Developing a Web assisted knowledge construction system based on the approach of constructivist knowledge analysis of tasks

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  • CKAT includes four dierent stages: knowledge objective, knowledge gathering, knowledge

    analysis, and task knowledge structure. In order to match these four stages, this research

    1. Introduction

    The idea that knowledge is the most valuable source of competitive advantage has

    been widely considered for years. Although no clear consensus has yet emerged on

    the most appropriate denition of knowledge, it can be seen as the capacity, em-

    Computers inHuman Behavior*designs an assisted knowledge construction system that includes four systematic sub-functions:

    the keyword function, the URL resource function, the analysis function, and the construction

    function. After understanding users perceptions toward the WAKC system, users have highlypositive behavioral intention to use the system as a Web-based assisted knowledge con-

    struction tool.

    2004 Elsevier Ltd. All rights reserved.

    Keywords: Knowledge analysis of tasks; Constructivist reection cycle; Search engines; Knowledge

    constructionDeveloping a Web assisted knowledgeconstruction system based on the approachof constructivist knowledge analysis of tasks

    Shu-Sheng Liaw *

    General Education Center, China Medical University, 91, Shiuesh Road, Taichung 404, Taiwan, ROC

    Available online 24 July 2004


    The purpose of this study is to develop a Web assisted knowledge construction (WAKC)

    system as an individual knowledge construction tool for Internet users. The system is based on

    the theory of constructivist knowledge analysis of tasks (CKAT). The CKAT integrates

    constructivist reection cycle and knowledge analysis of tasks. The conceptual model of

    Computers in Human Behavior 21 (2005) 2944Tel.: +886-422053366x1927.

    E-mail address: (S.-S. Liaw).

    0747-5632/$ - see front matter 2004 Elsevier Ltd. All rights reserved.doi:10.1016/j.chb.2004.02.003

  • constructed to form humans knowledge. Nonaka (1994) divides knowledge into twoparts: explicit knowledge that can be easily expressed in words and numbers; and

    30 S.-S. Liaw / Computers in Human Behavior 21 (2005) 2944tacit knowledge, such as bodily skills and mental models, that is not articulated.

    Although Web applications are popular today, the primary use of the Internet,

    other than e-mail, is to use Web search engines as a knowledge retrieval tool. Various

    search engines have been developed for helping users to look for online information,

    but there is just too much information on the Web. From the Google (http:// search engine, there are over three billion Web pages on the

    Internet. Though it is fair to say that Web information retrieval would collapse if

    search engines were not available on the Internet, the issues of helping users to ndtheir needed information and assisting them to construct their knowledge from the

    Internet remain critical.

    Based on the approach of constructivist knowledge analysis of tasks (CKAT), the

    current study is to develop a Web assisted knowledge construction (WAKC) system

    to help individual Internet users when they search for knowledge with search engines.

    In this paper, the types of search engines will be introduced rst. Then the approach

    of CKAT will be modulated. The third section presents a WAKC model that is based

    on CKAT. And the last section analyzes users attitudes toward the WAKC system.

    2. Types of search engines

    Search engines have three major functions: First, they gather a set of Web pages

    that form the universe from which a searcher could retrieve information; second,

    they represent the pages in this universe in a fashion that attempted to capture their

    content; and third, they allow searchers to issue queries by employing information orknowledge retrieval algorithms that facilitate the search for the most relevant pages

    from this universe (Gordon & Pathak, 1999). Although various search engines have

    similar search functions, each of them has its own unique database and search

    methods. Regarding search types, search engines adopt from three basic paradigms,

    directory-based services, query-based, and lter-based search engines.

    Directory-based services, such as Yahoo! ( for the generalbodied in the brains of people and embedded in social practice, which interprets and

    transforms information (Davenport & Prusak, 1998). In other words, knowledge is

    not only context-specic and relational, but also connected to human action as it

    interprets, transfers, and constructs information into knowledge (Nonaka &

    Takeuchi, 1995). Kang and Byun (2001) stated that knowledge is the product of a

    learning activity in which a learner, based on experience acquired through cognitiveactivities (such as perception, interpretation, and analysis), assimilates and accom-

    modates information into his/her cognitive structure in accordance with the envi-

    ronment as he/she understands it and in collaboration with other people. Under the

    cognitive perspective, knowledge is the advanced stage of information. It means that

    information represents the fundamental basis of knowledge and is directly associated

    with the facts of the real world. Information needs to be interpreted, processed, andpurpose or MedWeb (, Medengine (http://

  • Retrieval Vagabond on Information Network) (Baujard, Baujard, Aurel, Boyer, &

    Appel, 1998), OMNI (, MEDBOT (

    S.-S. Liaw / Computers in Human Behavior 21 (2005) 2944 31medbot), and HONselect ( (Boyer, Baujard, Griesser,

    & Schrrer, 2001) for the medical purpose, potentially lead to better retrieval andoutcomes. With the growth of the Internet, there are continued changes in the types,

    features, and functions of search tools, capturing our attention and interests.

    3. Knowledge construction

    Regarding knowledge, it has become the preeminent economic resource that is

    more important than automobiles, oil, steel, or any of the products of the IndustrialAge; thus, the emergence of knowledge-intensive products and services increases

    amount of information and knowledge retrieval in the Internet Age. The prolifera-

    tion of the Internet and the emergence of knowledge-based society are accelerating

    the need for a exible and generative knowledge construction system. The meth-

    odology of knowledge construction has changed from its traditional methodology of

    non-digital accumulation to a new and popular nding method of digital accumu-

    lation that takes place via the Internet and the World Wide Web (WWW/Web).

    Knowledge can be divided into two kinds of formats: explicit knowledge and tacitknowledge. Explicit knowledge can be expressed in words and numbers, as well as

    distributed as data, scientic formulae, product description, basic principles, and so

    on. In other words, explicit knowledge is easy to transmit in denite and organized

    forms. It can be easily managed on a computer, communicated via a network, and

    stored in a database (Trentin, 2001). In contract, tacit knowledge is highly personal

    as well as hard to dene and express. In addition, it is also dicult to, and Medical Matrix ( for

    medical use, provide a hierarchical organization of resources, most often developed

    by human cataloguers who select, index, and annotate links (Callery & Tracy-

    Proulx, 1997). Careful organization of resources present directory in services enables

    rapid discovery and browsing of resources by topic or category a more intuitive

    mode of access than keyword selection and query renement for users (Dempsey,Vreeland, Sumner, & Yang, 2000). In contrast to directory-based services, query-

    based search engines, such as Excite (, Altavista (http://, and Google for general purpose or med411 (http://, MedExplorer (, Medscape

    (, and HON ( for medical needs,

    provide broad coverage of the Web through intensive automation of the indexing

    and retrieval processes. These services construct databases from robotic collection of

    remote Web pages and rely primarily on textural input from the user to match arequest with a set of Web links. The lter-based search engine is a kind of agents that

    integrated various search engines. In essence, lter-based search engines usually are

    built for specic purposes, such as for medical or business application. Filter-based

    search engines, such as MediAgent (Bin & Lun, 2001), MARVIN (Multi-Agentand share tacit knowledge with others because it embraces individual perception,

  • 32 S.-S. Liaw / Computers in Human Behavior 21 (2005) 2944intuition, and foresight. Tacit knowledge is rmly rooted in personal experience, as

    are ones ideals, values, and emotions.

    3.1. Task knowledge

    The term task can be dened as a specied objective, undertaken as part of aneducational course or at work (Long & Crookes, 1992). Long and Crookes (1992)

    further distinguish between target tasks and pedagogical tasks. Target tasks are real-

    world tasks for which learners should acquire both linguistic and sociolinguistic

    competences. They focus on authentic language use for a specic purpose and are

    derived from a need analysis. In general, reading a technical manual, solving a math

    problem, reporting a chemistry experiment, taking lecture notes, or even buying a

    train ticket are examples of target tasks. Pedagogical tasks are derived from target

    tasks. In other words, they consist of one or more skills or knowledge componentsrepresented by a target task (Wenden, 1995). For instance, taking lecture notes re-

    quires learners to recognize dierent discourse types, that is they should be able to

    identify relevant cues and use techniques for recording, analyzing, and organizing

    information. Pedagogical tasks refer to problem posing activities; at the heart of a

    task, there is a learning problem or a communication problem. Pedagogical tasks can

    vary from the simple to the complex; they can also have a learning goal as well as a

    communicative goal.

    Task knowledge refers to what teachers know and what learners need to under-stand about the purpose of a task, its demands, and a determination of the kind of

    task it is (Wenden, 1995). Additionally, task purpose refers to the outcome of a

    pedagogical task. It is what the teacher expects students to learn. From the viewpoint

    of learners, knowledge of task purpose is their perceptions of the learning needs

    which the task intends to meet, and a basis for determining its relevance. Knowledge

    of task demands is commonly known as domain-specic knowledge and it refers to

    the knowledge (or skills) that is necessary to do the task and the ways of doing it.

    Determining the kind of task means that learners classify a learning activity. Whenclassifying a pedagogical task, learners seek connections between prior learning tasks

    and a current one. They try to identify the nature of the problem posed by the task

    by comparing it with others that they are familiar.

    3.2. Task knowledge construction

    Developing an eective knowledge construct methodology is a crucial issue for

    using search engines as a knowledge construction tool. This research develops aknowledge construction conceptual model that integrates knowledge analysis of tasks

    (KAT) (Johnson & Johnson, 1992) and constructivist reection cycle (CRC) (Oliver,

    2000). Based on theoretical research, the conceptual model, called CKAT, is expected

    to be an eective methodology for constructing knowledge for Internet users.

    Constructivism is a theory of learning that describes how individual minds create

    knowledge or how individual knowledge structures their deeper conceptual under-standing. A CRC (Fig. 1) is included: individuals express their conceptions of ideas

  • S.-S. Liaw / Computers in Human Behavior 21 (2005) 2944 33or their mental models, reect on feedbacks about their ideas, and revise initial

    conceptions to account for new expressions (Oliver, 2000). Essentially, reection

    allows individuals to have opportunities to modify misconceptions or improve in-

    adequate understanding.

    KAT develops structures to represent the knowledge that individuals require to

    perform a particular task. KAT can be divided into four stages: knowledge objective,

    knowledge gathering, knowledge analysis, and task knowledge structure. The stage

    of knowledge objective is to create domain boundaries and helps individuals toensure that attention is concentrated on relevant activities. As for the stage of

    knowledge gathering, it is to nd relevant information or knowledge. The stage of

    knowledge analysis is based on individual experience that decides on what the de-

    manded knowledge is. The results of knowledge analysis are used to produce a model

    of tasks in terms of task knowledge structure, which represent the knowledge that

    individuals possess about the tasks they perform (Uden & Brandt, 2001). The stage

    of task knowledge structure is acquired through learning and previous task perfor-

    mances, and are dynamically structured into meaningful units in memory.In CKAT (Fig. 2), the rst stage is knowledge objective for establishing a tasks

    domain boundaries and for helping to ensure that attention is concentrated on the

    most critical and relevant activities. Once the rst stage has been accomplished,

    knowledge gathering can begin. The principal inputs to the second stage are

    knowledge objective itself and the knowledge gathered through search tools. The

    major outputs of the second stage are a preliminary picture of the domain knowledge




    Fig. 1. Constructivist reection cycle.expressed in terms of URLs (Universal Resource Locators), titles, percentages of

    relevance, brief descriptions, and keywords all intended to describe the Web pagescontents. The third stage, knowledge analysis, takes the outputs of the second stage

    and analyzes each in terms of its correlation with knowledge objective (the rst

    stage). The nal stage is to construct the task knowledge structure. In CKAT, the

    task knowledge structure includes three components: the task category, the aspect of

    task knowledge, and the URL. Users may input task categories to systematically

    construct knowledge. In addition, they may input abstract to note aspects of

    knowledge. Furthermore, the URL is a subordinate level that links users to a par-

    ticular instance of the objective.In essence, the human mind is similar to a computer process which

    explains psychological events in terms of input, storage, and output. Based on the

  • 34 S.-S. Liaw / Computers in Human Behavior 21 (2005) 2944Knowledge

    objective Revise


    Express information processing point of view, individual knowledge construction includes

    four dierent stages: information denition, information acquisition, information

    transformation, and knowledge construction (Gagne, Yekovich, & Yekovich, 1993).

    The information denition stage is similar to the stage of knowledge objective. In

    this stage, the...


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