Paper 2: Combined internal assessment (project)

Project brief: Will it rain tomorrow?

A local sports club wants to know the day before whether outdoor training is likely to be rained off. Build a machine learning model that predicts Rain tomorrow: Yes/No from today's weather. Starter data (you may collect more):

Day	Humidity (%)	Pressure (hPa)	Cloud cover (0–8)	Wind (km/h)	Rain tomorrow
1	85	1002	7	22	Yes
2	60	1021	2	10	No
3	90	998	8	30	Yes
4	55	1025	1	8	No
5	78	1008	6	18	Yes
6	65	1018	3	12	No
7		1004	7	25	Yes
8	50	1030	0	5	No
9	88	1000	8	28	Yes
10	70	1015	4	14	No
11	82	1006	6	20	Yes
12	58	1023	2	9	No
13	145	1012	5	16	No
14	75	1010	5	17	Yes
15	62	1020	3	11	No
16	60	1021	2	10	No

Requirements: - prepare the data, then train a classification model (e.g. a decision tree) - test it on data it was not trained on - explain how the club should use the prediction Suggested tools: Python (e.g. scikit-learn), a spreadsheet, or a decision tree built and traced by hand.

1(a)3 marks

Describe the problem your AI system will solve and who will use it.

1(b)4 marks

Write four success criteria for your system. Each criterion must be specific and measurable.

1(c)4 marks

Identify the AI technique you will use. Justify your choice and explain why one alternative technique would be less suitable.

2(a)6 marks

Produce a design for your system. Use a flowchart, pseudocode, decision tree or labelled system diagram (described in words if needed). Show the inputs, processing and outputs.

2(b)4 marks

Describe your data plan: what data you need, where it will come from, how much you need and (if relevant) the features and labels.

3(a)5 marks

Describe how you collected and prepared your data so that it was clean and correctly structured. Give specific examples of problems you found and how you fixed them.

3(b)2 marks

Explain how you separated data for training and testing, and why.

49 marks

Describe how you built your AI system. Include key code, rules or screenshots (described in words) as evidence, and explain how each part works.

5(a)6 marks

Create a test plan for your system with at least five tests. For each test give the input/test data, the type of test (normal, boundary or unexpected), the expected result and the actual result.

5(b)4 marks

Record the overall performance of your system on the test data and interpret the results. Show any calculations.

6(a)6 marks

Evaluate your system against each of your success criteria, using evidence from your testing.

6(b)4 marks

Explain the ethical, privacy or bias issues that could arise if your system were used for real, and how you would reduce them.

6(c)3 marks

Suggest three improvements to your system. For each, explain how it would improve the system.

Finished?

Answer every question to finish (13 left), or finish when the time’s up.

Score 0 / 60 · 0 of 13 marked

This paper is written by Plasmo in the style of the LRN GCSE Artificial Intelligence exam. It is not a past paper and is not produced or endorsed by the exam board.

LRN GCSE Artificial Intelligence Mock Exam: Paper 2: Combined internal assessment (project) (Mock D) | Plasmo