Assessment Cover Sheet and Feedback Form 2022-23
Module Code:

CS1S469
Module Title:

Logic Programming and Computational Thinking

Assessment Title and Tasks:

Poster presentation
Assessment No.

1

Date Set:

17-Oct-22
Submission Date:

16-Dec-22
Return Date:

15-Jan-23

IT IS YOUR RESPONSIBILITY TO KEEP RECORDS OF ALL WORK SUBMITTED

Marking and Assessment

This assignment will be marked out of 100%

This assignment contributes to 50% of the total module marks.

Learning Outcomes to be assessed (as specified in the validated module descriptor https://icis.southwales.ac.uk/ ):

1) To demonstrate knowledge and understanding of the essential facts, concepts and principles of programming within a mathematical context.
2) To utilise essential facts, concepts, principles and theories in the analysis, specification, design, planning, documentation, implementation and evaluation of solutions.
3) To formulate simple concepts and relations in logic that can be executed as a program to solve constrained AI problems.

Provisional mark only: subject to change and / or confirmation by the Assessment Board

Design expert system

In this coursework you are required to present a poster and give a presentation to introduce your solution of one of the following two questions.

Task

Design and implement an ES based on your Semantic nets and Rule base design using VisiRule and Prolog to ONE of the following problems:

1- Advise customers whither to buy or to rent accommodations based on their financial and social own circumstances; OR
2- Help doctors diagnose patinate with COVID19.

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You need to create a poster to represent your solution. Your poster must explain your solution in great details.

Submission
Your outputs should be presented in a poster format. You need to make sure your design and implementation are discussed in your poster. you can use the following questions as a guideline to help you format your poster;
• What was your data acquisition method?
• How to load suggest the question that lead to the decision?
• What is the knowledge representation method?
• How to explore the designs of the user interface?
• How to develop robust system to give accurate results?

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You are required to produce a poster that provides a visual introduction to the topic.
You must also prepare presentation notes for the poster and a supporting commentary. These will be used in lieu of a formal oral discussion.

Blackboard Submission
You should submit all code, and documentation as a zip file through blackboard. Please allow time for the upload to take place and factor this into the deadline!
The file name should include your student ID and first name, i.e. “ Mabrouka-123456.docx”.
Content
Your poster must introduce the topic and provide context. It should investigate the appropriate techniques and algorithms. Please note that technical content must be included. You should consider adding results from your own implementation where appropriate.
Target audience: The poster is to be targeted at recent graduates of Artificial Intelligence with Computer Science or related discipline and well-informed laypeople.
Poster: The poster should be an A2 portrait. The poster can be produced in any appropriate tool but must be submitted as a PDF.
Need first-class papers? Get Fast Essay Writers US & urgent essay writing service Ca – Notes and commentary: These can be presented in Word format or PDF. They should be presented in a formal style. You are not looking to repeat the content of the poster but to provide additional information and detail where appropriate.
Need first-class papers? Get Fast Essay Writers US & urgent essay writing service Ca – Note: The notes and commentary are to support the poster in lieu of a formal presentation; the grade will be derived from the poster and notes together. There will not be a separate grade for the notes and commentary.
Individual working: This is not a group assessment. You are required to work on the task individually and submit your own work. You should expect your work to be submitted for automated plagiarism checks.

Marking Scheme:
Fail Narrow Fail 3rd Class / Pass Lower 2nd Class / Pass Upper 2nd Class / Merit 1st Class / Distinction
Algorithms and methods 20%  Algorithms and/or methods that illustrate the topic not included  Algorithms and/or methods intended to illustrate the topic at hand included, but fail to do so  Algorithms and/or methods intended to illustrate the topic at hand included, but are very limited in scope and/or do little to illustrate the topic  Algorithms and/or methods intended to illustrate the topic at hand included, but may be limited in scope or comprehension  Algorithms and/or methods intended to illustrate the topic at hand included  Algorithms and/or methods intended to illustrate the topic at hand are included and completely understood and placed within the wider context of the field
Critical awareness of topic 20%  Very little or no evidence of critical awareness of the topic  Little evidence of critical awareness of the topic  Some evidence of critical awareness of the topic, which may also include significant errors  Some evidence of topic critical awareness of the topic, but one that is let down by frequent errors  Strong evidence of some critical awareness of the topic, which may include some minor errors  Excellent critical awareness of the topic that contains no errors
Model and model accuracy 20%  Very poor model missing component. code does not work  Poor model code does not work  Satisfactory model, the component are complete but the code is not fully functional or have some wrong outputs  Good model, the component are fully functional and the code is fully functional but the evaluation and the accuracy is not very good  Very good the component are fully functional and the code is fully functional but the evaluation and the accuracy is acceptable  Excellent and outstanding model. The component are fully functional and the code is fully functional with and excellent evaluation and accuracy
Need first-class papers? Get Fast Essay Writers US & urgent essay writing service Ca – Notes and Commentary 10%  Commentary and notes contradict poster or add no additional information  the notes and commentary are incomplete or inaccurate  commentary provides some limited complimentary information to the poster. Message may still not be clear or may be lacking in technical content  commentary provides some complimentary information to the poster. Commentary indicates an understanding of the field discussed  Commentary provides complimentary information to the poster. such that together they make a cohesive whole which clearly addresses the allocated title  Commentary provides complimentary information to the poster such that together they make a cohesive whole which clearly addresses the allocated title whilst also placing this into the wider context
Quality of the poster presentation including speakers notes 30%  Very little content in the poster is relevant to the project

 Has captioned graphics that are poorly selected and/or not cited where required
 None or very few items of importance are labelled and can be read from three feet away
 Distractedly messy or poorly designed and/or uninformative
 Little or no consideration for grammar and/or spelling evident  Little content in the poster is relevant to the project and/or includes significant inaccuracies

 Has captioned graphics that not particularly well selected cited where required
 Few items of importance are labelled and can be read from three feet away
 Poorly designed and/or marginally informative
 Many grammatical or spelling mistakes  Much of the content is relevant to the project and/or includes inaccuracies

 Has at least one graphic related to the object with relevant caption(s) cited where required
 Some items of importance are labelled and can be read from three feet away
 Reasonably attractive, although it may be messy, and marginally informative
 Several grammatical or spelling mistakes  All content is relevant and accurate to the project

 Has at least one good graphic related to the object with relevant caption(s) cited where required
 Most items of importance are labelled and can be read from three feet away
 Attractive in terms of design, theme and colour use, layout and neatness, and reasonably informative
 A few grammatical or spelling mistakes  All content is relevant, accurate and Mostly appropriate to the project

 Has at least two good graphics related to the object with relevant captions cited where required
 Almost all items of importance are labelled and can be read from three feet away
 Attractive in terms of design, theme and colour use, appropriate orientation , layout and neatness, and informative
 Research Paper Writing Service: Professional Help in Research Projects for Students – One or two grammatical or spelling mistakes  All content is relevant, accurate and appropriate to the project

 Has at least two excellent graphics related to the object with relevant captions cited where required
 All items of importance are labelled and can be read from three feet away
 Exceptionally attractive and attention grabbing in terms of design, theme and colour use ,appropriate orientation, layout and neatness, and very informative
 Grammar, spelling and clarity excellent
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This is a coursework assignment for the module “Logic Programming and Computational Thinking” with module code CS1S469. The assessment is a poster presentation and contributes to 50% of the total module marks. The learning outcomes to be assessed are: 1) knowledge and understanding of programming concepts, 2) application of programming concepts, and 3) formulation of simple concepts in logic for AI problems.

The task is to design and implement an expert system based on semantic nets and rule base design using VisiRule and Prolog for either advising customers on buying or renting accommodations or diagnosing COVID-19 patients. The poster should explain the solution in detail and include questions such as data acquisition method, knowledge representation method, user interface design, and system robustness.

The poster must be in A2 portrait format and submitted as a PDF, along with presentation notes and a supporting commentary in Word format or PDF. The poster and notes will be graded together, with the algorithms and methods being 20% of the grade. The assignment is individual and will be checked for plagiarism.

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