Microsoft Word - izanga.doc ISSN 1822-8402 EUROPEAN INTEGRATION STUDIES. 2007. No 1 KNOWLEDGE MANAGEMENT FRAMEWORK PROPOSAL Mirela Minica Florin Frant University „Eftimie Murg” Resita Abstract Based on production process in companies we developed a model of knowledge management that can be implemented in our university. This model is using organizational knowledge base of three entities: the research engine, the production engine and the learning engine. We try to identify several direct and indirect feedback from the production process and research process linked with external demands and internal university objectives. This model can be implemented on World Wide Web and Internet technologies using collaborative model. Keywords: Academic management, research, knowledge. Introduction More than a decennium, idea of public higher education that has come to dominate is that of an industry, rather than that of a social institution and identified three interrelated mechanisms: 1) academic management, 2) academic consumerism, and 3) academic stratification. (Gumport, 2000). Academic management assume that managers are expected to monitor the organization-environment interface, determine appropriate strategies, and develop effective bridging and buffering mechanisms. In academic consumerism public universities and colleges serve needs and interests of several types of consumers (e.g., taxpayers, employers, research funders, students) come to mind, when considering who. Now the students are consumers of public higher education, and treat those as potential or current employee who seeks workforce training. Academic re-stratification1 based upon the increased use-value of particular knowledges in the wider society and exchange-value in certain markets and involve academic subjects and academic personnel (Clark, 2001). Knowledge is the defining core of academic work and academic workers, higher education has central knowledge functions. For those reason, several concepts and technologies like: Group Support Decision (GSS), Computer Supported Cooperative Work (CSCW), Web Based Learning (WBL), Web- 1 Knowledge is “the prime material around which activity is organized ...Knowledge materials, and advanced ones at that, are at the core of any higher education system’s purposes and essence. This holds true throughout history and across societies as well”, (Clark, 2001, p. 13) Base Course Environment, Open Distributed Processing – Reference Model – Enterprise Viewpoint2, and CommonKADS methodology KMM methodology can help us to find a model for an academic virtual enterprise, based collaborative paradigm, in which we centre Knowledge management and intellectual capital. (Bodea, 2004) Conceptual Model of Knowledge Management Framework Gravin (1993) defines the learning organization as one that is “skilled at creating, acquiring and transferring knowledge, and at modifying its behavior to reflect new knowledge and insights” (p. 80) and the members of a learning organization are continually creating knowledge and increasing their capacity to produce results and take effective action (Huber, 1991). Knowledge management is defined as a process through which organizations create, store and utilize their collective knowledge. His process includes three stages: organizational learning (the process of acquiring information) knowledge production (the process of transforming and integrating information into usable knowledge) and knowledge distribution (the process of disseminating knowledge throughout the organization) (Sarvary,1999). In universities like any organization knowledge creation is changed from tacit to explicit in four modes: socialization, externalization, combination and internalization (SECI). (Nonaka, I., Takeuchi, H, 1995), (Ahmad, 1999). The hypertext organization 2 ISO/IEC documents for conceptual modeling in virtual enterprise (eg. holonic, fractal and bionic) 57 ISSN 1822-8402 EUROPEAN INTEGRATION STUDIES. 2007. No 1 has “a strategic ability to acquire, create, exploit, and accumulate new knowledge continuously and repeat- edly in a circular process” (Nonaka, I., Takeuchi, H 1995, p. 34). In our model we present a conceptual model of knowledge management inspired by Nonaka’s concepts, adapted on virtual enterprise paradigm and linked on Strategic Plan in “ Eftimie Murgu” University (Lipnack and Stamps, 1997). We have developed and applied the concepts of knowledge management, Nonaka’s hypertext organization and learning organizations to the university context, based on Piccoli approach, and we try to provide a framework for drawing on the capabilities of faculty and students and managing information (Ahmad, 1999) in order to increase intellectual capital and academic stratification for staff and faculties, in perspective of globalization. We use engineering representation with several feedback’s loop depending on several management processes, provided by three entities: Learning Engine, Production Engine and Research Engine (figure 1). Learning Engine has the aim to manage knowledge utilization, by giving students possibilities to use, apply, absorb the stored knowledge. Knowledge acquisition and generation are made in faculty and researchers’ teams in the Research Engine. This engine monitoring progress and evaluating results and provide guidance for Development Programs, depending on a set goals for the organization. Research Projects and Programs has a role to increase intellectual capital and generate a high value of knowledge. In the production engine, stored knowledge are using to produce and codify knowledge as part of knowledge generation and knowledge storage. This engine has a feedback from Research Engine, as a supervisor of managing knowledge. As we saw, we have three different feedbacks, depending on external influences in every loop. First we have Direct and indirect feedback on the learning outcome gived by Development Programs, and Indirect feedback. Development Programs are depending on management strategy from university and major goals from Consortioum Universities or partnership with other universities from globalization perspective. Indirect feedback depends on interaction with social, economical environment. Second loop link Research Engine to external demands (international programs, national strategy, educational priorities) to the Production Engine, as a slave engine coordinate by increased knowledge storage from Project goals and directives. Third loop has major role to knowledge quality, by measuring intellectual capital as a quantification of fundamental and applied results from Research projects and Programs3. Actors and their role Learning Engine (LE) coordinates and makes guidance for undergraduate and graduate students, and is main user of knowledge created by others engine. Production Engine(PE) has concerned to graduate students or post graduate students and Research Engine (RE) bring together faculties, postgraduate student, doctoral candidate and other researcher. For LE and PE we have several particular situations in “Eftimie Murgu” University (UEM): • undergraduate students in two different Faculties; • undergraduate students in one faculty and graduate students in other faculty; • post graduate students in one university and graduate students in other faculty/ university; • post graduate students in UEM and graduate students in other faculty/ university ; • undergraduate students in one specialization, and graduate students in other specialization, in same faculty ; • graduate students in one specialization, and post graduate students in other in same faculty ; For this reason we will meet same actor (student) in LE and PE in same time. Learning is a continuous and cyclical process that provides participants at different levels in the organization either with the necessary information or the means to obtain it. RE has membership from different departments from same faculty/ different faculties, or different faculties from same universities/different universities, research centers, different postgraduate students and researchers. Their role in the research engine is: • select research areas to explore; • identify theories and hypotheses to formalize the exploration; • operationalize these theories and hypotheses in development projects; • establish guidelines and provide direction for learning and development; • assess the validity of the hypotheses and theories; • ensure the quality of the final product. • Actors from production engine can be able to: • research the content areas of the required knowledge module; 3 These results are available as research activities in thel project: “Higher Education Institution Efficiency in Romania focused on dinamics’ educational and informational demands” Grant Consortium CEEX05-D08-66/2005-2007, director Prof. Ion Gh.Roşca, PhD 58 ISSN 1822-8402 EUROPEAN INTEGRATION STUDIES. 2007. No 1 • acquire the technical skills required for its development; • confirm the final requirements for the knowledge module; • design and develop the module; • assure its quality.(Piccolo,2000). Learning engine describes how stored knowledge can be employed as a teaching tool. The courses are designed for undergraduate students but could be targeted to employees in any organization. An application and teaching offer the material and simultaneously allows the students to practice each skill. The graded assignments are structured so that the students cannot just passively follow the tutorials, but instead must actively apply and than verifying them. (Ahmad, 1999) Conclusions Internet technologies and KM paradigm, web- based learning environment facilitate a “cumulative knowledge building” (Jarvenpaa and Ives, 1994). In our model we try to three engines play a specific role in the knowledge creation process, while membership in the different engines is flexible. Most important think is how undergraduate student follow this process and is coordinate by every engine until became a actos in RE or a specialist in economical or social environment. Even in this case he can became an actor in PE or RE. References Ahmad R., Effectiveness of virtual learning environments in business education, focusing on basic skills training for information technology, Louisiana State University, Baton Rouge, LA (1999). Bodea V., Managementul cunoştinţelor în proiecte, în Managementul proiectelor informatice, Editura ASE Bucuresti, 2004. Clark, B.R., The problem of complexity in modern higher education’, in Rothblatt, S. and Wittrock, B. (eds.), The European and American University Since 1800. Cambridge: Cambridge University Press. Garvin, D.A., Building a learning organization, Harvard Business Review 71 (1993) 78–92. Gumport, P.J., Academic restructuring: Organizational change and institutional imperatives, Higher Education 39: 67–91, Kluwer Academic Publishers, 2000 Lipnack J. and Stamps J, Virtual Teams: Reaching Across Space, Time and Organizations with Technology (John Wiley & Sons, Inc., 1997). Massy W.F. and Zemsky R., Using Information Technology to Enhance Academic Productivity (Inter-University Communications Council, Inc., 1995). Merrill M.D., Instructional Design Theory (Educational Technology Publications, Englewood Cliffs, NJ, 1994). Huber G.P., Organizational learning: The contributing processes and the literatures, Organization Sciences 2 (1991) 88–115. Jarvenpaa S. and Ives B., The Global Network Organization of the future: Information opportunities and challenges, Journal of Management Information Systems 10 (1994) 25– 57. Nonaka, I., Takeuchi, H., The Knowledge-Creating Company: how Japanese companies create the dynamics of innovation. Oxford University Press. New York, 1995. Piccoli G. Ahmad R., Ives B., Knowledge management in academia: A proposed framework, Information Technology and Management 1 229–245 229, Baltzer Science Publishers BV, 2000. Sarvary M., Knowledge management and competition in the consulting industry, California Management Review 41 (1999) 95–108 59 1Learning Engine Indirect feedback Stored Knowledge Production Engine Research Engine Feedback to the production process External Demands Project Goals and Directives Development Programs Research Projects and Programs Feedback on the Research Process Management Strategy Demands Fundamental and applied results Direct and indirect feedback on the learning outcome Figure 1. Conceptual model of Knowledge Managemenent 60 ISSN 1822-8402 EUROPEAN INTEGRATION STUDIES. 2007. No 1