Knowledge Integration Framework Research Articles

Preservice elementary teachers' perceptions of their science laboratory instructors in a phenomena‐based laboratory and how it impacts their conceptual development

AbstractPhenomena‐based approaches have become popular for elementary school teachers to engage children's innate curiosity in the natural world. However, integrating such phenomena‐based approaches in existing science courses within teacher education programs present potential challenges for both preservice elementary teachers (PSETs) and for laboratory instructors, both of whom may have had limited opportunities to learn or teach science within the student and instructor roles inherent within these approaches. This study uses a convergent parallel mixed‐methods approach to investigate PSETs' perceptions of their laboratory instructor's role within a Physical Science phenomena‐based laboratory curriculum and how it impacts their conceptual development (2 instructors/121 students). We also examine how the two laboratory instructors' discursive moves within the laboratory align with their's and PSETs' perceptions of the instructor role. Qualitative data includes triangulation between a student questionnaire, an instructor questionnaire, and video classroom observations, while quantitative data includes a nine‐item open response pre‐/post‐semester conceptual test. Guided by Mortimer's and Scott's analytic framework, our findings show that students primarily perceive their instructors as a guide/facilitator or an authoritarian/evaluator. Using Linn's knowledge integration framework, analysis of pre‐/post‐tests indicates that student outcomes align with students' perceptions of their instructors, with students who perceive their instructor as a guide/facilitator having significantly better pre‐/post‐outcomes. Additional analysis of scientific discourse from the classroom observations illustrates how one instructor primarily supports PSETs' perspectives on authentic science learning through dialogic–interactive talk moves whereas the other instructor epistemologically stifles personally relevant investigations with authoritative–interactive or authoritative–noninteractive discourse moves. Overall, this study concludes by discussing challenges facing laboratory instructors that need careful consideration for phenomena‐based approaches.

Knowledge Integration in Science Learning: Tracking Students' Knowledge Development and Skill Acquisition with Cognitive Diagnosis Models

AbstractIn scientific literacy, knowledge integration (KI) is a scaffolding‐based theory to assist students' scientific inquiry learning. To drive students to be self‐directed, many courses have been developed based on KI framework. However, few efforts have been made to evaluate the outcome of students' learning under KI instruction. Moreover, finer‐grained information has been pursued to better understand students' learning and how it progresses over time. In this article, a normative procedure of building and choosing cognitive diagnosis models (CDMs) and attribute hierarchies was formulated under KI theory. We examined the utility of CDMs for evaluating students' knowledge status in KI learning. The results of the data analysis confirmed an intuitive assumption of the hierarchical structure of KI components. Furthermore, analysis of pre‐ and posttests using a higher‐order, hidden Markov model tracked students' skill acquisition while integrating knowledge. Results showed that students make significant progress after using the web‐based inquiry science environment (WISE) platform.

Organizational unlearning and service innovation of Chinese service-oriented firms: the moderating role of knowledge integration

ABSTRACT In the context of constructing an ecosystem-oriented business model, this study uses 276 questionnaire data from Chinese service-oriented firms for empirical analysis. After developing a theoretical model associate to the impact of organizational unlearning on service innovation, this study explores the moderating effect of knowledge integration. The results indicate that organizational unlearning has a positive effect on service innovation while knowledge integration has a moderating effect on this relationship. This study not only enriches the analytical framework of knowledge integration from the perspective of organizational unlearning, but also provides valuable insights for firms to optimize service innovation.

Music Information Technology as a Practical Direction for Developing the Innovative Abilities of Future Music Educators

In the contemporary education landscape, music education often finds itself sidelined or undervalued, prompting educators to continually seek its significance. As the 21st century unfolds, education is not just about knowledge dissemination but is evolving to emphasize societal integration and interaction. Music education, in tandem, is transitioning from mere musical training to nurturing diversified thinking and societal viewpoints. Yet, the potential of music information technology in this redefined context remains under-explored. This study delves into this domain, employing the Technological Pedagogical Content Knowledge (TPACK) integration framework and the Project-Based Learning (PBL) method. Findings underscore the centrality of the TPACK framework in the teaching process, emphasizing that educators must not only master content and pedagogical knowledge but also adeptly harness technology to augment teaching and learning. This manuscript uniquely positions music information technology as a pivotal tool for cultivating the innovative prowess of future music educators.

Innovation design oriented functional knowledge integration framework based on reinforcement learning

According to the basic law of Design Science, new product design is based on existing design knowledge. Knowledge integration can be applied to product function design to shorten design time and improve the design quality through effective use of the existing knowledge. With the increase of the product design complexity and the number of design knowledge, it is harder and harder for traditional traversal-based algorithms to complete knowledge integration under acceptable time cost. A Reinforcement Learning (RL) based functional knowledge integration framework is proposed. The functional knowledge is represented by its input and output, and organized using a knowledge graph. The Q-network is constructed and trained for the deep Monte Carlo method-based functional unit chain generation algorithm. The performance experiments show that comparing with the traditional searching algorithms, the RL based algorithm can provide same quality design scheme with much shorter time. The proposed algorithm is promising to realize real-time functional knowledge integration in large-scale knowledge bases.

CBKI: A confidence-based knowledge integration framework for multi-choice machine reading comprehension

External knowledge has been introduced into pretrained models to enhance answer reasoning in machine reading comprehension tasks. However, most methods directly take the retrieved knowledge as input without considering the reliability and applicability, which may induce information redundancy and generate noise. In this paper, we propose a confidence-based knowledge integration framework (CBKI) to enhance the pretrained model with the ability of active knowledge acquisition and identification. In particular, we introduce a confidence mechanism, which is composed of three modules, namely, confidence estimation, confidence perception and knowledge integration. Specifically, for the candidate knowledge retrieved from the external knowledge base, the confidence estimation module first calculates the probability score of the candidate knowledge effectiveness in answer prediction. Then, the confidence perception module determines whether the candidate knowledge should be adopted for semantic inference at the current step. Finally, the knowledge integration module evaluates how much information should be absorbed from the candidate knowledge and merges the knowledge into the model. Experimental results on standard datasets show that the proposed CBKI is superior to BERT with an increase of 4.08% in accuracy. Furthermore, the CBKI also shows great advantages in robustness and interpretability.

Data science knowledge integration: Affordances of a computational cognitive apprenticeship on student conceptual understanding

AbstractThis study implements a computational cognitive apprenticeship framework for knowledge integration of Data Science (DS) concepts delivered via computational notebooks. This study also explores students' conceptual understanding of the unsupervised Machine Learning algorithm of K‐means after being exposed to this method. The learning of DS methods and techniques has become paramount for the new generations of undergraduate engineering students. However, little is known about effective strategies to support student learning of DS and machine learning (ML) algorithms. The research questions are: How do students conceptualize their understanding of an unsupervised ML method after engaging with interactive visualizations designed using the computational cognitive apprenticeship approach? How do the affordances of the interactive visualizations support or hinder student knowledge integration of an unsupervised machine learning method? Design‐based research allowed for the iterative design, implementation, and validation of the pedagogy in the context of a working classroom. For this, data collection methods often take the form of student artifacts. We performed a qualitative content analysis of students' written responses and reflections elicited during the learning process. Results suggest that the computational cognitive apprenticeship promoted knowledge integration. After interacting with the computational notebooks, most students had accurate conceptions of the goal and the nature of the method and identified factors affecting the output of the algorithm. Students found it useful to have a concrete representation of the method, which supported its conceptual understanding and showcased the acquisition of strategic knowledge for its appropriate execution. However, we also identified important misconceptions students held about the algorithm.

Preservice elementary teachers’ explanations of properties of sound using a Web-based Inquiry Science Environment (WISE)

ABSTRACT Background Understanding the properties of sound is difficult for students across all grade levels and even preservice elementary teachers (PSETs). Because of their abstract nature, there are challenges interpreting common features of sound waves. Purpose The goal of this study is to understand pre-service elementary teachers’ (PSETs) understanding of the properties of sound waves, specifically frequency, wavelength, and amplitude. Sample We had 59 PSETs from an elementary methods science course learn about the properties of sound in small groups through a Web-based interface. Design and Methods After they used a simulation model of an oscilloscope, we analyzed PSETs’ responses to three prompts assessing their understanding of the relationships among frequency, wavelength, and amplitude. They were asked to construct explanations for the changing frequency in an oscilloscope, how adding water to a container changes the pitch of sound and how the frequency changes in a water-based xylophone. We used the Knowledge Integration (KI) framework to understand how PSETs reasoned through properties of sound waves. Results Our findings delineated three levels of explainers that PSET groups divided into. After the unit PSETs’ overall understanding of sound waves became more normative, particularly around ideas of frequency and wavelength. Conclusions The merging of science and technology played a crucial role in promoting meaningful learning for PSETs. Implications of using technology-enhanced units in supporting PSETs’ understanding of sound waves are discussed.

Deep knowledge integration of heterogeneous features for domain adaptive SAR target recognition

How to integrate various heterogeneous features for better recognition performance is increasingly critical for automatic target recognition. Existing integration methods present the following drawbacks: (1) most feature integration methods ignore the information, both common and discriminate knowledge, among different types of features; (2) most decision integration methods ignore the fact that different knowledge contributes differently; (3) the feature weights of integration model learned in the source domain cannot perform well in the target domain. To tackle these problems, we propose a deep Knowledge Integration framework by combining heterogeneous features for Domain Adaptive synthetic aperture radar (SAR) target recognition (KIDA). In the training phase, we implement deep knowledge integration at both feature and decision levels. At the feature level, to exploit the common and discriminative knowledge, multiple heterogeneous features are projected from the feature space into a unified label space by exploring the shared and specific structures simultaneously. The shared structure integrates common information in different features, while the specific structure reserves discriminative information of each type of feature. At the decision level, to reveal the relative importance of different knowledge, a decision integration strategy with feature weights is adopted in the label space. In the online testing phase, to improve the generalization of the model in dynamical environments, we employ online learning with sequential target domain knowledge to update the feature weights, thus achieving domain adaptation. Extensive experiments on different datasets validate the effectiveness and advantages of the proposed KIDA, especially in noisy environments.

Weakly Correlated Knowledge Integration for Few-shot Image Classification

Various few-shot image classification methods indicate that transferring knowledge from other sources can improve the accuracy of the classification. However, most of these methods work with one single source or use only closely correlated knowledge sources. In this paper, we propose a novel weakly correlated knowledge integration (WCKI) framework to address these issues. More specifically, we propose a unified knowledge graph (UKG) to integrate knowledge transferred from different sources (i.e., visual domain and textual domain). Moreover, a graph attention module is proposed to sample the subgraph from the UKG with low complexity. To avoid explicitly aligning the visual features to the potentially biased and weakly correlated knowledge space, we sample a task-specific subgraph from UKG and append it as latent variables. Our framework demonstrates significant improvements on multiple few-shot image classification datasets.

SSC-KA: A Framework of Space Situational Knowledge Acquisition for Status-Cognition of Satellites

With the rapid development of space technology, the environment of the space domain has become more and more complex and changeable, which brought great difficulties in cognition of space domain activity. As space domain awareness (SDA) required, any relevant information and knowledge from various sources are needed as much as possible, while all of those can be sorted and integrated for effective cognition of space objects, including the cognition of their status. This paper proposes a knowledge integration framework (SSC-KA) designed for the cognition of space target and its status. In the framework (SSC-KA), open-source information and data acquired from multi-kinds of sensors are sent into parallel channels, and then processed by the algorithm this paper designed into sequence data as the channels’ output. Furthermore, the rules and four statuses defined in this paper can be judged for the anomaly detection of satellites. Based on the space domain knowledge acquisition framework of SSC-KA, this paper describes a complete abnormal state detection method for satellites step by step through multi-level feature engineering. Therefore, the method is used to analyze four different statuses of satellites in this paper, to verify the validity and feasibility of the application of the method in the cognition of spatial events, thus laying the foundation for the cognition of Space Domain Awareness.

Computer-based guidance to support students’ revision of their science explanations

As they encounter new ideas, students need to make integrated revisions to their science explanations, a key aspect of science learning. This involves filling gaps, resolving inconsistencies with evidence, and strengthening connections among ideas. Rather than making integrated revisions, even after automated, adaptive guidance, students typically add disconnected ideas or fix mechanical errors. The knowledge integration framework, supported by new technologies including natural language processing, guided the design of the Annotator, a tool that models the revision process for students’ written explanations. This research investigates the added value of the Annotator compared to automated, adaptive guidance to support students to make integrated revisions to their science explanations and to strengthen knowledge integration. 798 6th and 7th-grade students from 4 schools participated in a study featuring pretests, posttests, embedded student explanations, student interviews and observations. Students using the Annotator who initially displayed unintegrated ideas were more likely to make integrated revisions to their explanations, than students receiving automated, adaptive guidance. These students also made greater knowledge integration revisions on the posttest one week later. Thus, modeling revision with the Annotator strengthened the ability of students who started with unintegrated ideas to explain scientific phenomena.

Convergence of Blockchain, Autonomous Agents, and Knowledge Graph to Share Electronic Health Records

In this article, we discuss a data sharing and knowledge integration framework through autonomous agents with blockchain for implementing Electronic Health Records (EHR). This will enable us to augment existing blockchain-based EHR Systems. We discuss how major concerns in the health industry, i.e., trust, security and scalability, can be addressed by transitioning from existing models to convergence of the three technologies – blockchain, agent-based modeling, and knowledge graph in a decentralized ecosystem. Each autonomous agent is responsible for instantiating key processes, such as user authentication and authorization, smart contracts, and knowledge graph generation through data integration among the participating stakeholders in the network. We discuss a layered approach for the design of the proposed system leading to an enhanced, safer clinical decision-making system. This can pave the way toward more informed and engaged patients and citizens by delivering personalized healthcare.

The role of knowledge integration in shaping the capabilities and success of a charity: an in-depth case study analysis

PurposeMaking effective use of the knowledge available to a charitable organization is crucial to the achievement of its strategic objectives and the outcomes of its humanitarian interventions. This study aims to explore the integration of knowledge at an international development charity from the perspective of its workforce.Design/methodology/approachRich primary data were collected through an in-depth case study of a large international development charity actively embracing the management of knowledge using semi-structured interviews (n = 42), participant observation and organizational documentation. The data were integrated and analyzed thematically.FindingsThe analysis of the empirical data sheds light on how a more systematic framework for knowledge integration and application could enhance the capabilities and strategic effectiveness of a charitable organization.Originality/valueThe findings enable important contributions to the strategic management and effective use of knowledge in charitable organizations by empirically uncovering how a more coherent and structured approach to knowledge management could enhance the focus, efficiency, flexibility and relevance of its actions and those of its members. Accordingly, this paper advances a new integrated schema to meet the goals of charities and their stakeholders for broader application and testing by charities and future researchers.

Longitudinal impact of interactive science activities: Developing, implementing, and validating a graphing integration inventory

AbstractIntegrating sophisticated graphical analysis skills as they learn science is essential for K‐12 students and emphasized in current standards. In this study, we iteratively designed a Graphing Integration Inventory (GII) over a three‐year period, while also supporting students to develop their capabilities to use graphs to learn science content in complex ways through interactive curriculum materials implemented on a novel technology enhanced curriculum platform. We applied the Knowledge Integration framework to design the curriculum, the assessments, and the rubrics for scoring student explanations. The framework delineates ways to promote links among graphs and science ideas. The rubrics award students higher scores on their explanations based on the level of complexity of their connections between science concepts and, in this research, graphs. The GII and the aligned curriculum were implemented by over 300 middle school students (Grades 6–8) across a 3‐year period. We investigated the impact of the designed curriculum on the integration of graphing and science while also studying the psychometric properties of the GII to validate it for use in future studies. Findings suggest both that the curriculum used to support these students improved their Knowledge Integration capabilities significantly and that the GII instrument is suitable for use with populations across gender and native English language status demographics in Grades 6–8. Implications are discussed around using graphs to learn complex science ideas, as well as the affordances of technology enhanced platforms to support this type of learning and assessment.

Elaboration and Use of Communication Media in Teaching and Learning The Arabic Language for Foreigners | اندماج وسائل الاتصال واستخدامه في تعليم وتعلم اللغة العربية للناطقين بغيرها

This paper addresses the issue of teaching and learning the Arabic language for non-native speakers through its focus on an integrated vision of the means of communication. Through the descriptive method the process of employing communication techniques in teaching and learning the Arabic language for non-native speakers through three topics. The first topic deals with teaching and learning the Arabic language for non-native speakers, and the second topic deals with the employment and use of communication methods in this matter, and the third topic is a vision on strengthening the relationship between Sudan and the Republic of Indonesia, through the establishment of a Sudanese Center for Distance Education to spread the Arabic language and Islamic sciences.The paper concluded that the adoption of audio and visual laboratories in teaching Arabic in various stages of study, in addition to traditional methods, can create an attractive environment to contribute to teaching the Arabic language for non-native speakers and upgrade the skills of Arabic writing by adopting the concept of paper and network research. The research analysis relied on some primary references and secondary sources, which were available to the researcher.This research is distinguished from other previous research in a number of points. One of them is the ground on which the researcher relies on the specialization in the field of media, as he addresses the issue of the Arabic language from several approaches that combine education, media and linguistics to achieve the goals of the research within the framework of knowledge integration between science.

Uncovering Demographic Trends and Recent Urban Expansion in Metropolitan Regions: A Paradigmatic Case Study

While urbanization trends have been characterized for a long time by deconcentration of inner cities with expansion of low-density settlements, economic repolarization leading to re-urbanization and recovery of central districts are now counterbalancing population shrinkage in compact urban areas and slowing down suburban growth. In this context, the recent demographic evolution of a large metropolis such as Athens (Greece)—following expansion, crisis, and a more subtle economic recovery—may reveal original relationships between form and functions at the base of recent urban growth. Based on an exploratory analysis of demographic indicators on a metropolitan and urban scale, the present study provides an updated and integrated knowledge framework that confirms and integrates the most recent urban trends in southern Europe. Documenting the emergence of more individualized paths of urban expansion at the local scale (recovery of the historic center, shrinkage of semicentral neighborhoods, ‘reverse gentrification’ of disadvantaged peripheral areas, late suburbanization of accessible peripheral areas), results of the present study justify an ad hoc analysis of metropolitan growth based on demographic indicators as a proxy for sustainable land management and local development.

The philosophy of the workplace spirituality in the third millennium organizations: A field study at the Ministry of Health Center

Purpose: The research aims to build an integrated knowledge framework for the basic research topic. The spirituality of the workplace is through access to the most important scientific proposals on these topics. In Management Thought Framing the knowledge within them in a serious attempt is to provide the appropriate answers about the intellectual dilemma of research. By diagnosing the nature of the relationship with the influential elements and its historical development . METHODOLOGY: The study relied on the analytical survey method. The research sample targeted (88) managers in the center of the Iraqi Ministry of Health exclusively from the researched senior leaders (general manager, assistant general manager, and head of department), and the main tool for research was represented by relying on solid international standards For the research variable after it has been adapted to the needs of the Iraqi environment, hypotheses and data analysis have been tested using the appropriate statistical tools (arithmetic mean, standard deviation, differential coefficient and confirmatory factor analysis) Theoretical results: The research results are formulated according to the process of intellectual reasoning and philosophical variables. Workplace spirituality in its broad sense encompasses a multidimensional concept linked to hope, desires, thinking patterns, emotions, feelings and behaviors. They are critical element in organizations' interactions with employees , customers and the community Individuals were able to integrate into their careers and enhance their job satisfaction . Practical results: The results of the statistical analysis showed the weak interest of the Ministry of Health in the spirituality of the workplace, as a result of the Ministry’s focus on routine official aspects and neglecting the spiritual aspects, feelings, and feelings of workers, which generally affected the organizational climate of the Ministry, which lost it the element of spiritual interaction that is most in need The result of the ministry’s work, which calls for a spirituality in the workplace. Originality/ Value: Focusing on the emotional and spiritual aspect of the employees. Technological developments have adversely affected social communication between employees and The sense of isolation has increased. This has adversely affected performance and creativity at work. So it was necessary to increase the actual attention to spiritual reality in the workplace. This is evidenced by the fact that some organizations have begun to set up special sections dealing with the spirituality of the workplace as the case within the American Academy, the spirituality of management and the religious interests group (MSR Group). To address specific spiritual issues

Design and validation of a music technology course for initial music teacher education based on the TPACK framework and the project-based learning approach

This project outlines a design for, and presents an evaluation and validation of, an information and communication technology (ICT) training course on an initial teacher education programme for pre-service music teachers at a Spanish University. The primary objective was to improve initial teacher education in music technology through a course design with two key components: (1) constructivist learning through collaborative projects (PBL) and (2) the technological pedagogical content knowledge (TPACK) integration framework. The course saw students carry out four real-life projects, three of which involved the elaboration of educational material through the exclusive use of musical technology, and one of which involved an ICT research project. Results were obtained through an end-product evaluation and a self-assessment questionnaire and indicated that the course was well received and highly valued by the participants. In their self-assessment responses, students spoke of the academic value of the course, a confidence in their own skills, their willingness to use ICTs in future teaching contexts, the importance of ICTs in their degree programme, the fact that the course surpassed their expectations in terms of achievement (a fact corroborated through data triangulation in the end-product evaluation) and the transferability of the knowledge acquired to the music classroom. Finally, they provided suggestions for potential improvements to the course.

BERST: An Engine and Tool for Exploring Biomedical Entities and Relationships

To facilitate the search of rapidly growing biomedical knowledge in literature, we developed a Biomedical entity-relationship search tool (BERST). It is also a biomedical knowledge integration framework, which presently contains six popular databases represented in terms of a network of concepts and relations extracted from these knowledge sources. Users search the integrated knowledge network by entering keywords, and BERST returns a sub-network matching and representing the keywords and their relationships. The resulting graph can be navigated interactively allowing users to explore specific paths between any two nodes representing potentially interesting relationships between them. A graphical UI was developed to provide a more intuitive and overall view of the information being searched and studied. BERST framework can be naturally expanded to integrate other biomedical knowledge sources. BERST is implemented as a Java web application.