Interconnected digital environments have the potential to disclose invaluable insights into the psychosocial attributes, expectations, and needs of users, and to influence future directions, through the collection and analysis of data. In this unit, we explore how to harness this data to inform decisions and the methodologies used in industry. We also deconstruct the notion of data and investigate using data on our own terms. A range of data sources, including metrics that are sometimes overlooked such as accessibility and sustainability metrics form part of our explorations. Learning analytics are a type of web analytics gaining importance for students and academics. We review the implications and the 'actionable insights' from this type of data. 

Students will learn about analytical tools available to professionals, in particular, those that measure the performance of digital environments or products. They will learn how such tools inform research into the behaviour of users, product or service developments and improvements in campaign or project outcomes.

The unit is grounded in the consideration of the complexities in the field including those of trust, privacy, and information injustice.

Unit details

Location:
Remote
Study level:
Postgraduate
Credit points:
12
Unit code:
ADM5004

Learning Outcomes

On successful completion of this unit, students will be able to:
  1. Formulate responsible, well-informed and ethical judgments in considering the role of the practitioner in a complex and highly dynamic digital media industry;  
  2. Exhibit the ability for agile thinking in complex environments;  
  3. Critically evaluate the strengths and limitations of industry standards as they apply to gathering information from digital environments; and  
  4. Propose and resolve a professional web and social network analysis tasks.  

Assessment

Assessment type Description Grade
Case Study A case study of data 15%
Presentation A series of strategies based on social network data and analysis 40%
Report A research report based on web data and analysis 45%

Where to next?

As part of a course

This unit is studied as part of the following courses. Refer to the course page for information on how to apply for the course.

VU takes care to ensure the accuracy of this unit information, but reserves the right to change or withdraw courses offered at any time. Please check that unit information is current with the Student Contact Centre.