Syllabus
Syllabus
Syllabus
3 Subject content
Candidates for Cambridge International AS Level Information Technology study topics 1–11.
Candidates for Cambridge International A Level Information Technology study all topics.
The content of the AS Level topics 1–11 is assumed knowledge for the A Level components.
The following information identifies content which must be covered within all topics. Where the term ‘including’ is
used, everything listed must be studied. However, this list is not exhaustive and other related aspects should also
be studied.
Note that no marks are awarded for brand names in candidate responses.
This syllabus gives you the flexibility to design a course that will interest, challenge and engage your learners.
Where appropriate you are responsible for selecting suitable subject contexts, resources and examples to support
your learners’ study. These should be appropriate for the learners’ age, cultural background and learning context as
well as complying with your school policies and local legal requirements.
• Uses
• Write an algorithm
• Advantages and disadvantages of
different methods of processing
5 eSecurity
Candidates should know and understand:
5.1 Personal data
• What personal data is Including:
Why personal data should be kept confidential
• Keeping personal data secure How personal data can be kept confidential, including the
removal of geotags from photos/videos
• Preventing misuse of personal data How personal data can be gathered by unauthorised persons
and how this might be prevented including: smishing, vishing,
phishing and pharming
Candidates will be expected to evaluate the methods of
prevention
5.2 Malware
• Types Types of malware including: Trojan Horse, worms, spyware,
adware, rootkit, malicious bots, ransomware and others
• Uses Uses including: fraud, industrial espionage, sabotage
• Consequences for organisations and
individuals
• Prevention Prevention including software and physical
7 Expert systems
Candidates should know and understand:
7.1 Expert systems
• How expert systems are used to Components including: user interface, inference engine,
produce possible solutions for different knowledge base (as a database of facts and rules base),
scenarios explanation system, knowledge base editor
Scenarios including: mineral prospecting, investment analysis,
financial planning, insurance planning, car engine fault
diagnosis, medical diagnosis, route scheduling for delivery
vehicles, plant and animal identification
Candidates are expected to understand the concepts of
backward chaining and forward chaining
Including the terms: data driven and goal driven, their use in
diagnoses, gaming and artificial intelligence
8 Spreadsheets
Candidates should be able to:
8.1 Create a spreadsheet
Create structure
• Create page/screen structures to meet Including: page orientation, page size, fit to page, margins,
the requirements of an audience and/ header, footer
or task specification/house style
• Create/edit spreadsheet structures Insert, delete, hide, resize, merge, edit spreadsheet structure
including: rows, columns, cells
• Protect cells and their content Including: cells, rows, columns, worksheets and workbooks
• Freeze panes and windows
8 Spreadsheets (continued)
Candidates should be able to:
8.1 Create a spreadsheet (continued)
Use validation rules (See 1.4)
Use appropriate input and error messages
• Format cells Including: date, time, text, numeric, currency, percentage,
fractions, text orientation, alignment
• Format cell emphasis Including: size, style, colour, shading, merge, borders,
comments, conditional formatting
9 Modelling
Candidates should be able to:
9.1 Modelling and simulations
Use what-if analysis Including: what-if analysis, predicting the result of changing
data, goal seek
Test a spreadsheet model Create and apply a test plan to test a spreadsheet model
Know and understand: Including for: financial forecasting, population growth, climate
change, weather systems, queue management, traffic flow,
• What-if analysis
construction
• The characteristics of modelling
software
• The need for computer models
• The effectiveness of spreadsheet
models
• The use of a model to create and run Uses including: natural disaster planning, pilot training, learning
simulations to drive a car, nuclear science research