Knowledge Generation Process Research Articles

Research-practice partnerships: a strategy for promoting educational recovery

Resumen This paper argues that efforts to help education systems recover following the recent global pandemic should involve collaboration amongst schools, and partnerships between practitioners and academic researchers. Drawing on a series of projects carried out over the last three decades, this approach is defined as a process of knowledge-generation that occurs when researcher and practitioner knowledge meet in particular sites. Underlying these collaborations is a common pattern. Most importantly, they involve an engagement with evidence collected by practitioners with support from university researchers. The paper points to the potential benefits of the approach, whilst also throwing light on some of the challenges involved. Keywords Educational recovery collaboration inquiry ecology of equity.

Uncertainty-aware visual analytics: scope, opportunities, and challenges

AbstractIn many applications, visual analytics (VA) has developed into a standard tool to ease data access and knowledge generation. VA describes a holistic cycle transforming data into hypothesis and visualization to generate insights that enhance the data. Unfortunately, many data sources used in the VA process are affected by uncertainty. In addition, the VA cycle itself can introduce uncertainty to the knowledge generation process but does not provide a mechanism to handle these sources of uncertainty. In this manuscript, we aim to provide an extended VA cycle that is capable of handling uncertainty by quantification, propagation, and visualization, defined as uncertainty-aware visual analytics (UAVA). Here, a recap of uncertainty definition and description is used as a starting point to insert novel components in the visual analytics cycle. These components assist in capturing uncertainty throughout the VA cycle. Further, different data types, hypothesis generation approaches, and uncertainty-aware visualization approaches are discussed that fit in the defined UAVA cycle. In addition, application scenarios that can be handled by such a cycle, examples, and a list of open challenges in the area of UAVA are provided.

Indicadores bibliométricos y toma de decisiones

The analysis of the publication of scientific articles, a fundamental link within the research process, has become the standard unit that allows for the assessment of the quality of the knowledge generation process and its impact on the scientific environment. This article aims to describe the general aspects of the relationship between bibliometric studies and decision-making. Data on scientific activities are increasingly being used to govern science. Research evaluations that were once individually designed for their specific context and conducted by peers are now routine and based on metrics. The issue is that the evaluation has shifted from being based on expert assessments to relying on these metrics. The opportunity to apply bibliometric techniques proves useful when making decisions that involve a redirection of all research-development plans and the selection of capable leaders to coordinate projects with the purpose of generating technological and financial resources.

Indicadores bibliométricos y toma de decisiones

The analysis of the publication of scientific articles, a fundamental link within the research process, has become the standard unit that allows for the assessment of the quality of the knowledge generation process and its impact on the scientific environment. This article aims to describe the general aspects of the relationship between bibliometric studies and decision-making. Data on scientific activities are increasingly being used to govern science. Research evaluations that were once individually designed for their specific context and conducted by peers are now routine and based on metrics. The issue is that the evaluation has shifted from being based on expert assessments to relying on these metrics. The opportunity to apply bibliometric techniques proves useful when making decisions that involve a redirection of all research-development plans and the selection of capable leaders to coordinate projects with the purpose of generating technological and financial resources.

Wastewater Surveillance for Public Health: Beyond the Pandemic

Wastewater-based epidemiology (WBE) is a public health tool that enables informed, targeted responses to crises such as disease outbreaks and epidemics. In this paper, we discuss the significance of the practice of open science in generating social impact through policy decisions on day-to-day pandemic management when public institutions adopt WBE as part of the COVID-19 pandemic response. Further, we examine how open science helped communicate the importance and credibility of cutting-edge science to the public through continuous engagement using publicly available data, scientific communication interfaced through mass media, and information sharing via a live dashboard. Critical to the translation of science to policy was the philosophy of complete access to the entire knowledge generation process, results, and findings. We analyze the success of such an initiative in the city of Bengaluru in India amidst other academic studies in the country with regard to their translation to policy engagement. We posit that Bengaluru’s success may be due to the presence of an open science ethos, and multi-stakeholder inputs for knowledge creation and dissemination, leading to nuanced science communication which is empowering rather than patronizing. We further suggest policy-level recommendations for the incorporation of WBE as a public health surveillance tool and impress upon the interweaving of open science as part of scientific practice and its broader uptake by the policy ecosystem.

Toward a Decolonial Parenting Science Through Centering Majority World Parenting: A Commentary on “Parenting Culture(s): Ideal-Parent Beliefs Across 37 Countries”

In “Parenting Culture(s): Ideal-Parent Beliefs Across 37 Countries,” Lin et al. examine reports of parents from 37 countries regarding the qualities they consider in an ideal parent and then use a method called Leximancer Semantic Network Analysis to identify broad culture zones across the 37 countries based on shared notions of an ideal parent. I appreciate this substantial effort to explore parenting beyond Euro-American samples, upon which a bulk of parenting science literature is based. I also concur with a data-driven exploratory approach and examination of ideal-parent beliefs across parents with differing educational levels. However, I argue that to advance parenting science, we need more than inclusion of samples from the Majority World (i.e., regions where the majority of the world’s population resides). Future parenting research should be grounded in (a) decolonial epistemology that involves generating localized knowledge by exploring parenting in various communities in the Majority World that are formed through intersecting influences of neighborhood composition, religion, region, social class, urban, rural, and suburban residence, along with other locally relevant social dimensions, (b) decolonial research methodology that values different ways of generating knowledge and includes local communities as partners in the knowledge generation process, and (c) understanding and interpreting parenting in Majority World communities from a cultural resource rather than a deficit framework.

Evolution of the academic emotions of academically low-achieving students in knowledge building

Knowledge Building is a pedagogical approach that emphasizes students’ collective responsibility to continuously improve their community knowledge. Advancing the frontiers of community knowledge is an exciting but challenging process, especially for low-achieving students, because it involves a continuous experience of cognitive disequilibrium and equilibrium. This knowledge generation process triggers various emotions (e.g., curiosity, surprise, and confusion) that may promote or hinder Knowledge Building. This study investigated the types and evolution of emotions experienced by academically low-achieving students in the Knowledge Building process supported by Knowledge Forum. The participants were 120 students from two Grade 9 classes and two Grade 11 classes in a Band 3 secondary school in Hong Kong. This school enrolls students performing at the 10th percentile on a pre-admission government examination at the end of elementary school. The participants built knowledge around Visual Arts. The emotions reflected in the digital Knowledge Forum notes and the evolution patterns of emotions in inquiry threads were both analyzed using content analysis and sequential pattern analysis. The participants demonstrated a high percentage of joy and relatively low percentages of frustration and boredom. Emotions were likely to maintain consistency (e.g., joy to joy) or transition between similar emotions (e.g., boredom to frustration) in the inquiry threads. By synthesizing the emotion transitions and subsequences manifested in the inquiry threads of different classes, we constructed a model of the evolution of emotions of academically low-achieving students during Knowledge Building. This model has implications for designing scaffolding or interventions to facilitate low-achieving students' learning and promote favorable emotions.

Learning behavior, digital platforms for learning and its impact on university student's motivations and knowledge development.

Learning digital technologies in higher education is a process of knowledge generation, and the rapid growth of technology in education has a significant impact on students' learning behaviors, motivation, and knowledge development. Pakistan's remarkable technological breakthrough has increased in the education field. The study focuses on estimating students' learning behaviors, identifying the positive influence of educational apps on digital learning platforms, and analyzing their impact on students' motivation and knowledge development. According to the study's objectives, a questionnaire survey was conducted to gather the primary data. The participants were students of universities in Lahore city of Pakistan. For this study, the sample size was N = 300, carefully chosen using the purposive sampling technique. Of the respondents, there were 146 male and 154 female students, and the sample consisted of individuals aged 25-35 years. Smart-PLS-Bootstrapping, T-Values (PLS) 3.2.9 and the structural equation model (SEM) were applied to get the appropriate outcomes from the proposed study framework. SEM analysis results shows that all proposed hypotheses [Animated Movies (AM) -> Student Motivation (SM), Educational Apps (EA) -> Knowledge Development (KD), Learning Behavior (LB) -> Animated Movies, Learning Behavior -> Educational Apps, Learning Behavior -> Knowledge Development, Learning Behavior -> Virtual Classrooms (VCr), Virtual Classrooms -> Knowledge Development, Virtual Classrooms -> Student Motivation] are confirmed while Learning Behavior -> Student Motivation is not confirmed. This study found that digital learning platforms significantly impact students' learning and what motivates them to learn. The study also found that using educational apps and virtual classrooms more often helps students learn more and be more motivated to learn.

Intelligent architecture of space unmanned system with learning and reasoning capabilities

Spacecraft represented by satellites, manned spaceships, and deep space probes are typical unmanned systems that are developing from automation to autonomy. To improve the adaptability and intelligent autonomy level of spacecraft to unknown space environments and complex space tasks, an intelligent architecture of space unmanned system with learning and reasoning capabilities is designed and the architectural components and functions are proposed. Then, the operating mechanism of learning and reasoning capabilities in the architecture are analyzed, and the solutions for key technologies, such as the construction, update, and expansion methods of the action and knowledge libraries, are proposed. Finally, through an example of the extraterrestrial surveying and sampling task, the process of new knowledge generation, knowledge-based reasoning, and autonomous task execution under this intelligent architecture, as well as the interaction between the knowledge library, environment, task, and action library, are explained.

Inside the black box: domestic homicide reviews as a source of data

Domestic Homicide Reviews (DHRs) are a statutory review process to better understand domestic homicide in England and Wales. As a policy intervention, DHRs are intended to build a picture of the circumstances before such deaths and identify gaps in practice, policy and system response. The rationale is that this learning can improve response to domestic violence and abuse and reduce the likelihood of future homicides. However, little is known about how the DHR process operates, including how knowledge is produced or its subsequent use, including any outcomes. In effect, for the most part, DHRs are a ‘black box’. Yet, researchers are increasingly using DHR reports as a source of data. By locating ourselves within these processes, this article explores the implications of limited engagement with DHRs as a process of knowledge generation to date. It focuses on the implications for researchers, in particular the epistemological and methodological issues that arise, before considering what this might mean for policy and practice. It identifies recommendations to address key gaps in the understanding and use of DHRs for research purposes.

Democratising the interface research-policymaking in landscape planning: experiences in Friuli Venezia Giulia (Italy)

In the current, extended socio-environmental crisis, the interface research-policymaking in landscape planning has evolved, seeking responses to pressing global dynamics (e.g., climate change, international migration fluxes, etc.) and critical local demands (e.g., recognition of community-based initiatives, “public governance” of landscape interventions, etc.). Depending on contextual conditions, different political agendas and legal frameworks shape the interplay between knowledge production mechanisms and practices on landscape. The evolution of the interface research-policymaking involves the interactions between structured research policies and informal knowledge generation processes, the (ideological) use of participation in the actions on landscape and the redefinition of power equilibria in the planning arena. Exploring the experiences of landscape planning developed in Friuli Venezia Giulia, Italy (i.e., territorial plans involving landscape conservation norms, regional landscape plans, “integrated landscape projects”), the research shows the need to readdress landscape governance and policymaking towards inclusiveness, fostering knowledge co-production initiatives at all levels and (re-)thinking power as a complex factor of change in the relationships between planning authorities, academia, communities and citizens.

Spatial Knowledge and Urban Planning

Urban planning is simultaneously shaped by and creates new (spatial) knowledge. The changes in planning culture that have taken place in the last decades—especially the so-called communicative turn in planning in the 1990s—have brought about an increased attention to a growing range of stakeholders of urban development, their interests, logics, and participation in planning as well as the negotiation processes between these stakeholders. However, while this has also been researched in breadth and depth, only scant attention has been paid to the knowledge (claims) of these stakeholders. In planning practice, knowledge, implicit and explicit, has been a highly relevant topic for quite some time: It is discussed how local knowledge can inform urban planning, how experimental knowledge on urban development can be generated in living labs, and what infrastructures can process “big data” and make it usable for planning, to name a few examples. With the thematic issue on “Spatial Knowledge and Urban Planning” we invited articles aiming at exploring the diverse understandings of (spatial) knowledge, and how knowledge influences planning and how planning itself constitutes processes of knowledge generation. The editorial gives a brief introduction to the general topic. Subsequently, abstracts of all articles illustrate what contents the issue has to offer and the specific contribution of each text is carved out. In the conclusion, common and recurring themes as well as remaining gaps and open questions at the interface of spatial knowledge and urban planning are discussed.

These are the stories of our physical activities: Decolonial re-existence and poetry

In this paper, I aim to disseminate the knowledge that was generated during participatory art-based action research on which I collaborated with a group of young Afghan asylum seekers in Sweden. The focus of the research was the lived experiences of the youth in relation to sport and physical activity. I have chosen a narrative poem that I crafted using vox participare (voices of participants) (Norton & Sliep, 2019) to do this work. In this way, I have grounded the dissemination of our research in the shared epistemology of our peoples, the Khorasani peoples of central/western Asia. By adopting the persona of شاعر (the poet) (Olszewska, 2015), and by writing in a reflective manner that does not obscure my own privilege, I work towards decolonising the process of research and knowledge generation as it relates to sport. I attempt to show how Afghan youth re-make sport (and physical activity) in ways that re-create conditions of dignity for themselves and their community in their everyday living. In this way, I aim to disrupt the dominant understandings about what sport is, what it is supposed to do, and how it can be utilised by those who are living with social injustices.

Heinrich Wittenwilers ›Ring‹ als Krisenexperiment: Erwartung und Störung didaktischer Kommunikation

Heinrich Wittenwilers ›Ring‹ als Krisenexperiment: Erwartung und Störung didaktischer Kommunikation

A Typology of Guidance Tasks in Mixed‐Initiative Visual Analytics Environments

AbstractGuidance has been proposed as a conceptual framework to understand how mixed‐initiative visual analytics approaches can actively support users as they solve analytical tasks. While user tasks received a fair share of attention, it is still not completely clear how they could be supported with guidance and how such support could influence the progress of the task itself. Our observation is that there is a research gap in understanding the effect of guidance on the analytical discourse, in particular, for the knowledge generation in mixed‐initiative approaches. As a consequence, guidance in a visual analytics environment is usually indistinguishable from common visualization features, making user responses challenging to predict and measure. To address these issues, we take a system perspective to propose the notion of guidance tasks and we present it as a typology closely aligned to established user task typologies. We derived the proposed typology directly from a model of guidance in the knowledge generation process and illustrate its implications for guidance design. By discussing three case studies, we show how our typology can be applied to analyze existing guidance systems. We argue that without a clear consideration of the system perspective, the analysis of tasks in mixed‐initiative approaches is incomplete. Finally, by analyzing matchings of user and guidance tasks, we describe how guidance tasks could either help the user conclude the analysis or change its course.

Seeking Patterns of Visual Pattern Discovery for Knowledge Building

AbstractCurrently, the methodological and technical developments in visual analytics, as well as the existing theories, are not sufficiently grounded by empirical studies that can provide an understanding of the processes of visual data analysis, analytical reasoning and derivation of new knowledge by humans. We conducted an exploratory empirical study in which participants analysed complex and data‐rich visualisations by detecting salient visual patterns, translating them into conceptual information structures and reasoning about those structures to construct an overall understanding of the analysis subject. Eye tracking and voice recording were used to capture this process. We analysed how the data we had collected match several existing theoretical models intended to describe visualisation‐supported reasoning, knowledge building, decision making or use and development of mental models. We found that none of these theoretical models alone is sufficient for describing the processes of visual analysis and knowledge generation that we observed in our experiments, whereas a combination of three particular models could be apposite. We also pondered whether empirical studies like ours can be used to derive implications and recommendations for possible ways to support users of visual analytics systems. Our approaches to designing and conducting the experiments and analysing the empirical data were appropriate to the goals of the study and can be recommended for use in other empirical studies in visual analytics.

Epistemic orientation toward teaching science for knowledge generation: Conceptualization and validation of the construct

AbstractResearch in science education has emphasized the importance of knowledge generation approaches to learning. Creating generative learning environments requires teachers to address the epistemic underpinning of science practices and shift their orientations toward knowledge generation approaches. This study aimed to propose epistemic orientation as a key component of teacher development for implementing knowledge generation approaches and develop an empirically grounded model of the construct through a mixed‐method approach. Epistemic orientation toward teaching science for knowledge generation (EOTS‐KG) was defined as a particular direction of thinking concerning how to deal with knowledge and knowledge generation processes when a teacher aims to create generative learning environments for teaching science. Building on the theoretical model of EOTS‐KG established through a critical literature review, we conducted a multiple case study of exemplary elementary teachers and designed an instrument called the Epistemic Orientation Survey. The model from the case study described four major subdimensions indicated by 11 essential elements that should be considered when preparing teachers for implementing a knowledge approach, suggesting that teachers' beliefs about learning should be a priority in teacher development. Using the instrument, we tested the dimensionality of the construct, leading to the suggestions that both unidimensional and multidimensional models are valuable for use in future research. We believe the model developed in this study would serve as a powerful framework to allow researchers to examine changes in teachers' epistemic orientation in various contexts.

Knowledge hierarchy and mechanisms of power in environmental impact assessment: Insights from the Muskrat Falls hydroelectric project

AbstractDiscussions surrounding the improvement of decision‐making processes like environmental impact assessment (EIA) often emphasize pluralism in the knowledge generation process, in an effort to increase effectiveness. However, empirical research indicates that such attempts to integrate multiple ways of knowing often fall short and significant knowledge conflicts remain. Scholars suggest this may be due to inadequate attention to power in the regulatory arena. The purpose of this study is to examine how power and knowledge influence the process and outcome of EIA in a participatory context. We develop a case study analysis of the Muskrat Falls hydroelectric project, located in Labrador, Canada. We use situational analysis to analyze documents produced over the course of the EIA and semi‐structured interviews. We find evidence of pluralism in knowledge production in the EIA process, but a distinct knowledge hierarchy in EIA outcome. We argue that this knowledge hierarchy is achieved through depoliticization of the EIA process. In particular, we identify the concept of “project inertia” as a distinct mechanism of depoliticization present in EIA and make policy prescriptions to improve the Canadian EIA process. This research contributes to broader theoretical discussions about pluralism in decision‐making processes.

Unboxing knowledge in collaboration between academia and society: A story about conceptions and epistemic uncertainty

AbstractPolicymakers increasingly emphasize knowledge collaboration between academia and society as important means to generate innovations and solve complex issues. However, while recent literature on such collaboration suggests that knowledge needs to be integrated and generated across disciplines and sectors, there are surprisingly few studies that define what is meant by ‘knowledge’ or focus on the process of generating knowledge. Subsequently, the aim of this paper is to unbox ‘knowledge’ in knowledge collaboration by focusing specifically on how knowledge is understood by heterogenous actors during the process of generating knowledge. We build on insights from an in-depth case study and contribute to the literature on knowledge collaboration by bringing in theory on boundary work that specifically addresses the knowledge generation process. We argue that to better meet the expectations of collaboration, there is a need for more discussions and focus on the participating stakeholders’ heterogenous epistemological as well as ontological understanding.

Knowledge formalization for Earth Science informed decision-making: The GEOEssential Knowledge Base

During the past two centuries, the world has undergone deep societal, political, and economical changes that heavily affected human life. The above changes contributed to an increased awareness about the deep impact that policy decisions have at the local and the global level. Therefore, there is a strong need that policy-making and decision-making processes for a sustainable development be based on the best available knowledge about Earth system and environment.The recent advance of information technologies enables running complex models that use the large amount of Earth Observation datasets available. However, data and model interoperability are still limited to the syntactic level allowing to access and process datasets independently of their structural characteristics (data format, coordinate reference systems, service interface, …) but with no clear reference to their content (the semantic level) and context of use (the pragmatic level). This poses heavy limitations to the reusability of scientific processes and related workflows.The paper presents a general framework to address this issue through the design of a Knowledge Base supporting data and model semantic (and pragmatic) interoperability. In this framework, a general ontology represents the knowledge generation process for policy relevant decision-making, while multiple vocabularies formalize the semantics of data and models, identifying different types of observables, process variables, and indicators/indices. To evaluate the proposed approach to semantic interoperability of data and models, the Knowledge Base has been integrated with an advanced model-sharing framework, and a proof-of-concept has been developed for the assessment of one of the indicators of the Sustainable Development Goals defined by the United Nations.