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This paper presents a proposal for a new area of investigation that connects the metacognition literature, and especially the recently developed meta-reasoning framework, with research into mathematical reasoning, mathematics learning, and mathematics anxiety. Whereas the literature on mathematics anxiety focusses on the end result of learning and problem-solving, the metacognitive approach can offer further insight by a fine-grained analysis of the stages of these processes. In particular, it provides tools for exposing students' initial assessment of tasks and test situations, the targets they set for themselves, the process of monitoring progress, and decisions to stick with or abandon a particular solution. The paper outlines various ways in which the metacognitive approach could be used to investigate the effects of mathematics anxiety on mathematics learning and problem solving. This approach could help in answering questions like: Do anxious and non-anxious learners differ in how they prepare for an exam? Are anxious students more or less prone to overconfidence than non-anxious students? What metacognitive decisions mediate maths anxious participants' tendency to give up on problems too early? Additionally, this line of work has the potential to significantly expand the scope of metacognitive investigations and provide novel insights into individual differences in the metacognitive regulation of learning and problem solving. It could also offer some practical benefits by focusing the attention of educational designers on particular components within the learning process of anxious students.

Metacognitive research aims to explain how people regulate their effort when performing cognitive tasks, to expose conditions that support reliable monitoring of chance for success, and to provide a basis for developing improvement guidelines. The essence of the domain is that monitoring drives control: people continually self-assess their chance for success before, during, and after performing a cognitive task, and use these judgments to guide their effort-allocation decisions (e.g., whether to reconsider an answer option, change strategy, seek help, or give up). Thus, factors that underlie metacognitive judgments affect the efficiency with which people perform cognitive tasks. This paper focuses on meta-reasoning – the monitoring and control processes that apply to reasoning, problem-solving, and decision-making tasks. So far, relatively little is known about heuristic cues used for inferring meta-reasoning judgments. This paper reviews the known heuristic cues and offers methodological guidelines for a critical reading of existing research and for designing high-quality studies that will advance this important domain.

This paper presents a proposal for a new area of investigation that connects the metacognition literature, and especially the recently developed meta-reasoning framework, with research into mathematical reasoning, mathematics learning, and mathematics anxiety. Whereas the literature on mathematics anxiety focusses on the end result of learning and problem-solving, the metacognitive approach can offer further insight by a fine-grained analysis of the stages of these processes. In particular, it provides tools for exposing students' initial assessment of tasks and test situations, the targets they set for themselves, the process of monitoring progress, and decisions to stick with or abandon a particular solution. The paper outlines various ways in which the metacognitive approach could be used to investigate the effects of mathematics anxiety on mathematics learning and problem solving. This approach could help in answering questions like: Do anxious and non-anxious learners differ in how they prepare for an exam? Are anxious students more or less prone to overconfidence than non-anxious students? What metacognitive decisions mediate maths anxious participants' tendency to give up on problems too early? Additionally, this line of work has the potential to significantly expand the scope of metacognitive investigations and provide novel insights into individual differences in the metacognitive regulation of learning and problem solving. It could also offer some practical benefits by focusing the attention of educational designers on particular components within the learning process of anxious students.

Metacognitive research aims to explain how people regulate their effort when performing cognitive tasks, to expose conditions that support reliable monitoring of chance for success, and to provide a basis for developing improvement guidelines. The essence of the domain is that monitoring drives control: people continually self-assess their chance for success before, during, and after performing a cognitive task, and use these judgments to guide their effort-allocation decisions (e.g., whether to reconsider an answer option, change strategy, seek help, or give up). Thus, factors that underlie metacognitive judgments affect the efficiency with which people perform cognitive tasks. This paper focuses on meta-reasoning – the monitoring and control processes that apply to reasoning, problem-solving, and decision-making tasks. So far, relatively little is known about heuristic cues used for inferring meta-reasoning judgments. This paper reviews the known heuristic cues and offers methodological guidelines for a critical reading of existing research and for designing high-quality studies that will advance this important domain.