Anxiety about maths “locks pupils in cycle of despair

Children as young as six feel fear, rage and despair as a result of "mathematics anxiety", a condition which can cause physical symptoms and behaviour problems in class, according to a study.

Pupils in both primary and secondary school can find themselves locked in a cycle of despair, suffering from anxiety that has a negative     1    on their maths performance, which in turn leads to increased anxiety.

Researchers say maths anxiety should be treated as a "real     2    " because of the damage it does to a child's learning. They also point out it may be     3    to a growing maths crisis in the UK, where the level of adult numeracy is relatively low and getting worse.

According to the Nuffield Foundation report, Understanding Mathematics Anxiety, the     4     of adults with functional maths skills equivalent to a GCSE grade C has fallen from 26% in 2003 to 22% in 2011. In contrast, functional literacy skills are steadily increasing, with 57% of working-age adults     5     the equivalent level.

Researchers from the faculty of education and the centre for neuroscience in education at Cambridge University worked with 2,700 primary and secondary students in the UK and Italy – including detailed one-to-one interviews – to explore maths anxiety and its     6    .

The children they interviewed provided graphic descriptions of their fears about maths. "I felt very unwell and I was really scared," said one primary school student, describing his     7     during a lesson about equivalent fractions. "Because my table's in the corner I kind of tried not to be in the lesson."

Researchers found there was a general sense that maths was hard compared with other subjects, which led to a loss of     8    , yet the study points out that most children with high levels of maths anxiety are normal to high     9    in the subject.

Key triggers for anxiety included poor marks, test pressures, teasing by fellow pupils and a confusing     10     of teaching methods.

How do AI chatbots answer my questions

Chatbots might appear to be complex conversationalists that respond like real people. But if you take a closer look, they are     1     an advanced version of a program that finishes your sentences by predicting which words will come next. Bard, ChatGPT, and other AI technologies are large language models—a kind of algorithm (算法) trained on exercises similar to the Mad Libs-style questions found on elementary school quizzes. More simply put, they are human-written     2     that tell computers how to solve a problem or make a calculation. In this case, the algorithm uses your prompt and any sentences it comes across to     3     the answer.

Let’s pretend you plugged this sentence into an AI chatbot: “The cat sat on the ______.” First, the language model would have to know that the missing word needs to be a noun to make     4     sense. But it can’t be any noun—the cat can’t sit on the “democracy,” for one. So the algorithm searches texts written by humans to get a sense of what cats actually rest on and picks out the most probable answer. In this scenario, it might     5     the cat sits on the “laptop” 10 percent of the time, on the “table” 20 percent of the time, and on the “chair” 70 percent of the time. The model would then go with the most     6     answer: “chair.” The system is able to use this prediction process to respond with a full sentence. If you ask a chatbot, “How are you?” it will generate “I’m” based on the “you” from the question and then “good” based on what most people on the web reply when asked how they are.

The way these programs process information and arrive at a decision sort of     7     how the human brain behaves. “    8     as this task—predicting the most probable response—is, it actually requires an incredibly advanced knowledge of both how language works and how the world works,” says Yoon Kim, a researcher at MIT’s Computer Science and Artificial Intelligence Laboratory.

The beauty of language models is that researchers don’t have to     9     define any rules or grammar for them to follow. An AI chatbot learns how to form sentences that make sense by consuming textual elements, which are common sequences of characters     10     together taken from the raw text of books, articles, and websites. All it needs are the patterns and associations it finds among certain words or phrases.