General Knowledge Research Articles

Digitalization as a trend in the modern development of the economy of Kyrgyzstan and increasing the financial literacy of the country’s population

In modern Kyrgyzstan, transformational processes related to digitalization are taking place, which have led to a change in public consciousness, a reassessment of values in the field of economics, finance and in general in public life. At the moment, society is faced with the introduction of digital technologies, which have led to a powerful generation of new knowledge, attitudes and skills; there is a need to adjust personal financial management and lifestyle changes. Changing the model of financial behavior can be regarded as a way for the population to respond to the current situation, the purpose of which is to create opportunities for managing personal finances and ensuring relationships that allow the subject to achieve their life priorities. Citizens understand the need to involve them in new technological solutions in order to keep up with

An Extension of Small Business Cybersecurity Into the Classroom and Community

Small business owners often feel immune to hackers because of their business’s size and consequently do not have adequate security training, safeguards, policies, or insurance. Accordingly, small businesses are easy and frequent cybercrime targets because of limited budgets, technical personnel, and awareness. To increase small business owners’ awareness, a university conference for Cybersecurity and Small Business was offered with PCI DSS, Social Engineering, and Company Cases topics. To augment such cyber knowledge generation, this paper contains cybersecurity outreach activities for small businesses and cybersecurity learning activities for entrepreneurship students who aspire to be small business owners.

Bring digital twins back to Earth

AbstractWe reflect on the development of digital twins of the Earth, which we associate with a reductionist view of nature as a machine. The projects of digital twins deviate from contemporary scientific paradigms in the treatment of complexity and uncertainty, and does not engage with critical and interpretative social sciences. We contest the utility of digital twins for addressing climate change issues and discuss societal risks associated with the concept, including the twins' potential to reinforce economicism and governance by numbers, emphasizing concerns about democratic accountability. We propose a more balanced alternative, advocating for independent institutions to develop diverse models, prioritize communication with simple heuristic‐based models, collect comprehensive data from various sources, including traditional knowledge, and shift focus away from physics‐centered variables to inform climate action. We argue that the advancement of digital twins should hinge on stringent controls, favoring a nuanced, interdisciplinary, and democratic approach that prioritizes societal well‐being over blind pursuit of computational sophistication.This article is categorized under: Climate Models and Modeling > Earth System Models Climate Models and Modeling > Knowledge Generation with Models Climate, History, Society, Culture > Disciplinary Perspectives

Leveraging artificial intelligence and machine learning analytics for development effectiveness: a comprehensive approach to extract insights from project data

ABSTRACT In the normal course of business, international development institutions investing in development projects generate thousands of project-related documents summarising and analysing each aspect of their policymaking processes and policy lifecycles from design and financing through implementation performance and ultimately project/policy outputs, outcomes and effectiveness-related data. Moreover, institutions’ internal processes for quality assurance, monitoring and results measurement systems generate quantitative and qualitative primary and secondary data that can be employed to extract insights about lessons learned, internal decision-making processes, business model changes and project and portfolio performance. Resource and time constraints, however, result in the underutilisation of these valuable data sources for knowledge management, planning, evaluation and analysis. Specifically, qualitative insights housed in project documents remain largely inaccessible and cannot be employed systematically in combination with other quantitative data, in a unified framework. This article explores how machine learning can accelerate knowledge generation and management and aid results-based decision-making in line with development institutions’ existing development effectiveness frameworks through two main channels. The first leverages project documentation for historical portfolio systematisation to extract key strategic topics as well as lessons learned through the application of techniques such as text mining and topic modelling. The second proposes an agency-based system for predictive analytics, which analyses current and historical data to make predictions about future outcomes or trends to strengthen data-driven decision-making.

Proposal of a Knowledge Management Model for Complex Systems: Case of the Supervision and Control Subsystem of the Colombian Health System.

Considering regulatory, supervision, and control health policy, an innovative knowledge management model is proposed for the Colombian health system, which is recognized as a complex system. A model is constructed through a comparative analysis of various theoretical and conceptual frameworks, and an original methodology is proposed based on an analysis of the macroprocesses of the Supervision and Control System (SSC) of the Colombian General Social Security System in Health (SGSSS). After formulating hypotheses and conceptual references, information errors are determined within the different macroprocesses of the SGSSS, including those of governance and the SSC. The risks of generating duplicate, wrong, hidden, or non-existent information arise when the associated regulations need more specificity to be applied in all cases, thus leading to the risk of different interpretations by some actors. In this way, it is possible to hinder the generation of unified information, as there is no clarity as to who is responsible for the generation or creation of certain data. The proposed model is characterized by its flexibility and adaptability, integrating several processes that can be executed simultaneously or cyclically (depending on the system's needs) and allowing for the generation and feedback of knowledge at different stages, with some processes simultaneously executed to complement each other.

Multiple ways to bend the curve of biodiversity loss: An analytical framework to support transformative change

Abstract Humans are significantly impacting ecosystems worldwide. Scientists of the IPBES Global Assessment are therefore calling for a transformative change that includes all aspects of society in order to address drivers of biodiversity loss. However, these calls are rather abstract, and thus it remains unclear how this goal can be achieved. With this conceptual contribution, we present an analytical framework for evaluating existing processes of societal change which are enhancing biodiversity, and we illustrate its application using three case studies in Germany. We argue that an empirical analysis provides insights into the causal mechanisms that initiate or promote change processes. In doing so, we can draw recommendations for future transformative change processes with regard to biodiversity conservation. In our analysis, we are dealing with questions concerning the following three areas: the drivers and context of societal change processes, the change processes themselves and finally their impacts. Subsequently, we generate recommendations on how to enhance and support the process of future societal transformation that aims at biodiversity conservation: (a) Retaining co‐benefits for biodiversity with goals that are primarily focussing on other objectives; (b) harmonising biodiversity use and conservation by turning conflicts into drivers of transformation; (c) prioritising biodiversity conservation by taking advantage of windows of opportunity. With our conceptual framework, we provide an analytical tool to learn from existing processes of societal change how to support future transformative change. This is an important step that contributes to the generation of relevant knowledge of promoting transformative change for nature and people. Read the free Plain Language Summary for this article on the Journal blog.

The ethical motivation for post-normal science

This paper focuses on the concept of post-normal science, originally proposed by Silvio Funtowicz and Jerome Ravetz, as an advanced method of knowledge generation for policy, and reflects on the ethical motivations for both its theoretical meaning and its practical realisation. In order to put the reflection on the why and how of post-normal science in a broader contemporary and future-oriented context, I will first elaborate on what I call ‘the politics of hypothesis’ and argue that the fundamental challenge for science that aims to advice policy today is not the problem of strategic manipulation of scientific advice by politics, civil society or the market, but rather the problem of dealing with the lack of evidence in situations where politics, civil society or the market ‘need’ that evidence to (urgently) inform, criticise or justify specific actions or practices. Confronted with the need to deal with incomplete and speculative knowledge, in many cases, scientific hypotheses have become the ‘end products’ of science themselves, and society has no other choice than to deal with them in a responsible way. The challenge of science in these cases is therefore not any longer the production of convincing proofs, it is the construction of credible hypotheses. Against this backdrop, a second part will recall how the normative motivation for post-normal science was originally worked out by Funtowicz and Ravetz. I will re-emphasize why and how the argumentation of Funtowicz and Ravetz in favour of the democratisation of science and the opening up of the dialogue to include opinions, beliefs and lay knowledge of ‘non-experts’ is ethical. Consequently, the third part proposes some paths for further ethical reflection with regard to the value and meaning of post-normal science in the ‘post-normal age’. I will briefly elaborate on the concept of transdisciplinarity, the idea of ‘co-creation’ of complexity, the concept of holism and the idea of the unavoidable moral authority of the present generation in intergenerational ethics. The reason is that each of these explorations is at the same time and in its own way an invitation to reflect on who we are as humanity, and on how we can possibly make sense of things for the better. I hope to make clear not only how these concepts and ideas may inspire the ethics of post-normal science, but also that they should become topic of concern in post-normal science dialogues themselves. Finally, in conclusion, I will situate the original ethical motivation for post-normal science in a broader perspective on responsible knowledge generation ‘in face of’ the complexity of complex problems and argue that the overall ethical motivation for postnormal science is to enable an emancipatory and (respectfully) confrontational dialogue and not to come to a full understanding of the complexity of a complex problem or to ‘proof’ specific hypotheses. I will consequently suggest that, responding to the ‘ethical appeal’ of complexity, ‘reflexivity’ with respect to the own position, interests, strategies, hopes, hypotheses, believes and concerns would be the fundamental ethical attitude for anyone concerned. Reflexivity as a ‘quality’ of the science-policy interface does not only require science to reform in order to enable it to generate more reflexive policy advice, but also politics to reform into inclusive and deliberative forms of decision making prepared to become inspired and instructed by that reflexive policy advice. Post-normal science can in that sense be understood as a ‘method’ that can generate reflexivity at the science-policy interface and even as a deliberate political ‘act’ of knowledge generation involving science, political decision makers and civil society.

The Evaluation Purposes Visualization

Background: The article outlines the development of a visualization that aimed to represent the purpose of different evaluation theories. This visualization used a stream/river metaphor to show the evolution of different purposes (e.g. utilization, knowledge generation, accountability) of evaluation, and also highlighted the historical context that had influenced their development. The visualization shows that the end goal of all these evaluation approaches (i.e. the ocean in which the rivers flow towards) is societal improvement. Purpose: The article highlights the lessons learned and influences that led to the development of an evaluation theory categorization system. We hope that this would serve as an example (and maybe inspiration) for future efforts that aim to understand how evaluation theories have evolved and developed. Setting: Not applicable Intervention: Not applicable Research Design: Not applicable Data Collection and Analysis: Not applicable Findings: Not applicable Keywords: Evaluation theory, information visualization, evaluation historical context, organizing framework, theory development.

MCKP: Multi-aspect contextual knowledge-enhanced prompting for conversational recommender systems

Empowering conversational recommender systems (CRSs) with knowledge facilitates the generation of high-quality human-like recommendation proposals to users. Despite substantial endeavors in developing knowledge-based CRSs, they mainly focus on modeling entity knowledge by introducing external data, which cannot sufficiently contribute to understanding complex contextual semantics. Additionally, the source of knowledge relies on external data, ignoring the effective use of original training data, significantly increasing the cost of building efficient CRSs.To tackle the issues above, we explore how to leverage raw dialogue data for modeling and exploiting contextual knowledge to compensate for existing knowledge's shortcomings. Specifically, we first train knowledge generators by constructing multiple standard hybrid prompt templates and answer spaces, which is conducive to perceiving the reasons behind contextual connections from multiple aspects and storing corresponding contextual knowledge. Then, we design answer-guided prompt templates based on the answer space, closing the gap between inference and training of knowledge generators and facilitating the generation of aspect-specific contextual knowledge. Next, we extend our approach by harnessing external knowledge graphs to construct entity knowledge. We propose a local-to-global semantic fusion strategy to fuse knowledge representations from different sources better. Finally, based on the fused knowledge representations, we tailor contextual knowledge-enhanced prompt templates for the CRS to stimulate the reasoning ability of pre-trained language models on dialogue and recommendation tasks. We evaluate the performance of our method on separate evaluation datasets, including the ReDial and the INSPIRED datasets. Based on the Recall, MRR, NDCG, and Distinct evaluation indicators, we demonstrate the effectiveness of the proposed method in dialogue tasks and recommendation tasks. At the same time, we demonstrate that by constructing an interpretable multi-aspect hybrid prompt template, we can effectively mine contextual knowledge from multiple aspects of dialogue.

Investigating Preservice Teachers’ Conceptualizations of Mathematical Knowledge for Teaching Through Video Analysis

Mathematics Preservice Teachers’ (M-PSTs) conceptions of Mathematical Knowledge for Teaching (MKT) enhance their reflective skills because they utilize such conceptions to reflect on how to contextualize content knowledge during secondary mathematics teaching. While previous studies suggested M-PSTs develop MKT, including pedagogical content knowledge by analyzing teaching in video lessons, how M-PSTs enhance their conceptions of MKT through such analysis is underexplored. I used a collective case study approach to investigate how four secondary M-PSTs conceptualized MKT when they analyzed and discussed teaching represented in a video lesson using the MKT framework. The findings indicated that the M-PSTs often described teacher knowledge either as purely pedagogical or solely content knowledge in their initial analyses of the video lesson. After engaging in a discussion that introduced the MKT framework, the M-PSTs began to illustrate how a teacher’s content knowledge influenced her instructional decisions and actions. Through this discussion, M-PSTs began identifying MKT as professional content knowledge unique to teaching and, thus, distinguished MKT from generic pedagogical or content knowledge. I argue that the language and concepts offered through the framework enhanced the M-PSTs’ conceptions of MKT and suggest that the instructional activities from this study contribute to developing M-PSTs as reflective practitioners.

Understanding the academic use of KM-driven Metaverse technology: insights from medical colleges

Purpose This study delves into the behavioural intentions of educators within medical colleges at Mosul Universities concerning the adoption of Knowledge Management-Driven Metaverse technology (KM-D-MT). Rooted in an adapted Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model, the research aims to enrich the understanding of Metaverse adoption factors, exploring correlations among key constructs such as performance expectancy, effort expectancy, social influence, facilitating conditions, perceived value, hedonic motivation and interaction. Furthermore, the study investigates the mediating roles of knowledge generation and knowledge sharing in the relationship between interaction and behavioural intention. Design/methodology/approach The research employs a quantitative approach, gathering 278 responses from educators in medical colleges. Structural Equation Modelling-Partial Least Squares (SEM-PLS) is used to analyse the data, rigorously examining the reliability and validity of research instruments. The investigation involves an extensive evaluation of various factors influencing educators’ intentions to adopt KM-D-MT, using a cross-sectional design. Findings The study reveals significant positive impacts of performance expectancy, effort expectancy, social influence, facilitating conditions, perceived value and hedonic motivation on behavioural intention to adopt KM-D-MT. Interaction is identified as a key factor positively influencing knowledge sharing and knowledge generation. Furthermore, knowledge sharing and knowledge generation exhibit positive correlations with behavioural intention. Interaction indirectly impacts behavioural intention through the mediating roles of knowledge generation and knowledge sharing, highlighting the transformative potential of Metaverse technology in reshaping knowledge processes. Practical implications The findings of this study hold practical implications for educators, institutions and policymakers. The adoption of KM-D-MT can enhance educational experiences, facilitate global collaboration and contribute to the continuous professional development of educators in medical colleges. Institutions are encouraged to strengthen technological and organisational infrastructure to support effective Metaverse implementation. Furthermore, promoting positive social norms, providing technical support and offering training programs can contribute to overcoming barriers and fostering a conducive environment for Metaverse adoption in medical education. Originality/value This research significantly contributes to theoretical perspectives by advancing Metaverse research and addressing the call for extensive studies covering theoretical, conceptual and empirical elements. It extends current UTAUT2 frameworks, exploring correlations in the context of medical education and contributes to knowledge management paradigms. The study’s originality lies in its exploration of Metaverse acceptance in higher education institutions, specifically in medical colleges in Iraq, providing valuable insights for further research and practical applications globally.

Field Experiments: Here Today Gone Tomorrow?

Once believed to be an impossibility, field experiments in economics now occupy a central place in the empiricist’s quiver. In the past few decades alone, field experiments have taken on much greater import in academe, across organizations, as well as for policymakers. But is this emergence simply a fad that will soon return field experiments to obscurity? I argue in this article that there is something fundamental about the emergence of field experiments, as controlling the assignment mechanism in the field provides unparalleled power to both understand the “effects of causes” and the “causes of effects”. This knowledge generation then begins to uncover the generalizability of knowledge. Quite the opposite of a withering tool that will be gone tomorrow, I urge economists to “double down” on this comparative advantage and in doing so I provide four methodological paths which I hope will cement the promise and growth of field experiments in the social sciences.

Социально-экономические проблемы реализации подходов к обучению в звеньях «индивид-группа-организация», осуществляемых в интересах наращивания объемов знаний

The relevance of the presented study is determined by the fact that as the post-industrial society develops, more and more attention is paid to the knowledge economy, the basic components of which are the generation and training of new knowledge. At the same time, the accumulation of this knowledge by organizations in the competitive struggle is of fundamental importance. Currently, there are quite a lot of approaches to considering training in the individual-group-organization links both as processes and as modeled structures, including in the interests of the strategic development of the organization. At the same time, an obvious drawback of the known approaches is the hypothesis of a monotonous increase in the volume of knowledge in the organization without taking into account the socio-economic problems arising in the process of acquiring and using new knowledge. The purpose of the presented studies is to identify the problems of implementing approaches to training in the individual-group-organization links in the interests of increasing the volume of knowledge, conditioned by the socio-economic aspects of acquiring and using new knowledge in a competitive environment, from the standpoint of strategic development. The scientific novelty of the obtained results lies in the identification of the key problem of the transition from tacit knowledge to explicit knowledge, caused by agency conflicts associated with the rights to this type of intangible asset between an individual generating new knowledge and an organization seeking to convey this knowledge through training to its employees. The practical significance of the research results lies in the possibility of their use in the implementation of approaches to training in the individual-group-organization links both within the framework of the concept of management based on the use of human capital in the 2030s and within the framework of the concept of management based on the use of the intellectual capital of an organization in the 2040s.

Conceptualizing the Digital Pedagogy in Arts Higher Education: Examining the Roles of Training, Technology Support, and Teacher Mindsets

In this concept paper, the propositions for incorporating professional development, ICT awareness, and technical support to introduce technology incorporation practices among College of Arts instructors are discussed. Drawing from past research in practice, this study’s conceptual framework posits value and ability beliefs as the mediators of technology integration practices. This research establishes professional development, ICT knowledge, and technical assistance as determinants of technology integration practices for learning in the study and looks at the value and ability beliefs and their impact on the instructors’ decision to integrate technology into the teaching practice. This work contributes to the generation of practical and theoretical knowledge for designing effective technology integration in arts education practices, underscoring the centrality of the multipronged perspectives of instructors’ belief, content, and practice knowing. In this case, this study seeks to improve the quality of arts education and better prepare College of Arts students for the job market of the still-growing technology focused era by raising the level of preparedness for integrating technology into lessons of the College of Arts instructors.

A framework for decolonising and diversifying biomedical sciences curricula: rediscovery, representation and readiness.

To date, most efforts to decolonise curricula have focussed on the arts and humanities, with many believing that science subjects are objective, unbiased, and unaffected by colonial legacies. However, science is shaped by both contemporary and historical culture. Science has been used to support imperialism, to extract and exploit knowledge and natural resources, and to justify racist and ableist ideologies. Colonial legacies continue to affect scientific knowledge generation and shape contemporary research priorities. In the biomedical sciences, research biases can feed into wider health inequalities. Reflection of these biases in our taught curricula risks perpetuating long-standing inequities to future generations of scientists. We examined attitudes and understanding towards decolonising and diversifying the curriculum among students and teaching staff in the biomedical sciences at the University of Bristol, UK, to discover whether our current teaching practice is perceived as inclusive. We used a mixed methods study including surveys of staff (N = 71) and students (N = 121) and focus groups. Quantitative data showed that staff and students think decolonising the curriculum is important, but this is more important to female respondents (P < 0.001). Students are less aware than staff of current efforts to decolonise the curriculum, while students from minority ethnic groups feel less represented by the curriculum than white students. Thematic analysis of qualitative data revealed three themes that are important for a decolonised curriculum in our context: rediscovery, representation and readiness. We propose that this '3Rs framework' could guide future efforts to decolonise and diversify the curriculum in the biomedical sciences and beyond.

Adversarial Multi-Teacher Distillation for Semi-Supervised Relation Extraction.

The shortage of labeled data has been a long-standing challenge for relation extraction (RE) tasks. Semi-supervised RE (SSRE) is a promising way through annotating unlabeled samples with pseudolabels as additional training data. However, some pseudolabels on unlabeled data might be erroneous and will bring misleading knowledge into SSRE models. For this reason, we propose a novel adversarial multi-teacher distillation (AMTD) framework, which includes multi-teacher knowledge distillation and adversarial training (AT), to capture the knowledge on unlabeled data in a refined way. Specifically, we first develop a general knowledge distillation (KD) technique to learn not only from pseudolabels but also from the class distribution of predictions by different models in existing SSRE methods. To improve the robustness of the model, we further empower the distillation process with a language model-based AT technique. Extensive experimental results on two public datasets demonstrate that our framework significantly promotes the performance of the base SSRE methods.

The Dynamics of Islamic Educational Institutions Management

This research aims to explain the dynamics of Mathla’ul Anwar educational institution from a management perspective. This research type is qualitative with a Library Research approach. The research data is in the form of data about The dynamics of Mathla’ul Anwareducational institution from its management aspect from primary sources in the form of books on the dynamics of educational institutions, Mathla'ul Anwar educational institutions, book development institutions in Islamic education and relevant journals. Data collection techniques were carried out using documentation studies. The researchers' data sources were obtained from books and journals about the dynamics of Mathla’ul Anwar educational institution from a management perspective. Data analysis uses Content Analysis. Based on the research results obtained, the dynamics of Mathla’ul Anwar educational institution in terms of management shows that this institution has succeeded in integrating various important elements in education to achieve its main goals. With a strong historical background and commitment to Islamic values, Mathla'ul Anwar continues to innovate and adapt to changing times. Management aspects, which include planning strategies, organizational structure, curriculum development, monitoring, and evaluation, as well as the development of human resources and facilities, have been implemented well. Overall, effective and efficient management at Mathla'ul Anwar has produced an educational institution that not only focuses on academic achievement but also builds the character and morals of students. This institution is able to face challenges and make good use of opportunities, continuing to be committed to producing a generation of knowledge, faith, and piety. Through good management, it is hoped that Mathla'ul Anwar can continue to make a meaningful contribution to the progress of education in Indonesia. Thus, this conclusion shows that the Mathla'ul Anwar educational institution continues to innovate and adapt to changing times and can make a positive contribution to creating a better educational institution.

The nexus of fertility and politics: exploring the influence of social tolerance, religiosity, and political conservatism on the acceptance of assisted reproduction in Spain.

How do individual religious, political, and social tolerance orientations influence the acceptance of ART among Spanish citizens? Social tolerance and religiosity are predictive factors for the acceptance of ART, with more tolerant individuals and those with lower levels of religiosity being more accepting of ART; political conservatism mediates the relationship between social tolerance and acceptance of ART, particularly for left-leaning individuals. The rapid advancement of ART has raised questions about its societal acceptance, especially in the context of religious, political, and social beliefs. The analysis utilized data from the combined Europe Values Study and World Values Survey, comprising cross-sectional national surveys from 1981 to 2021. Each country's population was surveyed a maximum of seven times and a minimum of two times during this period. This study uses the cross-sectional data of 2021. After filtering for Spanish citizens and deleting cases with missing key variables, a sample of 1030 valid responses from Spanish citizens was obtained. Quotas were set for sex, age, and educational level, following guidance from the Spanish Statistics Institute. The study surveyed participants' attitudes towards ART, their religious and political orientations, and collected demographic information. The sample consisted of 51.7% women, most respondents were married or in common-law partnerships, and 61.6% had children. Catholicism was the dominant religion (53.0%) and a majority had completed secondary education (66.2%), with half earning over 1400 euros per month. Using two linear models to test hypotheses, the study found that social tolerance and religiosity significantly predict acceptance of ART, with more tolerant and less religious individuals being more accepting. Political conservatism mediated the relationship between social tolerance and ART acceptance, particularly among left-leaning individuals. This study is cross-sectional and based on self-reported data, which may have limitations. Additionally, the findings are based on a Spanish sample and may not be universally applicable. The results have significant implications for policymakers and healthcare professionals in the field of reproductive technologies. They also contribute to public debates on ethical considerations surrounding ART. This work was funded by the Mineco-FrontVida Program, Frontiers of Life, Social Change, and Changing Values Around the Beginning and End of Life (grant number PID2019-106882RB-I00), as part of the State Program for Knowledge Generation and Scientific and Technological Strengthening, and the State R&D Program Oriented to the Challenges of Society, 2019, Ministry of Science, Innovation, and Universities of Spain. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. N/A.

Outcomes of Concept-Based Curricula: An Integrative Review.

Complexity and change in health care environments, the rapid pace of knowledge generation, and changing education policy have led to national calls for change in nursing education. Many nursing programs have adopted a concept-based curriculum (CBC) to address these challenges. Yet, much is still uncertain about the outcomes and effectiveness of CBC, which requires large scale, time-consuming, and resource-intensive change. This integrative review assesses the outcomes of CBC in nursing higher education with a focus on the comparison of CBC to traditional curricula. The four relevant themes that emerged after an extensive literature review were critical thinking/clinical judgment, NCLEX-RN© (National Council Licensure Examination for Registered Nurses) pass rates, graduation rates, and student satisfaction scores. Overall, the evidence base is not robust. A valid and reliable tool to measure clinical judgment is needed. The review specifically addresses CBC effects on student critical thinking and clinical judgment, traditional outcome metrics, (NCLEX-RN success, graduation rates, and student satisfaction), and other perceived benefits. The authors found promising results on the effect CBC may have on critical thinking and clinical judgment and other perceived benefits. Findings were inconclusive on traditional outcome metrics. [J Nurs Educ. 2024;63(X):XXX-XXX.].

Clustering Open Data for Predictive Modeling of Residential Energy Consumption across Variable Scales: A Case Study in Andalusia, Spain

The energy budget of households, linked to residential energy consumption (REC), serves as a critical indicator of quality of life and economy trends. Despite the lack of widely available accurate statistics at regional or smaller scales, they are of crucial interest for a better understanding of the features influencing REC and its impact on energy poverty, wellbeing, and the climate crisis. This research aims to present a new information model for predictive parameters and REC forecasting through an innovative use of available open data. Geoprocessing, data mining, and machine learning clustering algorithms were applied to open datasets of location, population, and residential building stock parameters highly correlated with their REC, on the ensemble of 785 municipalities of Andalusia, Spain. The model identified 65 clusters of towns sharing the same potential REC, with 73% of the population concentrated in 10 of these. The resulting data-driven bottom-up model of provincial REC had a mean absolute error of only 0.63%. Furthermore, it provided the territorial distribution, with local resolution, of the identified clusters of cities with similar characteristics. This methodology, with a flexible regional- to city-scale analysis, provides knowledge generation that offers numerous practical applications for energy policy planning. Its future implementation would assist stakeholders and policymakers in enhancing the performance and decarbonization of the residential building stock.