The Psychology of Superorganisms: Collective Decision Making by Insect Societies

Under the superorganism concept, insect societies are so tightly integrated that they possess features analogous to those of single organisms, including collective cognition. If so, colony function might fruitfully be studied using methods developed to understand individual animals. Here, we review research that uses psychological approaches to understand decision making by colonies. The application of neural models to collective choice shows fundamental similarities between how brains and colonies balance speed/accuracy trade-offs in decision making. Experimental analyses have explored collective rationality, cognitive capacity, and perceptual discrimination at both individual and colony levels. A major theme is the emergence of improved colony-level function from interactions among relatively less capable individuals. However, colonies also encounter performance costs due to their reliance on positive feedback, which generates consensus but can also amplify errors. Collective learning is a nascent field for the further application of psychological methods to colonies. The research strategy reviewed here shows how the superorganism concept can serve as more than an illustrative analogy.

How student perceptions about online learning difficulty influenced their satisfaction during Canada's Covid-19 response

The COVID-19 pandemic has posed a significant challenge to higher education and forced academic institutions across the globe to abruptly shift to remote teaching. Because of the emergent transition, higher education institutions continuously face difficulties in creating satisfactory online learning experiences that adhere to the new norms. This study investigates the transition to online learning during Covid-19 to identify factors that influenced students' satisfaction with the online learning environment. Adopting a mixed-method design, we find that students' experience with online learning can be negatively affected by information overload, and perceived technical skill requirements, and describe qualitative evidence that suggest a lack of social interactions, class format, and ambiguous communication also affected perceived learning. This study suggests that to digitalize higher education successfully, institutions need to redesign students' learning experience systematically and re-evaluate traditional pedagogical approaches in the online context.

How can we apply decision-making theories to wild animal behavior? Predictions arising from dual process theory and Bayesian decision theory

Our understanding of decision-making processes and cognitive biases is ever increasing, thanks to an accumulation of testable models and a large body of research over the last several decades. The vast majority of this work has been done in humans and laboratory animals because these study subjects and situations allow for tightly controlled experiments. However, it raises questions about how this knowledge can be applied to wild animals in their complex environments. Here, we review two prominent decision-making theories, dual process theory and Bayesian decision theory, to assess the similarities in these approaches and consider how they may apply to wild animals living in heterogenous environments within complicated social groupings. In particular, we wanted to assess when wild animals are likely to respond to a situation with a quick heuristic decision and when they are likely to spend more time and energy on the decision-making process. Based on the literature and evidence from our multi-destination routing experiments on primates, we find that individuals are likely to make quick, heuristic decisions when they encounter routine situations, or signals/cues that accurately predict a certain outcome, or easy problems that experience or evolutionary history has prepared them for. Conversely, effortful decision-making is likely in novel or surprising situations, when signals and cues have unpredictable or uncertain relationships to an outcome, and when problems are computationally complex. Though if problems are overly complex, satisficing via heuristics is likely, to avoid costly mental effort. We present hypotheses for how animals with different socio-ecologies may have to distribute their cognitive effort. Finally, we examine the conservation implications and potential cognitive overload for animals experiencing increasingly novel situations caused by current human-induced rapid environmental change.

Dynamic resource allocation strategies in the human brain under cognitive overload: evidence from time-varying brain network analysis

The impact of excessive cognitive workload on personal work and life is widely recognized, yet the brain information processing mechanisms under cognitive overload remain unclear. This study employed a spatial configuration task, combined with time-varying brain network analysis and source localization techniques based on electroencephalography signals, to delve into the dynamic adjustment processes of the brain among healthy participants during cognitive overload. The results revealed that under cognitive overload, the overall activation level of the brain significantly decreases, with characteristics of delayed responses. Further analysis indicated that under overload, the brain network connectivity in the right hemisphere brain networks closely associated with spatial object recognition and localization was weakened. In contrast, the brain network connections between the left hemisphere are enhanced. These changes suggest that during cognitive overload, the brain prioritizes resource allocation to support spatial memory functions, which might lead to restricted resources for subsequent spatial information processing. Notably, the significant differences in brain network connectivity observed in the hippocampus, fusiform gyrus, and superior frontal gyrus make them important potential markers for identifying cognitive overload states during spatial configuration tasks. This study provides a fresh perspective and scientific foundation for understanding the impact of cognitive overload on work performance.

User avoidance behavior in pharmaceutical e-commerce intelligent customer service: a stressor-strain-outcome perspective

Introduction

This study explores the implementation of Intelligent Customer Service (ICS) in pharmaceutical e-commerce, aiming to enhance user acceptance and service efficiency while addressing the psychological factors influencing user behavior. It expands the boundaries of technology acceptance research by focusing on ICS use and avoidance in high-risk environments.

Method

A total of 418 valid questionnaires were collected from participants, ensuring data quality through rigorous screening. The study employed SPSS for data normality tests and SmartPLS for structural equation modeling to analyze the relationships between emotional stress, system overload, and user avoidance behavior.

Results

The findings indicate that system overload, information overload, and service overload significantly contribute to user emotional stress, which in turn drives avoidance behavior. The analysis revealed strong explanatory power (R 2 values ranging from 0.450 to 0.586) and confirmed the mediating role of emotional stress in the relationship between overload factors and user avoidance.

Discussion

This research highlights the critical role of emotional stress in user interactions with ICS, suggesting that pharmaceutical e-commerce companies must refine their ICS design to meet diverse user needs and reduce cognitive burdens. By leveraging big data and establishing robust feedback mechanisms, companies can enhance user experience and loyalty. The study also identifies limitations in demographic representation and suggests future research should incorporate qualitative methods for a deeper understanding of user behavior.

Designing Instruction That Supports Cognitive Learning Processes

OBJECTIVE: To provide an overview of current cognitive learning processes, including a summary of research that supports the use of specific instructional methods to foster those processes. We have developed examples in athletic training education to help illustrate these methods where appropriate. DATA SOURCES: Sources used to compile this information included knowledge base and oral and didactic presentations. DATA SYNTHESIS: Research in educational psychology within the past 15 years has provided many principles for designing instruction that mediates the cognitive processes of learning. These include attention, management of cognitive load, rehearsal in working memory, and retrieval of new knowledge from long-term memory. By organizing instruction in the context of tasks performed by athletic trainers, transfer of learning and learner motivation are enhanced. CONCLUSIONS/RECOMMENDATIONS: Scientific evidence supports instructional methods that can be incorporated into lesson design and improve learning by managing cognitive load in working memory, stimulating encoding into long-term memory, and supporting transfer of learning.

The Impact of Mobile Social Media Use on Depressive Mood Among College Students: A Chain Mediating Effect of Upward Social Comparison and Cognitive Overload

Background

The 18-24 age group has a much higher rate of depression risk than other age groups, and this age group has the highest proportion among users of mobile social media. The relationship between the use of mobile social media and depressive mood is inconsistent and the mechanism of action is controversial.

Purpose

This study explored the relationship among the intensity of social media use, upward social comparison, cognitive overload and depressive mood.

Methods

In this research, we used the Brief Self-rating Depression Scale (PHQ-9), the Social Media Usage Intensity Questionnaire, the Social Comparison Scale on Social Networking Sites and the Social Networking Site Cognitive Overload Scale to investigate the depressive mood and mobile social media use of 568 college students.

Results

The intensity of mobile social media use, social networking site upward social comparison, and social networking site cognitive overload are all positively correlated with depressive mood. The intensity of mobile social media use has a positive predictive effect on depressive mood, with upward social comparison and cognitive overload acting as independent mediators in the relationship between mobile social media use intensity and depressive symptoms, as well as exhibiting a chained mediating effect of upward social comparison-cognitive overload.

Conclusion

The upward social comparison and cognitive load that occur during the use of mobile social media are important predictive factors for the occurrence of depressive mood. This study is a supplement to the mechanism of the relationship between mobile social media use and depression, providing more evidence-based evidence and intervention directions for university teachers, mobile social media developers, and psychologists.