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School of Computer Science
Level 4
Ingkarni Wardli Building
SA 5005

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COMP SCI 1010 Puzzle Based Learning


An introduction to unstructured problems and puzzle solving.

Course Details

Important details about the course are found in the Course Profile document located here. All other information including lecture schedule, practials, tutorials and announcments will be available through the MyUni.

Course Description

The focus of this course is on getting students to think about framing and solving unstructured problems (those that are not encountered at the end of some textbook chapter). The general objective is to increase the student's mathematical awareness and problem-solving skills by discussing a variety of puzzles. The puzzle-based learning approach has a long tradition as the first mathematical puzzles were found in Sumerian texts that date back to around 2,500 BC The puzzles selected for the course satisfy most of the following criteria:
  • Generality: educational puzzles explain some universal mathematical problem-solving principles;
  • Simplicity: educational puzzles are easy to state and easy to remember;
  • Eureka factor: educational puzzles often frustrate the problem-solver! The Eureka factor also implies that educational puzzles have often elementary solutions that are not obvious;
  • Entertainment factor: educational puzzles are very entertaining!

Such educational puzzles are used to illustrate basic concepts of critical thinking, mathematics, and problem-solving. The course presents some problem-solving rules and covers issues of understanding the problem and the role of intuition in problem-solving activities. Further, some mathematical problem-solving principles are discussed and elements of modeling, constraint-processing, optimization, probability, statistics, simulation, pattern recognition, and strategy are introduced.

Level: 1
Credit: 3 units
Assumed Knowledge: SACE Stage 2 Mathematical Studies

Course Offerings

North Tce, Adelaide
  • 2017 semester 1
  • Objectives and Graduate Attributes

    The objectives of this course are:

    • Understand the need to undertake lifelong learning
    • Be able to think about framing and solving unstructured problems
    • Understand and apply problem-solving principles
    • Understand the broad concepts of modelling, constraint-processing, optimisation, probability, statistics, simulation, and pattern recognition.

    The graduate attributes that will be developed in this course are:

    • Knowledge and understanding of the content and techniques of a chosen discipline at advanced levels that are internationally recognised.
    • The ability to locate, analyse, evaluate and synthesise information from a wide variety of sources in a planned and timely manner.
    • An ability to apply effective, creative and innovative solutions, both independently and cooperatively, to current and future problems.
    • Skills of a high order in interpersonal understanding, teamwork and communication.
    • A proficiency in the appropriate use of contemporary technologies.
    • A commitment to continuous learning and the capacity to maintain intellectual curiosity throughout life.
    • A commitment to the highest standards of professional endeavour and the ability to take a leadership role in the community.
    • An awareness of ethical, social and cultural issues within a global context and their importance in the exercise of professional skills and responsibilities.