Bridging cognitive neuroscience and education: Insights from EEG recording during mathematical proof evaluation.

BACKGROUND: Much of modern mathematics education prioritizes symbolic formalism even at the expense of non-symbolic intuition, we contextualize our study in the ongoing debates on the balance between symbolic and non-symbolic reasoning. We explore the dissociation of oscillatory dynamics between algebraic (symbolic) and geometric (non-symbolic) processing in advanced mathematical reasoning during a naturalistic design. METHOD: Employing mobile EEG technology, we investigated students' beta and gamma wave patterns over frontal and parietal regions while they engaged with mathematical demonstrations in symbolic and non-symbolic formats within a tutor-student framework. We used extended, naturalistic stimuli to approximate an authentic educational setting. CONCLUSION: Our findings reveal nuanced distinctions in neural processing, particularly in terms of gamma waves and activity in parietal regions. Furthermore, no clear overall format preference emerged from the neuroscientific perspective despite students rating symbolic demonstrations higher for understanding and familiarity.

Math on cortex-enhanced delta phase synchrony in math experts during long and complex math demonstrations.

Neural oscillations are important for working memory and reasoning and they are modulated during cognitively challenging tasks, like mathematics. Previous work has examined local cortical synchrony on theta (4-8 Hz) and alpha (8-13 Hz) bands over frontal and parietal electrodes during short mathematical tasks when sitting. However, it is unknown whether processing of long and complex math stimuli evokes inter-regional functional connectivity. We recorded cortical activity with EEG while math experts and novices watched long (13-68 seconds) and complex (bachelor-level) math demonstrations when sitting and standing. Fronto-parietal connectivity over the left hemisphere was stronger in math experts than novices reflected by enhanced delta (0.5-4 Hz) phase synchrony in experts. Processing of complex math tasks when standing extended the difference to right hemisphere, suggesting that other cognitive processes, such as maintenance of body balance when standing, may interfere with novice's internal concentration required during complex math tasks more than in experts. There were no groups differences in phase synchrony over theta or alpha frequencies. These results suggest that low-frequency oscillations modulate inter-regional connectivity during long and complex mathematical cognition and demonstrate one way in which the brain functions of math experts differ from those of novices: through enhanced fronto-parietal functional connectivity.

Smart grading: A generative AI-based tool for knowledge-grounded answer evaluation in educational assessments.

Evaluating text-based answers obtained in educational settings or behavioral studies is time-consuming and resource-intensive. Applying novel artificial intelligence tools such as ChatGPT might support the process. Still, currently available implementations do not allow for automated and case-specific evaluations of large numbers of student answers. To counter this limitation, we developed a flexible software and user-friendly web application that enables researchers and educators to use cutting-edge artificial intelligence technologies by providing an interface that combines large language models with options to specify questions of interest, sample solutions, and evaluation instructions for automated answer scoring. We validated the method in an empirical study and found the software with expert ratings to have high reliability. Hence, the present software constitutes a valuable tool to facilitate and enhance text-based answer evaluation.•Generative AI-enhanced software for customizable, case-specific, and automized grading of large amounts of text-based answers.•Open-source software and web application for direct implementation and adaptation.

Understanding Randomness on a Molecular Level: A Diagnostic Tool.

Undergraduate biology students' molecular-level understanding of stochastic (also referred to as random or noisy) processes found in biological systems is often limited to those examples discussed in class. Therefore, students frequently display little ability to accurately transfer their knowledge to other contexts. Furthermore, elaborate tools to assess students' understanding of these stochastic processes are missing, despite the fundamental nature of this concept and the increasing evidence demonstrating its importance in biology. Thus, we developed the Molecular Randomness Concept Inventory (MRCI), an instrument composed of nine multiple-choice questions based on students' most prevalent misconceptions, to quantify students' understanding of stochastic processes in biological systems. The MRCI was administered to 67 first-year natural science students in Switzerland. The psychometric properties of the inventory were analyzed using classical test theory and Rasch modeling. Moreover, think-aloud interviews were conducted to ensure response validity. Results indicate that the MRCI yields valid and reliable estimations of students' conceptual understanding of molecular randomness in the higher educational setting studied. Ultimately, the performance analysis sheds light on the extent and the limitations of students' understanding of the concept of stochasticity on a molecular level.