Differences in brain signal complexity between experts and novices when solving conceptual science problem: a...

Area of Science:

• Neuroscience
• Educational Psychology
• Cognitive Science

Background:

• Assessing conceptual change in science education traditionally lacks objectivity.
• Developing objective neurobiological indicators is crucial for accurate assessment.
• Functional near-infrared spectroscopy (fNIRS) offers a non-invasive method to measure brain activity.

Purpose of the Study:

• To explore permutation entropy (PE) based complexity as an objective neurobiological indicator for assessing conceptual change.
• To differentiate between novice and expert understanding of a science concept using neuroimaging.
• To investigate the role of the inferior frontal gyrus (IFG) in conceptual change.

Main Methods:

• Utilized functional near-infrared spectroscopy (fNIRS) to record hemodynamic responses in the inferior frontal gyrus (IFG).
• Employed permutation entropy (PE) analysis to quantify time series complexity from fNIRS data.
• Conducted behavioral assessments, activation analysis, PE complexity analysis, and k-means clustering.

Main Results:

• Engineering students (experts) outperformed humanities students (novices) in behavioral tasks.
• Experts exhibited lower PE values in the IFG, particularly the right IFG, compared to novices.
• K-means clustering demonstrated PE's effectiveness in classifying students into expert and novice groups.

Conclusions:

• Permutation entropy (PE) shows promise as a reliable neurobiological indicator for assessing science conceptual change.
• fNIRS combined with PE analysis offers an objective method to evaluate understanding.
• The findings contribute to developing more effective and objective science education assessments.