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Before yesterdayWiley: Mind, Brain, and Education: Table of Contents

Informed Consent in Educational AI Research Needs to Be Transparent, Flexible, and Dynamic

ABSTRACT

Generative artificial intelligence (AI) has become a major research trend in the fields of education and psychology. However, several risks posed by this technology concerning the cognitive and socio-emotional development of children and adolescents have been identified. While it would be highly useful to have a clear understanding of these potential negative effects, empirical results cannot be obtained without putting the participants of these studies in a situation that potentially endangers their development. Research fields such as the biomedical sciences utilize several measures to minimize risks, such as dose escalation and stopping rules. In addition, dynamic and flexible forms of informed consent could be adopted by our field to maximize transparency. By including methodological advancements and ethical developments in the psychological and educational research process, risks could be averted, and the ethical soundness of AI research involving children and adolescents could be maintained.

Coupling Spatial Working Memory With STEM Educational Performance and Related Neural Markersβ€”Evidence From ERPs

ABSTRACT

Working memory is a hot topic in the field of cognitive neuroscience and has attracted the attention of many researchers in the field of education. In recent years, it has been found that the cognitive ability related to spatial information in working memory can positively affect STEM academic performance, which is highly important for educational practice. However, empirical studies on the relationship between spatial working memory and education, especially STEM education, are still scarce, especially studies on the combination of brain electrophysiological activities. On this basis, we designed an n-back spatial working memory experiment and recorded the electrophysiological data at the same time. The results indicate that STEM education level has a significant main effect on participants' behavioral accuracy, whereas working memory load has no significant main effect on behavioral accuracy. The differential characteristics of the N1, P3, and LPP components in electrophysiological ERP performance also have potential as biomarkers to distinguish between different types of STEM educational performance. This means that there is a new direction and focus for STEM education from macro decision-making and reform to micro design and intervention. Moreover, this study provides exploratory ideas for the optimization of different subject courses in STEM education and science education related to students' growth process.

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