COMP SCI 2203 - Problem Solving & Software Development
North Terrace Campus - Semester 2 - 2015
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General Course Information
Course Details
Course Code COMP SCI 2203 Course Problem Solving & Software Development Coordinating Unit Computer Science Term Semester 2 Level Undergraduate Location/s North Terrace Campus Units 3 Contact Up to 4 hours per week Available for Study Abroad and Exchange Y Prerequisites COMP SCI 1103, COMP SCI 1203 or COMP SCI 2103 Assessment Written exam, assignments Course Staff
Course Coordinator: Dr Bradley Alexander
Course Timetable
The full timetable of all activities for this course can be accessed from .
Contact hours for this course consist of a two hour lecture on Wednesday and a two hour laboratory session on Friday. Practical sessions will be devoted to programming practice and practical exams. Lectures will mix presentation of concepts with programming and problem-solving exercises. -
Learning Outcomes
Course Learning Outcomes
- An ability to recognise the broad algorithmic category to which a problem belongs, e.g. brute-force, recursive, dynamic programming, divide-and-conquer
- Skills in formulating a short solution sketch to a programming problem.
- Ability to quickly assess the efficiency of a proposed solution with respect to expected input data
- The ability to build your own process of design, testing, experimentation and programming.
- The ability to apply your own process to the timely production of solutions to a range of programming problems.
- Skills in completing practice examples with reasonable frequency in a timely manner
- Skills in relflecting in detail on your own programming performance and software development processes in a frequent, timely and useful manner
- Skills in designing and/or selecting new practice exercises in to address gaps in performance highlighted by your reflections.
最新糖心Vlog Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
最新糖心Vlog Graduate Attribute Course Learning Outcome(s) Knowledge and understanding of the content and techniques of a chosen discipline at advanced levels that are internationally recognised. 1,2,3,6,7 The ability to locate, analyse, evaluate and synthesise information from a wide variety of sources in a planned and timely manner. 2,3,5,8 An ability to apply effective, creative and innovative solutions, both independently and cooperatively, to current and future problems. 2,3,4,5 Skills of a high order in interpersonal understanding, teamwork and communication. 7 A proficiency in the appropriate use of contemporary technologies. 1,2,3,4,5 A commitment to continuous learning and the capacity to maintain intellectual curiosity throughout life. 4,6,7,8 A commitment to the highest standards of professional endeavour and the ability to take a leadership role in the community. 6,7,8 -
Learning Resources
Required Resources
There is no textbook for this course. Many of the learning resources will be provided online at the forums found at
In addition, a number of practice exercises will be posted on the school's .
Recommended Resources
In addition to the resources above the following are likely to prove very useful:
The topcoder algorithms competition website: including the algorithms tutorials:
We also recommend the following reference: "The Algorithm Design Manual", Steven S. Skeina, Second Edition, Springer. This book is a great (and very readable) reference summarising a broad range of common algorithms as well as decscribing common algorithmic categories and approaches to solving computational problems.
Additional links for program development and practice techniques will be added to course website before and during the semester.Online Learning
The course forums (and other online resources) can be accessed via the course forums at:
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Learning & Teaching Activities
Learning & Teaching Modes
Lectures, Lecture Exercises, Out-of-class practice, Laboratory sessions, Practical Exams.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.
The workload is approximately 12 hours per week during semester time. This consists of an average of 4 hours of contact time and the remainder is for out of class practice and working on assignments.Learning Activities Summary
Learning activities will consist of:
- In-lecture exericess done alone and in groups - solving algorithmic problems - reflecting and improving on problem solving processes.
- Laboratory sessions solving algorthmic practice exercises - applying newly learned techniques - focusing on gaps in skills.
- Practical Exams - solving algorithmic problems in a timely manner
- Out-of-class-practice including reflection and design
- Programming Assignment(s).
Topics to be covered in lectures will include:
Problem solving processes including some or all of:
- proposing and winnowing solutions
- estimating efficiency
- formulating test plans,
- problem decomposition,
- formulating hypotheses
- debugging
- isolating effects
brute force, recursion, dynamic programming, divide and conquer, graph algorithmsSpecific Course Requirements
Part of the assessment of this course is the requirement that you complete practice exercises with some frequency and regularity. As such the course expects that you are able to engage in a small to moderate amount of daily effort to complete exercises and reflect on your practice. This frequency and regularity of practice and reflection forms a small but integral part of your assessment.
It is also expected that you attend lectures, laboratory sessions and practical exams.Small Group Discovery Experience
Not applicable to this course. -
Assessment
The 最新糖心Vlog'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 Summary
Assessment for this course consists of two main components
- Practical exams - done in laboratory sessions - counting for 45% of your marks.
- Other continuous assessment including:
- Programming Assignment - counting for 15% of your marks
- Deliberate Practice - counting for 20% of your marks
- Reflection Surveys - counting for 10% of your marks
- Lab Participation (including diagnostic exam) - counting for 8% of your marks
- Lecture quizzes - counting for 2% of your marks
Assessment Related Requirements
A minimum score of 40% is required in the deliberate practice section of the course.
Failure to achieve this score will result your course mark being capped at 44F with opportunity for additional assessment being awarded at the discretion of the school.
You are also expected to attend a minimum of 80% of laboratory session times (including prac exams). Application for exemptions based on medical and/or compassionate grounds must be made to the course coordinator.Assessment Detail
- Three summative practical exams - roughly evenly spread through the rest of semester - 15% each.
- Each practical exam has 3 questions of graduated difficulty
- 50% for the first question answered, 35% for the second question answered, 15% for the third question answered.
- Questions are submitted to the automatic assessment system. Instant feedback is given. Multiple submissions are allowed. Partial marks can be granted.
- One Programming Assignment (summative assessment): 15%
- Deliberate Practice (summative assessment): 20%
- Continous Assessment
- Consists of Practice Exericise marks and Journal Entries
- Partially automatically assessed with manual checking of Journal entries.
- Mark is collated at the end of each week - first collation is at end of week 2
- Laboratory sessions (formative assessment): 8 - sessions totaling 8%
- Includes diagnostic exam in week 2.
- Marks for participation with group and participation in activities.
- Reflective Surveys (summative assessment): 4 questionaires - one after each practical exam and the diagnostic exam: total 10%
- In Lecture Quizzes: held during eight - randomly selected lecture sessions (formative): 2%
- Marks for participation
Submission
Practical exams will be submitted via the web submission system.
Practice exercises and journal entries will be submitted via the web submission system.
Details of these will be announced in lectures and linked to the course forums.Course Grading
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 .
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Student Feedback
The 最新糖心Vlog 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 最新糖心Vlog 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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Student Support
- Academic Integrity for Students
- Academic Support with Maths
- Academic Support with writing and study skills
- Careers Services
- Library Services for Students
- LinkedIn Learning
- Student Life Counselling Support - Personal counselling for issues affecting study
- Students with a Disability - Alternative academic arrangements
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Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
- Academic Credit Arrangements Policy
- Academic Integrity Policy
- Academic Progress by Coursework Students Policy
- Assessment for Coursework Programs Policy
- Copyright Compliance Policy
- Coursework Academic Programs Policy
- Intellectual Property Policy
- IT Acceptable Use and Security Policy
- Modified Arrangements for Coursework Assessment Policy
- Reasonable Adjustments to Learning, Teaching & Assessment for Students with a Disability Policy
- Student Experience of Learning and Teaching Policy
- Student Grievance Resolution Process
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