Structured Knowledge Acquisition Research Articles

Holacracy: redefining organizational ontology and epistemology

Purpose This paper aims to examine Holacracy as a self-management system and its implications for organizational theory. By exploring its distinctive ontology and epistemology, the paper explains how Holacracy redefines organizational structures and contributes to organizational change. Design/methodology/approach Adopting a conceptual approach, this essay draws upon existing literature to explore Holacracy’s departure from conventional organizational theories. Findings The paper discusses how Holacracy challenges traditional organizational concepts, defining its holarchical approach, and emphasizing dynamic hierarchies and role-based organization. It also highlights Holacracy’s focus on emergent intelligence, continuous feedback loops and structured knowledge acquisition through roles and organization spaces. By examining its unique ontology and epistemology, the paper offers insights into how Holacracy aligns with an emergent paradigm known as integral, metamodern or teal. Research limitations/implications Further empirical research is needed to assess its practical implementation and long-term effects on organizational performance and employee well-being. Future studies could also explore challenges and limitations associated with adopting Holacracy in different organizational contexts. Practical implications Organizations considering alternative ways of working should examine Holacracy. Implementing Holacracy requires understanding its principles and may involve significant changes, with potential benefits such as increased agility and employee engagement. Social implications Holacracy’s departure from traditional structures and approach to power can have broader social implications and contribute to more democratic and participatory cultures. Originality/value This paper is a pioneering contribution to the under-researched domain of alternative organizational models. It sheds light on the originality and distinctiveness of Holacracy, highlighting its unique approach to hierarchy, role-based organization and consciousness within organizations.

Effect of Knowledge Acquisition on Organizational Performance

In today's ever-evolving and fiercely competitive business environment, the acquisition, assimilation, and effective utilization of knowledge have emerged as quintessential drivers of organizational success. Knowledge acquisition, which encompasses not just the accumulation of data but also the cultivation of tacit and explicit knowledge, plays a pivotal role in fuelling innovation, facilitating informed decision-making, and fostering adaptability. This study examines the impact of knowledge acquisition on organizational performance, with a null hypothesis guiding the inquiry. The research design adopted was survey research, A purposive technique was utilized. A sample size of 412 respondents from selected manufacturing companies in Oyo State, Nigeria, formed the study's subject group. Data collection was executed through a questionnaire, with a rigorous validation process. The findings of this study indicate a significant positive effect of knowledge acquisition on organizational performance. Enhanced knowledge acquisition is shown to empower organizations to achieve sustainability by developing new competencies that cascade across different organizational levels. This underscores the vital role of knowledge acquisition in positively influencing organizational performance. It was recommended that organizations invest in structured knowledge acquisition processes, mentorship programs, and knowledge management systems. Fostering a culture of continuous learning and knowledge sharing should also be a top priority, as these measures are poised to yield substantial enhancements in overall organizational performance and long-term sustainability.

Continual Learning, Fast and Slow.

According to the Complementary Learning Systems (CLS) theory (McClelland et al. 1995) in neuroscience, humans do effective continual learning through two complementary systems: a fast learning system centered on the hippocampus for rapid learning of the specifics, individual experiences; and a slow learning system located in the neocortex for the gradual acquisition of structured knowledge about the environment. Motivated by this theory, we propose DualNets (for Dual Networks), a general continual learning framework comprising a fast learning system for supervised learning of pattern-separated representation from specific tasks and a slow learning system for representation learning of task-agnostic general representation via Self-Supervised Learning (SSL). DualNets can seamlessly incorporate both representation types into a holistic framework to facilitate better continual learning in deep neural networks. Via extensive experiments, we demonstrate the promising results of DualNets on a wide range of continual learning protocols, ranging from the standard offline, task-aware setting to the challenging online, task-free scenario. Notably, on the CTrL (Veniat et al. 2020) benchmark that has unrelated tasks with vastly different visual images, DualNets can achieve competitive performance with existing state-of-the-art dynamic architecture strategies (Ostapenko et al. 2021). Furthermore, we conduct comprehensive ablation studies to validate DualNets efficacy, robustness, and scalability.

Masked image modeling-based boundary reconstruction for 3D medical image segmentation

Accurate segmentation of 3D medical images is vital for computer-aided diagnosis. However, the complexity of target morphological variations and a scarcity of labeled data make segmentation more challenging. Furthermore, existing models make it difficult to fully and efficiently integrate global and local information, which hinders structured knowledge acquisition. To overcome these challenges, we introduce the TNT Masking Network (TNT-MNet), a groundbreaking transformer-based 3D model that utilizes a transformer-in-transformer (TNT) encoder. For the first time, we present masked image modeling (MIM) in supervised learning, utilizing target boundary regions as masked prediction targets to enhance structured knowledge acquisition. We execute multiscale random masking on inner and outer tokens in online branch to tackle the challenge of segmenting organs and lesion regions with varying structures at multiple scales and to enhance modeling capabilities. In contrast, the target branch utilizes all tokens to guide the online branch to reconstruct the masked tokens. Our experiments suggest that TNT-MNet’s performance is comparable, or even better, than state-of-the-art models in three medical image datasets (BTCV, LiTS2017, and BraTS2020) and effectively reduces the dependence on labeled data. The code and models are publicly available at https://github.com/changliu-work/TNT_MNet.

The Impact of a Gross Anatomy Curriculum With Donor Family Interaction: Thematic Analysis of Student Letters to Silent Mentors.

PurposeTzu Chi University’s anatomy curriculum incorporates interaction with donors’ families and regards body donors as silent teachers and altruistic role models. In this silent mentor program (SMP), students learn about their donor’s life before dissection to better appreciate the selfless donation. This study explores the influence of the program on students’ humanistic literacy based on student letters to silent mentors, which students wrote near the end of the program and laid by the silent mentor during the coffining ceremony.MethodThe study included 125 letters from third-year medical students who took the gross anatomy curriculum in academic years 2015, 2016, and 2017. With student consent, the program collated and published the letters in the open-access SMP yearbook. Using thematic analysis, the authors manually analyzed the letters in their original Mandarin, with the names of students made anonymous to ensure the authors were blind to students’ identity throughout the study.ResultsThe analysis identified 3 themes and 11 subthemes. Theme 1, my silent mentor, included 3 subthemes: life characteristics, altruistic attitude, and expectation of offering body. Theme 2, connection to silent mentor and family, included 4 subthemes: intersubjective bonding, emotive first encounter, spiritual communication, and encouragement from silent mentor. Theme 3, reflection and transformation, included 4 subthemes: reflection on life and death, professional self-expectation, inner transformation, and feedback action.ConclusionsThe findings suggest that interactions with donors’ families increased students’ appreciation of the donation and enhanced students’ humanistic literacy. Further, the letters seem to indicate that the SMP inspired students to develop a grateful, respectful, and empathic attitude toward life and their career. Thus, by implementing similar programs, gross anatomy curricula could go beyond the acquisition of structural knowledge to the cultivation of medical students’ humanistic literacy.

Empirical research on how social capital influence inter-organizational information systems value co-creation in China

ABSTRACT Previous literature revealed that the lack of knowledge resources and the existence of an assimilation gap may be responsible for the high failure rate in the Inter-Organizational Information Systems (IOS) post-adoption stage of value co-creation. Drawing on social capital theory and knowledge-based theory, this paper aims to explore how structural (social interaction), relational (trust), and cognitive (shared IOS vision) capital influences knowledge acquisition among key partners and further improves IOS assimilation and value co-creation. The hypotheses, proposed in this work, were tested by partial least squares (PLS) analysis of 150 sets of survey data conducted in Chinese companies. The obtained results suggest that all three aspects of social capital have an indirect, yet significant influence on IOS assimilation and IOS value co-creation. This study argues that, knowledge acquisition plays a fully mediating role in structural capital and relational capital effect on IOS assimilation and IOS value co-creation. From the same stance, it adds that knowledge acquisition has a partial mediation effect on the cognitive capital-IOS assimilation link and cognitive capital-IOS value co-creation link. Moreover, the work at hand presumes that, if implemented effectively, IOS assimilation sets fourth IOS value co-creation.

Inter-organizational social capital as an antecedent of a firm’s knowledge identification capability and external knowledge acquisition

PurposeThis paper concentrates on the antecedents of external knowledge acquisition of companies based on their inter-organizational relationships. Specifically, it considers social capital (i.e., the result of a firm’s inter-organizational relationships) as an essential precursor of knowledge identification capabilities and deliberated knowledge acquisition strategies. This study aims to propose that cognitive and relational dimensions of a firm’s inter-organizational social capital are mediating factors of the relationship between structural social capital and knowledge identification capabilities and the relationship between structural social capital and the deliberated acquisition of external knowledge, respectively. The relationship between knowledge identification capability and external knowledge acquisition is also analyzed.Design/methodology/approachThis is a cross-sectional quantitative study with a sample of 87 firms from Spanish biotechnology and pharmaceutical industries. From an extensive literature review, we developed three hypotheses that were tested using the partial least squares technique and structural equations model.FindingsThe results only support a mediating effect of cognitive social capital in the relationship between structural social capital and knowledge identification capability and a partial mediation effect of relational social capital in the relationship between structural social capital and knowledge acquisition. In addition, the findings show that firms with more advanced abilities to identify and assess the value of external knowledge will be likely to develop optimal deliberated strategies to acquire effectively such knowledge from its network partners.Research limitations/implicationsThe limitations of this study are small sample size and the cross-sectional nature of the study. The study also focuses on only two specific and innovative industries.Practical implicationsManagers should understand that “good” management of inter-organizational social capital allows the firm to develop dynamic capabilities for the identification and acquisition of valuable knowledge. The results of the study show that managers should concentrate on building knowledge identification capabilities and should also be aware of the possibilities that social capital can provide to a firm to formulate and implement effective strategies for external knowledge acquisition.Originality/valueTo date, there are relatively few studies focussing on knowledge identification capability and its relationships with the dimensions of a company’s social capital as enablers of external knowledge acquisition. For managers, the identification of valuable knowledge by using inter-organizational relationships and networks is an essential issue, especially in innovative industries characterized by continuous change. Theoretically, this research highlights that social capital contributes to the development of dynamic capabilities, allowing the firm to sense and seize business opportunities based on external knowledge acquisition to achieve competitive advantages.

Structural social capital and knowledge acquisition: implications of cluster membership

This paper analyzes the implications of belonging to a cluster through the relationship between structural social capital and knowledge acquisition. The findings suggest structural social capital only indirectly affects knowledge acquisition through the relational and cognitive dimensions of firms’ membership of a cluster. However, the structural dimension also has a direct impact on knowledge for external firms outside a cluster. This paper contributes to the cluster literature with a better contextualization and understanding of the relationship between structural social capital and knowledge acquisition. In addition, the paper also consolidates the inter-organizational approach to social capital theory by helping to understand how and in what context social capital dimensions are interrelated. The study analyzes how firms can acquire valuable knowledge from their networks, filling the gap in the literature on how this process occurs inside and outside clusters. This works also proposes recommendations for companies and institutions, and new complementary lines of research.

Curious Cat--Mobile, Context-Aware Conversational Crowdsourcing Knowledge Acquisition

Scaled acquisition of high-quality structured knowledge has been a longstanding goal of Artificial Intelligence research. Recent advances in crowdsourcing, the sheer number of Internet and mobile users, and the commercial availability of supporting platforms offer new tools for knowledge acquisition. This article applies context-aware knowledge acquisition that simultaneously satisfies users’ immediate information needs while extending its own knowledge using crowdsourcing. The focus is on knowledge acquisition on a mobile device, which makes the approach practical and scalable; in this context, we propose and implement a new KA approach that exploits an existing knowledge base to drive the KA process, communicate with the right people, and check for consistency of the user-provided answers. We tested the viability of the approach in experiments using our platform with real users around the world, and an existing large source of common-sense background knowledge. These experiments show that the approach is promising: the knowledge is estimated to be true and useful for users 95% of the time. Using context to proactively drive knowledge acquisition increased engagement and effectiveness (the number of new assertions/day/user increased for 175%). Using pre-existing and newly acquired knowledge also proved beneficial.

Easily too difficult: Estimating item difficulty in computer simulated microworlds

Dealing with complexity and dynamics is increasingly becoming part of people's everyday lives. The necessity of dealing with complex systems has instigated the use of computer simulations, so-called microworlds (MWs), to assess and study human behavior in complex situations. Although these MWs enjoy great popularity with both practitioners and researchers, their psychometric qualities have been questioned, and studies that have investigated these qualities have been sparse. In particular, only a few studies have investigated the factors that contribute to item difficulty in MWs. To fill this gap, we analyzed data from 3128 Finnish students with a linear logistic test model. Our results suggest that item difficulty in MWs can be almost perfectly predicted by six basic item characteristics, namely, (a) the use and number of eigendynamics, the numbers of (b) input and (c) output variables, the numbers of (d) input and (e) output variables not related to any other variables, and (f) the total number of relations between all variables. In addition, we provide evidence for the necessity of differentiating between the difficulty of controlling an MW (knowledge application) and understanding its underlying structure (knowledge acquisition). Finally, we discuss further theoretical and practical implications of an increased understanding of MWs for their use as assessment instruments.

Constructivism in Practice: an Exploratory Study of Teaching Patterns and Student Motivation in Physics Classrooms in Finland, Germany and Switzerland

For the last three decades, moderate constructivism has become an increasingly prominent perspective in science education. Researchers have defined characteristics of constructivist-oriented science classrooms, but the implementation of such science teaching in daily classroom practice seems difficult. Against this background, we conducted a sub-study within the tri-national research project Quality of Instruction in Physics (QuIP) analysing 60 videotaped physics classes involving a large sample of students (N = 1192) from Finland, Germany and Switzerland in order to investigate the kinds of constructivist components and teaching patterns that can be found in regular classrooms without any intervention. We applied a newly developed coding scheme to capture constructivist facets of science teaching and conducted principal component and cluster analyses to explore which components and patterns were most prominent in the classes observed. Two underlying components were found, resulting in two scales—Structured Knowledge Acquisition and Fostering Autonomy—which describe key aspects of constructivist teaching. Only the first scale was rather well established in the lessons investigated. Classes were clustered based on these scales. The analysis of the different clusters suggested that teaching physics in a structured way combined with fostering students’ autonomy contributes to students’ motivation. However, our regression models indicated that content knowledge is a more important predictor for students’ motivation, and there was no homogeneous pattern for all gender- and country-specific subgroups investigated. The results are discussed in light of recent discussions on the feasibility of constructivism in practice.

Science Teacher Education in the Twenty-First Century: a Pedagogical Framework for Technology-Integrated Social Constructivism

Changes in our global world have shifted the skill demands from acquisition of structured knowledge to mastery of skills, often referred to as twenty-first century competencies. Given these changes, a sequential explanatory mixed methods study was undertaken to (a) examine predominant instructional methods and technologies used by teacher educators, (b) identify attributes for learning and teaching in the twenty-first century, and (c) develop a pedagogical framework for promoting meaningful usage of advanced technologies. Quantitative and qualitative data were collected via an online survey, personal interviews, and written reflections with science teacher educators and student teachers. Findings indicated that teacher educators do not provide sufficient models for the promotion of reform-based practice via web 2.0 environments, such as Wikis, blogs, social networks, or other cloud technologies. Findings also indicated four attributes for teaching and learning in the twenty-first century: (a) adapting to frequent changes and uncertain situations, (b) collaborating and communicating in decentralized environments, (c) generating data and managing information, and (d) releasing control by encouraging exploration. Guided by social constructivist paradigms and twenty-first century teaching attributes, this study suggests a pedagogical framework for fostering meaningful usage of advanced technologies in science teacher education courses.

Measuring knowledge sharing in inter-organisational networks: evidence from the healthcare sector

This paper aims at developing and evaluating an instrument for measuring knowledge sharing at the individual level in inter-organisational networks. To achieve this objective, we proceed as follows: (1) identification or generation of individual items, (2) developing a psychometric instrument and (3) empirical validation. For the latter, a questionnaire was applied to 202 professionals from different healthcare organisations in Portugal. The results reveal a high validity of a two-factor structure (Knowledge Acquisition and Knowledge Transfer). Hence, the psychometric instrument for measuring knowledge sharing we propose has potential for future research and application in networks as knowledge transfer mechanisms. Our study contributes to advancing theory at the interface of knowledge management and networks.

Managing complex socio-technical systems: A proactive approach to airport security

The purpose of security checks at airports is to achieve a reduction in the risk of malevolent attacks on the aviation system. The introduction of new security measures aims at reducing this perceived level of risk, and often takes place as a direct reaction to (attempted) attacks. This procedure means that offenders remain one step ahead of security agents. The aim of the approach presented here is to overcome this shortfall by supporting decision-making in the context of airport security by a systematically created knowledge base. The combination of two well-accepted methods – scenario analysis and structural complexity management – supports a structured knowledge acquisition process that serves as a basis for the proactive identification of system weaknesses. Furthermore, this combination of methods can be applied to the search for optimisation potentials concerned with possible future threats. The basis for the approach is composed of threat scenario components, security measures and dependencies between these elements. A Multiple-Domain Matrix is applied for system modelling. Clustering of threat scenarios and intensity of relations to security measures are used for analysis. The interpretation of findings makes use of portfolio representations.

A Bayesian Network-Based Knowledge Engineering Framework for IT Service Management

Service management is becoming more and more important within the area of IT management. How to efficiently manage and organize service in complicated IT service environments with frequent changes is a challenging issue. IT service and the related information from different sources are characterized as diverse, incomplete, heterogeneous, and geographically distributed. It is hard to consume these complicated services without knowledge assistant. To address this problem, a systematic way (with proposed toolsets and process) is proposed to tackle the challenges of acquisition, structuring, and refinement of structured knowledge. An integrated knowledge process is developed to guarantee the whole engineering procedure which utilizes Bayesian networks (BNs) as the knowledge model. This framework can be successfully applied on key tasks in service management, such as problem determination and change impact analysis, and a real example of Cisco VoIP system is introduced to show the usefulness of this method.

Automatic knowledge extraction from documents

Access to a large amount of knowledge is critical for success at answering open-domain questions for DeepQA systems such as IBM Watson™. Formal representation of knowledge has the advantage of being easy to reason with, but acquisition of structured knowledge in open domains from unstructured data is often difficult and expensive. Our central hypothesis is that shallow syntactic knowledge and its implied semantics can be easily acquired and can be used in many areas of a question-answering system. We take a two-stage approach to extract the syntactic knowledge and implied semantics. First, shallow knowledge from large collections of documents is automatically extracted. Second, additional semantics are inferred from aggregate statistics of the automatically extracted shallow knowledge. In this paper, we describe in detail what kind of shallow knowledge is extracted, how it is automatically done from a large corpus, and how additional semantics are inferred from aggregate statistics. We also briefly discuss the various ways extracted knowledge is used throughout the IBM DeepQA system.

Unconscious structural knowledge of tonal symmetry: Tang poetry redefines limits of implicit learning

The study aims to help characterize the sort of structures about which people can acquire unconscious knowledge. It is already well established that people can implicitly learn n-grams (chunks) and also repetition patterns. We explore the acquisition of unconscious structural knowledge of symmetry. Chinese Tang poetry uses a specific sort of mirror symmetry, an inversion rule with respect to the tones of characters in successive lines of verse. We show, using artificial poetry to control both n-gram structure and repetition patterns, that people can implicitly learn to discriminate inversions from non-inversions, presenting a challenge to existing models of implicit learning.

Effects of segmenting, signalling, and weeding on learning from educational video

Informed by the cognitive theory of multimedia learning, this study examined the effects of three multimedia design principles on undergraduate students' learning outcomes and perceived learning difficulty in the context of learning entomology from an educational video. These principles included segmenting the video into smaller units, signalling to direct students' attention to relevant information, and weeding to remove any non-essential content (SSW). It was hypothesized that the SSW treatment would decrease perceived learning difficulty and facilitate the transfer of knowledge and the structural knowledge acquisition. Results of the study demonstrate that participants in the SSW group outperformed the non-SSW group on the tests of knowledge transfer and structural knowledge acquisition and reported lower levels of learning difficulty. These findings support the use of SSW to help novice learners organize and integrate knowledge from complex, dynamic audio-visual media like video.

Knowledge Acquisition Strategies and Company Performance in Young High Technology Companies

Research on knowledge strategies argues that the configuration of activities used by companies to acquire new and leverage existing knowledge is an important influencing factor of company performance. However, we do not know very much about how companies actually structure knowledge acquisition. In addition, we do not know which configurations of knowledge acquisition are conducive to company performance. Furthermore, knowledge strategies have largely been neglected in the context of young and entrepreneurial companies. Drawing on an explorative analysis of quantitative and qualitative data, we investigate strategies and activities for knowledge acquisition in the context of young biotechnology companies in Germany. The study reveals four distinct knowledge acquisition strategies (low key, mid range, focus and explorer) and shows that these strategies differ in their relation to company performance as a result of their configuration of knowledge acquisition activities and the type of knowledge acquired.

ICT for Education

This paper presents the modeling, design and implementation of a learning platform in Cameroon. This platform contains structured knowledge acquisition modules as well as teaching, learning and assessment modules to promote a constructive learning. The objective of this project is to show how ICT can be used to improve teaching and learning with modern digital tools. This will result into enabling teaching of the official computer curriculum in secondary schools at the national level. A second objective of the project is to put in place a set of ICT based administrative and managerial tools that will guide the day-to-day activities of a secondary school. This will aid in generating informations accessible from all levels of the educational system and all its related departments and partners. This project will aim at promoting ICT accessibility in the educational system while contributing to reducing the digital divide.