13 Computer Science (13CSI)
Course Description
Teacher in Charge: Vincent Brannigan.
13 Computer Science
This course builds on Level 2 Computer Science and can lead on to tertiary study in that area. The course introduces many career pathways in Computer Science.
Course Components
- Learn to use complex programming techniques in the Python programming language
- Students will iteratively develop their own software project
- Learn about key concepts in computer science such as Artificial Intelligence, and Formal computer languages
Course Overview
Term 1
Revision of Computer programming using Python.
Term 2
Complex Programming and Development Using Python.
Students will design and develop a 2d maze game. The game will include complex programming techniques.
● uses variables storing at least two types of data (e.g. numeric, text, Boolean, object)
● uses sequence, selection and iteration control structures
● takes input from a user, file, sensors, or other external source
● produces output
● uses two or more complex programming techniques.
Examples of complex programming techniques include:
● programming or writing code for a graphical user interface (GUI)
● reading from, or writing to, files or other persistent storage
● object-oriented programming using class(es) and objects defined by the student
● using types defined by the student
● using third party or non-core API, library or framework
● using complex data structures (e.g. stacks, queues, trees)
The design of the program will be completed by the end of term 2 and assessed with AS 91901: Apply user experience methodologies to develop a design for a digital technologies outcome.
Term 3
The development of the program will be completed by the end of term 3 and assessed with AS 91906: Use complex programming techniques to develop a computer program.
AS 91906: Use complex programming techniques to develop a computer program.
and
AS 91907: Use complex processes to develop a digital technologies outcome.
Computer science concepts. Develop understanding of complexity and tractability.
Coveringr: polynomial and non-polynomial time complexity, Big O notations O(1),O(log(n)), O(n), O(2n), O(n!), O(nk), best-case, worst-case, and average-case time complexity), NP-complete (e.g. travelling salesman / knapsack), and solving complex problems (approximation algorithms / heuristics / brute force).
Assesed with AS 91908: Demonstrate understanding of a computer science concept. in term 4.
Term 4
External Comon assessment task AS 91908: Demonstrate understanding of a computer science concept.
Recommended Prior Learning
Entry Requirements
12 credits from 12CSI, or approval from TIC
Assessment Information
Possible Credits 18External - 3 credits
Internal - 15 credits
Credit Information
You will be assessed in this course through all or a selection of the standards listed below.
This course is eligible for subject endorsement.
This course is approved for University Entrance.
External
NZQA Info
Digital Technologies and Hangarau Matihiko 3.2 - Apply user experience methodologies to develop a design for a digital technologies outcome
NZQA Info
Digital Technologies and Hangarau Matihiko 3.7 - Use complex programming techniques to develop a computer program
NZQA Info
Digital Technologies and Hangarau Matihiko 3.8 - Use complex processes to develop a digital technologies outcome
NZQA Info
Digital Technologies and Hangarau Matihiko 3.9 - Analyse an area of computer science