For some children, arithmetic is no problem at all. They work quickly, make few mistakes and are often classified as ‘strong calculators’. However, according to a recent study published in Learning and Individual Differences by Emilie J. Prast, Marian Hickendorff and Eva Van de Weijer-Bergsma, this group is less homogeneous than you might think.

The researchers analysed the results of 625 Dutch pupils from groups 3 to 6  who belonged to the 20% best-performing mathematicians. Their analysis showed that there were apparent differences within this group in terms of cognitive and motivation. Some pupils had high intelligence and a strong working memory, while others, despite average cognitive ability, still belonged to the better mathematicians. In addition, there were major differences in motivation: some children found math very interesting, while others scored well but showed little enthusiasm. The level of self-confidence and math anxiety also appeared not to be the same for everyone.

These findings suggest that a one-size-fits-all approach for ‘fast mathematicians’ is not necessarily optimal for all students. Differentiation remains important, but not every strong mathematician may benefit from the same enrichment programs. A student with high self-confidence but little interest in mathematicians may need a different approach than a child who feels insecure but is curious. Also, mathematician skills such as automation may be less well developed in some strong mathematicians, while others have no difficulty with them.

This study highlights the value of looking beyond math performance. There are different profiles within the group of high-achieving mathematicians, which may mean they also have different educational needs. Although further studies are needed to better understand these differences, the results offer an interesting perspective for schools that want to further refine their education for strong mathematicians.

Abstract of the study :

Although high-achieving students in mathematics are often regarded as a homogeneous group, there may be differences within this group. This study used a person-centered approach to investigate quantitative and qualitative differences between 625 high-achieving students (top 20 %) of Grades 3–6 in the Netherlands. Latent profile analyzes were conducted based on a range of cognitive (nonverbal intelligence, verbal working memory and visual-spatial working memory), motivational (interest, perceived competence, and anxiety), and mathematics achievement (general mathematics achievement and arithmetic fluency) measures. Per grade, two to four latent profiles emerged (eg, in Grade 3: ‘relatively low on all variables’, ‘relatively uninterested very high achievers’ and ‘motivated’). While the variation on all variables was substantial, motivational variables contributed most to the distinction between the profiles. This heterogeneity among high-achievers implies that high-achieving students may have diverse educational needs to flourish and reach their full mathematical potential.