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This paper first introduces Bloom’s cognitive hierarchy theory of music education goal classification and revises it to construct a new version of Bloom’s educational goal-setting system. After that, it adopts multi-objective hierarchical analysis (AHP) to calculate the weights of the music education objectives assessed by experts and optimizes the convergence of AHP based on Bergh’s improved particle swarm (PSO) optimization algorithm. New music education objectives and teaching contents were created based on the experimental results. The CR values of the six cognitive subprocesses of the second-level evaluation indexes were 0.0001, 0.0011, 0.0014, 0.0014, 0.0023, and 0.0029, respectively. The results of the consistency test of the first-level and second-level indexes were all CR<0.05, indicating that their consistency and trustworthiness were extremely high. The top three indicators in terms of the weights of the secondary indicators are inference, recall and differentiation, whose weights are 0.5723, 0.5276 and 0.5192, respectively; the three indicators with the lowest proportion are interpretation (0.2422), normalization (0.2661) and creation (0.3201). The purpose of this paper is to create a music course instructional design system with a 4-dimensional and 18-indicator system and evaluate the importance of each indicator. It fully embodies the basic spirit of quality education and reflects the common requirements of the new curriculum system of colleges and universities that combines epochal, basic, and selective. The teaching design system proposed in this paper is expected to serve as a reference for the current music teaching reform.

Decision makers and researchers recognize the need to effectively confront the social dimensions and conflicts inherent to invasive species research and management. Yet, despite numerous contentious situations that have arisen, no systematic evaluation of the literature has examined the commonalities in the patterns and types of these emergent social issues. Using social and ecological keywords, we reviewed trends in the social dimensions of invasive species research and management and the sources and potential solutions to problems and conflicts that arise around invasive species. We integrated components of cognitive hierarchy theory and risk perceptions theory to provide a conceptual framework to identify, distinguish, and provide understanding of the driving factors underlying disputes associated with invasive species. In the ISI Web of Science database, we found 15,915 peer-reviewed publications on biological invasions, 124 of which included social dimensions of this phenomenon. Of these 124, 28 studies described specific contentious situations. Social approaches to biological invasions have emerged largely in the last decade and have focused on both environmental social sciences and resource management. Despite being distributed in a range of journals, these 124 articles were concentrated mostly in ecology and conservation-oriented outlets. We found that conflicts surrounding invasive species arose based largely on differences in value systems and to a lesser extent stakeholder and decision maker?s risk perceptions. To confront or avoid such situations, we suggest integrating the plurality of environmental values into invasive species research and management via structured decision making techniques, which enhance effective risk communication that promotes trust and confidence between stakeholders and decision makers.

Understanding the perceptions of young people is a critical issue in the formulation and implementation of climate change mitigation strategies. Based on cognitive hierarchy theory, the present study aims to investigate the factors that motivate or hinder young people’s perception of forestation as a strategy to mitigate climate change in post-conflict Somalia. This study hypothesized a model in which climate change knowledge, risk perception and forest value orientations (anthropocentric/biocentric) influence attitude toward forestation and attitude, in turn, predicts behavioral intentions. We randomly surveyed students from three universities in three different regions of Somalia and collected 434 structured survey questionnaires. Using structural equation modeling, the results showed that climate change knowledge is a significant predictor of behavioral intention but not attitude toward forestation. The results also revealed that young people’s perception toward forestation as a strategy to mitigate climate change is significantly influenced by biocentric value orientation both directly and indirectly through attitude toward forestation. Contrary to previous studies, our results indicate that attitude partially mediates the relationship between biocentric value orientation and behavioral intentions and fully mediates the relationship between anthropocentric value orientation, risk perception and behavioral intentions, while it did not show any mediation results between climate change knowledge and behavioral intention. We found that the young people’s climate action or inaction is mainly shaped by climate change knowledge, biocentric value orientation, and attitude toward forestation. Finally, climate change mitigation efforts should avoid relying solely on attitude for behavioral decision-making formation and instead incorporate other factors into a more comprehensive framework.

Researchers, planners, and decision makers admit the need to take into account the social conflicts inherent to invasive species management in order to minimize controversy. These conflicts are mainly based on differences in values systems, thus causing antithetical policies in environmental management. On the topic of Eucalyptus plantations, this paper studies two cases in Galicia, a region under an emerging social fight between advocates and opponents: firstly, we analyze a local community that is progressively eradicating Eucalyptus through the principles of ecological restoration; and secondly, a planning initiative led by a local government with a common goal. In order to set the spatial and social dimensions of the conflict, the methodological approach is based on the components of cognitive hierarchy theory and risk perception theory. The results are discussed with the purpose of examining to what extent the case studies imply a new model of rural governance, and in this respect, are transferrable to other situations. We conclude that institutional non-interference in Eucalyptus management facilitates the emergence of diverse new governance practices in the local scale but endures the conflict in its regional dimension.

Wildlife tourism can act as an incentive for the conservation of marine species and habitats. One of the most important outcomes can be a change in the views of participants towards target species and their habitats that may promote more conservation-oriented actions. While a handful of studies have documented the wildlife value orientations (WVOs) of tourists participating in marine wildlife tourism, no studies have explored the WVOs of locals working in tourism. However, it is equally important to understand the WVOs of locals working in community-based tourism, and whether these are linked with changes in locals' attitudes and behaviors towards marine wildlife and the ocean. This article assesses the WVOs of locals working in community-based whale shark tourism at four sites in the Philippines, and explores the relationship between WVOs and conservation attitudes and behaviors using a mixed methods approach with a total of 114 structured interviews. Three WVO groups were identified (mixed utilitarian-protectionist, moderate protectionist, and high protectionist), suggesting a WVO continuum. Those respondents with more protectionist views reported more conservation outcomes, including changes in attitudes and behaviors to protect whale sharks. Further, respondents who worked in tourism had more protectionist views than those from a failed tourism site, indicating that tourism can change communities by helping locals value their marine resources and incentivizing protection of those resources.

Generalizing experiences to guide decision-making in novel situations is a hallmark of flexible behavior. Cognitive maps of an environment or task can theoretically afford such flexibility, but direct evidence has proven elusive. In this study, we found that discretely sampled abstract relationships between entities in an unseen two-dimensional social hierarchy are reconstructed into a unitary two-dimensional cognitive map in the hippocampus and entorhinal cortex. We further show that humans use a grid-like code in entorhinal cortex and medial prefrontal cortex for inferred direct trajectories between entities in the reconstructed abstract space during discrete decisions. These grid-like representations in the entorhinal cortex are associated with decision value computations in the medial prefrontal cortex and temporoparietal junction. Collectively, these findings show that grid-like representations are used by the human brain to infer novel solutions, even in abstract and discrete problems, and suggest a general mechanism underpinning flexible decision-making and generalization. Cognitive maps are theorized to enable generalizing experiences in new situations. Park et al. show that non-spatial experiences sampled piecemeal are integrated into a two-dimensional cognitive map of social hierarchy, and a grid code is used for novel inferences.

The resemblance between the methods used in quantum-many body physics and in machine learning has drawn considerable attention. In particular, tensor networks (TNs) and deep learning architectures bear striking similarities to the extent that TNs can be used for machine learning. Previous results used one-dimensional TNs in image recognition, showing limited scalability and flexibilities. In this work, we train two-dimensional hierarchical TNs to solve image recognition problems, using a training algorithm derived from the multi-scale entanglement renormalization ansatz. This approach introduces mathematical connections among quantum many-body physics, quantum information theory, and machine learning. While keeping the TN unitary in the training phase, TN states are defined, which encode classes of images into quantum many-body states. We study the quantum features of the TN states, including quantum entanglement and fidelity. We find these quantities could be properties that characterize the image classes, as well as the machine learning tasks.

While game theory has been transformative for decision making, the assumptions made can be overly restrictive in certain instances. In this work, we investigate some of the underlying assumptions of rationality, such as mutual consistency and best response, and consider ways to relax these assumptions using concepts from level- k reasoning and quantal response equilibrium (QRE) respectively. Specifically, we propose an information-theoretic two-parameter model called the quantal hierarchy model, which can relax both mutual consistency and best response while still approximating level- k , QRE, or typical Nash equilibrium behavior in the limiting cases. The model is based on a recursive form of the variational free energy principle, representing higher-order reasoning as (pseudo) sequential decision-making in extensive-form game tree. This representation enables us to treat simultaneous games in a similar manner to sequential games, where reasoning resources deplete throughout the game-tree. Bounds in player processing abilities are captured as information costs, where future branches of reasoning are discounted, implying a hierarchy of players where lower-level players have fewer processing resources. We demonstrate the effectiveness of the quantal hierarchy model in several canonical economic games, both simultaneous and sequential, using out-of-sample modelling.

Two dominant perspectives of job crafting—the original theory from Wrzesniewski and Dutton (2001) and the job demands resources perspective from Tims, Bakker, and Derks (2012)—remain separate in research. To synthesize these perspectives, we propose a three-level hierarchical structure of job crafting, and we identify the aggregate/superordinate nature of each major job crafting construct. The first level of the structure is job crafting orientation, or approach versus avoidance crafting, which we argue is an essential yet often neglected distinction in the literature. We address the debate surrounding cognitive crafting and identify crafting form (behavioral versus cognitive crafting) as the next hierarchical level of constructs. Finally, we concur that job resources and job demands, or crafting content, capture different ways that individuals craft their jobs. Using this integrated hierarchical structure, we were able to review antecedents and outcomes from both perspectives. We show, for example, that approach crafting in its behavioral form is very similar to other proactive behaviors in the way it functions, suggesting a need for closer synthesis with the broader proactive literature, whereas avoidance crafting appears to be less proactive and often dysfunctional. On the basis of our review, we develop a road map for future research.

In coming to understand the world--in learning concepts, acquiring language, and grasping causal relations--our minds make inferences that appear to go far beyond the data available. How do we do it? This review describes recent approaches to reverse-engineering human learning and cognitive development and, in parallel, engineering more humanlike machine learning systems. Computational models that perform probabilistic inference over hierarchies of flexibly structured representations can address some of the deepest questions about the nature and origins of human thought: How does abstract knowledge guide learning and reasoning from sparse data? What forms does our knowledge take, across different domains and tasks? And how is that abstract knowledge itself acquired?