Cohort Gap Analysis: How to Use Learner Data to Improve Foundation Skills Support

From Individual to Cohort: Why the Distinction Matters

Most RTOs think about LLN assessment at the individual level: this learner has gaps, those learners are ready. But the most valuable insight comes from looking at your learner cohort as a whole.

When you aggregate LLN assessment data across a cohort, patterns emerge that are invisible at the individual level:

• A majority of learners in a specific qualification are below the required level in Numeracy — suggesting the assessment tool, delivery approach, or learner recruitment profile needs attention
• Writing skills are consistently underperforming for mature-age learners enrolled via a particular pathway
• Digital Literacy gaps are concentrated in one delivery location, suggesting a resource or infrastructure issue

These are systems issues. You cannot address them by supporting individual learners. You address them by changing how the program is designed, delivered, or marketed.

What Cohort Gap Analysis Looks Like

A useful cohort gap analysis presents data at two levels: summary and skill-by-skill.

Summary Level

At the summary level, you want to know:

• What percentage of this cohort have at least one identified gap?

  • Low gap rate: individual support plans may be manageable.
  • Moderate gap rate: consider group-level foundation skills support.
  • High gap rate: program delivery, learner entry information, or support resourcing may need review.

• What percentage are ready to commence without support? This is your starting point for planning trainer workload and support resource allocation.

Skill-by-Skill Level

For each of the five ACSF core skills - and for any separate digital literacy measures you track - you want to see:

• The required level for the qualification (from your ACSF mapping)
• The average achieved level across your cohort
• The percentage of learners who are below the required level
• The distribution of scores (are gaps clustered, or spread evenly?)

This data lets you answer targeted questions: Is this a Numeracy cohort problem, or a Reading problem? Is the gap consistent across all learners, or concentrated in a subgroup?

How to Identify Systemic Gaps

The most valuable use of cohort data is identifying systemic patterns. Look for:

Pattern 1: A skill gap that affects a large share of cohorts If many learners assessed for a specific qualification have a Numeracy gap, the issue may be with how the qualification is marketed or who it attracts — not just who needs support. This is a recruitment and program design conversation.

Pattern 2: A skill gap that is consistent across time If you run the same qualification three times per year and always see Writing gaps, the issue is structural. Your LLN support pathway for Writing is either not working or not being followed.

Pattern 3: A gap that is concentrated in a specific delivery location or mode If online learners consistently show higher Digital Literacy gaps than face-to-face learners, this may reflect the self-selection of learners into online study — or it may reflect that online learners are not getting adequate digital literacy orientation.

Pattern 4: A skill gap that predicts completion rates Over time, you can correlate LLN gap severity with learner completion and achievement. If learners with gaps in two or more skills have significantly lower completion rates, your current support provision is insufficient.

Using the ACSF Spiky Profile

One of the most intuitive visualisations for cohort gap analysis is the ACSF spiky profile - a radar chart showing average cohort performance across the five ACSF core skills, with digital literacy tracked separately if you review it.

The "spiky" shape of the chart immediately reveals which skills are strong and which need attention. A cohort that is consistently above the required level for Reading and Oral Communication but below for Numeracy and Digital Literacy shows a very different profile from one that is uniformly below the required level in all skills.

The spiky profile is a useful tool for:

• Board and management reporting (easy to read without LLN expertise)
• Designing targeted support interventions (address the specific spikes)
• Comparing cohorts across time (is the profile improving?)

Building Cohort Gap Analysis into Your Quality Cycle

Cohort gap analysis is most valuable when it is part of a regular quality review cycle — not a one-off exercise. Consider building it into your:

Trainer review process: At the end of each intake, trainers review the cohort gap profile and document any adjustments made to delivery or support.

TAS review: Annually, use cohort gap data to review whether your Training and Assessment Strategy accurately reflects the LLN support needs of your learner cohort.

Management reporting: Present cohort readiness data as a standard quality metric — alongside completion rates, achievement rates, and employer satisfaction scores.

Learner recruitment review: If a particular cohort profile is consistently showing major gaps, review your recruitment messaging, entry requirements, and pre-enrolment information.

From Analysis to Action

The purpose of cohort gap analysis is not to generate data — it is to drive action. Every analysis should end with documented responses:

Document every action taken in response to cohort analysis. This documentation is what transforms gap analysis from a compliance exercise into genuine continuous improvement — and it is exactly what ASQA looks for when reviewing your quality systems.