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ASSESSMENT BRIEF
Subject Code and Name MIS602 Data Modelling & Database Design
Assessment One – Peer Assessment of File-based Database Design
Individual/Group Individual
Length See below for details
Learning Outcomes B
Submission Thursday 11:59 PM AEST/AEDT of Module 2 (week 4)
Sunday 11:59 PM AEST/AEDT of Module 2 (week 4)
Weighting 25%
Total Marks 25 marks
Context:
The MIS602 Data Modelling & Database Design subject is designed for you to progressively add to
your understanding of data and database management and its relevance with in business context. It
also introduces you to some of the key features of database management system and designing
database systems that will feature in later modules of this topic. In order for you to do well in this
subject, it is imperative that you undertake all of the learning activities in the modules. The learning
activities are presented as a way of scaffolding your learning so that you can attempt the building
blocks of the assessments and be in a safe environment to fail and to learn from them. Therefore,
doing your learning activities and seeking feedback from them from peers and from the learning
facilitator is the single best way of preparing for doing well in this assessment.
Instructions:
There is an imperative requirement in this assessment; you must submit different versions of the
files by Thursday of week 4 at midnight (Sydney time). The files should ideally be of excel format.
The data in the files should be composed based on the following scenario:
Torrens University Australia (TUA) is interested in a new Student record management
system. This system needs a database to manage students enrolled, courses students
enrolled in and staff facilitating the course. You will need to store and manage the data for
the enrolled students, courses and the staff assigned to the courses. The system is intended
to be built in-house. The university has a very strong information systems suite of programs
and the students of that program are showing great insight and promise. It has signalled its
intention to seek input from those students in a consulting arrangement.
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The system should allow the staff to add, update and delete the records of students, staff
allocated to course and courses. In addition, University staff should be able to see the list of
students enrolled in a particular course facilitated by a particular learning facilitator.
Based on this scenario, you should identify key data objects and their attributes and define them as
columns in the spreadsheet. Create multiple versions of the spreadsheet file as per below
instruction:
• Version 1 (V1.0) with all possible database objects and attributes and create 30 rows of data.
• Version 2 (V1.1) of the file should update last 2 records and add 5 additional records
• Version 3 (V1.2) of the file should add 2 new attributes
• Version 4 (V1.3) of the file should remove 5 existing attribute and add 5 more rows of data
When you are finished this, combine the four versions of the Excel database solution with a
document that in more than 1000 words, describing your experience. On the morning following
submission, the learning facilitator will allocate you another student’s spreadsheets and summary
document to assess. It is then your turn to assess another student’s work. You will have three days
to assess the other student’s work and to upload your response to Blackboard.
In no more than 500 words, provide a critique of that student’s work to them. You can choose
whether to identify yourself but you should provide constructive feedback, balancing good points
and points where the student can improve. You should use the scenario and provide feedback to
the other student on their list of data objects, data attributes and summary document. You are free
to use whatever framework you like and the following should be minimum inclusions:
• Comment on the overall suitability of the data objects and attributes as an input for
database design and the summary document
• Provide constructive criticism on how the other student can improve their data objects and
attributes in future
• Provide some useful readings the other student may peruse that helps them develop their
understanding of data and data attributes
Submission Instructions:
Your spreadsheets and summary should be submitted by Thursday at midnight (Sydney time) of
week 4. Do not include any identifying information on your submission (i.e. not your student
number, name or anything else that might identify you). This is important because the peer review
is to be done anonymously. Non-submission or lateness will be treated in accordance with the late
assessment policy of the university.
Please note that late submissions mean that another student will effectively have less time to do
their peer assessment of your work.
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Learning Rubric: Assessment One
Assessment Criteria
Fail
(Unacceptable)
0-49%
Pass
(Functional)
50-64%
Credit
(Proficient)
65-74%
Distinction
(Advanced)
75 -84%
High Distinction
(Exceptional)
85-100%
Understanding of the
Data and Data
attributes
30%
Demonstrates limited
understanding of Data
and Data attributes.
Fair understanding of Data
and Data attributes
demonstrated. May
neglect to provide
resources or that these are
cursorily provided without
reference to specific areas
in the source.
Provides a thoughtful critique
in the context of the scenario
that the peer can use and
genuinely develop from.
Effective
communication
30%
Difficult to understand for
audience, no logical/clear
structure, poor flow of
ideas, argument lacks
supporting evidence.
Audience cannot follow
the line of reasoning.
Information, arguments and
evidence are presented in a
way that is not always clear
and logical. Line of
reasoning is often difficult
to follow.
Information, arguments
and evidence are well
presented, mostly clear
flow of ideas and
arguments. Line of
reasoning is easy to
follow.

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