23708 Studio 1: Foundation

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 2025 is available in the Archives.

UTS: Business: Economics
Credit points: 6 cp

Subject level:

Postgraduate

Result type: Grade and marks

There are course requisites for this subject. See access conditions.
Anti-requisite(s): 230708 Foundation Studio 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)

Upon successful completion of this subject students should be able to:

1.	Apply analytics in specified contexts
2.	Utilise advanced skills in collaborating with individuals 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 contributes to the development of the following graduate attribute(s):

Communication and collaboration
Professional and technical competence

More specifically, this subject contributes to the development of the following program learning objective(s):

Convey information and decisions clearly in written, verbal and visual form to business stakeholders (2.1)
Interact with colleagues and stakeholders to work effectively towards agreed outcomes (2.2)
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

The subject is highly interactive with a key focus on collaborative big data analyses activities. Other teaching methods include lectures, class and group discussions and case study analyses. Students will present their work in different forms in class and coursework assessment and will receive feedback as part of the learning experience.

Preparation outside the class: Students are required to read specified articles and case study material in preparation for each class. These learning materials will be available on the subject webpages on the learning management system.

Feedback: Students will be involved in active learning experiences during class. These experiences will be completed in collaboration with other students and will provide students with the opportunity to obtain in-class peer feedback on their learning as well as feedback from their lecturer.

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 (Group)

Objective(s):	This addresses subject learning objective(s): 2 and 3
Weight:	30%
Criteria:	Appropriate analysis instrument is used Results interpretation is valid Results and interpretation are clearly conveyed

Assessment task 2: Business Analytics Simulation (Individual)

Objective(s):	This addresses subject learning objective(s): 1 and 3
Weight:	30%
Length:	No more than 10 pages including any figures, tables and references.
Criteria:	Visualization techniques are utilised to analyse the trends within the data Relevant economic theory is utilised to inform answers Results are presented clearly and unambiguously to a professional audience

Assessment task 3: Business Analytics Project (Individual)

Objective(s):	This addresses subject learning objective(s): 3
Weight:	40%
Length:	The report should be no longer than 3,000 words.
Criteria:	Analytical methodology is relevant and applied appropriately Findings are clear and coherently presented Logic of conclusion and understanding of the context is sound

Minimum requirements

Students must achieve at least 50% of the subject’s total marks.