MODELO PARA A FORMATAÇÃO DOS ARTIGOS A SEREM UTILIZADOS NO ENEGEP 2003

PRESENT AND PERSPECTIVES OF THE INTELLECTUAL CAPITAL MANAGEMENT IN ROMANIAN UNIVERSITY ENVIRONMENT

Radu Bucea Manea Tonis

Hyperion University, Romania

E-mail: radub_m@yahoo.com

Cezar Braicu

Hyperion University, Romania

E-mail: cezar_braicu@hotmail.com

Submission: 12/06/2018

Revision: 12/19/2018

Accept: 1/05/2019

ABSTRACT

The theory of organizational learning seems to be practical when researchers can find connections between two or more variables that can be justified and implemented. The term “intellectual capital” has appreciated over time acquiring a growing value. Work based on sustained learning contributes to the development of the intellectual capital not only of the employers, but also of the universities. In the current period of “knowledge economy” and “corporate university” development, the creation and evaluation of knowledge are recognized as important and necessary to be included in the educational programs. Knowledge management regards tacit and explicit knowledge. During the theoretical training, students mainly access information in written or verbal format, transmitted mainly on the teacher-student communication channel. During practical activities and mutual interactions, students agree to the informal knowledge, highly sought after by employers. In this paper, we will deal mainly with the ways of coding the information of statistical interest, which will be subject to a meta-level coding at the programming languages level, applicable to the analysis of the central trend and the shape of the data series distribution by estimating the parameters of the regression equation. According to the analysis, it results that in the absence of some measures to stimulate birth rate or attract foreign students, the Romanian higher education will register a considerable decline compared to the reference period in terms of the number of enrolled students.

Keywords: knowledge management, intellectual capital, university environment, information

1. INTRODUCTION

The education system of a nation occupies one of the most important places for the development of that nation, given that it envisages the transfer of knowledge, the development of human creativity, allowing the personal and social ascension of individuals.

Universities in the European space are currently under increasing pressure due to increased competition from both new universities in Europe as well as from North American and Asian universities and also to the increased negative demographic trends.

According to Giannakouris (2010, p. 11-16), Europe’s population is set to grow by 5% until 2030, with great differences between its countries and regions. For Romania, by 2030, a population reduction of almost 1.3 million is expected, due to a negative natural increase of -3.1‰ and a migration rate of 0.1‰.

Increasing the amount of intellectual capital requires two critical levers: managing its development and providing components and programs for information technology – the essential electronic elixir to gain more human, social and structural capital.

Labour-based learning offers the chance to fundamentally expand the intellectual capital of the university. Focusing on a university-based learning program as a process of recognizing, creating and applying knowledge through and for work rather than simply at work challenges the position of the university as a single validator and evaluator of high-level knowledge.

The need to demonstrate “purpose-matching” typically not only requires cognitive skills of traditional higher education (analysis, synthesis, evaluation), but also requires them to be applied in a complex situation to maximize the effectiveness of resources taking into account stakeholder expectations and time limits.

According to Dalkir (2005), coding is the final stage of the information acquisition process, after the initial stage of identifying the information source, and that of conceptualizing or understanding the information (see Figure 1).

Figure 1: The stages of the information acquisition process after Dalkir

Two aspects of the coding stage are addressed by the authors: organization and outsourcing of knowledge. The organization of explicit knowledge includes three forms: cognitive maps, decision trees, and taxonomy.

The information we are interested in is taxonomically structured on the INS website (www1) on seven main categories: social, economic, finances, justice, environment, land administration and public utilities.

2. LITERATURE REVIEW

According to Tarlea and Freyberg-Inan (2018), in Romania, higher education is oriented towards providing low and medium quality education, while the economy is oriented towards the production of industrial goods and services that require small and medium skills. In short, Romania is rooted in a low balance of abilities.

The authors started from the premise that the political and economic implications of the deterioration of higher education in Romania from 1989 can be better understood by exploring the dynamics of demand and supply of higher education and high-level skills in the Romanian economy. They argue that an imbalance of skills has emerged in our country, where a medium-educated population produces goods and services with low added value. This would not only be a symptom of Romania’s status as a dependent market economy but also helps explain the failure to overcome the quality deficiencies of the post-communist system in Romania.

The most likely way out of the current imbalance would be an evolution towards the liberal model, where universities provide general skills, and workplace preparation is done on the ground. Without an acceleration of the government’s regulatory effort and expenditures to safeguard the quality of higher education, there is little hope in the country’s ability to use better qualifications as a path to greater economic competitiveness.

Zamfir (2017) confirms the results of previous studies that highlight the persistence of educational gaps between rural and urban areas in developing countries. On the other hand, educational poverty has a positive overall trend. Unfortunately, younger generations account for a higher proportion of poorly educated people, especially in rural areas.

Moreover, the spread of new technologies (4G and 5G networks for communication, mobile interfaces in the era of IoT -Internet of Things) brings a new perspective for collaborative and distance learning that allows a balanced between work and social life for modern students.

They are keen of new technologies and IoT and come in university to experience knowledge through modern teaching methods such as VR (virtual reality) facilities integrated in E-learning platforms, in classrooms, in labs, in museums or libraries etc. Knowledge is everywhere now: on internet, in libraries, in schools, but is very difficult to access it, because the students must be initiated in the access of enormous data-warehouses and bigdata technologies.

Here comes knowledge management system that has to be offered by universities to students. These systems have to offer dynamic, interactivity, 3D visualization, Virtual reality experience as to improve education and knowledge acquisition having fun in the same time (NAZIM, 2016; SHUJAHAT, 2019; HERNÁNDEZ-LÓPEZ, 2016; PETROVA, 2015; ȚONIȘ, 2018a).

Knowledge management refers to design a model of innovation that facilitates the link between academia and the business environment is described in. The academies have to be a member of a business environment network (BEN), in which corporations and state institutions may invest in a performing open innovation platform and in licenses. In this ecosystem, students can come out with innovation in different fields. The innovation will be validated by an ecological agency as to be in accordance with circular economy principles.

This environment has to integrate a market agency to test the innovation on the market. The feasibility of the idea has to be tested by a consultant (financial) agency, that has to be part of the environment. Should all the tests finish with success, the inventors within the network and the academic researchers can come up with possible implementation solutions (XU, 2019; TONIS, 2018B; LINA, 2012).

Modern knowledge management system has to use AI technologies that are integrated in machine learning based on neural networks to image recognition based on hundreds of raw pictures of the given target to extract the most appropriated knowledge that the student is searching for. Thus, modern knowledge management system integrates deep learning and predictive analytics as machine learning methods. They also integrate translation, classification & clustering, and information extractions as method of natural language processing (NLP). They also integrate speech, robotics and vision (image recognition and machine vision) as modern methods of AI (SAĞSAN, 2016; BRAICU, 2018).

Romania faces a phenomenon of human capital polarization. This means that, in the post-communist period, Romania recorded a simultaneous increase in the share of people with higher education and an increase in the share of people with lower secondary education. Moreover, the educational level according to the residence environment indicates that this polarization tends to increase the gap between an educated urban area and a poorly educated rural area.

3. RESEARCH METHODOLOGY

3.1. The purpose and objectives of the research

This paper aims to identify the factors influencing the qualitative and quantitative indicators of higher education in Romania, and how they varied between 2013 and 2016. The desire was to determine the medium-term tendencies in terms of youth employment in higher education, the share of students by specialization groups in the public and private environments and the average increase in residence environments, given the effective decrease in the number of pupils in high school education [www2].

The objective of the current research is to highlight the influence of knowledge management on the intellectual capital of the Romanian university environment. In this sense, a theoretical research was carried out in two stages:

1) the study of specialized literature in the field, accessing articles and books from international databases.

2) establishing the topic to be analyzed statistically, as a result of the previous stage: the evolution of the Romanian education and the determinants of this evolution:

a) choosing the variables to be entered in a statistical model: POP214A, SCL102A, SCL103L. The variable were choses in accordance with the anterior review section.

b) collection of data from the Social Statistics category from the INS database regarding the variables previously established for the period 2013-2016

c) choosing and implementing the statistical model

d) interpreting the results and formulating the conclusions.

3.2. Methodology and aspects of the data analysed

The research presented in the paper is an office research based on the statistical analysis of the social statistics category of the INS database, the subcategories:

· POP214A – Natural population growth by residence area, macro-regions, development regions and counties;

· SCL102A – Degree enrolment in education of the school age population, by sex;

· SCL103L – Undergraduates and students enrolled in higher education, by groups of specializations.

In the research, we have taken into account the factors that lead to the failure of knowledge management (FROST, 2014), among which we mention:

· Lack of performance indicators and metrics associated with the objectives pursued;

· Lack of relevance, quality and adequacy of information;

· Poor methodology and inappropriate use of statistical and IT tools.

The gthnk free system for knowledge management is the main way of retaining and transferring knowledge from the perspective of the General Knowledge Model (NEWMAN; CONRAD, 1999). The results of our research will be stored in this system in the form of text-based notes. In addition, it also provides long-term chronological storage of handwritten knowledge, notes on mobile devices and attached pictures, see Figure 2.

Figure 2: The gthnk system implemented in Python

Source: www6

According to Sandor (2013), the longitudinal research strategy, comprising at least two measuring intervals, allows us to study the evolution of social phenomena over time and even to identify a model to explain this evolution. In addition, in conducting case studies on mass phenomena, the aim is to compare the results obtained on different groups, e.g. population categories.

It can be seen in Figure 3 that natural growth followed a sharp decline between 2013 and 2015, especially in the rural area (from -3.5 to -5), followed by an overall stabilization (rural + urban) after 2015 (-4.4 in 2016). We consider that the trend of decreasing the number of rural populations through emigration was reversed by population migration from the city to the village amid the deindustrialization and aging of the urban population.

The percentage of population’s education followed a downward trend amid negative natural growth and increase of school dropout (see Figure 4), Romania ranking third in the European Union in number of school dropouts. Malta ranks first (19.6%), followed by Spain (19%) and Romania (18.5%), according to www3. Virtually, two out of ten students end up dropping out of school, most of them coming from the countryside and from poor families. In fact, Romania is one of the few countries where school dropout has increased in the last decade, from 17.9% in 2006 to 18.5% in 2016, according to (MIHAI, 2018).

Figure 3: Natural population growth by residence area

Source: own processing data from www4

Figure 4: Degree of enrolment in school by age population

Source: own processing data from www4

The situation of the students enrolled in higher education changed slightly between 2013 and 2016, the highest share having the full-time attendance education – 92%, followed by the distance learning – 5% and the evening classes – 3%, as it follows al the level of 2016, see Figure 5: