Knowledge In Form Research Articles

Dante entre o furor e os estudos

ABSTRACT This article analyzes a polemic of Italian Humanism around Dante Alighieri (1265-1321). In that period, intellectuals such as Cristoforo Landino (1424-1498) and Marsilio Ficino (1433-1499) interpreted Dante’s writing through the platonic prism of the Phaedrus, that is, as someone who was granted the grace to contemplate the divine and the power to describe it. Decades earlier, however, Coluccio Salutati (1331-1406) and Leonardo Bruni (1370-1444) had already attributed to Dante the merit of focusing on formal studies and, with that, being able to develop expressive artifices to his poetry on its own. For the analysis of the different readings, excerpts in which Dante gives evidence of his path and intellectual maturity will be observed, as well as those in which it is possible to observe the poet’s role in the dissemination of formal knowledge in line with his ethical values.

Mentoring as a factor of professional development of medical workers

The healthcare sector is a complex and constantly evolving industry that requires a high level of skills, knowledge and ex­pertise. Mentoring programs implemented in the medical field (both at the university and college levels and at the level of individual medical organizations) provide students with access to the professional experience, knowledge and wisdom of older, more experienced colleagues in order to be able not only to receive formal knowledge within the educational process, but also to receive advice and recom­mendations from reputable professionals. Mentoring programs in medical schools have positive results, including: They contribute to better career guidance and specialization of students, career planning, participation in scientific research, as well as contribute to better adaptation in the educational environment and reduce the associated stress.

Does Formal Interorganizational Relationship Shape Interpersonal Knowledge Exchange in Multiteam Construction Projects? A Multi-Level Network Analysis

This study investigates the differences in structural patterns of intra-and inter-team knowledge exchange networks in multiteam construction projects and explores the cross-levelinteraction between knowledge exchange networks and interorganizational formal networks, as represented by networks of contractual and task interdependence relationships. An empirical study is developed by using multiple exponential random graph models. The findings show that a discrepancy between intra- and inter-team knowledge exchange structural patterns arises with respect to reciprocity. Interorganizational task interdependencies are found to align with cross-team knowledge exchange. Significant homophily in work experience is found in cross-team knowledge exchange. Interorganizational task interdependence promotes cross-team knowledge exchange among project members with heterogeneous expertise. This study expands the research on project-based multiteam system knowledge exchange networks from a multi-level network analysis perspective.

Wortschatzerwerb – Wortschatzdidaktik – Wortschatzarbeit

Abstract Well-developed vocabulary skills are crucial for effective communication. Didactically speaking, it is therefore essential to explicitly foster the development of lexical competence in the classroom. This applies to both learners of German as a first and second language. The design of systematic vocabulary activities should aim to increase both the quality and quantity of learners‘ word knowledge and to ensure long-term retention of acquired words. While various approaches exist for teaching vocabulary in foreign language teaching, systematic and targeted approaches for supporting vocabulary acquisition in teaching German as a first language have yet to be established and, more importantly, effectively implemented in the classroom. Drawing upon findings from language acquisition research and linguistic models, we propose a framework for explicit vocabulary activities that facilitates the integration of new words into learners‘ mental lexicons (vocabulary breadth) and, in connection with this, promotes the development of semantic, relational, and formal word knowledge (vocabulary depth). The article will demonstrate how this framework was implemented in Deutsch Kindergarten, a new teaching resource developed in Switzerland. It will also highlight broader didactic principles, such as criteria for vocabulary selection and principles for vocabulary teaching, which should be considered in the classroom.

Cultivating writing skills: the role of ChatGPT as a learning assistant—a case study

Artificial intelligence (AI) has garnered considerable interest in the field of language education in recent times; however, limited research has focused on the role of AI in the specific context of register knowledge learning during English language writing. This study aims to address this research gap by examining the impact of ChatGPT, an AI-powered chatbot, on the acquisition of register knowledge across various writing tasks. The research design employed a one-case shot pre-experimental design, with 11 voluntary participants selected through convenience sampling. Preliminary results indicate that students found ChatGPT beneficial for acquiring formal register knowledge but perceived it as unnecessary for informal writing. Additionally, the effectiveness of ChatGPT in teaching neutral register was questioned by the participants. This research contributes to the existing literature by shedding new light on the effects of AI-generated chatbots in register learning during the writing process, offering insights into their potential as learning assistants. Further investigation is warranted to explore the broader implications and applications of AI in language learning contexts.

Interorganizational Knowledge Transfer in Mass Gatherings: Exploring the Health and Safety Stakeholders' Perceptions Participating in the Athens Marathon.

Mass gatherings (MGs) usually represent significant challenges for the public health and safety sector of the host cities. Organizing a safe and successful mass event highly depends on the effective collaboration among different public and private organizations. It is necessary to establish successful coordination to ensure that all the key stakeholders understand their respective roles and responsibilities. The inconsistency between the variety of participating agencies because of their different culture can result in delays in decision making. Interorganizational knowledge transfer can improve the success of the event; however, knowledge transfer among professionals and agencies in MGs is not well-documented. This study used the 2018 Athens Marathon as the empirical setting to examine how interorganizational knowledge transfer was perceived among the multiple public health and safety professionals during the planning stage of the event. Data comprised 18 semi-structured, in-depth interviews with key informants, direct observations of meetings, and documentary analysis. Open coding and thematic analysis were used to analyze the data. Findings indicated that sharing the acquired knowledge was a necessary and challenging step to create an enabling collaborative environment among interacting organizations. Experiential learning was identified as a significant factor, which helped promote joint understanding and partnership work. Informal interpersonal exchanges and formal knowledge transfer activities facilitated knowledge sharing across organizational boundaries, helping to break down silos. Interorganizational knowledge transfer is a necessary step to achieve joint understanding and create an environment where interaction among agencies can be more effective. The study findings can be beneficial for organizers of marathons and other mass sporting events to support valuable interorganizational collaboration and conduct a safe event.

Designing a smart city sustainability assessment information system based on the adapted SULPiTER methodology

Increasing number of smart cities, the rise of technology and urban population engagement in urban management, and the scarcity of open data for evaluating sustainable urban development determines the necessity of developing new sustainability assessment approaches. This study uses passive crowdsourcing together with the adapted SULPiTER (Sustainable Urban Logistics Planning to Enhance Regional freight transport) methodology to assess the sustainable development of smart cities. The proposed methodology considers economic, environmental, social, transport, communication factors and residents’ satisfaction with the urban environment. The SULPiTER relies on experts in selection of relevant factors and determining their contribution to the value of a sustainability indicator. We propose an alternative approach based on automated data gathering and processing. To implement it, we build an information service around a formal knowledge base that accumulates alternative workflows for estimation of indicators and allows for automatic comparison of alternatives and aggregation of their results. A system architecture was proposed and implemented with the Astana Opinion Mining service as its part that can be adjusted to collect opinions in various impact areas. The findings hold value for early identification of problems, and increasing planning and policies efficiency in sustainable urban development.

Imperative Formal Knowledge Representation for Control Engineering: Examples from Lyapunov Theory

In this paper, we introduce a novel method to formally represent elements of control engineering knowledge in a suitable data structure. To this end, we first briefly review existing representation methods (RDF, OWL, Wikidata, ORKG). Based on this, we introduce our own approach: The Python-based imperative representation of knowledge (PyIRK) and its application to formulate the Ontology of Control Systems Engineering (OCSE). One of its main features is the possibility to represent the actual content of definitions and theorems as nodes and edges of a knowledge graph, which is demonstrated by selected theorems from Lyapunov’s theory. While the approach is still experimental, the current result already allows the application of methods of automated quality assurance and a SPARQL-based semantic search mechanism. The feature set of the framework is demonstrated by various examples. The paper concludes with a discussion of the limitations and directions for further development.

“I notice I'm getting more involved, interested, and excited about my future topic.” Action research as a transition from research steps to navigating graduate students' scholarly dispositions

Graduate students often approach research with predefined steps emphasising procedural aspects that occasionally expose their inadequate preparation for research as social practice. The purpose of this paper is to show how an action research (AR) methodology, in conjunction with English for Specific Purposes (ESP) and Systemic Functional Linguistics (SFL), has facilitated the scaffolding of explicit formal, rhetorical, procedural, and strategic knowledge in research discourse. We followed a cyclical action research model consisting of 1) recognising students' limited understanding of research as a social practice, 2) developing interventions to promote understanding of how language is structured, represented, and negotiated in scientific discourse, 3) results of the intervention, and 4) reflection. Thematic analysis of six participants' data, including their tasks, reflections, and draft proposals, revealed a discernible progression towards scholarly thinking, transformative learning, and the embodiment of scholarly identity. Integrating ESP and SFL frameworks enhanced our ability to guide students through research-specific discourses, moving beyond a purely theoretical understanding to engage in authentic practices. This approach contributed to the cultivation of Communities of Practice (CoP) in which student-faculty collaboration fostered a shared scholarly mindset and facilitated the gradual integration of students into these academic communities.

Towards a knowledge graph framework for ad hoc analysis in manufacturing

The development of artificial intelligence models for data driven decision making has a lot of potential for the manufacturing sector. Nevertheless, applications in industry are currently limited to the actionable insights one can discover from the available data and knowledge of a manufacturing system. We call the process to obtain such insights “ad hoc analysis”. Ad hoc analysis at system level is very complex in an industrial setting due to the inherent heterogeneity of data and existence of data silos, the lack of information and knowledge formalization, and the inability to meaningfully and efficiently reason about the data, information and knowledge. In this paper, we provide and outline a framework for ad hoc analysis in manufacturing based on knowledge graphs and influenced by the metamodelling paradigm. We derive its requirements and key elements from an analysis of several industry application cases. We show how manufacturing data, information and knowledge can be combined and made actionable using this framework. The framework supports workflows and tools for the data consumer (i.e., data scientist), and for the knowledge engineer. Furthermore, we show how the framework is integrated with existing data sources. Then, we discuss how we applied the framework to several application cases. We discuss how the framework contributes when applied, and what challenges still remain.

Determinants of Smallholder Farmer Maize Production Efficiency in Western Parts of Oromia in Boneya Boshe woreda, East Wollega Zone: Evidence under Shifting Cultivation Area

Farming in Ethiopia can offer assistance in bringing dejected needs. Hence, the best possible means of achieving growth is by increasing the production efficiency of farmers. To estimate the levels of production efficiency, this study specifically used only data from farmers who are producing without plowing by oxen and without using fertilizers in the study area under shifting cultivation. Method: To determine the determinants of production efficiency, the Tobit model was used in this study. Result. The Tobit model results show that age of household, and herbicide use had a negative impact on the production efficiency of farmers. Regarding the positive determinants of production efficiency, labor, seed, and fertilizer (NPS) have a positive influence. Conclusion and Recommendation: The farmers in the study area are efficient in the production of maize. The government should give due attention to farmers' training by strengthening farmers' education and farmer training centers to make farmers more efficient producers and profitable by integrating local and traditional knowledge of farmers with formal knowledge of using herbicides. Farmers should also be advised, as they are youngest farmers engaging in farming work. Otherwise, the government should supply fertilizer and improve seed on credit.

Initial and continuing education of the pedagogue: what researches involving the teaching of mathematics indicate

The process of acquiring formal knowledge begins in the first stages of basic education, which makes the teacher in the early years of elementary school, the Pedagogue, the professional responsible for this process. Understanding the training of these professionals for teaching mathematical concepts, such as geometric concepts, at this level of education is necessary. In this sense, in this production, an excerpt from a larger research developed during the doctorate of the first author, under the guidance of the second, it is proposed to carry out a bibliographic research, in order to answer the following question: How does the training, both initial and education, from the pedagogue for the teaching of Mathematics/Geometry in the early years of elementary school is presented in research carried out from 2017 to 2021? To this end, a survey was carried out regarding the approach to this theme in research carried out in dissertations and theses, available on the Capes portal. In this way, it can be said that these studies point to the importance of initial and continuing education for the performance of the pedagogue, with regard to the teaching of Mathematics/Geometry in the Initial Years of Elementary School, as such training makes it possible to remedy possible gaps still on the understanding of these concepts, in addition to providing access to resources and methodologies aimed at the teaching process of this area of knowledge and the exchange of experience between these professionals.

Reflection on action by activation workers as professional learning strategy

ABSTRACT In this article, social work theory on reflective practice is used to explore the potential value of reflection on action for professional learning by activation workers who support people receiving welfare benefits to find work. The article focuses on the role of reflection on action in professional learning concerning three challenges which activation workers face: dealing with normative dilemmas, translating formal and informal knowledge into decision-making and dealing with power relations. The article presents tentative findings stemming from qualitative research on Dutch activation workers participating in reflection on action. Participants report multiple learning outcomes concerning these challenges. The theoretical and empirical exploration suggests that reflection on action can support learning by activation workers to better deal with professional challenges inherent to their work. However, these empirical findings are preliminary and based on a specific context. Further exploration by both scholars and practitioners is therefore suggested, in which the social work profession has a lot to offer.

Sensing complicated meanings from unstructured data: a novel hybrid approach

The majority of data on computers nowadays is in the form of unstructured data and unstructured text. The inherent ambiguity of natural language makes it incredibly difficult but also highly profitable to find hidden information or comprehend complex semantics in unstructured text. In this paper, we present the combination of natural language processing (NLP) and convolution neural network (CNN) hybrid architecture called automated analysis of unstructured text using machine learning (AAUT-ML) for the detection of complex semantics from unstructured data that enables different users to make understand formal semantic knowledge to be extracted from an unstructured text corpus. The AAUT-ML has been evaluated using three datasets data mining (DM), operating system (OS), and data base (DB), and compared with the existing models, i.e., YAKE, term frequency-inverse document frequency (TF-IDF) and text-R. The results show better outcomes in terms of precision, recall, and macro-averaged F1-score. This work presents a novel method for identifying complex semantics using unstructured data.

Model‐Based Framework for Data and Knowledge‐Driven Systems Architecting Demonstrated on a Hydrogen‐Powered Concept Aircraft

ABSTRACTAircraft development is a protracted process over many years. Novel concept aircraft with new energy sources and disruptive systems technologies are investigated during the aircraft conceptual design phase with the goal to achieve sustainable aviation. Current development cycles need to be accelerated to reduce time to market and development costs of novel aircraft, while still handling complexity and uncertainty of systems technologies. Therefore, a holistic framework for knowledgebased systems architecting using a model‐based systems engineering approach is presented. This framework has the purpose to conserve and provide knowledge, that is, information, data, and experiences about existing systems architectures, to the engineer. The developed framework consists of a database concept, a method for model‐based systems architecting, and an interface to the overall systems design software tool GeneSys. Based on evaluating different modeling languages and tools, MathWorks System Composer is selected as most suitable tool for knowledge‐based systems architecting. The developed framework is then demonstrated by conserving and reusing formalized knowledge for the design of a novel hydrogen‐powered concept aircraft. On‐board systems architecture models are saved in a database and automatically recreated reducing development time. The complete graphical representation could not yet be stored in a formalized manner partly reducing the advantage of a clear representation of model‐based systems architecting. However, this did not reduce automatic recreation and evaluation capabilities.

Knowledge ambidexterity in construction project-based organizations: predicaments of knowledge networking intention within outbound consultant-supplier interfaces

PurposeAgenda for knowledge creation within inter-project alliances and inter-firm supply chain networks has been extensively debated. However, the existing knowledge networks within consultant-supplier interfaces in the architecture, engineering and construction (AEC) industry seem to be vague, loose, incidental and insignificant. This study examines factors affecting knowledge networking intention (KNI) within construction service supply chain (CSSC) networks.Design/methodology/approachData analysis was conducted on a quantitative survey of 161 consulting professional service firms in Tanzania, employing stepwise regression modelling as the statistical technique.FindingsThe results indicate that three types of knowledge inertia (KI) exert varying effects on KNI. While both procedural (PI) and learning inertia (LI) negatively impact KNI, experience inertia (EI) has no impact on KNI. In addition, knowledge governance (KG) mechanisms are found to strongly strengthen and leverage the negative effects of PI and LI on KNI and the positive link between EI and KNI within outbound and heterogeneous CSSC actors, with formal KG having greater leverage than informal KG.Practical implicationsThe study offers guidance on how managers of PBOs should strategically orchestrate knowledge governance mechanisms within CSSC networks to leverage KI behaviours.Originality/valueCurrent literature on KNI, KI and KG within CSSC networks offers a limited understanding of how KI behaviours influence KNI of project-based organizations (PBOs) in tapping vibrant outbound peripheral knowledge. The research presents two major original contributions. First, the empirical evidence contributes to deepening the current understanding of how heterogeneous external knowledge within consultant-supplier interactions is negatively influenced by KI. Lastly, the study suggests formal and informal knowledge governance strategies for managers on how to counteract KI forces, thus extending the theoretical debate on KNI, KI and KG literature.

Formalization of Digital Knowledge And Modern Approaches to Data Management

Formalization of Digital Knowledge And Modern Approaches to Data Management

Overcoming Fuzziness with Semantic Modeling and AI

Today, customer service in mechanical engineering struggles with a wide variety of challenges when it comes to providing relevant information for specific use cases. The information requirements of service technicians, on the other hand, have increased enormously. On the one hand due to increasingly complex products, but also due to the growing shortage of trained specialists. Fast and efficient provision of relevant information is essential. Remote assistance systems and portal solutions are being used to meet these challenges. A heterogeneous information landscape, characterized by data silos, makes this difficult. In a preliminary study, the authors have developed an approach based on the formalization of knowledge in knowledge graphs that bridges the data silos and thus enables efficient information provision by linking information based on use cases. However, this approach requires high data quality and suitable metadata concepts. Inaccuracies in classification systems create unwanted fuzziness when linking information. The study based on this shows how the fuzziness can be eliminated by supplementary modeling of context information and by extended modeling methods in the form of so-called DynaRules. The authors also compare how AI methods and DynaRules can be used to check the plausibility of deep links with potential fuzziness.

User Experience Techniques Adopted by Brazilian Game Development Studios: An Exploratory Study

Game development studios deal with numerous challenges to achieve the publication of games that are acclaimed by the public. The difficulties range from a simple choice of color for a particular object within the game to mechanics and narratives. In this way, user experience (UX) techniques provide a better perception of the player’s experience. UX techniques are consolidated in the context of software engineering industries and literature. However, few works in the literature (which will be presented in this work) address this knowledge and treat digital games as a specific type of software. In this sense, we aim to explore and present innovative approaches and best techniques adopted by game development studios to integrate UX into their processes. The research included the participation of 41 digital game development studios from all regions of Brazil, of which 31 were interviewed and 10 chose to participate via questionnaire. The analysis revealed that many participants work in small companies (up to five employees) and apply UX techniques intuitively without formal knowledge and justification for using them. Furthermore, we noticed that many studios are unclear about their techniques and confuse them with game design. However, most understand that UX is fundamental for designing a successful game with community support and buy‐in. In addition, most of the justifications for not using UX techniques converged on a lack of knowledge. Finally, we developed a visual scheme to assist studios and future research, capable of consolidating the information extracted from participants about the UX techniques adopted, the benefits and challenges of applying them to the development process, the justifications for not adopting UX techniques (when not adopted), the test instruments implemented, and the UX dimensions evaluated by them.

The correlation between formal education and knowledge of used cooking oil management at Kampung Tersenyum society in South Jakarta

The phenomenon of used cooking oil collection at Kampung Tersenyum in South Jakarta has not been optimal. According to the data, there are only 36 sub-districts out of 65 sub-districts in South Jakarta that have been monitored to collect used cooking oil in the period October 2019 – June 2020. This research aims to analyze the knowledge of used cooking oil management in Kampung Tersenyum Society, South Jakarta. This research used a quantitative descriptive method. The population in this research is the residents of Kampung Tersenyum, South Jakarta. The sampling technique in this research was carried out with a purposive sampling method of 60 respondents. Data collection techniques used observation and interviews with questionnaires. Data analysis used percentage descriptive techniques. The results of the research showed that the last formal education majority of the society is at the high school level. The knowledge of used cooking oil management in South Jakarta is in the high category. From the results of the analysis, it was found that there is a correlation between formal education that has been taken with waste management knowledge which is the majority of elementary and junior high school education are knowledgeable in the category tends to be low, while the majority of education at the senior high school, bachelor,and master levels are knowledgeable in the high category.