Publications by authors named "Simon Schaerlaeken"

Article Synopsis
  • Executive functions (EFs) are interconnected skills that impact academic success, yet they are frequently studied in isolation, making it hard to see how they work together.
  • A study involving over 1200 students aged 7-15 utilized nine EF assessments to create cognitive profiles and analyzed their correlation with academic performance in reading and math.
  • The findings highlighted that while students exhibited different EF profiles, these variations did not demonstrate a straightforward link between specific EFs and academic achievement, suggesting diverse cognitive pathways can lead to success.
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Article Synopsis
  • * Research often takes place in controlled lab settings, which may not accurately reflect real-life school environments, and tends to focus narrowly on specific academic skills rather than broader academic success.
  • * In a study of over 700 students aged 9-14, it was found that sustained attention positively correlated with both targeted academic assessments (like math fluency and reading comprehension) and broader measures (such as standardized test scores).
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Musical meaning is often described in terms of emotions and metaphors. While many theories encapsulate one or the other, very little empirical data is available to test a possible link between the two. In this article, we examined the metaphorical and emotional contents of Western classical music using the answers of 162 participants.

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Background: Simulation is a useful method to improve learning and increase the safety of work operations, both for technical and non-technical skills. However, the observation, assessment, and feedback about these skills is particularly complex, because the process needs expert observers, and the feedback could be judgmental and ineffective. Therefore, a structured process to develop effective simulation scenarios and tools for the observation and feedback about performance is crucial.

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The unfolding dynamics of the vocal expression of emotions are crucial for the decoding of the emotional state of an individual. In this study, we analyzed how much information is needed to decode a vocally expressed emotion using affect bursts, a gating paradigm, and linear mixed models. We showed that some emotions (fear, anger, disgust) were significantly better recognized at full-duration than others (joy, sadness, neutral).

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