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Course Outlines

COMP SCI 2208 - Databases and Ethical Data

North Terrace Campus - Semester 2 - 2021

Databases have come a long way in the past decades and, rather than focusing purely on relational databases and SQL, this course introduces students to contemporary database applications and concepts, to develop a deep and thorough understanding of the principles that underpin all contemporary database systems. Students will be introduced to relational, NoSQL, and distributed database models, with an emphasis on the design, configuration, and ongoing maintenance of these systems. The course will cover consistency models, the evolution of transactional processing, and existing examples of all of the database types. With all of the data that is stored in systems, there are important questions of whether certain data should be collected, how it should be stored, how it should be processed, and whether answers can be shared from this data. Students will cover relevant ethical studies around the use of data, including the impact of local and international legislation such as the Australian Privacy Act and the European General Data Protection Regulation. This course will be assessed through programming assignments, small projects, lecture quizzes, contributions to group discussions, and written assignments. The majority of assessment is individual but some elements are group based to develop non-technical skills.

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  • General Course Information
    Course Details
    Course Code COMP SCI 2208
    Course Databases and Ethical Data
    Coordinating Unit Computer Science
    Term Semester 2
    Level Undergraduate
    Location/s North Terrace Campus
    Units 3
    Available for Study Abroad and Exchange
    Prerequisites COMP SCI 1015 OR COMP SCI 1102
    Assumed Knowledge COMP SCI 2207
    Course Staff

    Course Coordinator: Associate Professor Nickolas Falkner

    Lecturer: Dr Andrey Kan (Weeks 1-8)
    Course Timetable

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

  • Learning Outcomes
    Course Learning Outcomes
    1. Identify and discuss fundamental concepts of information and database theory
    2. Identify and discuss relational and non-relational database models
    3. Design and implement data models for all database types
    4. Describe and discuss the epistemological conflicts inherent in database design
    5. Interpret the data privacy acts of Australia and Europe
    6. Design and implement physical database designs
    7. Describe the impact of ethics on database design
    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)
    Deep discipline knowledge
    • informed and infused by cutting edge research, scaffolded throughout their program of studies
    • acquired from personal interaction with research active educators, from year 1
    • accredited or validated against national or international standards (for relevant programs)
    		 1-4,6-7
    Critical thinking and problem solving
    • steeped in research methods and rigor
    • based on empirical evidence and the scientific approach to knowledge development
    • demonstrated through appropriate and relevant assessment
    		 3,4,7
    Teamwork and communication skills
    • developed from, with, and via the SGDE
    • honed through assessment and practice throughout the program of studies
    • encouraged and valued in all aspects of learning
    		 1,2,4,5
    Career and leadership readiness
    • technology savvy
    • professional and, where relevant, fully accredited
    • forward thinking and well informed
    • tested and validated by work based experiences
    		 4,5,7
    Intercultural and ethical competency
    • adept at operating in other cultures
    • comfortable with different nationalities and social contexts
    • able to determine and contribute to desirable social outcomes
    • demonstrated by study abroad or with an understanding of indigenous knowledges
    		 4,5,7
    Self-awareness and emotional intelligence
    • a capacity for self-reflection and a willingness to engage in self-appraisal
    • open to objective and constructive feedback from supervisors and peers
    • able to negotiate difficult social situations, defuse conflict and engage positively in purposeful debate
    		 4,7
  • Learning Resources
    Required Resources
    There are no textbooks for this course.
    Recommended Resources
    Students should have access to a programming platform, preferably one that can support Linux/Unix images either natively, or through virtualisation. (Windows users, this is WSL2. Mac users, this is part of your OS)
    Online Learning
    All online learning will take place through the University's MyUni server.
  • Learning & Teaching Activities
    Learning & Teaching Modes
    Lectures will be delivered on-line, pre-recorded and asynchronously. Other activities will be held on campus, with a remote option. While the project work is individual, there is emphasis placed on group work and team support as part of the activities. Students will engage a wide range of skills, technical and non-technical.
    Workload

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

    Students are expected to allocate 10 hours per week for study-related activities, with an additional 30 hours in total for the two project assignments. This is a total of 150 hours for the course.
    Learning Activities Summary
    Students will take part in lectures (pre-recorded with interactive support sessions), and workshop sessions on a weekly basis. The workshop sessions will serve to develop skills and provide an opoortunity work on project and assessment related activities.
    Specific Course Requirements
    Students are expected to be able to code in the Python programming language and to be able to write programs based around object oriented principles. While students may have some familiarity with database systems, no expertise is assumed.
    Small Group Discovery Experience
    There is no small group discovery experience for this course.
  • 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
    The assessment consists of a number of items, most related to coursework and activities within the course itself. There is a small formal examination for this course, organised by the University. The main areas of assessment, and their weight towards the final marks, are:
    1. Practical Programming Exercises (60%)
    2. Workshops (10%)
    3. Quizzes (10%)
    4. Final Examination (20%)
    Assessment Detail
    1. Practical Assignments (60%)
      Practical assignments are split into three groups of two practicals each, with a total of 6 practicals in the semester.
      Simple practicals are worth 5% each, to a total of 10%.
      Developed practicals are worth 10% each, to a total of 20%.
      Advanced practicals are worth 15% each, to a total of 30%.
      There is no practical activity in Week 1.

      1. Workshops (10%)
        Workshops are held every two weeks, where students complete a worksheet before attending and then go through their answers during the workshop. Each workshop contributes 2% (half for worksheet submission, half for participation), to a maximum of 10%.

      2. Quizzes (10%)
        A quiz is held on each week's content material, with each quiz being worth 1% to a maximum of 10%.

      3. Final Exam (20%)
        The final exam will be on all course content covered during the course and will be a one hour examination, with 60 marks, held through the University's central examinations mechanism.
      Submission
      Work will be submitted through the University's MyUni learning management system. Some assignments may also be submitted through the School's Web Submission system. This will be clarified for each assignment.
      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 .

    2. 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.

      There is no previous feedback on this course.
    3. Student Support
    4. Policies & Guidelines

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

    5. 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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