The statement "studying at night is best" is an exaggerated and misleading. Whereas the article by Scholarly points out several advantages of studying at night, such as fewer distractions, a quieter environment, and even potential memory consolidation benefits, these are not universally applicable or supported by conclusive evidence. The article has also acknowledged challenges such as sleep deprivation and inconsistent energy levels that could negatively affect a student's performance. Additionally, the article fails to provide any solid empirical data or peer-reviewed research to support these claims but instead relies on general observations and user preferences. These advantages may favor certain individuals, like night owls, but this general statement of studying at night being the best lacks nuance and scientific rigor.
Scholarly is not very credible due to a lack of credentials or citations of academic research that may support the claims made in the source. Although the article is highly detailed, ranging from a variety of related topics including AI tools and study techniques, there are no references to original studies or empirical data. For example, it mentions the benefits of memory consolidation at night without citing specific scientific studies or journals. Without any credible references or any sort of established authority in the field of educational or psychological research, the article's conclusions seem to be speculative rather than evidence-based.
Further analysis of the claim, a 2019 study published in Nature and Science of Sleep showed that everyone's productivity peaks at different times, and studying during one's chronotype can optimize learning outcomes. This supports part of Scholarly's argument that night-time study may benefit night owls; however, the same study emphasized the importance of sleep hygiene and avoiding disruptions to natural circadian rhythms, warning of the risks of chronic night-time studying in individuals not biologically predisposed to late activity-re. While night-time studying might suit certain groups, a one-size-fits-all approach is not supported by the current research.
https://www.mdpi.com/2079-7737/11/4/487