Projects
Train 100 Data Analysts
The Train-100 Data Analysts pilot uses innovative methods to educate people in digital skills with the aim of discovering more accessible and inclusive digital skills pathways to create a more diversified talent pool with employer-required skills.
Train-100 Pilot structure
DSO contracted three types of training providers:
- TAFE QLD – Public Registered Training Provider
- Goanna Education – Private Registered Training Provider
- General Assembly – Unregistered Training Provider
Each training provider developed a new training product or updated an existing one to align with a skills-based approach to training. View the summary of offering from each provider here.
Four distinct learner cohorts were included:
- New entrants
- Mature-aged learners
- Aboriginal and Torres Strait Islander learners
- People seeking specialist data analyst skills who were already tertiary-qualified.
The process followed:
Two different approaches for screening and preparing the applicants into this program were tested, Aptitude testing and Foundation digital skills training.
Each of the three training providers gave instruction to the four distinct learner cohorts utilising a variety of teaching approaches. This training was unaccredited and the funding model included incentives tied to training completion and employment outcomes.
Watch more about about the pilot at DSO Q1 Livestream Showcase Recording which features our CEO, Patrick Kidd in conversation with:
- Sally Browner – Goanna, ICT Indigenous training provider
- Ryan Meyer – General Assembly, online training provider
- Jackie French – Tafe Queensland
Significant Findings
- Three of the four learning cohorts reached a 92% completion rate.
- 57% of participants have secured employment relating to a data analytics role. Some of the participants were already employed and were not actively looking for a new role, however they have successfully expanded their digital skills.
Training experiences:
- Two of the three training providers used aptitude testing to screen enrolments to ensure suitability to data analyst work. One training provider had students complete three related micro-credentials prior to enrolling in the course.
- All training providers used a variation of blended learning, but with varying levels of teacher support and interaction, synchronous and asynchronous delivery, pace, intensity, and duration.
- The capstone assessments created by training providers were highly aligned with employer-driven digital skills standards for data analysts.
Employer needs and engagement:
- One training provider worked with fewer employers but those employers had a significant impact on various stages of training development and delivery. The other training providers had employers being involved in every stage of the programme from start to finish.
- Some employers liked the unaccredited offering as it allowed for greater flexibility in aligning the training content to their specific needs. However some employers contradicted this, saying a junior data analyst role requires an accredited qualification and an employment offer would not be made following completion of a short, unaccredited training program.
Project costs and financial incentives
- Funding and incentives assisted with the completion of courses.
Next Steps
Longitudinal Study: Phase 2
Phase two will follow several participants in employment for 3 – 6 months, exploring the learner and employer journey to assess the progression of skill acquisition within the workplace.
Qualification Trial
The Train-100 Data Analyst pilot will assist in establishing a well-matched skills-based data analyst qualification for Australia’s modern digital economy.
Centralised knowledge
Investigate ways to centralise knowledge, expertise and training support together in one easy to access place to help the uplift capability across training providers.
No student assigned.