Knowledge Space Research Articles

The Cultural Political Economy of Knowledge in Neo-Liberal Indonesia

This article analyses the policy agendas and bureaucratic apparatuses that have shaped the norms and values directing knowledge production in neo-liberal Indonesia. It uses a Gramscian approach to hegemony to understand how knowledge, as power, is organised and imposed on workers. It unpacks the norms and values shaped during processes of neo-liberal capitalist reform, which are identified as knowledge imaginaries; or shared social systems that organise a field of knowledge commodities. Their mobilisation during material and discursive moments are crucial in the juncture between predatory and market interests that fundamentally benefit capital accumulation. It is argued that funding and policies serve as key apparatuses for knowledge elites to normalise and enforce notions of self-reliance, competitiveness, and entrepreneurship as common sense for their managers, which are exploitative for workers. Within the hegemony of knowledge capitalism, there are antagonisms and attempts to form alternative spaces of knowledge by using digital media. While merely leaving a dent on the surface of broader capitalist structures, its promotion of subversive ways of knowing remains no less meaningful in understanding the social positions of academic workers in an increasingly networked but fragmented neo-liberal social world.

Collective reflections to create knowledge spaces: Thinking about an inclusive, diverse, and participatory occupational science

ABSTRACT The first World Occupational Science Conference took place in Vancouver, Canada, in August 2022. As English was the official language of the event, this brought challenges for some non-anglophone participants, including some of the authors of this paper. In response, the authors gathered to support translation and communication efforts during the event. This strengthened mutual support and led to the establishment of a workgroup to reflect on knowledge production within occupational science. Framed within a call to expand the discipline beyond the English-speaking world and from a Portuguese-Spanish context, our objectives were to (i) share joint reflections on the potential barriers to participation in scientific events; and (ii) recommend options to democratize knowledge in academic events to develop a more inclusive, diverse, and participatory occupational science. This work could contribute to the creation of spaces for inclusive knowledge to engage more people in occupational science and therefore open opportunities for a more nuanced and diverse understanding of occupation.

Automata for knowledge assessment based on the structure of observed learning outcome taxonomy

The process of adaptive assessment of individuals' knowledge by knowledge space theory has been implemented in deterministic finite automata. However, such automata are not suitable for polytomous situations, which limits the application of automata for knowledge assessment. To overcome this limitation, this paper combines the structure of observed learning outcome (SOLO) taxonomy with the response scale and proposes an automata knowledge assessment process that can assess individuals' knowledge in polytomous situations. Specifically, an automaton suitable for assessing knowledge in the SOLO taxonomy situation is proposed, and a questioning rule is provided based on the quasi-order relation between items. Then, relying on the automaton state update and the questioning rule, an automata knowledge assessment process for knowledge assessment in the SOLO taxonomy situation is given. Finally, empirical research and simulation experiments show that it is necessary to provide a questioning rule for the automaton and that the automata knowledge assessment process proposed in this paper is feasible.

Modelling algorithms for learner interaction with training courses

This paper considers learning as a process of mastering a knowledge domain, investigating the interaction of learners with courses of study and the influence of learner actions on the state of mastery of the knowledge space in order to define a learning control function and to model algorithms for constructing the knowledge space. Key aspects of the interaction process, variables that can be changed to customise the learning model, are given. A threshold to mastery of a course element is formulated and a scale of mastery level for a particular knowledge element is described. As a result, algorithms for forming, expanding and segmenting the knowledge space were created. The research presented the concept of learning as a guided wave process of knowledge mastery, where the learner's actions correspond to the structure of the knowledge space and are determined by its properties.

PDF CHAT_BOT USING GENERATIVE AI (LLMS&RAG)

This paper delves into the increasing craziness of planting chatbots and artificially intelligent systems (AI) in academia and disquisition. Chatbots are employed even more frequently to deliver adapted backing, attack enterprises, and develop fascinating spaces for knowledge. Chatbots empower directors to hone education while delivering actual-time support for pupils with assignments and examinations and issue explanations by outsourcing executive tasks. The creation of a PDF chatbot using Large Language Models (LLMs) in generative AI is one example of such an application. This project uses prompt-based querying, tokenization, and a vector-based component to store PDF inputs. The chatbot uses LLMs to build embedded prompts and pull text snippets from a knowledge base to respond to user inquiries. Chatbots' accessibility and flexibility enhance pupil involvement and expedite learning objectives.

The influence of proximity and knowledge base on recombination innovation in R&D collaboration.

Recombination innovation invented during organizations' research and development (R&D) collaborations is a vital mechanism for creating new technological knowledge for organizations. This study aims to reveal the contribution mechanism of different dimensions of proximity to the recombination innovation at the collaborative dyad level and how this mechanism depends on the characteristics of organizations' knowledge base structuration. We conceptualize that the interdependence among knowledge elements in the knowledge base forms the knowledge space of the organization and build a theoretical framework to explain the interactive effect of proximity and organizations' knowledge base characteristics on collaborative recombination innovation. We validated the theoretical hypotheses using Logit regression models based on the longitudinal data of 150 organizations in the global nanotechnology industry. As demonstrated by our findings, technological proximity exerts a negative effect, while geographic proximity exerts an inverted U-shaped effect on collaborative organizations' joint recombination innovation. Organizations' knowledge base decomposability plays a negative role in moderating the effect of technological proximity and plays a positive role in regulating the effect of geographic proximity. In contrast, the degree centrality of the knowledge elements positively moderates the effect of both technological and geographic proximity.

Optimizing English Education in the Information Era: A Multimodal Approach Based on BOPPPS Teaching Model

The development of information society requires the reform of traditional English education. The progress of science and technology, especially the progress of Internet information technology, has penetrated into the English teaching system, reconstructed the relationship between the elements of the English teaching system, and provided technical support for the reform of English teaching. These two aspects are the internal and external impetus of English teaching reform. According to the theory of knowledge construction and multimodal information fusion, this research establishes a user-centered knowledge space, which can respond to user needs quickly, emphasizes the integration and integration of multimodal subject knowledge in resource organization, and expresses multi-dimensional relevance in functional form. The experimental results show that the optimized BOPPPS English teaching model is conducive to improving students’ participation in English classroom interaction. In the new information integration technology environment, students are more likely to put forward opinions or suggestions, and the transformation relationship of students’ interactive behavior becomes more complex.

A phenomenographic exploration of course leaders’ understandings of interdisciplinarity

ABSTRACT The number of interdisciplinary courses being developed in higher education across different countries is increasing. The people responsible for developing and enacting interdisciplinary courses can have significant design and teaching autonomy, but little is known about how they understand interdisciplinarity. This study uses phenomenographic interviews to address the question: how do interdisciplinary course leaders understand interdisciplinarity? This includes exploration of the relationships between different understandings of interdisciplinarity. Findings from interviews with 23 interdisciplinary course leaders reveal understandings of interdisciplinarity expressed in relation to (A) definitions, (B) knowledge spaces, and (C) situated knowledge work practices. Understandings were multiple and heterogeneous; they varied between participants and more importantly participants each expressed understandings belonging to multiple categories. Findings show that academics’ views about what interdisciplinarity means are rarely exclusively aligned with normative definitions, but instead are marked by individuals’ construction of meaning through processes of acquisition, sense-making and situational judgment. The study’s findings could be used in future educational design and planning work to elicit and discuss different stakeholder understandings of interdisciplinarity.

Monchique’s Innovation Laboratory—A Space for Dialogue and Knowledge Sharing to Foster Community-Based Disaster Risk Reduction

BRIDGE (bridging science and local communities for wildfire risk reduction) is an action–research project developing a community-based disaster risk reduction (CBDRR) process which is being fostered through a collaborative innovation laboratory (InnoLab). BRIDGE integrates different forms of knowledge and action, linking science and local communities to reduce their vulnerability and to enhance strategies for forest fire risk reduction. Applied in Monchique, a forest-fire-prone municipality in Portugal, the InnoLab creates a space for dialogue and knowledge sharing between multiple actors that, directly or indirectly, manage forest territories. BRIDGE attempts to facilitate social learning about forest fire risks, strengthen collaborative networks and enhance adaptive capacities (socially and institutionally) for forest fire prevention. This paper shares results of the InnoLab activities, which include (i) school community activities on wildfire risk perception; (ii) participatory mapping of Monchique’s vulnerabilities and risks; (iii) participatory sessions to create the community visioning for Monchique’s territory, to define priorities and capacities to be improved, and to identify functions and responsibilities to act upon; and (iv) workshop on CBDRR strategies for action. Lessons are shared on how InnoLab can represent an innovative participatory approach to promote CBDRR processes in forest-fire-prone territories by both contributing to the recognition of local knowledge systems and encouraging the active role of forest communities through strengthened local networks for a more lasting commitment to forest fire risk reduction policy.

Local contexts as alternative knowing spaces for design fields

ABSTRACT Lately, the notion of a single, unified form of knowledge has been questioned, and there has been increasing recognition of the importance of context-specific, varied forms of knowledge. This shift is reflected in the field of design studies, where there is a growing movement away from dominant models and strategies and towards contextually based methodologies and a pluralistic knowledge space of design. This paper explores the idea of diverse and equitable ‘ecologies of knowledge’ to understand the interplay between forms of knowledge and the customs and values that either facilitate or hinder their co-creation. Respectively, local contexts and knowledge are proposed as alternative spaces in which pluralistic design knowledge can flourish. By bringing together the latest efforts in design towards plurality with the ecologies of knowledge framework, this paper provides insights into the methods and processes involved in collaboration and co-creation of new knowledge within design research. These guidelines can aid designers and researchers in formulating methods that are contextually relevant and mutually agreed upon when engaging with local communities and in forging more accountable and epistemically imaginative links with local contexts.

A Study of Artificial Intelligence-Assisted Teaching on the Cultivation of Students’ Creative Ability

Abstract This paper first studies the use of artificial intelligence technology in the field of education and explores the realization process of “artificial intelligence + education”. Then, the teaching model of “AI+Education” is constructed from three perspectives: knowledge space, creation space and thinking space. Then, based on the logistic regression method, an analytical model of students’ innovation ability was established, and the parameters of the model were solved according to the data to analyze the causal relationship between the variables. Finally, the regression analysis model was used to analyze the relationship between intelligent assisted teaching and students’ innovative ability, innovative knowledgeability, innovative thinking ability, new learning ability and innovative practice ability. The results show that the correlation coefficients of intelligent-assisted teaching and innovative ability and innovative self-efficacy are 0.703 and 0.639, respectively, and all of them are positively correlated at the level of 10%, which indicates that intelligent-assisted teaching promotes the cultivation of students’ innovative ability.

A Comparative Analysis of Discourse Knowledge Structures in Different Disciplines of Education in Colleges and Universities in the Context of Informatization

Abstract In this paper, we first construct the discourse knowledge structure of education in different disciplines so that the knowledge points in a certain cross-cutting area between different disciplines are finite sets called knowledge domains, and we use the network of the discourse field system to characterize the logical relations in the knowledge space. Secondly, by defining the elements of hypertext as a triadic structure, a specific chain of dependencies is constructed by combining the hypertext structure with the knowledge space. Finally, we conducted a comparative analysis of the knowledge structure of educational discourse in various disciplines. The results show that among 45 knowledge states, 15 attributes corresponding to the whole column have all 0 information values and the knowledge structure model based on the knowledge space can master the corresponding effective skills of students in different disciplines, which indicates that it realizes this learning process of knowledge learning from point to point, from concrete to abstract, and from part to the whole under different disciplines. This paper examines the use of discourse in various knowledge structures, which may provide insights into the teaching of English academic writing in China.

Locking and Unlocking: The potentialities for intra-storying-activism in “this” baglady collective.

In this article we disrupt extractivist and privileged individualised knowledge production by decentering the human ‘I’ to ‘we’ through storying. By entangling more-than-human bodies, ‘we’ is re-configured through a posthuman praxis of an iterative metamorphosing Baglady storying collective. Starting with the provocation of locking and unlocking, we story as a way to make sense of political and ethical affectivities that disrupt and interrupt everyday materialities and spatialities. From here, we speculate with movements of response-ability as “intra-activism” (Renold & Ringrose, 2017, 631). For us, storying puts in motion intra-action, speculation, calls to act, relationality and feminist community building that we frame as intra-storying-activism. Making and re-making stories with intra-storying-activism navigates non-hierarchical post-authorship to re-imagine, speculate-with and trouble the human from extractivist positions. By foregrounding relationality as a multiplying storying, we create playful, dynamic and generative spaces for knowledge making as a collective that both welcomes and provokes calls to act. 
 

Dialogue and Repertoire: The Ever-Changing Nature of Walking and Talking Together

This conversation between Professor Diana Taylor and Dr. Andrea Maciel presents Taylor’s life-long experience fostering art and activism, as well as promoting dialogical research encounters through The Hemispheric Institute of Performance & Politics. The discussion encompasses the role of the archive as part of a mutual collaboration between performance and practice as research whilst opening a critical inquiry on how new epistemologies for artists and researchers can contemplate the archive as a force for the creation of laboratorial praxis.  Drawing on her long experience as a core member of Cross Pollination (CP), an international arts research platform for the exchange of knowledge and nomadic laboratory spaces, Maciel invites Taylor to also reflect about the power of performances and somatic practices to trace trauma related to social cultural alienation and oppression.

Research on the Construction of Multimodal Integration Resource Library for Online Teaching and Learning for Adult Education

Abstract This paper aims to construct a resource base for adult online education using a multimodal fusion basis. The fusion processing methods of knowledge resources incorporate temporal and non-temporal feature learning. This paper proposes a process for constructing a multimodal subject knowledge space that can aid educators in organizing and presenting multimodal teaching content effectively. Also, the operation process of each major functional module of the adult online education resource library, including the online teaching process, online learning process and online resource production process, is studied in detail. Finally, the performance test of optimizing small file storage, the performance test of de-duplication of redundant data of learning resources and the stress test were conducted on the constructed resource library. The study concluded that the resource memory occupancy of the computer class was reduced by 0.35 after the de-duplication process, and in the stress test, the login response time was less than 8 seconds, and the average CPU utilization of the database server was <50%.

On delineating forward- and backward-graded knowledge structures from fuzzy skill maps

Forward-graded and backward-graded structures of knowledge are two important classes of knowledge structures. Spoto and Stefanutti (2020) establish necessary and sufficient conditions for skill maps to delineate these structures. We introduce fuzzy skills to describe varying levels of proficiency in skills and extend the theoretical results of Spoto and Stefanutti (2020) for delineating forward- and backward-graded knowledge structures using fuzzy skill maps. The paper establishes necessary and sufficient conditions for fuzzy skill maps to delineate a backward-graded simple closure space, a forward-graded knowledge space, and a forward-graded simple closure space. Furthermore, the competence-based local independence model (CBLIM) with fuzzy skills is introduced and its unidentifiability is discussed.

Историзм как метанарратив: методологические основания гуманитарных наук

The article examines historicism as an interdisciplinary paradigm that constitutes the methodological foundations of the Humanities from the moment of their inception to the present day. The author puts forward and argues the thesis that the Humanities were constituted in the space freed up after the elimination of classical metaphysics, occupying this space along with the historical and social sciences, but taking possession of a very advantageous position within it. Historicism, according to the author, has become a means of radical repression of mechanism both from philosophy and from the space outlined by the Liberal Arts, and its assertion made possible the emergence of a discursive formation in which the Human Sciences developed as a scientific discipline with their own theoretical foundations and methodology not borrowed from the positive sciences, but having a structural commonality with these latter. In the system of the established Humanities, historicism continues to serve as a universal methodological platform, providing these scientific disciplines with scientific legitimacy and allowing them to create sustainable alliances in the space of scientific knowledge.

Heterogeneous graph-based knowledge tracing with spatiotemporal evolution

Knowledge tracing (KT), in which the future performance of students is estimated by tracing their knowledge states based on their responses to exercises, is widely applied in the field of intelligent education. However, existing mainstream KT models explore the importance of knowledge relations but ignore the key role of cognitive factors. According to the knowledge construction theory, the human cognitive system performs both spatial accommodation and temporal assimilation to internalize knowledge. In this paper, we propose an innovative heterogeneous graph-based Knowledge tracing method with spatiotemporal evolution (TSKT), in which knowledge state evolution is traced along both temporal and spatial dimensions. We construct a heterogeneous graph with multiple exercise attributes, including content, concepts, and difficulty, to obtain a knowledge space with richer exercise representations through hierarchical aggregation. We design a spatial updating module in which each interaction updates the current node’s state of the knowledge space and transfers its influence to its neighbors. We also design a temporal updating module to further update the knowledge state through short-term memory enhancing and long-term memory forgetting. Finally, we stack these modules to obtain deeper features by using alternate spatiotemporal updating. Extensive experiments on three datasets reveal the superiority of the proposed method and its variants in terms of future performance prediction.

Reference System Element Identification Atlas – methods and tools to identify references system elements in product engineering

Companies target innovations, successful new products. One major challenge is to increase efficiency and decrease the risk of developing new successful products. We want to reach these goals by improving the reusability of already existing knowledge elements extracted from e.g., already existing (sub-)systems or their documentation. These elements are called reference system elements and are meant to be the starting point for product development projects. Based on a systematic literature review complemented by an expert workshop and analysis of established methods and tools in product engineering, we developed the Reference System Elements Identification Atlas to support the identification of suiting reference system elements. Within the Reference System Elements Identification Atlas, we collected 30 methods and tools to identify reference system elements and allocated them to the various knowledge spaces they search. All 30 methods and tools were grouped in five clusters – creativity methods, data analysis methods, market/competition analysis methods, similarity methods, and trend analysis methods. We observed that methods and tools are hardly related to the identification of reference system elements in literature explicitly. We believe the Reference System Elements Identification Atlas provides valuable support to collect valuable reference system elements as the starting point in product engineering.

Scalable Transfer Evolutionary Optimization: Coping With Big Task Instances.

In today's digital world, we are faced with an explosion of data and models produced and manipulated by numerous large-scale cloud-based applications. Under such settings, existing transfer evolutionary optimization (TrEO) frameworks grapple with simultaneously satisfying two important quality attributes, namely: 1) scalability against a growing number of source tasks and 2) online learning agility against sparsity of relevant sources to the target task of interest. Satisfying these attributes shall facilitate practical deployment of transfer optimization to scenarios with big task instances, while curbing the threat of negative transfer. While applications of existing algorithms are limited to tens of source tasks, in this article, we take a quantum leap forward in enabling more than two orders of magnitude scale-up in the number of tasks; that is, we efficiently handle scenarios beyond 1000 source task instances. We devise a novel TrEO framework comprising two co-evolving species for joint evolutions in the space of source knowledge and in the search space of solutions to the target problem. In particular, co-evolution enables the learned knowledge to be orchestrated on the fly, expediting convergence in the target optimization task. We have conducted an extensive series of experiments across a set of practically motivated discrete and continuous optimization examples comprising a large number of source task instances, of which only a small fraction indicate source-target relatedness. The experimental results show that not only does our proposed framework scale efficiently with a growing number of source tasks but is also effective in capturing relevant knowledge against sparsity of related sources, fulfilling the two salient features of scalability and online learning agility.