COMP SCI 1015 - Introduction to Applied Programming
North Terrace Campus - Semester 1 - 2024
General Course Information
Course Code COMP SCI 1015 Course Introduction to Applied Programming Coordinating Unit Computer Science Term Semester 1 Level Undergraduate Location/s North Terrace Campus Units 3 Contact Up to 10 hours per week Available for Study Abroad and Exchange N Incompatible COMP SCI 1008, COMP SCI 1101, COMP SCI 1201, COMP SCI 2202, COMP SCI 2202A, ENG 1002, ENG 1003 Restrictions Not suitable for BCompSc, B(Adv)Comp Sc, BMaCompSc, or BEng students Course Description Introduction to Applied Programming is designed for students who are enrolled in the Bachelor of Information Technology. The course introduces the fundamental concepts of procedural and event driven programming, with a focus on approaches to programming relevant for IT, including scripting languages. Students take a practical approach to learning the fundamental topics in programming, including, data types and algorithms, functions, control structures, arrays, GUI, files, as well as the mechanics of running, testing, and debugging.
Course Coordinator: Dr Mohsen DorrakiLecturer, Course Coordinator: Mr. Arie Bennett
The full timetable of all activities for this course can be accessed from Course Planner.
Course Learning OutcomesOn successful completion of this course students will be able to:
1 Design algorithms to solve simple problems 2 Use those algorithms in an interactive programming environment 3 Demonstrate the ability to correct, test and debug programs 4 Explain how algorithms and programs work
The course is designed to develop the following Elements of Competency: 1.1 1.2 1.3 2.1 2.2 2.3 3.2 3.3 3.6
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.
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.
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.
Required ResourcesThere is no required text book for this course. All materials will be provided through the University's Learning Management System, MyUni.
Recommended ResourcesThere is a significant number of outstanding Python resources online that are readily available in the form of textbooks, tutorials, and videos that are available for free. To enhance your comprehension and grasp of challenging concepts, we have curated a collection of the best free resources and provide links to them through MyUni.
Our preferred textbooks for students is "Think Python 2e" authored by Allen B. Downey, which is freely accessible online.
Learning & Teaching Activities
Learning & Teaching ModesThis course has three contact activities: lectures, workshops and practicals. Each of these activities is used to support and build on each other.
Lectures: Weekly delivery of new material and are paired with an associated quiz. Remote options are provided as all lectures are livestreamed and recorded through Echo360.
Workshop sessions: Interactive sessions with your tutor where you will be presented with new material and/or exercises that you will complete and submit in the session. Workshops are designed to give you access to practical problems and work with your tutor available to identify any misconceptions or confusion. The sessions also allow us to check student performance and if we need to empthasize certain ideas more.
Practical sessions: Weekly practical assignments are provided most weeks. Students are expected to attempt these before coming to their practical session. In the session we will check your understanding with a short interview. Tutors are also available for support in this time.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.Students are expected to spend approximately 10 hours per week on this course. A typical week will involve 5-6 contact hours for learning and teaching activities and 4-5 hours of independant study. Independant study includes, reading the required reading, completing assessments, content revision and self-driven programming practise.
Learning Activities SummaryThe topics covered will include:
- Building your first program (Hello World!)
- Variables & inputs
- Conditions & iteration
- Lists & iteration
- Graphical User Interfaces (GUI)
- Working with files
- Dictionaries & tuples
- Immutability, pythonic way
- Code quality & testing
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Assessment Task Task Type Due Weighting Learning Outcome Weekly quizzes Summative
5% 4 Class participation* Summative Weekly 10% 1,2,3,4 Coding exercises Summative Weekly 15% 1,2,3 Assignments Summative Weeks 7,10,13 20% 1,2,3,4 Practical exams** Summative Weeks 4, 8, 12 50% 1,2,3
** The final practical exam is a hurdle assessment.
Assessment DetailWeekly quizzes (5%): There will be weekly quizzes on the MyUni system. These quizzes are designed to give immediate feedback on the content you have learnt during the key concept videos and required reading. These take place early in the week to motivate you to get to grips with the basics before attending the lecture and workshop where these concepts will be expanded.
There are 10 lecture quizzes during the course. You must work individually on all quizzes.
Class participation (10%): This is a fast-paced course, so keeping up-to-date with the materials and having good access to your help is important. As such, we expect active participation from all students. Active participation is defined as:
- completing weekly in-class workshop activities during your enrolled workshop session.
- passing in-person code comprehension interviews during your enrolled practical sessions. These interviews will assess your understanding of your weekly practical assignment submission.
Coding exercises (15%): Smaller practical coding exercises that give you an opportunity to demonstrate your understanding on recent material and get feedback on your progress.
There will be 9 practical assignments during the course, but only your highest scoring 8 will contribute toward your grade. You must work individually on all practicals. You must work individually on all coding exercises.Assignments (20%): You will have 3 individual coding assignments. These are designed to be more challenging assessments as you have 3 weeks to complete them. In these assessments, you will be able to combine your understanding of multiple topics together to form useful programs. You must work individually on all assignments.Practical examinations (50%): During weeks 4, 8, and 12, you have your practical exams. These will take place during your regularly scheduled practical session. You must attend these sessions. Failure to do so will earn you a zero. The final practical exam is a hurdle assessment.
SubmissionStudents will submit their code to Gradescope where it will be marked by their tutor and/or automatically using an auto-grader depending on the assessment (students are taught how to use this system in the course). Quizzes will be automatically marked in MyUni.
Failure to submit an assessment item on time or by the agreed extension deadline will result in penalties. For each day or part-day that a programming assignment is late, the maximum mark that can be awarded is reduced by 25%.
Any request for an extension of time for the submission of an assessment item should be made well before the due date to the Course Coordinator. Normally, extensions will only be granted for a maximum of two weeks from the original assignment submission date. Extensions will only be granted in cases of genuine extenuating circumstances and evidence, such as a medical certificate, must be provided.
Grades for your performance in this course will be awarded in accordance with the following scheme:
M10 (Coursework Mark Scheme) Grade Mark Description FNS Fail No Submission F 1-49 Fail P 50-64 Pass C 65-74 Credit D 75-84 Distinction HD 85-100 High Distinction CN Continuing NFE No Formal Examination 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 Access Adelaide.
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.
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This section contains links to relevant assessment-related policies and guidelines - all university policies.
- Academic Credit Arrangements Policy
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- Student Experience of Learning and Teaching Policy
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