The 3 types of learners in Singapore – and how they affect workplace productivity

WHEN workforce capability – the ability of an organisation to achieve its aims by harnessing its employees’ skills – falls short, firms can respond through the 4Bs: build, buy, borrow or bot.

In other words, they can train existing workers, hire new talent, tap external expertise or automate parts of work. The most common response for many organisations is to invest more in training, send staff for courses, expand the learning calendar and upskill the workforce.

It is a logical response – and, increasingly, an incomplete one.

Singapore has spent years building one of the world’s most deliberate and accessible skills ecosystems. Workers today have more opportunities than ever to upgrade themselves through formal courses, digital learning and workplace training.

Yet, many organisations still struggle with a persistent question: Why does sustained investment in training not always translate into workplace performance?

The answer may lie less in the training itself, and more in what workers return to after training.

Recent findings from the Institute for Adult Learning’s Skills and Learning Survey 2 (SLS2) help explain this gap by showing that training participation is only one part of the story. What matters is whether workers have the motivation and drive for skills mastery, and whether work and management practices support them in converting learning into practice.

Deep, nonchalant and defeated learners

SLS2 identified three broad learner profiles within Singapore’s workforce, by examining how motivation to learn, drive for skills mastery, and work and management practices come together.

The profiles suggest that while workers bring different levels of motivation to learning, workplace conditions play an important role in reinforcing motivation, supporting skills application and enabling mastery.

Where these conditions are weaker, training may still take place, but workers may find it harder to translate learning into better performance.

The first profile refers to “deep learners”. These individuals adopt a deep learning approach that involves an active, reflective and mastery-oriented way of learning, where workers do more than attend training. They connect ideas, reflect on what they learn, and apply knowledge across different work contexts.

Deep learners, who make up 29 per cent of workers, are not just intrinsically motivated to learn. They also have a strong drive for skills mastery and are more likely to work in environments that support the application of learning. Unsurprisingly, they report the strongest levels of training transfer into work.

The second group, “nonchalant learners”, accounts for 30 per cent of workers. They are not disengaged from learning. In fact, they participate in training at broadly similar rates as deep learners.

However, their learning orientation is less active. They tend to show lower internal motivation and only moderate drive for skills mastery. While they participate in training at similar rates as deep learners, their workplaces may provide fewer opportunities to apply skills or build mastery through work.

Meanwhile, “defeated learners” – who make up 41 per cent of the workforce – often show weaker motivation to learn and a lower drive for skills mastery. They are also more likely to work in conditions with limited autonomy, low task variety, and few opportunities to exercise judgment or apply new skills.

Over time, such conditions can further weaken motivation, confidence and the perceived value of learning itself, making it harder for a deep learning approach to take root.

The implications for organisations are significant. Two employees may attend the same course, yet produce vastly different outcomes afterwards – not because of the course itself, but because workers differ in motivation, drive for skills mastery, and the work and management practices to which they return.

Execution versus utilisation

The learner profiles point to a broader lesson: training transfer is not based on the individual worker alone. Whether training translates into performance also depends on how work is structured, and whether new skills can be used, refined, recognised and sustained.

Work design therefore becomes the bridge between training participation and workplace performance.

Many organisations still prioritise execution efficiency over skills utilisation. Employees often return from training to routine workflows and tightly controlled structures, with little room for experimentation or applying new ideas.

This challenge becomes even more important in an artificial intelligence-driven economy, where human value will increasingly lie in judgment, problem-solving, collaboration and applying knowledge creatively across contexts.

For employers, this means workforce transformation cannot focus only on sending employees for more training. It may require organisations to rethink how work itself is organised.

First, organisations need to redesign work so that employees have opportunities to use what they have learnt. This means giving workers greater autonomy, task variety and problem-solving opportunities, allowing them to exercise judgment and contribute beyond narrow job scopes.

Second, organisations need to enable managers to support training transfer by creating more room for experimentation, encouraging reflection, providing feedback and stretching workers’ development. When managers focus solely on immediate execution, learning can remain separate from work.

Third, organisations need to recognise mastery by making skills utilisation visible in job roles, responsibilities and career pathways. Workers increasingly seek lateral growth opportunities across functions and projects, not just upward promotion.

Organisations that support such “career lattices” may ultimately be better positioned to retain talent and sustain workforce adaptability over time.

In short, employers need to move from a training-first mindset to a learning-transfer mindset. The key question is not only “Have employees gone for training?”, but “Does the workplace help them use, deepen and sustain what they have learnt?”

Learning as a workplace value

This is not just a learning and development issue in the human resource department, but also, increasingly, a business performance issue.

Workers in low-activation environments report lower organisational commitment, weaker career confidence and higher job insecurity, affecting retention and innovation over time.

For businesses investing heavily in workforce development, this creates a hidden productivity challenge: organisations may be funding learning that the workplace itself is unable to absorb.

Singapore has made significant progress in building a culture of learning. The next challenge is ensuring that learning consistently translates into action, contribution and performance at work.

In the AI economy, competitive advantage may depend less on training volume, and more on whether organisations design work in ways that allow people to think, apply, experiment and grow.

Ultimately, the value of learning lies not in course participation alone, but in whether workplaces enable workers to apply, deepen and sustain what they have learnt.

The writer is a principal researcher at the Institute for Adult Learning