Knowledge Management in Academic Community

Students are roots of a country's economic-expansion, often opt for different forms of Code-Content based Plagiarism in University Programming-Labs to avoid time-consuming and challenging academic tasks or due to grades, and peers pressure. Students may lack analytical and logical program development skills. This urges for need of Smart and Computationally-Intelligent system like University Code-Content Plagiarism Prevention Model (UCCPM) to keep a check and prevent incidences of plagiarism in Universities. Integration of ‘UCCPM Intelligence' with ‘MARG's Prevention' would prove to be a beneficial Academic Predictive Model. It would open new vistas of knowledge oriented academic-research and knowledge management in academic and research community. Key to nation's wealth is knowledge, which in turn, traces back to academic research and the level of knowledge attained among students' in Universities. Hence the undertaken research provides directions to Universities to smartly detect cases of plagiarism and take appropriate measures to prevent it.

Application of Knowledge Management in University Research and Higher Education

Institutions of higher learning are continuously striving to create and sustain excellence. In this endeavor, one of the major initiatives is to harness the available inputs i.e., the in-house resources and put the same to optimal use. In organizations of higher learning, knowledge creation and dissemination are the assets of the institution. The Department of Commerce and Management at Jyoti Nivas College has initiated the formation of COPs .These COPs are created by the workforce among themselves. It is not handed down from the top level management. It fits into the framework of a ‘peer group' which can function as an informal community of peers and which can evolve into an institutionalized forum for interactions that creates and generates knowledge. In these COPs parallel or concurrent thought process happens, wherein, decentralization increases, dependence on one person as source for ideas reduces. These communities' sharing activity can be taken up at academic research community, researcher's group on KM. It is a step towards collaborative learning.

Knowledge Management Academic Research

The errands in various workplaces demand effective teamwork and cooperation among the personnel. To prove a best team member, leader and authority in industries, it is essential to develop strong human relationship-base at academics level itself. This base is nothing but surfing through entire life-cycle phases related to knowledge: acquire, represent, use, and augment. This chapter focuses on the implementation of Knowledge-Management and Augmentation for academics, to establish compatibility among various relationships in academic field like students, faculty, principal, higher authorities, teaching and non teaching staff, using Astrology & Numerology with IT. It also endeavours to promote the inclination in students of giving magnitude to create the compatibility in interpersonal relationships. This inclination will assist all academic entities, to be compatible with their colleagues in potential domains related occupations.

Data Mining Techniques in Knowledge Management

The ability to manage knowledge is becoming increasingly more crucial in today's knowledge economy. The creation and diffusion of knowledge have become ever more important factors in competitiveness. More and more, knowledge is being regarded as a valuable commodity that is embedded in products (especially high-technology products) and in the tacit knowledge of highly mobile employees. Data mining is an essential tool, which is used to predict and classify the data collected from the customers. Data mining can be applied for classifying and clustering student characteristics based on demographic, psychographic and behavioural variables. Data mining can also be applied by using if-then rule. In addition, it can describe the profile of successful and unsuccessful students based of GPA achieved during the semesters. This chapter aims to study the role of data mining in the education sector and emphasizes on the role of knowledge management in educational institutions.

The Knowledge Management Culture

Knowledge management is defined by different authors as the process that enables the sharing, capture and application of knowledge from the individual to the group and further to organizational level. The organizational atomization observed in the academia imposes importance in paying attention to a culture that encourages knowledge management and also assigns equal importance to the cooperation and the work in team. However, due to the different levels of heterogeneity among and within these organizations there is not just one model that fits well. Through a literature review on the knowledge management in the academia, the purpose of this chapter is an exploratory study that identifies the main cultural challenges in the development and implementation of a knowledge management system in the academic context.

The Technological Knowledge as Strategy for Academic Research

The chapter was intended to provide an original and creative review of the literature on the dynamics of technological knowledge. It is argued that among the new developments on the theme, the investigation on endogenous complexity in technological knowledge is certainly the most promising advance. First it provides an accurate representation of how knowledge is created and diffused at the analytical level, and second it also benefits of an empirical value since it can be expressed by a wide range of indicators and measures. In particular, it is claimed that such framework has a great potential in that it provides both the theoretical and empirical grounds to carry out an interdependent analysis of technology as an act and as an artefact. In this direction, the structure of technological knowledge is represented as a network the architecture of which is in turn influenced by the architecture of the network of innovation, and vice versa.

Impact of Interactive Multimedia in E-Learning Technologies

Multimedia-based technologies have significant impact on our daily life learning activities as they have shifted the education from teacher centered to learner centered. E-learning provides opportunities to people to take course online and provide a virtual classroom environment on the web through teacher learner interactions, course material distribution based on interactive multimedia. Interactive multimedia offers learners different forms of media to match their learning style, provides personalization of adaptive content delivery which enhanced learners learning effectiveness. In this chapter, we have discussed how information quality can be improved by multimedia based authoring tools and approaches, also identified the negative and positive effects of using interactive multimedia for learners in E-learning. Finally, focus was given on current E-learning multimedia technologies, their research challenges and future trends on social networking based technologies.

Five Principles for the Practice of Knowledge Exchange in Environmental Management

The principles are designed into the analysis; and different stakeholder should be consistently delineated within the research. Long-run relationships should be designed on trust and two-way dialogue between researchers and stakeholders so as to confirm effective co-generation of latest data. The delivery of tangible advantages within the analysis method helps to confirm continuing motivation and engagement of doubtless analysis users. Knowledge exchange could be a versatile method that has to be monitored, reflected on and endlessly refined, and wherever potential, steps should be taken to confirm a heritage of in progress Knowledge exchange on the far side initial analysis funding. The principles are used Knowledge exchange and Stakeholder engagement pointers for two international analysis programs. They're able to assist researchers, decision-makers and different stakeholders operating in contrasting environmental management settings to figure along to co-produce new data, and additional effectively shares and apply existing data to manage environmental modification.