Knowledge Management in Computer-supported Learning

Luyi Li School of Education Science Northeast Normal University

ChangChun, China e-mail: Lily857@nenu.edu.cn

Yanlin Zheng School of Computer Science &

Information Technology Northeast Normal University

ChangChun, China

Fanglin Zheng School of Media Science

Northeast Normal University ChangChun, China

e-mail: Zhengfl194@nenu.edu.cn

Shaochun Zhong* School of Software

Northeast Normal University Changchun, China

e-mail: zhongsc@nenu.edu.cn

Abstract— A learning process is substantially a knowledge management process. Computers can play multiple roles in human learning and facilitated human learning processes by providing technical, cognitive, and social support. This paper discusses knowledge management in computer-supported learning, explores the knowledge management process in learning process, and suggests how to better support knowledge management in computer-supported learning.

Keywords-computer;computer-supported learning;process; knowledge managment

I. INTRODUCTION Computers have been widely utilized for enhance

teaching and learning. From single computer-based CAI courseware design to networked computer supported online learning systems development, computer-supported e-learning has received increasing attention from researchers.

Computers have considerable potential to support and enhance human learning. Successful utilization of computers for learning scenarios requires considering multiple issues, such as pedagogical, learning theoretical, technological, and social issues. Computers can play multiple roles in human learning.

A learning process is substantially a knowledge management process. Knowledge management can exist at personal and organization levels. In the organizational context, knowledge management usually implies that all kinds of information will be pooled together to sort, classify, store, use and share in order to facilitate and promote communication between people, so that employees can continuously improve product quality and finally improve the core competence of the enterprise. Organizational knowledge management is often related to organizational learning and the creation of learning organizations. Personal knowledge management aims at the creation, retrieval, evaluation, use/reuse, and sharing of knowledge. Knowledge evolution, use/reuse and sharing are the final objectives of learning. Based on the understanding of the roles of computers in human learning, this paper explores the knowledge management in computer-supported learning, and suggests how to facilitate knowledge management in computer-supported learning by means of the introduction of ontologies and the recognition of learning context.

II. COMPUTER-SUPPORTED LEARNING Human learning might be differently interpreted by

different researchers. There are many learning theories, models, and other discussions about learning. For example,

Smith reviewed two main perspectives on learning [1]: learning as a product and learning as a process, and distinguished four different learning orientations, including the behaviorist orientation to learning, the cognitive orientation to learning, the humanistic orientation to learning, and the social/situational orientation to learning. According to [2], “conceives of learning as a relatively permanent change in behavior with behavior including both observable activity and internal processes such as thinking, attitudes and emotions.” Other researchers put forward a model of learning involving presage (factors brought to the learning situation by the learners and actual situation factors); process (which is determined by learners’ approaches to learning); and product (or outcomes). Learning outcomes might be new knowledge, skills (cognitive, social or physical), or values and attitudes[3].

A. Metaphors of human learning 1) Acquisition metaphor of learning

Sfard distinguished two metaphors of learning, the acquisition metaphor and the participation metaphor [4]. The acquisition metaphor represents a traditional view according to which learning is mainly a process of acquiring desired pieces of knowledge, and learning is a process that fills the container, implanting knowledge there. In this view, learning is a matter of individual construction, acquisition, and such outcomes, which are realized in the process of transfer; it consists in a person's capability to use and apply knowledge in new situations. Knowledge is a property and possession of an individual mind.

2) Participation metaphor of learning The participation metaphor of learning examines

learning as a process of participating in various cultural practices and shared learning activities, a process that structures and shapes cognitive activity in many ways[4]. Within the participation metaphor, learning is a matter of participation in a social process of knowledge construction, enculturation, guided participation, or legitimate peripheral participation [5]. The learning process is regarded as a process of becoming a member of community, learning to communicate and function according to its social norms, and developing a corresponding identity. Cognition and knowing are distributed over both individuals and their environments, and learning is "located" in these relations and networks of distributed activities of participation. Peripheral participation is a process during which novices gradually adopt experts' silent knowledge, culture of activity,

*Corresponding Author e-mail: sczhong@yahoo.com

978-1-4244-5326-9/10/$26.00 ©2010 IEEE

and grow up to be members of that expert culture through participating in experts' practices.

3) Knowledge-creation metaphor of learning Paavola et al. proposed a third metaphor of learning as

a process of knowledge creation [4]. The knowledge-creation metaphor regards learning as processes of inquiry, especially as innovative processes of inquiry where something new is created and the initial knowledge is either substantially enriched or significantly transformed during the processes. There are three typical learning models which did understand learning and knowledge advancement through a knowledge-creation metaphor. The three models include: Nonaka & Takeuchi's model of knowledge-creating organization, Engeström's expansive learning model, and Bereiter's theory of knowledge building.

B. Computers in Human Learning 1) Computers as Instructors and/or Peers

Computers may simulate instructors or peers to help learners construct knowledge and improve performance. For instance, Gutl & Pivec applied an expert system as a virtual tutor in their research [6]. The virtual tutor promises to: facilitate the repetition of basic knowledge; make it possible to analyze different details of the knowledge domain; facilitate synthesis of the fundamental parts; provide additional explanation with hypermedia pages; repeat various topics of learning contents; question the learning system; obtain additional explanations if required; and increase learners’ problem solving skills.

2) Computers as Cognitive Tools Jonassen defined cognitive tools as, "computer-based

tools and learning environments that have been adapted or developed to function as intellectual partners with the learner in order to engage and facilitate critical thinking and higher-order learning" [7]. Lajoie identified four types of cognitive tools according to the functions they serve. These include tools that [8]: (a) support cognitive and metacognitive processes; (b) share cognitive load by providing support for lower level cognitive skills so that resources are left for higher order thinking skills; (c) allow learners to engage in cognitive activities that would be out of their reach otherwise; and (d) allow learners to generate and test hypotheses in the context of problem solving.

In computer-supported learning environments, first, learning content might be designed with multiple entry points that enable learners to be engaged by their curiosity, shape their experience and follow their needs and interests. Second, computer can serve in the process of information gathering, inquiry, and collaboration, not merely as a vestige of direct instruction with its reliance on integrating technology in the existing curriculum [9]. Third, computer-mediated learning tools allow learners to repeatedly test, to revise, and to rebuild their ideas. Fourth, computers can enhance peer interaction and work in groups, and facilitate collaborative constructing, sharing and distributing of knowledge. Finally computers can record learners’ learning

processes, and allow learners to reflect and monitor how they are constructing their own understanding, which is beneficial to the development of higher-order thinking and metacognition skills, including defining problems, judging information, solving the problems, and drawing appropriate conclusions.

3) CMC and Social Skills Development Borsook suggested that to be interactive, learning

systems should stimulate seven characteristics of interpersonal communications [10]: immediacy of response, non-sequential access of information, adaptability, feedback, options, bi-directional and interruptability. By integrating asynchronous and synchronous communication tools, such as e-mail, discussion list, video conferencing, and bulletin boards to support interpersonal communications, CMC has the potential to speed, facilitate, and strengthen interpersonal communication, and to provide participants with opportunity to practice and develop social skills such as the social exchange of information, the management of cooperation and competition, the giving of mutual support, and the ability to manage the collaboration process [11].

III. KNOWLEDGE MANAGEMENT IN COMPUTER-SUPPORTED LEARNING

A. Knowledge and Knowledge Management 1) Knowledge

According to [12], there are three significant distinctions between knowledge and information. First, knowledge usually is related to a knower. Information is often treated as independent and more-or-less self-sufficient, self-contained substance, and can be detached from human factors, while knowledge is often human-dependent. Second, it is much more difficult to detach knowledge than information. In contrast to information, it is harder to pick up and harder to transfer. Third, knowledge is always based on personal understandings and collective construction, which often exists in explicit or implicit forms and entails the knower’s understanding and some degree of commitment.

Knowledge exists in two forms: explicit and tacit. The concepts of tacit and explicit knowledge were first introduced by Polanyi in his magnum opus Personal Knowledge. Explicit knowledge, or articulate knowledge, can be expressed in words, diagrams, or formulas, which can be easily codified, represented and shared asynchronously. Contrarily, tacit knowledge, or inarticulate knowledge, is ineffable, contextual, and based on personal experience, which directly relates to personal cognitive skills, embodies personal beliefs and values, and is best communicated through face-to-face encounters. Although knowledge cannot be totally extracted from the minds of individuals because the existence of its tacit dimension, Nonaka and his colleagues have argued that some embedded knowledge through documents, reports, repositories, routines, processes, procedures, practices, norms, apprenticeships, job rotation, and mentoring can be captured[13].

2) Knowledge Management

Knowledge management deals with knowledge evolution, use/reuse and sharing [14].

a) Knowledge Evolution Either an organization or an individual is always rooted

in the prior knowledge background and pursues improvement on this background for present use or future progress. Knowledge evolution covers the creation of new knowledge and the improvement of existing knowledge by the reconstruction of the knowledge structure, the re-organization of knowledge resources, etc.

b) Knowledge Use/Reuse Knowledge is not power if it cannot change our

behaviors or thinking. Knowledge use/reuse indicates the correct extraction and application of existing knowledge, which is the goal of learning. Knowledge should be actively integrated into work process and social practices of community. Knowledge use/reuse often implies the transformation from knowledge to action, which is typically represented as decision-making support and the ability to solve problems.

c) Knowledge Sharing In effective knowledge sharing, knowledge increment

occurs with honesty, trust, responsibility and openness [9]. Knowledge sharing endows knowledge with wider and deeper social values. Practically, effective knowledge sharing relies on effective communication.

B. Knowledge Management in Computer-supported Learning Process Mayes & Foweler described a model of technology-

mediated learning [15], which was characterized by a

continuous cycle of conceptualization and re-conceptualization- a process of iterative refinement of understanding. There are three identifiable stages in the gradual refinement cycle, including, conceptualization, construction, and dialogue. Table 1 illustrates how these processes are supported in computer-supported learning environments. Computer-supported learning environments can integrate a variety of tools thereby providing learners with opportunities to avail themselves of those most appropriate for improving learning performance and developing cognitive and social skills.

Conceptualization involves an interaction between the learner’s pre-existing framework of understanding and a new exposition. This process is directly related with knowledge dissemination, representation, integration etc. This process is corresponded with knowledge retrieval process in knowledge management.

Construction refers to the process of building and combining concepts through their use in the performance of meaningful tasks. Traditionally these have been tasks like laboratory work, writing, preparing presentations etc. The results of such a process are products like essays, notes, handouts, laboratory reports and so on. This process is corresponded with knowledge transformation process in knowledge management.

Dialogue refers to the testing and tuning of conceptualizations through use in applied contexts. The conceptualizations are tested and further developed during the application in real context, the conversation with both tutors and fellow learners, and in the reflection on these. This process is corresponded with knowledge sharing process in knowledge management.

Table1 Knowledge Management in Computer-supported Learning (based on Mayes’ conceptualization cycle, 1999) Stage of Learning Knowledge Management Technical Support Sample Tools

Conceptualization Knowledge Retrieval knowledge dissemination knowledge Representation knowledge Integration

Online library e-portfolio Search Engine Database

Construction Knowledge Transformation Combine knowledge with learning tasks Experience in real context Support Collaborative activity

Virtual Lab Shared workspace CMC tools

Dialogue Knowledge Sharing Feedback, Assessment, Apply in real context Encourage Social Interaction

Schedule Arrangement, CMC tools

C. Faciliate Knowledge Management in Computer-supported Learning

1) Using ontology for knowledge modeling Reasonable knowledge modeling is helpful for the

retrieval, transformation and sharing of knowledge. Ontologies are promising for effective knowledge modeling. An ontology is a formal specification of a conceptualization [16]. In more detail, Ontologies are agreements about shared conceptualizations. Shared conceptualizations include conceptual frameworks for modeling domain knowledge; content-specific protocols for communication among inter-operating agents; and agreements about the representation of

particular domain theories. In the knowledge-sharing context, ontologies are specified in the form of definitions of representational vocabulary.

Ontologies may be grouped into the following three areas, according to their main functions: to assist in communication between people, to achieve interoperability among computer systems, or to improve the process and/or quality of engineering software systems [17]. From the point view of knowledge, an ontology has its own characteristics as follows, which makes it possible to classify and analyze knowledge context in computer-supported learning with the use of ontologies.

(1) An ontology itself is knowledge.

(2) An ontology is knowledge on knowledge. (3) An ontology is explicit knowledge. (4)Ideally, an ontology is always true knowledge. (5)Generally, an Ontology is always related with some

knowledge domain. (6)An ontology points at knowledge use/reuse and

knowledge sharing. (7)An ontology is competent for serving the development

of Knowledge-based systems. 2) Recognition of computer-supported learning context

The term, context itself involves rich implications and has its own unique characteristics, including subject-oriented, integrative, and dynamic. First, subject-oriented attribute means that when we discuss context, there is always a subject. Second, integrative attribute implies when the subject is identified, all the information related with the subject will be integrated as the context of the subject. Third, dynamic attribute means the context for some subject is not static, but is embedded with a dynamical process with changes over time. Accordingly, research on context will be concerned with three interrelated links. One is to identify subject. The second is to mine relative information for the subject. The last is to provide application service according to the needs of the subject and the actual conditions derived from context analysis.

Computer-supported learning is a typical kind of e-learning. According to [14], in a broad sense, the e-learning context covers all the information that shapes e-learning situations, from physical settings to virtual space, from individual interests to social culture, from explicit conversations to tacit cognition, from technical media to human emotions, etc. Knowledge, human, and technology are highlighted as the three key elements in e-learning settings. Accordingly, the knowledge context, social context, and technical context can be identified as the 3 fundamental components of the learning context, which are interdependent and interwoven with one another, and jointly construct a contextual environment for computer-supported learning. The recognition of computer-supported learning context is helpful for the identification of the objectives, methods, conditions of knowledge management.

IV. CONCLUSIONS Computers have been widely applied in human learning.

Computer-supported learning is not technology-shielded learning, which has its rich social context. Computer can play multiple roles in human learning by providing technical, cognitive and social support. The evolution, use/reuse and sharing knowledge is the final objective of human learning. This paper discussed knowledge management in computer-supported learning. More efforts are required for the promotion of knowledge management process in learning.

ACKNOWLEDGMENT The Research is supported by the project “Research on

the Construction and Application of Teaching Practice Community oriented to Knowledge Management under Networks Environment” (No. CCA090126), from National Education Science Foundation of China, and by “the Fundamental Research Funds for the Central Universities”, China.

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