Network centrality,knowledge searching and creativity: The role of domain

This study aims to determine the role of knowledge searching on creativity in the fields of science research and technology development. Creativity is a process of knowledge combination, thus internal and external knowledge searching is important for creativity in both fields, particularly in the open innovation age. However, the nature of the work across these fields is different. While science research aims to solve theoretical problems and generate new knowledge, technology development aims to apply new knowledge to solve practical problems. Compared to science research, technology development has clear task goals, which make it easier to identify the related external knowledge and integrate this knowledge and in turn improve employee creativity. Thus, employees' attention to external knowledge as well as the influence of external knowledge on creativity might be different in the two fields. Results based on an empirical study of 211 employees from science research and 257 employees from technology development showed that external knowledge searching increased employee creativity in the field of technology development but not in science research. Furthermore, employees' centrality in the intra‐team problem‐solving network moderated the relationship between external knowledge searching and creativity in the science research field. Suggestions about employee creativity management in science and technology fields are discussed.     

复杂问题知识转换的综合集成

复杂问题处理是一项知识密集型任务,在综合集成法的应用中对于相关知识转换过程的把握具有重要意义。文中针对问题的复杂性特点提出一种知识转换过程模型,基于显性知识同隐性知识间的转换,经过认知、外化、集成、内化一系列螺旋上升的动态知识过程获得知识创新。该模型被用于支撑处理复杂问题的方法论——综合集成法,丰富充实问题研讨流程。通过复杂灾害问题实例说明结合知识管理的综合集成法应用。     

Model‐Based Visualization of Temporal Abstractions

We describe a new conceptual methodology and related computational architecture called Knowledge‐based Navigation of Abstractions for Visualization and Explanation (KNAVE). KNAVE is a domain‐independent framework specific to the task of interpretation, summarization, visualization, explanation, and interactive exploration, in a context‐sensitive manner, of time‐oriented raw data and the multiple levels of higher level, interval‐based concepts that can be abstracted from these data. The KNAVE domain‐independent exploration operators are based on the relations defined in the knowledge‐based temporal‐abstraction problem‐solving method, which is used to abstract the data, and thus can directly use the domain‐specific knowledge base on which that method relies. Thus, the domain‐specific semantics are driving the domain‐independent visualization and exploration processes, and the data are viewed through a filter of domain‐specific knowledge. By accessing the domain‐specific temporal‐abstraction knowledge base and the domain‐specific time‐oriented database, the KNAVE modules enable users to query for domain‐specific temporal abstractions and to change the focus of the visualization, thus reusing for a different task (visualization and exploration) the same domain model acquired for abstraction purposes. We focus here on the methodology, but also describe a preliminary evaluation of the KNAVE prototype in a medical domain. Our experiment incorporated seven users, a large medical patient record, and three complex temporal queries, typical of guideline‐based care, that the users were required to answer and/or explore. The results of the preliminary experiment have been encouraging. The new methodology has potentially broad implications for planning, monitoring, explaining, and interactive data mining of time‐oriented data.     

What does it mean? Students’ procedural and conceptual problem solving in a CSCL environment designed within the field of science education

This article discusses the relationship between procedural and conceptual problem solving in a computer-supported collaborative learning (CSCL) environment designed within the field of science education. The contribution of this article, and our understanding of this phenomenon, is anchored in our socio-cultural interpretation, and that implies distinctive inputs for the design and re-design of these kinds of learning environments. We discuss institutional aspects linked to the school as a curriculum deliverer, as well as to the presentation of the knowledge domain and the construction of the CSCL environment. The data is gathered from a design experiment in a science setting in a secondary school, and video data is used to perform an interaction analysis. More specifically, we follow a group of four secondary school students who solve a biological problem in a computer-based 3D model supported by a website. Our findings are clear in the sense that the procedural types of problem solving tend to dominate the students’ interactions, while conceptual knowledge construction is only present where it is strictly necessary to carry out the problem solving. Based on our analyses, we conclude that this can be explained partly by how the knowledge domain is presented and how the CSCL environment is designed, but that the main reason is linked to the institutional aspects related to the school as curriculum deliverer where its target is to secure that the students actually solve problems that are predefined in the syllabus list. We argue that this affords some particular challenges, linked to making conceptual knowledge constructions in science education explicit in the CSCL environment, and to encouraging the teachers and the school as a curriculum deliverer to give this kind of knowledge construction a prioritised value.     

The effects of computer simulation and animation (CSA) on students' cognitive processes: A comparative case study in an undergraduate engineering course

This study focuses on the investigation of the effects of computer simulation and animation (CSA) on students' cognitive processes in an undergraduate engineering course. The revised Bloom's taxonomy, which consists of six categories in the cognitive process domain, was employed in this study. Five of the six categories were investigated, including remember, understand, apply, analyze, and evaluate. Data were collected via a think‐aloud protocol involving two groups of student participants: One group learned a worked example problem with a CSA module, and the other group learned the same problem with traditional textbook‐style instruction. A new concept called frequency index was proposed for use in qualitative research that involves the quantitative comparison of the overall popularity of a particular mental activity performed by two groups of students. The results show that as compared to traditional textbook‐style instruction, CSA significantly increases students' activities in the understand category of the revised Bloom's taxonomy during learning and significantly increases students' activities in the understand, apply, analyse, and evaluate categories during subsequent problem‐solving. That learning via CSA has a profound impact on subsequent problem‐solving is attributed to intensive human–computer interactions built in the CSA learning module.     

Procedural versus content‐related hints for word problem solving: an exploratory study

For primary school students, mathematical word problems are often more difficult to solve than straightforward number problems. Word problems require reading and analysis skills, and in order to explain their situational contexts, the proper mathematical knowledge and number operations have to be selected. To improve students' ability in solving word problems, the problem solving process could be supported by procedural and content specific guidance or with only procedural support.. This paper evaluates the effect of two types of hints, procedural only and content‐procedural, provided by a computer programme presented in two versions. Students of grade 6 were randomly assigned to these two versions, which offered five lesson units consisting of eight word problems each. The results indicate that on average the students in the procedural‐content hints group (n = 54) finished about just as many problems in the programme as their counterparts in the procedural‐only condition (n = 51). However, the participants in the first group solved more problems correctly and improved their problem‐solving skills more as indicated by the scores on the problem‐solving post‐test. Apart from presenting our analysis of the findings of this study, also its limitations and its possible implications for future research are discussed in this paper.     

A flowchart‐based intelligent tutoring system for improving problem‐solving skills of novice programmers

Intelligent tutoring and personalization are considered as the two most important factors in the research of learning systems and environments. An effective tool that can be used to improve problem‐solving ability is an Intelligent Tutoring System which is capable of mimicking a human tutor's actions in implementing a one‐to‐one personalized and adaptive teaching. In this paper, a novel Flowchart‐based Intelligent Tutoring System (FITS) is proposed benefiting from Bayesian networks for the process of decision making so as to aid students in problem‐solving activities and learning computer programming. FITS not only takes full advantage of Bayesian networks, but also benefits from a multi‐agent system using an automatic text‐to‐flowchart conversion approach for engaging novice programmers in flowchart development with the aim of improving their problem‐solving skills. In the end, in order to investigate the efficacy of FITS in problem‐solving ability acquisition, a quasi‐experimental design was adopted by this research. According to the results, students in the FITS group experienced better improvement in their problem‐solving abilities than those in the control group. Moreover, with regard to the improvement of a user's problem‐solving ability, FITS has shown to be considerably effective for students with different levels of prior knowledge, especially for those with a lower level of prior knowledge.     

Shifting intra‐ and inter‐organizational innovation processes towards digital business: An empirical analysis of SMEs

The literature suggests that increasing investments in information and communication technologies (ICTs), knowledge exchange and sharing help SMEs tackle the current global and dynamic environment. Given that much of the useful knowledge resides outside the enterprises’ boundaries, these technological tools foster the gathering of big data and information. Despite these premises, few studies have considered the role of ICTs and big data in intra‐ and inter‐organizational ties and the consequent effects on enterprises’ innovation performance. The paper investigates whether ICTs oriented to intra‐organizational (in‐house research and development [R&D]) and inter‐organizational (open innovation) processes improve SMEs’ innovation performance. Therefore, via structural equation modelling (SEM), the study analyses a sample of 239 knowledge‐intensive SMEs located in Italy. The noteworthy results are that ICTs oriented to intra‐ and inter‐organizational innovation processes improve both these processes in generating new products and/or services. On this basis, managerial and academic implications are provided, along with avenues for further research.     

How do you frame ill-defined problems? A study on creative logics in action

Problem framing is pivotal to fostering knowledge and innovation, especially in the modern environment where problems are often ill defined. However, the managerial literature has thus far mainly addressed problem framing from an outcome perspective, overlooking the processes that lead to the outcomes. A common view is that the complexity, ambiguity and uncertainty of ill-defined problems call for a creative process. Therefore, through ethnographically observing six design thinking workshops, this study adopts a qualitative approach to explore the problem framing creative process. Specifically, we unpack three thinking modalities involved in the creative process (i.e. creative logics) of problem framing: analogical reasoning, associative thinking and abductive reasoning. We suggest that individuals enact these through seven creative operations. In addition, we link these creative operations to two types of problem framing outcomes: referenced frames and crafted frames. From a practitioner perspective, this study casts new light on the importance of problem framing for creativity and innovation, highlighting the ways in which individuals operationalize the creative logics to frame ill-defined problems as original problems worth solving.     

Towards a More Realistic Creative Problem Solving Approach

This paper takes a closer look at the existing multi‐step diamond shaped models for creative problem solving (CPS). A case history of a real‐life technical problem in which CPS techniques were used is our source of inspiration for some new ideas about approaching CPS. We propose three concurrent processes: Content finding, Acceptance finding and Information finding. In concrete in‐company projects, these three processes need to be managed simultaneously, which leads to a fourth overarching process: project management. Content finding is concerned with the process the creative session members are going through based on people's own active knowledge and ideas and on sharing their mental models to get new ideas. Acceptance finding is concerned with the co‐creation of new and additional mental systems that are needed for bringing new ideas into good currency within the existing organization and goes beyond agreement on implementation plans. Information finding is concerned with gathering additional knowledge on the ideas that are not readily available during the session. Finally, Project management is concerned with organizing and leading the creative session and in the embedding of the project into the larger organization.     

Factors of problem-solving competency in a virtual chemistry environment: The role of metacognitive knowledge about strategies

The ability to solve complex scientific problems is regarded as one of the key competencies in science education. Until now, research on problem solving focused on the relationship between analytical and complex problem solving, but rarely took into account the structure of problem-solving processes and metacognitive aspects. This paper, therefore, presents a theoretical framework, which describes the relationship between the components of problem solving and strategy knowledge.     

An analysis of collaborative problem‐solving activities mediated by individual‐based and collaborative computer simulations

Researchers have indicated that the collaborative problem‐solving space afforded by the collaborative systems significantly impact the problem‐solving process. However, recent investigations into collaborative simulations, which allow a group of students to jointly manipulate a problem in a shared problem space, have yielded divergent results regarding their effects on collaborative learning. Hence, this study analysed how students solved a physics problem using individual‐based and collaborative simulations to understand their effects on science learning. Multiple data sources including group discourse, problem‐solving activities, learning test scores, and questionnaire feedback were analysed. Lag sequential analysis on the data found that students using the two simulations collaborated with peers to solve the problem in significantly different patterns. The students using the collaborative simulations demonstrated active engagement in the collaborative activity; however, they did not transform discussions into workable problem‐solving activities. The students using the individual‐based simulation showed a lower level of collaboration engagement, starting with individual exploration of the problem with the simulation, followed by group reflection. The two groups also showed significant differences in their learning test scores. The findings and pedagogical suggestions are discussed in the hope of addressing critical activity design issues in using computer simulations for facilitating collaborative learning.     

Enhancing middle school students' scientific learning and motivation through agent‐based learning

Facing students' decreasing motivation to pursue scientific study, schools and educators need to coordinate new technologies with pedagogical agents to effectively sustain or promote students' scientific learning and motivation to learn. Although the provision of pedagogical agents in student learning has been studied previously, it is not clear what benefits the strategy might offer with regard to student motivation. This study proposes an agent‐based mechanism that integrates problem‐solving and inquiry‐based instructions to help students better understand complex scientific concepts and to sustain their motivation to learn science. In this study, a quasi‐experiment was conducted to evaluate the performance and feasibility of our proposed mechanism. The results revealed that the agent‐based mechanism was effective and feasible for enhancing students' learning and motivation to learn. The mechanism was associated with increases in the acquisition of knowledge when compared with the control group. Its effect in promoting and sustaining students' motivation was also statistically significant. Detailed discussions of the findings are provided in this study.     

Coordinated scheduling of production and logistics for large-scale closed-loop manufacturing using Benders decomposition optimization

This paper studies coordinated scheduling of production and logistics for a large-scale closed-loop manufacturing system by integrating its manufacturing and recycling process. In addition to the forward manufacturing process, different recycling units in reverse recycling process are also studied. A decentralized network is designed to formulate the coordinated scheduling problem as a mixed integer programming model with both binary and integer variables. As the problem for closed-loop manufacturing is large-scale and computational-consuming in nature, the model is divided into integer variable sub-models and complex binary variable sub-models for preprocessing and reprocessing respectively. An iterative solution approach by Benders decomposition is developed to accelerate the solving efficiency in large-scale case by updating custom constraints. A case study is conducted to investigate the managerial implications of the decentralized network for the closed-loop manufacturing system. Computational experiments demonstrate the validity and efficiency of the proposed iterative solution approach for the large-scale scenarios.     

The quality of group tacit knowledge

Organizational knowledge creation theory explains the process of making available and amplifying knowledge created by individuals as well as crystallizing and connecting it to an organization’s knowledge system. What individuals get to know in their (working) lives benefits their colleagues and, eventually, the wider organization. In this article, we briefly review central elements in organizational knowledge creation theory and show a research gap related to the quality of tacit knowledge in a group. We advance organizational knowledge creation theory by developing the concept of “quality of group tacit knowledge.” Based on this concept, we further develop a comprehensive model explaining different levels of tacit knowledge quality that a group can achieve. Finally, we discuss managerial implications resulting from our model and outline imperatives for future theory building and empirical research.     

What is TRIZ? From Conceptual Basics to a Framework for Research

This paper introduces six aspects of the theory of inventive problem solving (TRIZ), from conceptual basics to a framework for interdisciplinary research, and explains some of the specific terminology, such as inventive principles, standard solutions, substance‐field‐systems or contradictions. The conceptual approach of TRIZ comprises the way from a concrete problem over an abstract problem to an abstract solution and from there to a concrete solution. This is supported by a toolkit, which helps the problem‐solver analysing and solving problems in different perspectives. The ‘power supply for notebook computers’ example demonstrates a problem‐solving process with TRIZ using contradiction thinking, the contradiction matrix and the inventive principles as tools. The TRIZ tools may be combined within a comprehensive process model such as ARIS or WOIS, which are briefly discussed. A framework for further research suggests five fields: the tools and their combination as the core, inspiration by new knowledge domains, adaptation to new fields of usage, psycho‐ and sociological contingency and integration with other creativity tools. The paper concludes with an overview of cornerstones in the history of TRIZ and suggests some introductory books and informative websites.     

The Integration of TRIZ with Other Ideation Tools and Processes as well as with Psychological Assessment Tools

When TRIZ is introduced into an organization setting, it invariably encounters a host of processes and tools already in place. These can include enterprise tools such as Six Sigma, Design for Six Sigma (DFSS), QFD and Lean Manufacturing. It is fairly easy to combine TRIZ problem‐solving and technological forecasting with these processes and tools, because most of these enterprise tools are problem‐identifying processes that couple easily with the strong problem‐solving capabilities of TRIZ. What is more difficult is to integrate TRIZ thinking with other psychologically based creativity and assessment tools. Users and trainers for these various tools tend to be very protective about each process and do not spend sufficient time thinking about ways to integrate the best of all tools. Organizations also frequently use psychological assessment tools to assist employees in career development, but they are seldom used in a proactive way to improve group problem‐solving. These assessments can be used proactively within the use and implementation of TRIZ. This paper will review suggested ways to effectively integrate TRIZ innovation and problem‐solving principles with these other tools.     

Instructing in generalized knowledge structures to develop flexible problem solving skills

In contrast to routine knowledge and skills, flexible problem solving is associated with the ability to apply one’s knowledge structures in relatively new situations. In the absence of specific knowledge-based guidance, such processes could be very cognitively demanding. This paper suggests that learning flexible problem solving skills could be enhanced by explicitly instructing learners in generalized forms of schematic knowledge structures that are applicable to a greater variety of problems. The paper presents results of an experimental study that has investigated this approach in learning the operation of a technical device, and discusses implications of these results for the design of computer-based instruction.