Acquisition of new arithmetic skills based on prior arithmetic skills: A cross-sectional study in primary school from grade 2 to grade 5

BACKGROUND

In several countries, children's math skills have been declining at an alarming rate in recent years and decades, and one of the explanations for this alarming situation is that children have difficulties in establishing the relations between arithmetical operations.

AIM

In order to address this question, our goal was to determine the predictive power of previously taught operations on newly taught ones above general cognitive skills and basic numerical skills.

SAMPLES

More than one hundred children in each school level from Grades 2 to 5 from various socio-cultural environments (N = 435, 229 girls) were tested.

METHODS

Children were assessed on their abilities to solve the four basic arithmetic operations. They were also tested on their general cognitive abilities, including working memory, executive functions (i.e., inhibition and flexibility), visual attention and language. Finally, their basic numerical skills were measured through a matching task between symbolic and nonsymbolic numerosity representations. Additions and subtractions were presented to children from Grade 2, multiplications from Grade 3 and divisions from Grade 4.

RESULTS AND CONCLUSIONS

We show that addition predicts subtraction and multiplication performance in all grades. Moreover, multiplication predicts division performance in both Grades 4 and 5. Finally, addition predicts division in Grade 4 but not in Grade 5 and subtraction and division are not related whatever the school grade. These results are examined considering the existing literature, and their implications in terms of instruction are discussed.

An Approach to Model Children’s Inhibition During Early Literacy and Numeracy Acquisition

Early literacy and numeracy skills are developed during childhood at kindergarten level. Among the many factors that influence the development of such skills, the literature shows that the executive function of inhibition – i.e. the blocking out or tuning out of information or action that is irrelevant to the learning task – is one of the most important. There are many tests to assess children’s inhibition skills; however, such tests are generally time-consuming and have a short lifespan. In this context, we propose a computational approach to model children’s inhibition skills by using only student traces from a learning app as input. We propose a mathematical formalization of three related inhibition features, which could be used as input to classification algorithms.