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Course Outlines

COMP SCI 7210 - Foundations of Computer Science A

North Terrace Campus - Trimester 1 - 2024

This course will develop your coding and problem-solving skills with a focus on data and data science. You will learn fundamental programming concepts such as data, selection, iteration, functional decomposition, data organisation as well as how to apply these programming fundamental knowledge to practical problems. You will build fundamental software development skills including the use of the Python programming language and tools, debugging, object-oriented design, basic data structures, and fundamentals of good programming practice, style and design.

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  • General Course Information
    Course Details
    Course Code COMP SCI 7210
    Course Foundations of Computer Science A
    Coordinating Unit Computer Science
    Term Trimester 1
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Contact Up to 6 hours per week
    Available for Study Abroad and Exchange
    Incompatible COMP SCI 7202, COMP SCI 7208, COMP SCI 7103
    Assessment Assignments
    Course Staff

    Course Coordinator: Dr Weitong Chen

    Course Timetable

    The full timetable of all activities for this course can be accessed from .

  • Learning Outcomes
    Course Learning Outcomes
    Upon completion of this course/subject, students will be able to:

    1 Interpret and decompose problems in computational domains.
    2 Justify and demonstrate an understanding of programming fundamentals.
    3 Apply programming fundamental knowledge to practical problems.
    4 Use the Python programming language to construct programs to solve real-world problems.
    5 Independently find and interpret discipline-related documentation.
    6 Explain the benefits of object-oriented design and understand when it is an appropriate methodology to use.
    7 Design object-oriented solutions for small systems involving multiple objects.
    8 Translate real-world data to computer representation using different data structures.
    University Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    University Graduate Attribute Course Learning Outcome(s)

    Attribute 1: Deep discipline knowledge and intellectual breadth

    Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.

    		 .

    Attribute 2: Creative and critical thinking, and problem solving

    Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.

    		 1-5

    Attribute 3: Teamwork and communication skills

    Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.

    		 6

    Attribute 4: Professionalism and leadership readiness

    Graduates engage in professional behaviour and have the potential to be entrepreneurial and take leadership roles in their chosen occupations or careers and communities.

    		 .

    Attribute 5: Intercultural and ethical competency

    Graduates are responsible and effective global citizens whose personal values and practices are consistent with their roles as responsible members of society.

    		 .

    Attribute 6: Australian Aboriginal and Torres Strait Islander cultural competency

    Graduates have an understanding of, and respect for, Australian Aboriginal and Torres Strait Islander values, culture and knowledge.

    		 .

    Attribute 7: Digital capabilities

    Graduates are well prepared for living, learning and working in a digital society.

    		 .

    Attribute 8: Self-awareness and emotional intelligence

    Graduates are self-aware and reflective; they are flexible and resilient and have the capacity to accept and give constructive feedback; they act with integrity and take responsibility for their actions.

    		 .
  • Learning Resources
    Recommended Resources
    Zhang, Y., (2015), An Introduction to Python and Computer Programming,(1st ed. Lecture Notes in Engineering 353), Springer, London.

    Lee, K., & Mackie, I., (2014), Python Programming Fundamentals (2nd ed. Undergraduate Topics in Computer Science), Springer, London.

    Matthes, Eric. Python crash course: a hands-on, project-based introduction to programming.

    Phillips, D. (2015). Python 3 object-oriented programming. Packt Publishing Ltd.

    Baka, B. (2017). Python Data Structures and Algorithms. Packt Publishing Ltd.

    Lee, K. D., Lee, K. D., & Steve Hubbard, S. H. (2015). Data Structures and Algorithms with Python. Springer.

    Textbooks are available to students as e-books through the Library.
    Online Learning
    All materials are available from MyUni and it is possible to work through most of the course activities on-site.

  • Learning & Teaching Activities
    Learning & Teaching Modes
    This course is structured around supported active learning labs. Assessment, discussions and support occur face to face. The materials are available online. Attendance at all sessions is not mandatory and can be negotiated with course coordinator during the first week.
    Workload

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
    This course assumes a commitment of 20-25 hours per week over each week.
    Learning Activities Summary
    each week of the weeks, learning activities follow the pattern:

    Introduction
    Lessons, practice (in class or in own time) and text readings
    Face to Face discussion session and Peer sharing
    Further lessons, practice (in class or in own time) and text readings
    Research and Reflection (progress report related to project)
  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    Assessment Task Weighting (%) Individual/ Group Formative/ Summative
    		Due (week)*
    		 Hurdle criteria Learning outcomes CBOK Alignment**
    Programming Practice 0 Individual Formative Weekly 1-6. 1.1 1.2 2.2 2.6 3.1 3.2 3.3 4.1 4.2 4.3
    Module Tests 100 Individual Summative 4, 7, 10 & 13 85% 1-6 1.1 1.2 2.2 2.6 3.1 3.2 3.3 4.1 4.2 4.3
    Total 100
    * The specific due date for each assessment task will be available on MyUni.

    In accordance with the Assessment for Coursework Programs Policy, Procedure 1b: An exemption from the stated hurdle requirements has been granted.

    This course has a hurdle requirement. Meeting the specified hurdle criteria is a requirement for passing the course.

    **CBOK is the Core Body of Knowledge for ICT Professionals defined by the Australian Computer Society. The alignment in the table above corresponds with the following CBOK Areas:

    1. Problem Solving
    1.1 Abstraction
    1.2 Design

    2. Professional Knowledge
    2.1 Ethics
    2.2 Professional expectations
    2.3 Teamwork concepts & issues
    2.4 Interpersonal communications
    2.5 Societal issues
    2.6 Understanding of ICT profession

    3. Technology resources
    3.1 Hardware & Software
    3.2 Data & information
    3.3 Networking

    4. Technology Building
    4.1 Programming
    4.2 Human factors
    4.3 Systems development
    4.4 Systems acquisition

    5.  ICT Management
    5.1 IT governance & organisational
    5.2 IT project management
    5.3 Service management 
    5.4 Security management

    Assessment Related Requirements
    You must complete 4 specific modules as prescribed by your program of study.

    Each module has a hurdle requirement, which is the module test. You need to achieve at least 85% on the module test to pass the module. You will have a limited opportunity to retake module tests that you do not pass in subsequent test weeks but these will be arranged in conjunction with the course coordinator in later testing weeks. If you don’t pass enough of the module tests, you may be required to take any or all of the modules again in a subsequent offering.

    You will be required to demonstrate your ability to apply what you have learnt each week in the creation of programs to solve practice problems to be eligible to sit for the module test.

    Successful completion of an appropriate set of modules will result in a Non-Graded Pass (NGP) in this course.

    Assessment Detail
    There are two types of assessments in this course:

    Weekly Formative Assessments (Practicals and Quizzes):
    Weekly formative assessments encompass practicals and quizzes.

    - Students are required to earn a minimum of 50 points in practicals or quizzes.
    - Students can attempt each question multiple times before the section test, with the highest score recorded.
    - The performance in practicals and quizzes is crucial for determining eligibility to take the section test.

    Summative Section Tests:
    The summative assessment consists of section tests.

    - Students must pass each of the section tests to successfully pass the course.

    Submission

    Submission details and the assignment descriptions will be published on the course website in .

    Session Test

    Formative assessments must be completed prior to session test. Session tests are run under exam conditions and late submission is not accepted. You must be available during the replacement examination period (check University dates). If you are offered a replacement examination or additional assessment and are unable to attend for any reason, there may be no further opportunity for a replacement examination or additional assessment.

    Extensions for Assignments

    If you are unable to complete an assessment by the due date because of medical or compassionate circumstances, you must submit a request to the course coordinator prior to the due date. In your request, you must attach supporting documentation – a medical certificate and/or a letter from the student counselling service. Work requirements are not considered grounds for extensions. If you are working, please make sure you are available for all activities.

    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    GS8 (Coursework Grade Scheme)
    Grade Description
    CN Continuing
    FNS Fail No Submission
    NFE No Formal Examination
    F Fail
    NGP Non Graded Pass
    P Pass
    C Credit
    D Distinction
    HD High Distinction
    RP Result Pending

    Further details of the grades/results can be obtained from Examinations.

    Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

    Final results for this course will be made available through .

  • Student Feedback

    The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

    SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.

  • Student Support
  • Policies & Guidelines

    This section contains links to relevant assessment-related policies and guidelines - all university policies.

  • Fraud Awareness

    Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student鈥檚 disciplinary procedures.

The 成人大片 is committed to regular reviews of the courses and programs it offers to students. The 成人大片 therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.
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