Picture two recent graduates starting their first tech jobs. One lands at a large, well-established electronics manufacturer with clear roles and standard procedures. The other joins a scrappy start-up where the business model seems to shift every few weeks. Both will need to learn quickly, adjust on the fly, and figure out problems no one trained them for. But what mental abilities actually help them do that?
A study published in Behavioral Sciences set out to answer that question by looking at Generation Z employees and the specific thinking skills that support what researchers call “learning agility.” The findings suggest that the ability to adapt at work depends more on higher-order thinking, like creativity and problem-solving, than on basic mental efficiency such as memory or attention.
The question behind the research
Learning agility describes how well someone learns from experience and then applies that learning to new and unfamiliar situations. It is closely tied to being open to feedback, willing to experiment, and able to change strategies when conditions are uncertain. Employers increasingly value it, especially in technology-driven jobs where the work keeps changing.
The researchers, led by Dian Palupi Restuputri of the Bandung Institute of Technology in Indonesia along with her colleagues, noticed a gap in what was known. Earlier work often treated cognitive ability as a single broad thing, or studied learning agility mainly through personality traits and behaviors. Few studies had separated different levels of thinking and asked which ones matter most, particularly for young workers who grew up immersed in digital technology.
To do this, the team divided cognitive abilities into two levels. Basic cognitive abilities are the foundational mental processes that help people take in and handle information: reasoning, memory, attention, coordination, and perception. High-level cognitive abilities are the more advanced processes that let people interpret, evaluate, and transform information: creativity, critical thinking, and problem-solving. The question was whether these two levels contribute differently to learning agility, and whether the answer changes depending on the kind of company someone works for.
How the study was built
The researchers recruited 270 full-time employees in Indonesia, all between 20 and 27 years old. Half worked at start-up companies in fields like software development, digital creative industries, and financial technology. The other half worked at established companies in sectors such as consumer electronics, telecommunications, and electrical power. This equal split let the team compare the two work settings directly.
Rather than relying on a single survey for everything, the study measured thinking skills and learning agility in different ways. Basic cognitive abilities were assessed through CogniFit, a digital testing platform with tasks for logical inference, memory, attention, coordination, and perception. Creativity was measured with the Divergent Association Task, which asks people to name words that are as unrelated as possible, a quick test of divergent thinking. Critical thinking was measured using the Watson-Glaser Critical Thinking Appraisal, which evaluates how people analyze arguments and spot assumptions. Problem-solving was measured with a tool called FourSight, which looks at how people approach clarifying, generating ideas, developing, and implementing solutions.
Learning agility itself was captured through a questionnaire covering thirteen behaviors, including adaptability, feedback seeking, mental agility, self-directed learning, and willingness to learn. Using objective tests for the thinking skills and a self-report survey for learning agility helped separate the two, reducing the chance that the results simply reflected people answering questions in a consistent way.
The team then analyzed the data using a statistical method called Partial Least Squares Structural Equation Modeling, which can map relationships among many variables at once. They ran the analysis three times: once on the whole sample, once on just the established-company employees, and once on just the start-up employees.
What the analysis revealed
Across the board, the higher-order thinking skills stood out. In the combined sample, creativity, problem-solving, reasoning, and critical thinking all showed meaningful links to learning agility, while memory, attention, and coordination did not show significant direct connections. Creativity was the strongest predictor of the group.
The authors interpret this pattern as evidence that adaptive learning is driven by the ability to interpret and reshape information rather than by raw mental speed or storage. As they put it, learning agility appears “primarily driven by generative and evaluative cognitive processes rather than by basic cognitive efficiency alone.” In plain terms, being able to come up with new ideas and work through problems mattered more than being quick to memorize or stay focused on a task.
When the researchers compared the two workplaces, a split emerged. Creativity and problem-solving stayed important in both settings. But other skills shifted depending on context. In established companies, critical thinking was strongly linked to learning agility, which the authors connect to environments where employees evaluate technical information and make evidence-based decisions within structured systems. In start-ups, critical thinking dropped out as a significant factor, while perception, the ability to pick up on cues and signals, became important instead.
The researchers suggest this reflects the nature of start-up work. In fast-moving, uncertain environments, employees often need to read ambiguous signals and respond quickly rather than run extended analyses. They describe start-ups as “action-oriented,” where rapid experimentation and iterative learning tend to be prioritized over lengthy deliberation.
The models also explained a good share of the variation in learning agility, with the strongest explanatory power in the established-company group. The team reads this to mean cognitive factors play an especially prominent role in shaping adaptive learning within more structured organizations.
What it might mean for workplaces
The authors point to several possible takeaways for organizations. Since creativity and problem-solving were consistently linked to learning agility, they suggest that training programs encouraging idea generation, collaborative problem-solving, and experimentation could help employees become more adaptable. They also propose that assessing creative thinking and problem-solving during hiring might help identify people well-suited to fast-changing roles.
The context differences hint at a further idea: that development strategies could be matched to the setting. Start-ups might lean into environments that reward experimentation and quick learning cycles, while established firms might emphasize analytical evaluation and systematic problem-solving.
Some important caveats
The study comes with limits the authors are careful to name. All participants were young employees in Indonesia, recruited through a targeted (non-random) sampling method, so the results should not be read as representative of all Gen Z workers or as applying automatically to other countries or industries.
The design was also cross-sectional, meaning it captured a single moment in time. That makes it hard to establish direction. The team framed thinking skills as feeding into learning agility, but they acknowledge the relationship could run both ways, with agile learners developing certain cognitive skills over time through challenging experiences. The findings are best understood as predictive associations rather than proof of cause and effect.
One more nuance: learning agility was self-reported, so the results reflect how people described their own adaptive tendencies, not directly observed behavior. The authors suggest future work could add supervisor ratings, peer evaluations, or longitudinal data to build a fuller picture. Even with these caveats, the study offers evidence that when it comes to adapting at work, the ability to generate ideas and solve problems may carry more weight than a sharp memory or steady attention.
