230708 Foundation Studio
Warning: The information on this page is indicative. The subject outline for a
particular session, location and mode of offering is the authoritative source
of all information about the subject for that offering. Required texts, recommended texts and references in particular are likely to change. Students will be provided with a subject outline once they enrol in the subject.
Subject handbook information prior to 2024 is available in the Archives.
Credit points: 6 cp
Subject level:
Postgraduate
Result type: Grade and marksRequisite(s): ((260776 Foundation of Business Analytics AND 260777 Data Processing Using SAS AND 570100 Data Ethics and Regulation AND 12 credit points of completed study in spk(s): CBK91894 12cp Foundation Option (Business Analytics)) OR 220700 Data Driven Decision Making )
There are course requisites for this subject. See access conditions.
Anti-requisite(s): 23708 Studio 1: Foundation AND 23719 Economics Foundations
Description
The Foundational Studio provides an opportunity for students to put the skills learned in their core subjects into practice. The studio focuses on real-world analytics settings, where students identify business problems and solutions. Students are introduced to the theory of markets and learn how to use data for prediction as well as the evaluation of policies and other interventions.
Subject learning objectives (SLOs)
| 1. | Apply analytics in specified contexts |
|---|---|
| 2. | Utilise advanced skills in collaborating with colleagues of diverse technical backgrounds |
| 3. | Convey analytical results effectively to professional audiences |
Contribution to the development of graduate attributes
This subject requires students to work individually and as a team on analyses of big data contained in given case studies. In doing so, students need to apply developing knowledge of data analysis techniques to real-world data in collaborative learning environments. They will also be challenged to develop their communication skills by demonstrating the capability to convey analyses conclusions to professional audiences.
This subject is aligned with the following Graduate Attribute(s):
- Intellectual rigour and innovative problem solving
- Communication and collaboration
- Professional and technical competence
More specifically, this subject contributes to the development of the following program learning objective(s):
- Research, identify and evaluate the assumptions implicit in data and apply analytical techniques to facilitate business decision making (1.1)
- Create innovative business solutions utilising data for a range of business stakeholders (1.2)
- Integrate advanced data analysis techniques with business practices to generate actionable knowledge to inform and facilitate effective decision-making in local and international contexts (4.1)
Teaching and learning strategies
Orientation activities
Preparation for the Session - students are expected to undertake activities prior to the first week. These activities (approximately two hours in duration) include online readings, videos (database searching) and interaction with peers and are important in helping students prepare for the subject’s Assessment Tasks. This also provides students with an opportunity to meet and interact with peers.
Students will learn through independent learning activities, group work, peer review, and participation in collaborative online sessions through the learning management system.
Independent learning activities
Relevant readings, videos and activities will be made available online relevant to the topic of the week. Students are expected to come to the collaborative online sessions prepared. This will enhance the students’ ability to progress successfully throughout the subject and complete assessment items effectively. The online material aims to enhance students’ understanding of the topic or delve deeper into a more specific area. Information and links to all these learning activities can be accessed via Canvas as well as the subject outline.
Online collaborative sessions
The online collaborative sessions will provide opportunities for group activities and discussion, self-assessment, peer review and formative feedback from the subject facilitator. Online collaborative sessions will be conducted at a time that enables the majority of students to contribute.
Feedback
Feedback will be frequent and takes several forms including self-assessment and peer review. Formative feedback throughout the subject aims to increase student performance at summative assessments.
Content (topics)
- Collecting and analysing industry and firm data
- Consumer demand
- Firm behaviour
- Market structure and firm conduct
- Market equilibrium and government policy
- Trend analysis
- Introduction to causal evaluation
Assessment
Assessment task 1: Case analysis (Individual)
| Objective(s): | This addresses subject learning objective(s): 1 and 3 |
|---|---|
| Weight: | 30% |
| Length: | The Report should be no more than 2,000 words. |
| Criteria: |
|
Assessment task 2: Business Analytics Simulation (Individual)
| Objective(s): | This addresses subject learning objective(s): 2 and 3 |
|---|---|
| Weight: | 30% |
| Length: | Less than 12 pages including any figures, tables and references. |
| Criteria: |
|
Assessment task 3: Business Analytics Project (Individual)
| Objective(s): | This addresses subject learning objective(s): 3 |
|---|---|
| Weight: | 40% |
| Length: | The Report should be no more than 3,000 words. |
| Criteria: |
|
Minimum requirements
Students must achieve at least 50% of the subject’s total marks.
Required texts
There is no required textbook. Resources will be made available through the learning management system as required.