Understanding maths anxiety

While mathematics is often considered a hard subject, not all difficulties with the subject result from cognitive difficulties. Many children and adults experience feelings of anxiety, apprehension, tension or discomfort when confronted by a maths problem. Research conducted by the Centre for Neuroscience in Education at the University of Cambridge examined the maths performance of more than 2,700 primary and secondary pupils in the UK and Italy who were screened for maths anxiety and general anxiety. Researchers then worked one-to-one with the children in order to gain deeper understanding of their cognitive abilities and feelings towards maths using a series of cognitive tasks, questionnaires, and interviews.

Emma Carey and colleagues found that a general feeling that maths was more difficult than other subjects often contributed to feelings of anxiety about the subject, and that teachers and parents may inadvertently play a role. Girls in both primary and secondary school were found to have higher levels of both maths anxiety and general anxiety.

Pupils indicated poor test results, or negative comparisons to peers or siblings, as reasons for feeling anxious. Secondary school pupils also indicated that the transition from primary to secondary school was a cause of maths anxiety, as the work seemed harder and there was greater pressure on tests and increased homework.

The report sets out a series of recommendations, including:

  • Teachers should be aware that maths anxiety can affect pupils’ maths performance.
  • Teachers and parents need to be aware that their own maths anxiety might influence pupils’ math anxiety.
  • Teachers and parents also need to be aware that gendered stereotypes about maths ability might contribute to the gender gap in maths performance.
  • Reducing classroom pressure and using methods like free writing about emotions before a test could help to alleviate maths anxiety.

Source: Understanding mathematics anxiety: Investigating the experiences of UK primary and secondary school students (March 2019), Centre for Neuroscience in Education, University of Cambridge

Can AI better predict why children struggle at school?

Researchers from the Medical Research Council (MRC) Cognition and Brain Sciences Unit at the University of Cambridge have used machine learning – a type of computer algorithm – to identify clusters of learning difficulties which did not match the previous diagnosis children had been given.

The study, published in Developmental Science, used a sample of 530 children (ages 5­–18) who were referred to the Centre for Attention Learning and Memory (CALM) by health and education professionals because they were struggling in school. All the children in the sample completed a number of cognitive and learning assessments, they underwent a structural MRI scan, and their parents completed behaviour questionnaires.

Based on the data collected from these tests, the computer algorithm identified four groups that the children could be matched to: (1) broad cognitive difficulties and severe reading, spelling and maths problems; (2) age-typical cognitive abilities and learning profiles; (3) difficulties with working memory skills; and (4) difficulties with processing sounds in words.

While these groups aligned closely with other data on the children, such as the parents’ reports of their communication difficulties and educational data on reading and maths, there was no correspondence with their previous diagnoses. To check if these groupings corresponded to biological differences, the groups were checked against MRI brain scans from 184 of the children. The groupings mirrored patterns in connectivity within parts of the children’s brains, suggesting that the machine learning was identifying differences that partly reflect underlying biology.

The researchers conclude that these findings reinforce the need for children to receive detailed assessments of their cognitive skills to identify the best type of support.

Source: Remapping the cognitive and neural profiles of children who struggle at school (September 2018), Developmental Science