Pub Date : 2023-11-22DOI: 10.3390/knowledge3040040
Micah Watanabe, Danielle S. McNamara
Past research on knowledge has differentiated between dimensions (e.g., amount, accuracy, specificity, coherence) of knowledge. This paper introduces a novel dimension of knowledge, the Motivational Utility of Knowledge (MUK), that is based on fundamental human needs (e.g., physical safety, affiliation, actualization, reproduction). Adults in the United States (N = 190) were recruited from an online survey platform and paid for participation. Participants read a set of four texts arguing different views of houselessness and were administered a comprehension test after each text. Participants were asked about their conceptions of houselessness before and after reading. Finally, they were given the MUK scale, a demographics questionnaire, including questions about their personal experience with houselessness, and were administered a general prior knowledge test and a vocabulary knowledge test. We examined MUK, the factor structure of the scale and the relationship between MUK and other measures of knowledge. The analyses showed that the subscales of MUK loaded onto a single factor—an overall value of houselessness knowledge. In addition, we found that MUK was correlated with conceptions of houselessness and comprehension of texts on houselessness, indicating that the scale was valid. Overall, the findings demonstrate that MUK is an important dimension of knowledge to consider in learning tasks.
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Pub Date : 2023-11-22DOI: 10.3390/knowledge3040041
A. Rosa, Alessandro Massaro
Process mining organizatioQn (PMO) is an innovative approach based on artificial intelligence (AI) decision making suitable for designing healthcare processes for human resource (HR) organizations. The proposed work suggests some examples of PMO-based Business Process Modeling and Notation (BPMN) workflows by highlighting the advances in HR management and in risk decrease according to healthcare scenarios. Specifically proposed are different examples of “TO BE” process pipelines related to an upgrade of the organizational healthcare framework, including digital technologies and telemedicine. Important elements are provided to formulate HR management guidelines supporting PMO design. The proposed BPMN workflows are the result of different consulting actions in healthcare institutions based on the preliminary mapping of “AS IS” processes highlighting bottlenecks and needs in HR organization. A pilot experimental dataset is used to show how it is possible to apply AI algorithms providing organization corrective actions. The paper is mainly focused on discussing some validated BPMN models managing HR in the healthcare sector. The methodology is based on the application of the BPMN approach to deploy human resource organizational processes. The results show AI data-driven workflows adopted in healthcare and examples of AI fuzzy c-means outputs addressing organizational actions.
流程挖掘组织（PMO）是一种基于人工智能（AI）决策的创新方法，适用于为人力资源（HR）组织设计医疗保健流程。所提议的工作根据医疗保健场景，通过突出人力资源管理和降低风险方面的进展，提出了一些基于 PMO 的业务流程建模和符号（BPMN）工作流程示例。特别提出了与组织医疗保健框架升级有关的 "TO BE "流程管道的不同示例，包括数字技术和远程医疗。为制定支持项目管理办公室设计的人力资源管理准则提供了重要元素。所建议的 BPMN 工作流程是医疗机构在初步绘制 "AS IS "流程图的基础上开展不同咨询活动的结果，突出了人力资源组织的瓶颈和需求。本文使用了一个试点实验数据集来展示如何应用人工智能算法来提供组织纠正措施。本文主要侧重于讨论医疗保健领域管理人力资源的一些经过验证的 BPMN 模型。该方法基于应用 BPMN 方法来部署人力资源组织流程。结果显示了医疗保健领域采用的人工智能数据驱动工作流程，以及人工智能模糊 c-means 输出解决组织行动的实例。
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