Assessment 2 Problem Solving (Data Visualisation Project Progress Report & Individual Reflective Journal)
This document provides all information about the assessment requirements, including detailed instructions, resources, and the Criterion Reference Assessment (CRA) Rubric used for grading.
Task Overview Assessed Course Learning Outcomes (CLOs): CLO2: Assess and adapt contemporary and innovative data visualisation approaches to gain insight and value that support effective data-driven decision-making.
CLO3: Appraise and present complex and big data in visual form that is readily understandable by specialist and non-specialist audiences using data visualisation methods, tools, and techniques.
CLO4: Interact and collaborate effectively in teams to design and implement a data visualisation project.
Task Rationale Assessment 2: Problem Solving (Project Report & Individual Journal) involves:
Reporting the progress of the team in completing a data visualisation project.
Maintaining an individual reflective journal documenting the effectiveness of interaction and collaboration of team members.
Purpose: Completing this assessment enables students to develop as well-informed individuals who are:
Critical and creative thinkers
Effective communicators and collaborators
Employable and enterprising professionals in their chosen discipline
Task Instructions Task 1: Big Data Visualisation & Challenges (20 Marks, 1000 Words, CLO2 & CLO3) Task 1.1 (10 Marks, 500 Words): Explain, with an example from your data visualisation project, how visualisation concepts help identify trends and patterns in your dataset to support organisational decision-making.
Task 1.2 (10 Marks, 500 Words): Discuss challenges organisations face in undertaking a big data visualisation initiative. Highlight strategies to address data privacy and security for sensitive data in your dataset.
Task 2 – Big Data Visualisation Key Principles, Approaches & Data Modelling (20 Marks, 900 Words, CLO2) Discuss key principles and approaches your team will use to design the Big Data Visualisation project.
Emphasise the importance of data modelling in designing an effective dashboard, providing an example from your project.
Task 3: Big Data Visualisation Project Power BI (30 Marks, 500 Words, CLO4) Task 3.1 (10 Marks, 250 Words): Provide a data dictionary (Variable, Data Type, Description) for the dataset used. Include Table 3.1 captioned as “Data Dictionary (File Name)” and explain the purpose of each variable.
Task 3.2 (20 Marks, 250 Words): Describe your planned Power BI dashboard including four preliminary views. Include screenshots and submit the packaged Power BI workbook (.pbix).
Task 4 – Individual Reflective Journal, Peer Review & Active MS Teams Participation Each team member must maintain a journal listing activities, dates, duration, type of activity, and how participation contributed to completing Assessment 2.
Evidence must reflect individual participation and MS Teams discussions.
Collaborative team contribution is mandatory; marks may be reduced for inactivity.
Report Structure Cover Page
Title & Table of Contents
Body of Report with relevant Task headings and sub-headings:
Task 1
Task 2
Task 3
Task 4
References
Appendices
Presentation Guidelines:
Font: 12 pt Times New Roman
Line spacing: 1.5
Tables & Figures with captions
Clear, concise writing targeting middle to senior management
Free from spelling & grammatical errors
Referencing: Harvard AGPS style (in-text citations & full reference list)
Note: Reference list and Appendices are not included in the word count.
Task Snapshot Length: 2800 Words (+/- 10%) excluding references & appendices
Weighting: 35%
Marks: 100
Acceptable AI Use Level Level 1 – AI Assisted Structure Checking: AI tools may be used for grammar, coherence, and flow checks.
Prohibited: Using AI to generate new content.
Requirement:
Indicate AI tools used at the start of the assessment.
Include prompts used.
Save pre- and post-AI draft copies for verification.
Academic Integrity Students must follow UniSQ Academic Integrity policies.
Original work is required; collaboration outside your group is only allowed for clarification.
Prohibited: Copying from other students, tutors, or AI tools to produce content.
Assessment Marking Refer to the Assessment 2 CRA Rubric for detailed grading criteria.
Submission Instructions Team Leader: Submit:
Report (.docx) for Tasks 1, 2, 3
Power BI workbook (.pbix) with four preliminary views
Individual Team Members: Submit Assessment 2 Journal.xlsx
File Naming Convention:
Turnitin Automatic plagiarism checking upon submission.
Originality report indicates text matches in the Turnitin database; all matches must be reviewed.
Editing is not possible after submission.
Moderation All assessing staff discuss and compare judgements before final marks are released.
Assessment Policies & Procedures Information on extensions, late submissions, academic integrity, and marking is available on the USQ StudyDesk Assessment page.
Extensions are granted only under compassionate or compelling circumstances according to USQ procedures.
