Some methodological aspects of tacit knowledge elicitation

Methodological aspects of tacit knowledge elicitation with the aim of building expert systems are examined. Important aspects of expertise exerting considerable influence on knowledge elicitation have been enumerated and briefly described. Problems of knowledge elicitation are discussed in the light of findings of neuropsychology, investigations on brain asymmetry in particular. Several hypotheses in the course of the authors' work on development of expert systems in areas of psychology, human physiology and medical diagnostics have been formulated. In the framework of these hypotheses, the following points are discussed: the role of visual stimulus in the process of knowledge elicitation, expert strategies of the visual information analysis, influence exerted by the expert experience and formulation of question posed to the expert on his/her choice of strategy, alternation of strategy prepotency; exponential decrease of effectiveness of each strategy application and special significance of the end-insight. Proceeding from the principal propositions of the hypotheses having been formulated, methodological rules have been advanced, which can be assumed as a basis in working-out the semi-structured interview.     

Digital libraries in knowledge management: an e-learning case study

Knowledge and libraries – this conceptual symbiosis is as old as the idea of libraries itself: libraries collect artifacts of explicated knowledge and make them available for building up new knowledge in all areas of everyday life. Learning and qualification management support are further essential links in the knowledge supply chain, which starts at the expert knowledge of an author and ends at the targeted enhancement of another persons individual knowledge. Digital libraries and e-learning systems are thus important enabling technologies for the knowledge supply chain in the digital age.The e-Qualification project presented in this paper combines digital library, e-learning, and authoring support into an adaptable qualification management framework that provides integrated support and mediation for the various stakeholders involved in the qualification management process.     

Formal concept analysis for an e-learning semantic web

We capture student interactions in an e-learning community to construct a semantic web (SW) to create a collective meta-knowledge structure guiding students as they search the existing knowledge corpus. We use formal concept analysis (FCA) as a knowledge acquisition tool to process the students virtual surfing trails to express and exploit the dependencies between web-pages to yield subsequent and more effective focused search results. We mirror social navigation and bypass the cumbersome manual annotation of webpages and at the same time paralleling social navigation for knowledge.We present our system KAPUST2 (Keeper and Processor of User Surfing Trails) which constructs from captured students trails a conceptual lattice guiding student queries. We use KAPUST as an e-learning software for an undergraduate class over two semesters. We show how the lattice evolved over the two semesters, improving its performance by exploring the relationship between ‘kinds’ of research assignments and the e-learning semantic web development. Course instructors monitored the evolution of the lattice with interesting positive pedagogical consequences. These are reported as well in this paper.     

Knowledge sharing behaviors in e-learning community: Exploring the role of academic self-efficacy and sense of community

The purpose of this study was to explore the structural relationships between knowledge sharing behaviors (KSB), academic self-efficacy (ASE) and sense of community (SoC) of university students in e-learning community. The study was carried out with students who joined Facebook learning community that was created for the Computing I course which was taught with blended learning method. Data were collected from 316 university students by utilizing three self-report instruments: KSB scale, ASE scale (sub-scales: ‘social status’, ‘cognitive applications’ and ‘technical skills’) and classroom community (CC) scale (sub-scales: ‘connectedness’ and ‘learning’). The path analyses with structural equation modeling (SEM) further verified that students’ KSB were related to their ASE and SoC in e-learning community. The results of the study revealed that the ASE and SoC of the students positively affect their KSB. And in terms of sub-scales, the connectedness to the community, learning perception in the community, the self-efficacy of the students on the cognitive applications in the courses and their social status in the community positively affect KSB. However, students’ self-efficacy perceptions on their technical skills affect KSB positively but its affect size was smaller compared to other sub-scales. Further research studies and implications are presented and discussed.     

Knowledge engineering and psychology: Towards a closer relationship

Knowledge engineering projects deal with a wide range of domains within organizational and academic contexts. A number of elicitation techniques are used to acquire knowledge from experts. Most of these techniques originated within psychology but have been developed by knowledge engineers to become more structured, efficient and systematic. Until now, nobody has tried to re-apply these modified techniques back into psychology. This paper describes work that addresses this matter. It focuses on the psychological knowledge possessed by all people that enables them to deal with everyday problems and make life decisions. We refer to this as ‘personal knowledge’. To take a knowledge engineering approach to personal knowledge, we investigated the use of knowledge elicitation techniques to capture personal knowledge. We describe an empirical study involving ten participants and 80 knowledge acquisition sessions that assessed eight elicitation techniques in this context. The results revealed that each of the techniques showed promise at efficiently capturing and structuring aspects of an individual's personal knowledge. A content analysis of the acquired knowledge led to the construction of a meta-model (a primitive ontology) of personal knowledge and to the design for a new methodology for psychological research. From the perspective of psychology, the paper shows that knowledge engineering methods can be of value to psychologists. From the perspective of knowledge engineering and the wider computer science community, the paper shows that empirical methods used by psychologists can benefit the development and evaluation of ontologies and elicitation techniques.     

Knowledge as a Social Medium

The increasing popularity and access to computer networks such as the Internet has introduced a new form of interaction among individuals, and brought about the social dimension to intelligent systems that are embedded into group and community settings. Knowledge is now seen as an asset not only of an individual but also of groups; research fields such as organisational memory, knowledge management and community ware are beginning to emerge. This paper surveys recent approaches, discusses whether social knowledge is a tangible notion, and examines the role of social knowledge in the context of group and community oriented systems with new challenges it offers. Keiichi Nakata, Ph.D.: He is a research scientist at the Institute for Applied Information Technology (FIT) at GMD. He is currently a member of the “Social Web” research programme at GMD, with a particular interest in the investigation of social development of knowledge that belongs to communities, and its application to support social interactions. Prior to the current appointment, he has held lectureships at the University of Wales and Oxford Brookes University in UK. His academic background is BEng and MEng degrees in nuclear engineering from the University of Tokyo and PhD in AI from the University of Edinburgh.     

A comprehensive adaptive system for e-learning of foreign languages

The article presents a proposal, design and implementation of a new approach to adaptive e-learning systems. First, a proposal of a model is presented. This model aims at introducing adaptivity to current e-learning systems, which are rigid and limited in offering a truly personalised learning to individual students. Many of current e-learning systems enable personalised learning. However, in this paper, there is a new, innovative approach proposed for an adaptive personalised e-learning system. The primary area of our research is English as a second language (ESL). Adaptivity in our view is considered as an ability of the system to adapt to student's knowledge and characteristics. This pedagogical perspective requires introduction of such processes that enable to work the pedagogical aspects of teaching/learning. The required processes are of informatics nature. The proposed model was subsequently designed into a real application. Finally, the application was implemented and verified on a real data set. The results are also provided.     

A method toward dynamic e-learning services modeling and the cooperative learning mechanism

The advanced information technologies have made it possible for individuals to carry out cooperative learning efficiently and effectively from anywhere and at any time. To capitalize on the individual need and address the issues associated with the late entry into the e-learning area, it has great significance to study the service mechanism of CSCL on e-learning service and e-learning service computing modeling. This paper proposes an e-learning service model supporting for the life-cycle process management. The proposed model is developed by considering the learner’s behaviours during e-learning services, the scheduling policies, and the monitoring mechanism of learning activities. Business process modeling for e-learning services can be taken according to the study ordering of the knowledge points by using workflow modeling technology and process enactment mechanism. The overall life-cycle process management of knowledge is addressed by combining knowledge product modeling, knowledge resource modeling, and credit polices for member selection in research team by considering trust value of learners, advisers and providers in e-learning services. The proposed method can be used for supporting the sustainable development of e-learning services from planning and design, organizing e-learning process, maintenance of the e-learning process, to process improvement, as well as to support learners and advisers to effectively complete innovative team study and complex computation study. Lastly, an extended topic map tool has been developed by adding a knowledge requirement level and an information extraction tool to validate the proposed methodology. These tools can used to guide learners to concentrate on the required knowledge topics and drive knowledge providers to redevelop outdated knowledge hierarchy.     

The student experience of a collaborative e-learning university module

The aim of this paper is to present a picture of student experience of a collaborative e-learning module in an asynchronous e-learning environment. A distance learning module on music education worth five credit points for a bachelor online degree for primary school educating teachers was assessed using a self-evaluation questionnaire that gathered quantitative and qualitative data about student satisfaction of the collaborative e-learning activity. The quantitative part of the questionnaire consisted of 27 closed questions on a 10-point Likert scale and offered data about satisfaction with the module. The qualitative part of the questionnaire provided an insight into the participant perspective of the online collaborative experience. General open questions on satisfaction and dissatisfaction were analyzed with an inductive analysis which showed the evaluation criteria used by 92 students. Results of the analysis showed five themes of the participants’ perspectives, which were interpreted by the researcher as: teamwork, cognitive, operating, organizing, and emotive/ethic for the positive aspects and teamwork, operating, organizing, and emotive/ethic for the aspects to be improved. The aspects that were associated with satisfaction include: collaborating, comparing ideas, sharing knowledge and skills to support each other, peer learning, analyzing and integrating different points of view, the usability of the platform, group planning and workload management. Aspects of the student learning experience that should inform the improvements of e-learning include: more collaboration between students since some students engage differently; more coordination and organization, the workload management in the group activities, some technical problems such as updating modifications. The participants’ results in the module increased their didactic potential as primary school teachers. The findings are discussed in relation to their potential impact on developing collaborative activities addressed to teacher education in distance learning. Implications for future research are also considered.     

Knowledge construction in an outsider community: Extending the communities of practice concept

We present an empirical analysis of a web forum in which followers of a health-related community exchange information and opinions in order to pass on and develop relevant knowledge. We analyzed how knowledge construction takes place in such a community that represents an outsider position which is not accepted by majority society. For this purpose we applied the Community of Practice (CoP) concept as a guideline for our analysis and found that many well-known activities of CoPs were true of the Urkost community. The social network analysis findings also supported interpreting this community as a CoP. But we found as well that this community had a variety of structural characteristics that the CoP literature deals with insufficiently. We identified the structure of goals, roles, and communication as relevant features that are typical of this outsider CoP. For example, the attitude of the core members towards people of a ‘different faith’ was characterized by strong hostility and rejection. These features provided an effective basis for the development and maintenance of a shared identity in the community. Our findings are discussed against the background of the necessity for further development of the CoP concept.     

Knowledge-based recommendation: a review of ontology-based recommender systems for e-learning

Recommender systems in e-learning domain play an important role in assisting the learners to find useful and relevant learning materials that meet their learning needs. Personalized intelligent agents and recommender systems have been widely accepted as solutions towards overcoming information retrieval challenges by learners arising from information overload. Use of ontology for knowledge representation in knowledge-based recommender systems for e-learning has become an interesting research area. In knowledge-based recommendation for e-learning resources, ontology is used to represent knowledge about the learner and learning resources. Although a number of review studies have been carried out in the area of recommender systems, there are still gaps and deficiencies in the comprehensive literature review and survey in the specific area of ontology-based recommendation for e-learning. In this paper, we present a review of literature on ontology-based recommenders for e-learning. First, we analyze and classify the journal papers that were published from 2005 to 2014 in the field of ontology-based recommendation for e-learning. Secondly, we categorize the different recommendation techniques used by ontology-based e-learning recommenders. Thirdly, we categorize the knowledge representation technique, ontology type and ontology representation language used by ontology-based recommender systems, as well as types of learning resources recommended by e-learning recommenders. Lastly, we discuss the future trends of this recommendation approach in the context of e-learning. This study shows that use of ontology for knowledge representation in e-learning recommender systems can improve the quality of recommendations. It was also evident that hybridization of knowledge-based recommendation with other recommendation techniques can enhance the effectiveness of e-learning recommenders.     

A knowledge engineering approach to knowledge management

Knowledge management facilitates the capture, storage, and dissemination of knowledge using information technology. Methods for managing knowledge have become an important issue in the past few decades, and the KM community has developed a wide range of technologies and applications for both academic research and practical applications. In this paper, we propose a knowledge engineering approach (KMKE) to knowledge management. First, a knowledge modeling approach is used to organize and express various types of knowledge in a unified knowledge representation. Second, a verification mechanism is used to verify knowledge models based on the formal semantics of the knowledge representation. Third, knowledge models are classified and stored in a hierarchical ontology system. Fourth, a knowledge query language is designed to enhance the dissemination of knowledge. Finally, a knowledge update process is applied to modify the knowledge storage with respect to users’ needs. A knowledge management system for computer repair is used as an illustrative example.     

The impact of electronic environmental knowledge on the environmental behaviors of people

Nowadays, we examined the connection between individuals' relationships with the natural environment, their environmental behaviors, and their environmental knowledge with a focus on environmental attitudes, environmental awareness, environmental values, public information, environmental skills, and environmental responsibility is very interesting. Environmental knowledge involves human discourse about interrelationships with the environment. The impact of people to perceive and interpret the relative health of environmental systems and to take appropriate action to maintain, restore, or improve the health of those systems is very important. Therefore, environmental teaching and learning is very necessary and can help to improve the environment behaviors of the people. The purpose of this paper is to investigate the impact of e-learning system the environmental of the behavior. Data were collected from 330 students of Tabriz Branch, Islamic Azad University. After performing satisfactory reliability and validity checks, the structural model was tested with the use of smart PLS 2.0. Results indicate that electronic environmental knowledge learning has a direct effect on person's environmental behaviors.     

Guidelines for the development of e-learning systems by means of proactive questions

The current development approaches for e-learning systems fail to explain in a clear and consistent way the pedagogical principles that support them. Moreover, decisions with regard to the structuration of each component proposed by these approaches are mainly taken by the designer/developer. As a result, the ensuing e-learning systems reflect “common sense” rather than a theoretically informed and systematic design.The present paper proposes a global architecture model for any e-learning system whose blocks are extracted from the analysis of the main approaches that currently guide the development of these kinds of systems. We use Kipling’s famous questions to define and structure the blocks of the proposed model, and we base the answers to these questions on two disciplines that are closed to e-learning: presential education (i.e., its pedagogical theories) and knowledge management.     

Building a CAL Expert System based upon Two-phase Knowledge Acquisition

With the fast growing and globally accepted e-learning technology, Computer-Assisted Learning (CAL) system, which can provide the individualized materials, becomes a matter of great importance. In this paper, we propose a CAL Expert System (CAL-ES), in which teachers can provide their teaching strategy as guidance to students' learning. Because the knowledge hierarchy and the knowledge itself are both important in CAL domain, and the teaching strategy can be considered as rule-format, Two-phase Knowledge Acquisition is proposed to acquire the knowledge hierarchy and the rule-based knowledge by the cooperation of teachers and knowledge engineers. The prototype of CAL-ES is constructed of the mathematical teaching materials. The CAL-ES is useful for student learning and is easy for teachers maintaining.     

Knowledge maps for e-learning

Maps such as concept maps and knowledge maps are often used as learning materials. These maps have nodes and links, nodes as key concepts and links as relationships between key concepts. From a map, the user can recognize the important concepts and the relationships between them. To build concept or knowledge maps, domain experts are needed. Therefore, since these experts are hard to obtain, the cost of map creation is high. In this study, an attempt was made to automatically build a domain knowledge map for e-learning using text mining techniques. From a set of documents about a specific topic, keywords are extracted using the TF/IDF algorithm. A domain knowledge map (K-map) is based on ranking pairs of keywords according to the number of appearances in a sentence and the number of words in a sentence. The experiments analyzed the number of relations required to identify the important ideas in the text. In addition, the experiments compared K-map learning to document learning and found that K-map identifies the more important ideas.     

Developing inclusive e-learning systems

The requirement for e-inclusion relates to the employment of appropriate development strategies for software applications and services so as to accomplish accessibility and increased interaction quality at deployment time. Inclusive e-learning is the outcome from the application of e-inclusion design and implementation methods in the context of e-learning systems. This paper reports consolidated development experience from the construction of the following e-learning systems: (a) training applications for hand-motor impaired users and for people with cognitive disabilities; (b) learner-adapted courseware and (c) a universally accessible educational computer game. In this context, the primary emphasis is placed on the reporting of the design and implementation aspects to accommodate the inclusive system characteristics, rather than on the typical e-learning software engineering approaches.     

Investigating e-learning system usage outcomes in the university context

This paper investigates the outcomes of e-learning systems adoption and use by conceptualizing three e-learning systems adoption outcome constructs namely perceived learning assistance, perceived community building assistance and perceived academic performance. Utilizing these constructs, the paper proposes a research model for assessing the possible outcomes of e-learning systems adoption and use. The study collected longitudinal survey data from 249 university students participating in hybrid courses using a popular learning management system, Moodle. Partial least squares (PLS) approach was then used to test the research model.The findings suggest that beliefs about perceived usefulness and perceived ease of use, and how an e-learning system is used influence students' perceived learning assistance and perceived community building assistance. In turn, perceived learning assistance and perceived community building assistance influence the students' perceived academic performance.     

Articulation of information requirements for personalised knowledge construction

The quality of information provision influences considerably knowledge construction driven by individual users’ needs. In the design of information systems for e-learning, personal information requirements should be incorporated to determine a selection of suitable learning content, instructive sequencing for learning content, and effective presentation of learning content. This is considered as an important part of instructional design for a personalised information package. The current research reveals that there is a lack of means by which individual users’ information requirements can be effectively incorporated to support personal knowledge construction. This paper presents a method which enables an articulation of users’ requirements based on the rooted learning theories and requirements engineering paradigms. The user’s information requirements can be systematically encapsulated in a user profile (i.e. user requirements space), and further transformed onto instructional design specifications (i.e. information space). These two spaces allow the discovering of information requirements patterns for self-maintaining and self-adapting personalisation that enhance experience in the knowledge construction process.     

The double-edged effects of explanation prompts

Explanation prompts usually foster conceptual understanding. However, it has been claimed within cognitive load theory that prompts can take cognitive load to the upper limit when learning complex contents. Under such circumstances, prompts focusing the learners’ attention on specific aspects (e.g., conceptual aspects such as elaborations on domain principles) might have some costs: Other important aspects (e.g., procedural aspects such as how to calculate) cannot be processed deeply. Thus, we expected that conceptually-oriented explanation prompts would foster the detailedness of explanations, the number of elaborations on domain principles, and conceptual knowledge. In addition, we tested the influence of such prompts on the number of calculations performed during learning and procedural knowledge. We conducted an experiment in which we employed conceptually-oriented explanation prompts in a complex e-learning module on tax law. Tax law university students (N = 40) worked on this e-learning module under two conditions: (a) conceptually-oriented explanation prompts, (b) no prompts. The prompts led to double-edged effects: positive effects on the detailedness of explanations and on the number of elaborations on domain principles, as well as on conceptual knowledge and simultaneously negative effects on the number of calculations performed during learning as well as on procedural knowledge.