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Proposal for Investigating Self-Efficacy in Mathematics Using a Portable EEG System.

Athina Papadopoulou1, Spyridon Doukakis2

  • 1Department of Informatics, Ionian University, Kerkira, Greece. c20papa1@ionio.gr.

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Summary

This study explores the link between math self-efficacy, cognitive function, and test performance using EEG. Findings aim to enhance understanding of math learning and cognitive theories.

Keywords:
Brain imagingEEGElectrophysiologyFace trackingMathematicsNeurophysiologyNeuroscienceSelf-Efficacy

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Area of Science:

  • Cognitive Psychology
  • Neuroscience
  • Mathematics Education

Background:

  • Self-efficacy in mathematics is crucial for learning.
  • Neurocognitive and socio-cognitive factors influence mathematical abilities.
  • Integrating diverse data sources can deepen our understanding of math cognition.

Purpose of the Study:

  • To investigate the relationship between self-efficacy in mathematics, cognitive function during problem-solving, and test performance.
  • To clarify the role of neurocognitive findings in understanding perceived mathematical self-efficacy.
  • To determine if neurophysiological data can enrich socio-cognitive research and cognitive theories in mathematics education.

Main Methods:

  • Utilizing data from questionnaires, neurophysiological (MUSE 2 portable EEG system), and biometric measurements.
  • Analyzing correlations between self-efficacy scores, brain function during math tasks, and math test performance.
  • Examining the relationship between math self-efficacy and demographic characteristics, as well as pre- and post-experiment self-efficacy perceptions.

Main Results:

  • Correlations between overall math self-efficacy scores and brain function during math problem-solving will be assessed.
  • The study will determine if a correlation exists between high self-efficacy and high math test performance.
  • Relationships between math self-efficacy, participant demographics, and perceived self-efficacy changes will be investigated.

Conclusions:

  • Neurophysiological data can provide valuable insights into mathematical self-efficacy.
  • This research aims to bridge socio-cognitive and neurocognitive perspectives in mathematics education.
  • Findings will contribute to a more comprehensive understanding of cognitive theories related to mathematics learning.