Course Code :  COMM5501

Year :  2023

Term :  Term 3

Teaching Period :  T3

Delivery Mode :  In Person

Delivery Format :  Standard

Delivery Location :  Kensington

General Course Information

Course Code :  COMM5501

Year :  2023

Term :  Term 3

Teaching Period :  T3

Is a multi-term course? :  No

Faculty :  UNSW Business School

Academic Unit :  School of Risk and Actuarial Studies

Delivery Mode :  In Person

Delivery Format :  Standard

Delivery Location :  Kensington

Campus :  Sydney

Study Level :  Postgraduate

Units of Credit :  6

Useful Links

Handbook ClassTimetable

Course Details & Outcomes

Course Description

Data visualisation and communication are critical skills in many professions. The creation of easily digestible visuals allows us to make sense of complex information in an accessible and     easily understandable way. The ability to employ visuals will enhance almost any presentation to better engage our audience, make our messages more memorable, and facilitate more effective  decision-making.

This course will introduce students to communicating effectively using data visualisations, and apply basic design principles to ensure the intended message is conveyed. Students will then

apply these ideas in creating a data story on a topic of their choosing to address a challenge

identifed by the UN SDG’s, with a purpose of effecting positive change in the world. By the end of the course, students will have created an artefact that will showcase both their skills and themselves as a professional.

NOTE: Assumed knowledge - A level of knowledge equivalent to a frst-year undergraduate basic statistics course is assumed. Students without such knowledge are advised to complete an

appropriate self-assessment of university statistics knowledge before the commencement of their frst term and complete a Stats bridging course where appropriate.

Course Aims

This course aims to create a strong foundation in data storytelling for students. Students will receive hands-on experience in creating effective data visualisations with the aim of

communicating complicated issues to diverse audiences, with the intention to bring about

impactful change. This process will also involve students giving peer feedback on each other's work as part of building critical evaluation and refectionskills.

Relationship to Other Courses

The ideas introduced in this course around effective data storytelling will form a strong   foundation for effective, evidence-based communication applicable to many disciplines.

Course Learning Outcomes

Learning and Teaching Technologies

Moodle - Learning Management System

Learning and Teaching in this course

The two main approaches adopted in this course are a “fipped and blended” classroom and "project-based" learning.

The “fipped and blended” approach focuses on assisted self-study, and differs from the

traditional lecture-based approach. The main rationale for this “fipped and blended” structure is twofold. First, it frees up class time which can now be used to do in–class exercises and

learning-by-doing activities, which aim at enhancing students’ long-lasting (deep) learning.

Second, it brings a signifcant portion of the face-to-facetime later in the learning process, when students are more comfortable with the material, and more likely to interact and ask questions.

The "project-based" learning approach allows students to learn by directly working hands-on to create their own Data Story, as opposed working only in a theoretical setting in-class. Students

will spend class time exploring various frameworks for creating a Data Story, then apply these frameworks to their own work. The teaching team take a back seat, providing advice as

necessary. This approach also means that students take agency for their work and learning. By the end of the term will have created a Data Story on a topic of their own choosing and can

publish this as part of their professional portfolio.

Assessments

Assessment Structure

Assessment Details

Weekly Formative tasks

Assessment Overview

Tasks designed to give students feedback on their progress

Detailed Assessment Description

The weekly formative tasks will support students in the creation of their data story. Details will be provided on Moodle.

Assignment submission Turnitin type

This is not a Turnitin assignment

Data Story Content

Assessment Overview

Structured set of activities for students to create content for their data story

Detailed Assessment Description

Students will build a Data Story over the course of the term on a topic that both interests them personally and addresses a contemporary societal challenge. There is a strong scaffold of

support to assist students in this process, including feedback from both peers and the teaching team.

The Data Story Content component sits roughly in the frst half of the term. Students will conduct their research to create the content for their fnal Data Story.

Assignment submission Turnitin type

This is not a Turnitin assignment

Data Story Project

Assessment Overview

Structured set of activities for students to assemble and showcase their content

Detailed Assessment Description

Students will build a Data Story over the course of the term on a topic that both interests them personally and addresses a contemporary societal challenge. There is a strong scaffold of

support to assist students in this process, including feedback from both peers and the teaching team.

The Data Story project sits in the second half of the term. Students will take the content they have researched as part of the "Data Story Content" section and are provided guidance for     assembling this content into an effective data story.

Assignment submission Turnitin type

This is not a Turnitin assignment

Hurdle rules

Students need to complete Deliverable 5 of this task. Details provided on Moodle.

General Assessment Information

Grading Basis

Standard

Requirements to pass course

In order to pass this course students must:

• Achieve a composite mark of at least 50 out of 100

•  Engage actively in course learning activities and attempt all assessment requirements

•  Meet any additional requirements specifed in the assessment details

Attendance Requirements

Students are strongly encouraged to attend all classes and review lecture recordings.

Course Resources

Prescribed Resources

Course website on Moodle

Storytelling with data, A data visualisation guide for business professionals, C. N. Knafic

Statistics, Illowsky and Dean

Course Evaluation and Development

There will be many opportunities for informal feedback collection throughout the term, and also the formal MyExperience survey at the end of the term. As this is the frst time we are offering    this course in its revamped form, we will consider all feedback received in adjusting for future    offerings.

Staff Details

Other Useful Information

Academic Information

COURSE POLICIES AND SUPPORT

The Business School expects that you are familiar with the contents of this course outline and the UNSW and Business School learning expectations, rules, policies and support services as  listed below:

Program Learning Outcomes

Academic Integrity and Plagiarism

Student Responsibilities and Conduct

Special Consideration

Protocol for Viewing Final Exam Scripts

Student Learning Support Services

Further information is provided on the keypoliciesandsupport page.

Students may not circulate or post online any course materials such as handouts, exams, syllabi or similar resources from their courses without the written permission of their instructor.

STUDENT LEARNING OUTCOMES

The Course Learning Outcomes (CLOs) – under the Outcomestab – are  what you should be  able to demonstrate by the end of this course, if you participate fully in learning activities and successfully complete the assessment items.

CLOs also contribute to your achievement of the Program Learning Outcomes (PLOs),which are developed across the duration of a program. PLOs are, in turn, directly linked to UNSWgraduate capabilities. More information on Coursework PLOs is available on the keypoliciesand

support page. For PG Research PLOs, including MPDBS, please refer to the UNSWHDRLearning Outcomes.

Academic Honesty and Plagarism