GEN1000 for students admitted to Year 1 before AY2025/26, Year 2 before AY2026/27, or Year 3 before AY2027/28, except with the permission of the Module Coordinator
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This module introduces various data visualization techniques, from interactive dashboards to immersive infographics, to facilitate smart decision making in an ever-changing world. The module emphasizes digital competence, equipping students with the skills to analyse data critically and select the most appropriate visualization methods for different contexts. By leveraging cutting-edge tools and software, students will explore the aesthetics of design, colour theory, and data storytelling, ensuring their visualizations resonate intellectually. Through participating in in-class demonstration and completing group project, student will emerge as proficient data storytellers, capable of navigating the complex landscape of digital information for making smart decisions. Whether in business, academia, and society, they will harness the power of visualization to make data accessible, impactful, and memorable, contributing to the effective and creative communication of the broader community. Ultimately, the module empowers students to harness technological advancements with data visualization techniques ethically, cultivating their creative and digital mindset in data storytelling.
Upon completion of this module, students should be able to:
1. Foundations of Data Visualization
1.1. Examination of data visualization theories and frameworks
1.2. Historical analysis of visualization methods and their development
1.3. Impact of technological innovations
1.4. Discussion of cognitive principles influencing visual comprehension
2. Visualization Techniques and Tools
2.1. Comparative analysis of various visualization methodologies
2.2. Introduction to technological tools for data representation
2.3. Practical applications: Step-by-step demonstrations of creating visualizations
3. Data Analysis for Effective Visualization
3.1. Techniques for critical data analysis and interpretation
3.2. Identifying the target audience and context for visualizations
3.3. Criteria for selecting optimal visualization methods based on data characteristics
4. Aesthetics and Colour Theory in Visualization
4.1. Principles of design relevant to data visualization
4.2. Scientific understanding of colour theory and its psychological effects
4.3. Strategies for creating aesthetically coherent and informative visual narratives
5. Data Storytelling and Communication
5.1. Principles and concepts of effective data storytelling
5.2. Techniques for constructing compelling narratives using data
5.3. Ethical considerations and values
5.4. Examination of the role of context and emotional engagement in data communication
