A Framework for Technology Convergence in Learning ... - CiteSeerX

Educational Technology & Society 5(2) 2002 ISSN 1436-4522

A Framework for Technology Convergence in Learning and Working Miltiadis D. Lytras Athanasia Pouloudi Angeliki Poulymenakou eLTRUN – the eBusiness Centre Athens University of Economics and Business Evelpidon 47A & Lefkados 33 GR – 113 62 Athens, Greece Tel.: +30 1 8203682 Fax: +30 1 8203160 [email protected] [email protected] [email protected] ABSTRACT Information technology is arguably an important tool for knowledge management, facilitating learning in a business context. However, the current use of information technology in this area often fails to take into account the multifaceted and dynamic nature of knowledge creation, knowledge transfer and learning. In order to address this issue, the paper proposes a dynamic learning model that is based on three complementary dimensions: knowledge management, technology -supported learning pedagogy and application integration. We argue that this multidimensional model illustrates how technology -supported learning can work as a value-added process that supports the different needs of learners and businesses.

Keywords Learning, Knowledge management, Application integration, Value creation

Introduction The current business environment recognizes the exploitation of the intellectual capital as a critical business process. The need of modern organizations to utilize knowledge assets for the improvement of performance is well justified. For many companies, knowledge si often the competitive differentiator (Civi, 2000). The management of knowledge assets in business units incorporates the discovery of knowledge across many organizational levels (Staab & Maedche, 2000). Products, people and processes define a triptych of analysis. New technology forces change to traditional educational approaches. The utilization of knowledge can be organized through integrated models of management (Choo, 1996; Coulson, 2000; Despres, 1999; Liebowitz, 1999; Marquardt, 1996; Nissen et al., 2000; Tiwana, 1999; Wiig 1993). E-learning initiatives are expanding in academic and corporate settings driving interest in life -long learning (Rowley, 2000; Ruttenberg et al., 2000; Storey, 2000; Urdan & Weggen, 2000; Williams, 1999). A reasonable question is arising concerning e-learning solutions. The concern is concentrated on ways of enhancing organizational knowledge as a critical resource (Davenport & Prusak, 1998; Klaila, 2000; Nonaka & Takeuchi, 1995; O’Dell & Grayson, 1997; Senge, 1994). Our research unit (eLTRUN, www.eltrun.aueb.gr) had the opportunity to use and evaluate a number of technology supported learning integrated solutions such as WebCT, Lotus Learning Space, Blackboard and so on. Each had advantages and disadvantages but our emphasis is to reveal their limitation to support value adding learning processes. Poor learner satisfaction, unclear learning methodologies and indisposition of learners to use technology-supported learning are a few undesirable results we witnessed in the implementation of technologysupported learning. In more general terms, the dynamic nature of learning, different learners preferences, the customized learning content and the establishment of non-sequential learning scenarios seem to be crucial obstacles for the majority of technology supported learning platforms. From this point of view, we argue that technology supported learning is neither an effective solution nor a motivational driver unless its value dimension is understood and exploited.

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SCIENTIFIC VALUE DRIVERS 1. KNOWLEDGE MANAGEMENT CAPABILITIES

(+)

2. ENTERPRISE APPLICATION INTEGRATION

(+)

3. AVAILABILITY & CUSTOMIZATION OF LEARNING PROCESSES

(+)

E-LEARNING VALUE PERCEPTION

(+)

E- LEARNING PERFORMANCE

Figure 1. Factors influencing e-learning perception and performance

This paper dis cusses ways that justify technology-supported learning as a value adding process. The next section investigates value creation for the learning organization across three dimensions: knowledge management, technology-supported learning pedagogy and application integration. We argue that these three dimensions can be used as a methodological tool for the development of technology supported learning solutions that take into account the dynamic nature of learning. Figure 1 summarizes the factor influencing e-learning value perception is directly related to: (1) knowledge management capabilities of the integrated learning environment, (2) the enterprise application integration capacity; and, (3) the availability of well-defined learning processes. The cumulative result of the relevant effects expands further the e-learning performance in working environments. In this manner the performance of learning is based on three concrete scientific value drivers.

Three dimensions for supporting dynamic learning The cornerstone in our analysis is that every technology supported learning system irrelevant if it is present in a business environment or in academic institutions has to concentrate on business process training. This approach secures the modularity of the training content and sets an initial context for incremental learning effects in working practices. Its process can be broken down in several tasks, which represent a meaningful whole. The training for the accomplishment of each task requires the employment of specific learning processes. For each learning process, a learning template provides the layout where various learning products or learning objects can be accessed in parallel with a number of knowledge management mechanisms. Figure 2 summarizes the conceptual taxonomy of the technology supported learning knowledge management approach.

Business Process

Task 1

Learning Process 1

LP 2

Task 2

LP j

….

Task n

Learning Process 1

LP 2

LP k

Learning Template

Learning Product 1

Knowledge + Metadata

Learning Template

Learning Product n

Learning Product 1

Knowledge + Metadata

Knowledge + Metadata

Learning Product n

Knowledge + Metadata

Figure 2. The conceptual taxonomy

Our approach is investigating the ability of a three-dimensional model to expand the traditional considerations for technology-supported learning. The Multidimensional Dynamic technology supported Learning (MDL) Model is based on three complementary dimensions:

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a. b. c.

The knowledge management dimension The technology supported learning pedagogy dimension The application integration dimension

Figure 3 depicts the three-dimensional model and its relevant components. Each of these dimensions describe in considerations that confront knowledge management systems with embedded e-learning pedagogy and dynamic integration with other crucial business applications. The three dimensions of MDL model are explained next.

Low Value Learning Processes

Hi gh

n tio gra e t n nI tio n a c i pl nsio Ap ime D Dynamic Content

Lo w

E-Learning Dimension

High Value Learning Processes

Static Content KM processes

KM processes

Knowledge Management Dimension

Figure 3. The MDL model

The MDL model dimensions The Knowledge Management Dimension summarizes the ability of the e-learning platform to manage learning content in various formats, to re-use learning modules and to support knowledge management processes (Choo, 1996; Hahn & Subramani, 2000; Liebowitz, 1999) such as knowledge creation, knowledge codification, knowledge transformation and knowledge diffusion (Tiwana, 1999). The enrichment of content through a sophisticated model of metadata and semantics or annotations is of critical importance for the enhancement of dynamic learning (Gooijer, 2000). XML language is the last frontier, which speed up the realization of the Knowledge management dimension and promotes the embedment of dynamic features in traditional learning environments (Staab & Jürgens, 2000; Williams, 1999). The Technology supported learning pedagogy Dimension stands for the ability of a technology supported learning system to construct effective learning mechanisms and learning processes that support the achievement of different educational goals. This dimension incorporates issues like learning styles, learning needs, learning templates as well as learning specification settings. The Application Integration Dimension summarizes the capacity of collaboration with other business applications in order to obtain learning content. This dimension is the least developed of the three. The critical issue of insufficient content in many situations is due to the inability of organizations to establish effective knowledge generation mechanisms. The Technology supported learning pedagogy dimension requires further elaboration. Each learning process has a learning cycle - a continuum of learning tasks that reveal and exploit the learning content. We have defined ten different learning processes that have a different value in terms of learners satisfaction and learning content exploitation: Presentation, Explanation, Relation Synthesis, Analysis, Evaluation, Reasoning, Problem Solving, Collaboration, Learning Story Preparation. These ten learning processes are capable of supporting different learning modes. A technology supported learning platform should support such process in order to provide dynamic ways of constructing the learning scene. The availability of these learning processes in current systems is inadequate. In most cases this learning dimension is misunderstood or missing. One question is whether we can gain effectiveness from a technology supported learning system if it does not support learning goal hierarchies.

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The knowledge management Sophistication Dimension of MDL model is critical from a business perspective. The majority of technology supported learning platforms does not support mechanisms that enhance the reusability of learning content. The effort to redesign learning content or to adopt traditional content for technology-supported learning is not well supported in current system. MDL suggest that the knowledge management dimension is exploited when there are established knowledge processes that manipulate dynamic content. The re-usability of content and the support of high value learning processes presuppose the presence of an advanced KM subsystem capable of categorizing, enriching and integrating various learning objects. Very few learning platforms provide metadata to support reusability and dynamic configuration of objects. Moreover, current learning platforms do not directing support data mining. The application integration dimension is critical from holistic perspective. A technology supported learning system has to be enriched frequently with new learning content. In business setting this requirement results from need for immediate access to up-to-date knowledge. The current situation is very disappointing with regard to this requirement. The underlying requirement is to utilize knowledge that is dispersed. The desired outcome is to support e-learning with an advanced knowledge management mechanism based on an extensive accurate and upto-date knowledge base. XML can help insure dynamic reuse of knowledge. Figure 4 depicts an integrated KM framework. In this framework, knowledge transformation occurs dynamically in the center box based on our knowledge processes and the ability to reconfigure and reuse knowledge objects to satisfy a variety of knowledge uses.

KNOWLEDGE PROVIDERS VARIOUS KNOWLEDGE OBJECTS

KNOWLEDGE EXPLOITATION ACQUIRE ORGANIZE

RELATE VALUE

1.

2. 3. 4. 6. 5.

USE

ENABLE REUSE ADAPT ATRACT

TRANSFER

RELATE

2. 3. 1.

4.

ENGAGE

6. 5.

USE

LEARN

KNOWLEDGE UTILIZATION

LEARNING CASES

KNOWLEDGE USERS - LEARNERS

Figure 4. The integrated e-learning knowledge management framework

Each of the learning processes combines a number of learning objects and specific functionalities that permit knowledge exploitation for learning purposes. Each process has associated activities and technological components. A learning template specifies the way that each user will interact to the specific learning process.. The model emphasizes the role of knowledge management. The realization of organizational memory requires extensive technological considerations and development efforts.

The basic learning processes of the MDL model Metadata schemas provide a context for knowledge enrichment (Perez & Benjamins, 1999). Their focus is on a general-purpose schema for sharing knowledge objects. Unfortunately, learning is not simply delivering of

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object. Learning involves the utilization of knowledge and its transformation to support effective actions. We can imagine an indexed repository of interoperable learning objects not able to support learning. We have to investigate very seriously how these objects can be used to support learning in the context of meaningful leaning activities. In most metadata schema there is an avoidance of learning requirements. Moreover, e-learning system are not stand-alone systems but they have to support the networked enterprise. Our basic hypothesis is that e-learning effectiveness is directly related to specific learning processes that consist of the value drivers of learning outcomes. There is a need to model learning processes and to develop a new metadata or schema to support the effective employment of appropriate learning objects. In other words, we believe that the reusability of learning objects is not a panacea for higher learning performance unless some metadata support value hierarchies. Our basic assumption is that not all learning processes have the same value outcomes. The development of value hierarchies for learning processes can enhance the personalization of learning. Each process has to be analysed in detail and to be modelled using a modelling language such as UML (The Unified Modelling Language). For example a first draft of the model for the learning process Synthesis is as follows: Synthesis: (1) Define Objectives – State the Scope of the synthesis, (2) Find Relevant Learning products, (3) Present Learning Products through templates, (4) Summarize key contributions, (5) Integrate meaning, (6) Develop new Learning Products, (7) Store new Findings. The life cycle for the realization of each process has to be desired when we refer to knowledge providers or knowledge users. The life cycle of each process does not imply a sequential rotation of relevant tasks but rather a number of interconnected and integrated tasks. Figure 5 provides a screen shot from the case builder responsible for the dynamic integration of learning objects and learning processes.

ANALYSIS Case Builder Learning Scenario: Unit 1 : E-commerce Framework TOOLS

HELP

Case Study Index

LEARNING SCENARIO

Search Knowledge Base Personal Workspace

Summary of Learning Object

Modeling Facility

the knowledge providers synopsis

Here it is concluded

PRESENTATION ANALYSIS EXPLANATION EVALUATION

Collaborate

END

Detailed ANALYSIS FIND RELEVANT OBJECTS

PRESENT RELEVANT KNOWLEDGE

DISCOVER COMPONENTS

2. 3. 1.

4.

6. 5.

DEFINE CONNECTIONS RELATIONS

STORE DRAW CONCLUSIONS CONCLUSIONS

Read also:

(promoted by knowledg eprovider or linked using Knowledge Base)

Suggested Learning Objects Figure 5. The case builder

In e-learning system, the most authors (teachers) do not support specific learning processes. The majority of systems provide some evaluation tools, (e.g., quizzes). Very few tools concentrate on the learning dimension. In our approach, we investigate the hidden value of specific learning processes. The strategic model for the establishment of e-learning systems in working environments is presented in Figure 6.

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1. KM SPECIFICATION KNOWLEDGE SOURSES EVALUATION

CATEGORIZATION OF KNOWLEDGE

METADATA SPECIFICATION

KNOWLEDGE BASE DEVELOPMENT

DESIGN OF LEARNING TEMPLATES

LEARNING TEMPLATES BASE SPECIFICATION

2. E-LEARNING STRATEGY LEARNING OBJECTIVES SPECIFICATION

LEARNING PROCESSES DEFINITION

3. LEARNING EXPLOITATION USAGE SCENARIO

MOTIVATION SPECIFICATION

LINKAGE TO WORKING PRACTICES

PROBLEM SOLVING CAPABILITIES

TEAM SYNERGY

4. TECHNOLOGY INTERGATION INTERFACES SPECIFICATION

LEARNING PROCESSES POOL

SEMANTICS MODULE

LEARNERS PROFILING

COURSE BROKERING

LEARN. OBJECTS MGT SYSTEM

MINING FACILITY

COLLABORATON

Figure 6. The strategic model for technology convergence in learning and working

Figure 7 provides an overview of an integrated tool for the realization of technology convergence in learning and working. The aim is to support dynamic construction of learning scenarios selected based on the basis of learning value. Learning templates facilitate realization of the learning scenarios and provide a base for the incorporation of learning products. The metadata tool secures the knowledge components management in a systematic way.

KNOWLEDGE PROVIDERS COLLECTION OF LEARNING OBJECTS

LEARNING OBJECTS BASE + SEMANTICS (FOCUS ON LEARNING)

KNOWLEDGE MANAGEMENT CYCLE

E-LEARNING TRANSFORMATION

CYCLE

+ METADATA (FOCUS ON KNOWLEDGE) DYNAMIC MATCH OF LEARN. PROC. & LO

KNOWLEDGE BASE

POOL OF LEARNING PROCESSES

LEARNERS PREFERENCES LEARNING SCENE

APPLICATION INTEGRATORS

APPLICATION INTEGRATORS

Figure 7. A generic architecture based on MDL model

Conclusion The development of a flexible e-learning system capable of supporting the requirements discussed is a serious challenge. The specification of the learning processes life cycles and the determination of required metadata

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reveal a capacity for personalization. The interesting relation between value diffusion and learning satisfaction seems to increase learning outcomes. Our approach sets a context for further exploitation. Without doubt the current situation in the e-learning market does not represent the fascinating issue of the incorporation of information and communication technologies in education. Many people use the term e-learning to imply the presence of a PowerPoint presentation accompanied with audio. The achievement of higher student satisfaction in the DML framework is one of key findings. The full realization of MDL remains a challenging task for the future.

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