Notice: Function _load_textdomain_just_in_time was called incorrectly. Translation loading for the astra domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /home/studyfoxx/public_html/proactivetraining.com.au/news/wp-includes/functions.php on line 6131
Exploring the VET sector’s market segments – Proactive Training
Deprecated: Function WP_Dependencies->add_data() was called with an argument that is deprecated since version 6.9.0! IE conditional comments are ignored by all supported browsers. in /home/studyfoxx/public_html/proactivetraining.com.au/news/wp-includes/functions.php on line 6131

Exploring the VET sector’s market segments

This recent paper from NCVER authored by Bryan Palmer looks at “how vocational education and training (VET) students cluster and segment in the Australian VET market.”

VET is a large and complex sector, how should its complexity and that of its market be comprehended and mapped? This is what this paper has sought to address. It’s very much a technical paper but may be of interest to some readers.

Using a couple of clustering algorithms, a number of segments within the Australian VET market were identified. These include targeted English programs/students, overseas students (studying in Australia), younger students (including VET in Schools programs), migrants, social inclusion programs/students, jurisdictional priorities, program enrolments not elsewhere identified (NEI) and subject only enrolments NEI. The characteristics of each of these is described in greater detail in the paper using a series of interesting word clouds and listings of ‘top features.’

It then takes a closer look at 3 of the segments: (1) migrants — people born overseas, (2) social inclusion — people with limited prior education and/or other markers of potential disadvantage and (3) targeted English — people undertaking specific English education programs.

However, as the paper notes:

“While clustering algorithms can carve a dataset into clusters, identifying something that is meaningful to practitioners in a way that explains the clusters is not always guaranteed. Sometimes it can be challenging to bring a useful human perspective or narrative to the clustered outputs.”

In addition:

“The algorithms applied assumed single cluster membership to the exclusion of all others. This is an analytically useful (but unrealistic) simplification. In real life, the identified market segments are not mutually exclusive, and students may belong to more than one segment.”

So, as the paper’s author Bryan Palmer speculates, it’s hard to determine “whether the identified clusters align with, or bring insights to, the other typologies for segmenting the Australian VET market.”

Exploring the VET sector’s market segments | VDC