The ability to link new pieces of information together and the capacity to solve entirely new problems reinforce each other as children grow. Researchers tracking elementary school students over three years found that improvements in learning associations predicted later gains in reasoning, and vice versa. These results, published in the journal Intelligence, show that these two foundational cognitive abilities develop in tandem rather than strictly operating in isolation.
Associative learning is the mental process of forming connections between different pieces of information. Remembering a person’s name by linking it to their face or matching a vocabulary word to its basic definition relies on this process. Experiencing these connections allows people to organize scattered pieces of input into useful, structured knowledge. In a classroom, associative learning forms the bedrock of basic memorization, sequence recognition, and early concept formation.
Fluid intelligence involves a decidedly different set of mental tools. It describes a person’s ability to think abstractly, adapt to unfamiliar situations, and solve novel problems. Instead of relying heavily on prior knowledge or memorized facts from a textbook, fluid intelligence requires the brain to analyze new patterns in real time. Both mental processes mature heavily during late childhood, setting the stage for lifelong academic achievement.
Prior psychological theories debated how exactly these two attributes interact over a child’s lifespan. Some early models proposed that fluid intelligence acts as an innate baseline tool that individuals apply to learn new associations. In this view, a naturally high reasoning ability allows a student to detect patterns and gather knowledge at an accelerated pace. These theorists argued that fluid intelligence serves as the main investment engine driving educational success.
Other theorists suggested the exact opposite direction of growth. They proposed that the ongoing process of learning combinations and patterns slowly builds overall problem-solving power. Under this framework, children who engage in active, effortful learning experiences gradually assemble the flexible thinking capacities necessary for high-level reasoning. By continually practicing new associations, a child stretches their cognitive flexibility over time until abstract problem-solving feels more natural.
Recent developmental frameworks view the brain as a highly active, interconnected network. Under these mutualism models, distinct cognitive abilities like memory and reasoning do not develop in isolation. They are thought to mutually reinforce one another over the years, meaning a breakthrough in learning efficiency might trigger subsequent improvements in analyzing complex patterns.
To test these developmental models in real time, Xuezhu Ren, an education researcher at Huazhong University of Science and Technology in Wuhan, China, and a team of colleagues conducted a multi-year tracking study among elementary school children. The researchers wanted to see if superior performance in associative learning actively predicted later gains in reasoning ability. They also wanted to measure whether early reasoning ability predicted later associative learning gains.
The study followed 160 fourth-grade students in China. Teams evaluated the children at three distinct time points, with each testing session spaced exactly twelve months apart. The scientists tracked the students from the fourth grade through the sixth grade to capture a critical period of cognitive development.
To measure associative learning, the researchers used a computer-based trial. The team introduced the children to sets of abstract graphics, each of which mapped to a specific letter and a subsequent secondary graphic. After practicing these chains of associations, the children had to locate the exact three-part combination from a lineup of incorrect choices.
To measure fluid intelligence, the investigators administered two standard reasoning tests. One test asked the children to look at progressive geometric patterns that contained a missing puzzle piece. The students had to determine the hidden rules of the pattern and select the correct shape to complete the sequence. The other test presented strings of numbers or letters that followed a specific logical progression, challenging the students to find the single item that broke the rule.
The team also evaluated the students on their working memory and processing speed at the beginning of the study. Working memory acts as a mental notepad, allowing people to hold and manipulate short-term information. Processing speed measures how quickly the brain can perceive and react to simple visual cues. The team wanted to be sure that any relationship between learning and problem-solving was not just a side effect of having a naturally faster or more spacious mental workspace.
For the working memory evaluation, students completed a visual-spatial task where they had to remember the locations of red squares that briefly flashed on a grid. They also completed a direction-based task that required them to inhibit their natural reflexes. To measure processing speed, the children completed a rapid-fire visual task requiring them to determine which side of a grid contained more dots or triangles.
On a general level, the researchers found that students who scored high on associative tasks also tended to score high on the reasoning tasks. A steady positive correlation existed between the two distinct skills across the entire group. To understand how abilities grew within each specific child, the researchers used statistical models that separate broad group trends from individual growth curves.
By tracking each child against their own baseline performance, the team found reciprocal growth effects. When a child performed better than their own expected baseline in associative learning in one year, they tended to show greater than expected gains in fluid intelligence the following year. This pattern suggested that practice with associative links laid the groundwork for better abstract reasoning.
The reverse developmental path was also evident. Children who experienced a spike in fluid intelligence subsequently showed better-than-expected scores on the associative memory tests the next year. The researchers observed no statistical evidence that one direction was overwhelmingly stronger than the other. The two skills appeared to fuel one another equally over the three-year period.
These reciprocal patterns held steady even when the statistical models factored out the students’ baseline working memory and processing speed. The relationship between forming associations and abstract reasoning appears to exist as a dedicated connection, rather than just an artifact of general brain speed. Associative learning involves the formation and stabilization of novel relational structures, which is fundamentally different from the short-term maintenance duties handled by working memory.
The authors suspect that both skills might share underlying mental mechanisms. For example, both tasks require the ability to focus on relevant rules while successfully blocking out distracting information. Higher reasoning skills might also allow children to invent better logical strategies for remembering combinations, rather than just relying on rote repetition.
While the researchers documented a clear reciprocal relationship, they cannot claim strict causality. Because the study relied on observing test scores over time, it is impossible to say with absolute certainty that raising one skill directly causes an increase in the other. In future test settings, scientists might implement controlled experiments to see if specific educational routines meant to boost associative learning actively improve fluid reasoning test scores.
The study featured a relatively small sample size. Evaluating these developmental markers required intensive, one-on-one administration for each child, limiting the broader number of participants. The research also concentrated solely on children in the late elementary school years, leaving younger and older age groups out of the data set.
Tracking students across a wider span of ages might reveal whether these mutual benefits hold steady during earlier childhood or through adolescence. Certain tasks used at the initial testing point also demonstrated lower internal reliability, which might have muted some of the early data patterns. If cognitive skills truly develop in tandem, school curriculums that balance memory-building tasks with problem-solving challenges might foster broader intellectual growth in students.
The study, “More than correlates: Longitudinal evidence of bidirectional effects between associative learning and fluid intelligence in elementary school children,” was authored by Xuezhu Ren, Shaochun Zhao, Xinyu Huang, and Xiaojing Lv.
