstrate knowledge and understanding of number representations, logical formulas, algorithms and data structures; and how to use them correctly in the context of a computer program. |
K2a | Demonstrate knowledge and understanding of the underlying concepts and mathematical techniques (e.g., counting or sums) to analyse the complexity of algorithms. |
K3a | Identify which data structures and algorithms are best suited to solve a typical data processing problem |
Subject Specific Skills
S1a | Identify the technical, social and management dimensions of algorithms, their correctness and complexity, in real-world applications. |
S3a | Evaluate basic data structures, algorithms and logical operations in existing software and interpret qualitative or quantitative results. |
Transferable and Employability Skills
T1a | Communicate results (e.g., complexity of basic data structures and algorithms) accurately with structured and coherent arguments in written reports. |
T3a | Display a developing technical proficiency in written English and an ability to communicate clearly and accurately in structured and coherent pieces of writing.. |
Teaching and Learning
This course has a dedicated Virtual Learning Environment (VLE) page with a syllabus and range of additional resources (e.g. readings, question prompts, tasks, assignment briefs, discussion boards) to orientate and engage students in their studies.
The scheduled teaching and learning activities for this course are:
- Lectures/labs. 40 scheduled hours – typically including induction, consolidation or revision, and assessment activity hours:
- Version 1:All sessions in the same sized group, or
- Version 2: most of the sessions in larger groups; some of the sessions in smaller groups
Faculty hold regular ‘office hours’, which are opportunities for students to drop in or sign up to explore ideas, raise questions, or seek targeted guidance or feedback, individually or in small groups.
Students are to attend and participate in all the scheduled teaching and learning activities for this course and to manage their directed learning and independent study.
Indicative total learning hours for this course: 150
Assessment
Both formative and summative assessment are used as part of this course, with purely formative opportunities typically embedded within interactive teaching sessions, office hours, and/or the VLE.
Summative Assessments
AE: | Assessment Activity | Weighting
(%) |
Duration | Length
(words) |
1 | Set Exercises | 80 | 32-40 hours | |
2 | Role Play | 20 | 8-16 hours |
Further information about the assessments can be found in the Course Syllabus.
Feedback
Students will receive formative and summative feedback in a variety of ways, written (e.g. marked up on assignments, through email or the VLE) or oral (e.g. as part of interactive teaching sessions or in office hours).
Indicative Reading
Note: Comprehensive and current reading lists are produced annually in the Course Syllabus or other documentation provided to students; the indicative reading list provided below is for a general guide and part of the approval/modification process only.
- Harriet Fell and Javed Aslam. 2017. Discrete Structures. Cognella Academic Publishing
- Kenneth H. Rosen. 2019. Discrete Mathematics and its Applications (8th edition). McGraw-Hill.
Indicative Topics
Note: Comprehensive and current topics for courses are produced annually in the Course Syllabus or other documentation provided to students; the indicative topics provided below are used as a general guide and part of the approval/modification process only.
- Computing (i.e., number representations, circuits, and logic)
- Combinatorics (i.e., sets, counting, and probability)
- Algorithmic analysis (i.e., sequences, series, sums, recurrences, induction, and growth of functions)
- Graph algorithms
Version History
Title: LCSCI4212 Discrete Structures Course Descriptor
Approved by: Academic Board Location: academic-handbook/programme-specifications-and-handbooks/undergraduate-programmes |
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Version number | Date approved | Date published | Owner | Proposed next review date | Modification (as per AQF4) & category number |
2.0 | July 2024 | August 2024 | Dr Alexandros Koliousis | November 2027 | Category 2: Change to summative assessment |
1.0 | November 2022 | January 2023 | Dr Alexandros Koliousis | November 2027 |