=Paper=
{{Paper
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|title=
The Application of EM for Knowledge Flow Analysis and the Development of an Educational IT Ecosystem
|pdfUrl=https://ceur-ws.org/Vol-933/pap9.pdf
|volume=Vol-933
|dblpUrl=https://dblp.org/rec/conf/ifip8-1/StaleM12
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The Application of EM for Knowledge Flow Analysis and the Development of an Educational IT Ecosystem
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https://ceur-ws.org/Vol-933/pap9.pdf
The Application of EM for Knowledge Flow Analysis and
the Development of an Educational IT Ecosystem
Ginta Stale1, Ivars Majors2
Distance Education Study Centre, Riga Technical University, 1 Kalku, Riga,
1
LV-1658, Latvia, ginta.stale@gmail.com
Vidzeme University of Applied Science, Cesu 4, Valmiera, LV-4200, Latvia
2
Faculty of Economics, Latvian University of Agriculture, 2 Liela iela, Jelgava,
LV-3001, Latvia, ivars.majors@gmail.com
Abstract. Knowledge flow is invisible but plays an important role in
educational processes. A wide range of accessible information technology (IT)
for educational purposes as well as the potential for new technologies allow
people to learn throughout their lives. Accelerated IT development and short
amount of time for learning activities emphasize the requirement for continuing
education and the synergy between accessible technologies. Analysis of
knowledge flow becomes important during the learning process within an
educational information technology (IT) ecosystem. Learning objects within IT
are the major medium that enables knowledge to pass between teacher and
learner. The developer of an educational system can identify factors that may
impact on the learning process more successfully by using enterprise modeling
The objective of this article is to apply the enterprise modeling approach to the
analysis of knowledge flow in continuing education. The proposed approach
can be applied not only to educational institutions but also in business
organizations. The digital ecosystem approach is implemented in the model to
support the knowledge flow analysis within educational and business processes.
Keywords: Enterprise Modeling Method, Information Technology, Continuing
Education, Knowledge Flow Analysis.
1 Introduction
Analysis of knowledge flow within the educational system has become more
important during the development of information technologies (IT). The main
characteristic of an educational system is its organization which is controlled by
knowledge flow within learning processes. Other qualities are that they are selective
and are continued within and are certain limits self-regulating [Skyttner, 2005]. The
lack of a comprehensive approach to using technology for educational purposes
means that there is a limited approach for linking technologies used for teaching
purposes, to the learning content and the learner’s portfolio. Consequently there is a
need to apply the principles of ecosystems in the development of teaching systems.
User portfolio and technology communication are an important obstacle to be taken
into account in the analysis, design and evaluation of teaching systems. Knowledge
flow is invisible but plays an important role in educational processes and can enhance
creativity and competitiveness of knowledge-intensive business processes.
The focus of this paper is on educational IT ecosystems in continuing education. A
wide range of accessible information technology (IT), as well as the potential of new
technologies allow people to learn throughout their lives. The necessity for life-long
learning defines turbulent change and the rapidly-changing demand for new
knowledge and skills. Current IT development and the short amount of time for
learning activities emphasize the requirement for continuing education. The objective
of this article is to present practical experience of enterprise modeling applied to the
analysis of knowledge flow as well as the requirements for the development of
software prototype. The ecosystem approach matches more precisely the needs of the
learner to become and remain competitive in the ever-changing world. The aim of the
applied approach is to support knowledge flow analysis in an educational IT
ecosystem according to the learning situation, learner needs and the available
technology in a specific time, place and learning situation.
The following sentences briefly outline the main points of the paper. The concept
of knowledge flow analysis is analyzed in Section 2. Section 3 describes related work.
Section 4 reflects enterprise modeling for knowledge flow analysis while section 5
provides the conclusions.
2 Concept of the Knowledge Flow Analysis
The aim of this section is to discuss the main concepts of particular research. The
main concepts analyzed in this section are: knowledge flow, an educational IT
ecosystem, continuing education service providers and consumers, the learner’s
portfolio and learning processes.
Knowledge flow in the context of knowledge-intensive teamwork is the passing of
knowledge within a team [Zhuge H., et al., 2006]. Knowledge flow begins and ends at
a knowledge node [Zhuge H., et al., 2006]. A knowledge node is either a team
member or a role that can generate, process, or deliver knowledge [Zhuge H., et al.,
2006]. From the organizational perspective, knowledge flow is defined as a method
that supports knowledge accumulation and sharing [Uden L., Damiani E., 2007]. In
the context of an educational IT ecosystem, knowledge flow is the passing of
knowledge between knowledge nodes which are between the continuing education
content provider and the consumer of education. The provider of the continuing
education content is teacher in the education institution or another professional in this
field. The consumer of the content is student.
Continuing education is a broad concept which includes all of the learning
opportunities which any person wants or need outside basic and primary education. It
extends beyond the completion of formal studies and into the less formal area of adult
education [Stale G., Cakula S., Kapenieks A., 2011]. In the context of this paper,
continuing education is defined as the active and informal learning process of adults,
using different learning options, content accessibility, applied methods and IT
solutions according to learning needs, learning solution, style and accessible
technologies.
An Educational IT ecosystem is a term developed from digital ecosystems. A
digital ecosystem is a self-organizing and adaptive digital infrastructure that supports
an organization or communities working together to create and share of knowledge
[Uden L., Damiani E., 2007]. An IT ecosystem for educational purposes is an
adaptive digital infrastructure that supports the learning process in an organization
[Stale G., Madsen P., 2009]. The digital infrastructure consists of digital components
which comprise software components, applications, services, knowledge, business
processes and models as well as training modules. An educational IT ecosystem in the
context of this paper is defined as a digital environment which supports the continuing
education process according to the learner’s needs and competences. Competence
includes knowledge, skills, attitudes, values and experience to solve particular
problems, obstacles or barriers [Karampiperis P., 2006].
A learner’s portfolio contains the results written and record of previous education
and competences in a particular field [Yang T.C., et al., 2012]. The portfolio reflects
the level of competence within a subject or area of knowledge.
Figure 1 represents the concept of knowledge flow. According to Figure 1,
knowledge content is provided by the knowledge provider – a teacher or other
professional. The knowledge content is the learning object which is delivered through
the internet in the knowledge space. The knowledge repository collects knowledge
metadata for the educational IT ecosystem to provide a knowledge flow analysis.
Figure 1. The concept of knowledge flow
The main concepts have been discussed in this section. The next section describes
related work in this field.
3 Related Work
There are three main categories of work related to the IT ecosystem approach. The
first category concerns is supporting a more effective learning process – the
application of a learning ecosystem approach. The second concerns the analysis and
modeling of knowledge flow. Third is the technological support of the educational
process.
First area includes Educational Modelling Language (EML), a learning design
specification [Whitman L., Huff B., 2001] and an education-oriented development
framework [Jing, M., Li, X., Bin, Q., 2008], digital ecosystem paradigm for IT course
development [Chin L. K, Chang E., Atkinson D., 2008] and an e-Learning ecosystem
[Uden L., Damiani E., 2007] where the research describes the behavior of a learning
ecosystem.
Koper and Tattersall described the necessary preconditions for the learner to
become active in the learning process [Koper R., Tattersall C., 2005]. They are:
• the development and delivery of educational courses which include role-
plays and game-playing, where multiple users perform a variety of interdependent
tasks;
• the provision of problem-based learning courses where teams of learners
collaborate in problem-solving and teachers have assessment, coaching or monitoring
roles;
• the application of learning community approaches based on social-
constructivist principles, where the design of the learning environment stimulates
collaboration and the sharing of knowledge and resources;
• the application of performance-supported approaches, where learning tasks
are assigned depending on the knowledge gaps assessed;
• the development of courses which can be adapted according to pedagogical
models, learning processes and learning needs, preferences and the learning style of
consumer
• the application of peer coaching and assessment approaches, where learners
support each other.
Figure 2. Fields of related work
From the learning ecosystem viewpoint there are models developed [Chang V.,
Guelt Ch., 2007], [Quinones, M., et al., 2008], [Guetl, C., et.al., 2005] where the main
conceptual parts of learning ecosystem have been described. Chang described a
learning ecosystem consisting of biotic abiotic units. Biotic units are learning
communities, stakeholders, teachers, tutors, content providers, instructional designers
and pedagogical experts. Abiotic units are the learning utilities, the learning
environment which includes the learning media and technology [Chang V., Guelt Ch.,
2007]. The significant part of a learning ecosystem is the learning ecosystem
conditions which are determined by external influences such as the evaluation of
knowledge, educational goals, learning tasks, cultural and social aspects, as well as
the expectations of society, private industry and business organizations, the
government, public service and not-for-profit organizations. The significant areas of
interest in the learning domain are relationships and interactions related to the
information flow as well as knowledge transfer and transformation [Guetl, C., et.al.,
2005].
The second part of related work includes analysis and the modeling of knowledge
flow in different contexts [Fan I., Lee R., 2009], [Huggins R., Johnston A., 2010], [Leistner
F., 2010], [Park H.W., et al., 2011], [Zhuge H., 2006]. The results describe knowledge
flow principles and application domains. The aim of this particular piece of research
work was to develop an enterprise model for knowledge flow analysis in an
educational IT ecosystem. This model could meet the challenge of supporting
learning organizations with appropriate technological and content solutions to support
knowledge sharing and management, and the life-long learning process in learning
communities.
The third related field is the technological support of the educational process [Jing
M., et al., 2008], [Peter-Quinones M.A., et al., 2008]. The main problem defined in the
related work was that, in many cases, the software applications on all the user’s
devices were designed to be functional copies of each other, often with an emphasis
on keeping their form and function consistent with the same application on other
device platforms. In one part of the related work [Jing, M., Li, X., Bin, Q., 2008], the
idea of a personal information ecosystem was presented, as an analogy to a biological
ecosystem which allows us to discuss the interrelationships between users’ devices. A
complementary approach defined the IT ecosystem as an interconnected system
within which computing services were requested and delivered [Driscoll M.P., 2005].
The components of the ecosystem included any and all items that were required to
conduct these service-based transactions, including, but not limited to, handheld -
mobile phones, PDAs, laptops, etc., desktop computers, in-home networked
appliances, networked printers, servers and storage devices, networking equipment
and data centers. Defining an IT Ecosystem in this way highlights the
interconnections and interdependence of the components within the system.
4 An EM for Knowledge Flow Analysis
Enterprise modeling enables a common understanding of all the pertinent aspects,
the clear description of problems in an educational IT ecosystem and the requirements
for knowledge flow analysis. It also enables the definition of various design
alternatives and a mechanism to analyze these options for design implementation at
strategic, tactical, operational and technological levels [Whitman L., Huff B., 2001].
The following methodologies were chosen as benchmarks [sown in Table 1]:
• the Yu methodology – strategic relationship development [Horkoff J., Yu E.,
2009];
• the EKD (Enterprise Knowledge Development) – an enterprise modeling
method [Bubenko J.A., Kirikova M., 1999], [Persson A., 2001];
• the Keith A.Butler method – for business process modeling and software
requirements definition [Buthler K.A., 2000];
• the BPR (Business Process Redesign) – a method aimed at business process
redesign and optimization [Gao Sh., Krogstie J., 2009];
• the Business Process Management Systems – a method for business process
analysis from organizational, functional and behavioral viewpoints [Carvalo J.P.,
French X., 2009];
• the DRM (Decision Relationship Model) – reflecting actors, processes, input
flows und decisions [Shahzad K., Zdravkovic J., 2009];
• the Service-Driven Information Systems Evaluation – this provides an
analysis of business processes and abilities to use resources accessible to enterprises
[Arni-Bloch N., Ralyte J., Leonard M., 2009];
• the Zachman Enterprise Architecture; this is a two dimensional classification
scheme for describing different characteristics of an enterprise which consists of
different characteristics of the final product [Zachman, 2006].
Table1.Benchmarking of the Methods used for the Analysis of Knowledge Flow
and Development of an Educational IT Ecosystem
Methodology Service-Driven
Criteria Business Process DRM (Decision Zachman
Information
Management Relationship Enterprise
Systems
Systems Model) Architecture
Evaluation
Defining goals
- + - +
Defining
processes for +/- excluding
comparing with -/+ + + relationship
goals and between models
recourses
Possibility to
define knowledge - -/+ - -
gaps
Definition of
hierarchical - + - +
structure
Define
requirements for a - + +/- -
CE system
Defining goals - + - +
Defining
processes in
comparing with +/- + + +
goals and
recourses
Possibility to
define (reflect) + +/- - +
knowledge gaps
Definition of
hierarchical + - - +
structure
Define
requirements for + + +/- +
CE system
The Enterprise Knowledge Development (EKD) method has been chosen as the
Enterprise modeling method. The use of enterprise modeling methods and an
“ecosystem” approach to knowledge flow analysis within the educational IT
ecosystem provided a wide range of options to implement a more dynamic analysis of
educational processes and supports definition of requirements for the development of
a prototype to support these processes. Figure 3 shows a developed model for
knowledge flow analysis within an educational IT ecosystem.
The EKD methodology is one of the enterprise modeling methods that was
developed some years ago and is increasingly used by business consultants. This
method has been the subject of research in a number of multinational European
projects, including the 7th framework programme. It has proved its effectiveness both
in the business and public sector by providing a framework for stating, modeling, and
reasoning regarding pertinent knowledge in difficult problem situations which
typically occurring in organizations and society.
Figure 3. A Model of a Knowledge Flow Analysis within an Educational IT
ecosystem
The EKD aims at setting an organization’s vision, mission and goals, providing
guidance in restructuring in changing different processes. EKD methodology has been
expanded in this article by providing different levels of the model.
The Figure 3 shows a strategic level where goals are reflected and planning level
where processes and concepts are shown. The next level shows the requirements for
information and communication technologies and the knowledge analysis tool. The
final level shows data and knowledge resources. Figure 4 reflects a conceptual model
for the a prototype of an educational IT ecosystem to support the knowledge flow in
the learning process. Knowledge flow analysis is implemented in the knowledge
support system by analyzing the competence level of the student and matching to an
appropriate learning path. A learning path is constructed depending on the learning
objects.
Figure 4. Conceptual Model for the Prototype of an Educational IT Ecosystem
Figure 5 and Figure 6 show a prototype of the software for a knowledge flow
analysis in an educational IT ecosystem. Figure 5 shows the main screenshot form of
the prototype. It demonstrates a competence field where the users can demonstrate
their competences within particular subject. A meta-competence field is also shown.
Meta-competences are defined by the study of the research done within 6 th
Framework Project [Berlanga A. J., et al., 2008]. Figure 6 shows the screenshot from the
module for a knowledge flow analysis within business processes. An appropriate
learning path is shown to the user after the definition of the student’s competences,
business processes and knowledge flow. The learning path is analyzed according to
the user’s initial competences, business processes and knowledge flow.
Figure 5. A Prototype of Educational IT Ecosystem - competence definition level
Figure 6. A Prototype of an Educational IT Ecosystem
(level for knowledge flow analysis)
5 Conclusions
Theoretical study was carried out during the research process for the knowledge
flow analysis and the requirements definition of the educational IT ecosystem.
Research on related work has shown that there is wide range of research done in the
theoretical aspect of the e-learning ecosystem field and supporting a learning process
through the provision of technologies. But, there is luck of knowledge flow analysis
in educational processes. Appropriate software could offer a learning path to students
for time-consuming learning process with technological solution according to the
principles of the educational IT ecosystem.
The use of the Enterprise Modeling Method for the analysis of knowledge flow in
continuing education provides a wide range of options to implement a more dynamic
learning process in learning communities. EKD methodology also provides core
support in the development of an educational IT ecosystem. The definition of
different levels also provides a more structured analysis and also supports the detailed
development of an educational IT ecosystem.
This paper has described a model for the identification of the knowledge flow and
the gap which exists within educational processes and the learning path for
competence development to meet an organization’s needs and requirements.
Future work will be focused on the more specific and detailed development of the
software prototype for knowledge flow analysis within the educational IT ecosystem.
This will be done not only from the perspective of service consumers but also from
the provider’s point of view.
Acknowledgment
This research has been supported by a grant from the European Regional
Development Fund (ERDF), "E-technologies in innovative knowledge source and
flow systems (ETM)" Project No. 2DP/2.1.1.1.0/10/APIA/ VIAA/150 (RTU PVS ID
1534). (Contract No. 2010/0222/2DP/2.1.1.1.0/10/APIA/VIAA/150).
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