Date: Thursday 23 May, 1.00pm - 2.00pm ACST

Cost: Free

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This webinar will showcase the advanced data analytics work recently undertaken by NCVER to obtain a deeper understanding into how VET students behave and the outcomes they achieve.

Using examples from recently published work, Melinda Lees and Michelle Hall will demonstrate how NCVER use:

  • longitudinal data analysis to explore VET student pathways and outcomes
  • the ABS Person Level Integrated Data Asset (PLIDA) to investigate occupation and employment outcomes for VET students
  • advanced data analytics platforms and techniques to explore VET data with greater efficiency and depth.

The presenters will discuss how NCVER can support decision making through further exploration of both VET data and external data assets to enhance our understanding of the sector.


Melinda Lees, Team Leader, Research & Data Analytics, National Centre for Vocational Education Research (NCVER)

Melinda manages a range of advanced analytics projects designed to deliver insights for stakeholders into the VET sector. Recent examples include overseeing the design and build of a cloud-based analytics platform, the development of a longitudinal student view and the exploration of machine learning for predicting VET completion rates. In her previous role at NCVER, Melinda was responsible for managing the total VET activity and VET in Schools collections and reporting.

Dr. Michelle Hall, Senior Data Analyst, Research & Data Analytics, National Centre for Vocational Education Research (NCVER)

Michelle's work explores training activity trends within the Vocational Education and Training (VET) sector, drawing on quantitative analysis and data science methods. Recent examples include in-depth examination of student-centric training activity trends, analysis of training pathways of foundation skills learners, and exploring experimental approaches to predicting qualifications completion rates.

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