COMP108 - Fundamentals of Programming Design

Year

Credit points

Campus offering

Prerequisites

Nil

Unit rationale, description and aim

A secure grounding in the theory and practice of programming is vital to the development of disciplinary expertise in digital technology (computing).

This unit provides the foundations of programming and software design through a focus on real-world problems. Students acquire practical skills in programming and software project management and use these skills to create simple software solutions to real-world problems by applying their developing computational, systems and design thinking skills. Students consider the social impact of past, present and emerging computing technologies, and use this knowledge to inform their own programming projects.

The aim of this unit is to foster students’ exploration of the fundamentals of software design and to give students the opportunity to learn through experience to apply their developing programming and software design skills to a variety of practical design challenges.

Learning outcomes

To successfully complete this unit you will be able to demonstrate you have achieved the learning outcomes (LO) detailed in the below table.

Each outcome is informed by a number of graduate capabilities (GC) to ensure your work in this, and every unit, is part of a larger goal of graduating from ACU with the attributes of insight, empathy, imagination and impact.

Explore the graduate capabilities.

On successful completion of this unit, students should be able to:

LO1       Define programming techniques and apply them to the solution of real-world problems (GA5, GA8)

LO2       Design flowcharts, pseudocode and algorithms (GA5, GA8, GA9)

LO3       Select and use a non-visual programming language in the development of software programs (GA5, GA10)

LO4       Evaluate algorithm and programming code using test data to check for desired outcomes (GA2, GA4, GA8).

LO5       Plan and manage software projects using an iterative and collaborative approach, identifying risks and considering ethics, safety and sustainability (GA3, GA4, GA5, GA6, GA7, GA8, GA9, GA10).

Graduate attributes

GA2 - recognise their responsibility to the common good, the environment and society 

GA3 - apply ethical perspectives in informed decision making

GA4 - think critically and reflectively 

GA5 - demonstrate values, knowledge, skills and attitudes appropriate to the discipline and/or profession 

GA6 - solve problems in a variety of settings taking local and international perspectives into account

GA7 - work both autonomously and collaboratively 

GA8 - locate, organise, analyse, synthesise and evaluate information 

GA9 - demonstrate effective communication in oral and written English language and visual media 

GA10 - utilise information and communication and other relevant technologies effectively.

Content

Topics will include:

Module 1-Programming techniques –LO1

• Sequence, selection and repetition,
• Data structures: Lists tuples, dictionaries, sets
• Functions
• Files and exception handling
• Strings

Module 2-Program Design- LO1, LO2

• Flowcharts
• Pseudocode
• Algorithms
• Artificial Intelligence -machine learning algorithms

Module 3- Software Development Life Cycle -LO1, LO2, LO3, LO4, LO5

• Software Project Management -design, development, evaluation of software solution

Learning and teaching strategy and rationale

A student-focused, problem-based learning approach is used in this unit. This enables the development of conceptual, procedural and professional knowledge and skill which allows students to practise design thinking, system thinking and computational thinking skills.

The learning trajectory follows the ACU’s 3A framework:

Acquisition: Students encounter programming concepts through interactive lecture demonstrations, concepts are discussed and broadened through analysis of specific real-world problems and further informed by research during development of software projects. In tutorial classes students design, develop and evaluate software solutions.

Assimilation: Issues in software design and development are introduced through a practice-oriented learning method. This method involves the parallel development of procedural and conceptual skills required for design, development and documentation of software solutions.

Application -Students combine conceptual knowledge in programming design and procedural knowledge of software development methodologies to work on software development projects.

Using a computational thinking approach, students develop solutions to real-world problems: designing developing, communicating and evaluating software solutions. 

Assessment strategy and rationale

The problem-based learning strategy employed in this unit is supported by the integration of progressive authentic assessment tasks completed at critical points in the students’ learning.

Initially students acquire knowledge in software program design by undertaking tutorial exercises and they develop skills in design and development through practical tutorial classes. Practical tutorials provide opportunities for formative assessment which supports assimilation of knowledge.

Summative assessment aims to assess students’ competencies and how well they can apply knowledge and skills (conceptual, procedural and professional) in a holistic manner using an integrated approach to solving design problems.

In this unit, students’ problem-solving skills are assessed by means of quizzes and a problem-solving test that evaluates students’ achievement of a synthesis between design theory and the application of programming skills to a software project. The software design project will assess students’ project management skills in object-oriented software design and development and will require evidence of successful project definition, research, ideation, prototyping, iteration, critical evaluation and risk assessment.

Overview of assessments

Representative texts and references

Deitel, P.J., & Dietal, H. (2020). Intro to Python for computer science and data science: Learning to program with AI, big data and the cloud. New York: Pearson Education.

Downey, A. (2012). Think Python: How to think like a computer scientist. Green Tea Press.

Farrell, J. (2018), Introductory programming logic and design. Cengage Learning US.

Guzdial, M.J. & Ericson, B. (2016). Introduction to computing and programming in Python: A multimedia approach. Boston: Pearson.

Miller, B.N., Ranum, D.L. & Anderson, J. (2021). Python programming in context (3rd ed.). Burlington, Massachusetts: Jones & Bartlett Learning.

Perry, G. & Miller, D. (2019). Sam’s teach yourself: Beginning programming in 24 hours (4th ed.). Pearson Higher Education.

Schneider, G.M., & Gersting, J. (2019). Invitation to Computer Science. Cengage Learning US.

Spraul, V. A. (2012). Think like a programmer: An introduction to creative problem solving. Retrieved from https://ezproxy.acu.edu.au/login?url=https://ebookcentral.proquest.com/lib/acu/detail.action?docID=1137575

Stephens, R. (2019). Essential algorithms: A practical approach to computer algorithms using Python and C# (2nd ed.). Indianapolis, IN: Wiley.

Sweigart, A. (2012). Making games with Python & Pygame. Sweigart, Al. https://open.umn.edu/opentextbooks/textbooks/677