An approach for on-demand e-learning to support knowledge work1 Stefan Thalmann (University of Innsbruck, Austria
[email protected])
Fredrik Enoksson (Royal Institute of Technology, Sweden
[email protected])
Abstract: The requirements on learning support from knowledge work differ compared to traditional work. Based on those observations an approach for supporting learning in knowledge work is proposed considering requirements from e-learning as well as from knowledge management. In addition to traditional e-learning, on-demand e-learning takes the current situation of the knowledge worker into consideration to ensure learning support of knowledge work is proposed. For using a broad variety of resources in on demand e-learning a single metadata schema for describing seems not sufficient for every organisation. Therefore, application profiles appear adequate for describing resources used in the proposed approach for arranging knowledge elements. Identifying the knowledge workers current situation a learning need should be derived and to use it afterwards for selecting and delivering knowledge elements. Keywords: on-demand e-learning, workplace learning, metadata, learning need, work-based learning, knowledge work Categories: H.1.2, H.5.4, H.3.3, H.3.5
Introduction Looking upon e-learning (EL) and knowledge management (KM) there are fundamental differences influencing the design of EL solutions. Currently, EL see learning as a continuous, lifelong process transferring knowledge for predefined tasks. Primary the transfer of more general knowledge usable in different situations to build competencies and more general job requirements are well supported. Therefore, predefined, didactically well prepared courses that end with an examination, to verify the learning success, are used. In KM the demand for knowledge is triggered directly from business process, an unforeseeable knowledge gap initiates the learning process. Learning is primary seen as process to acquire knowledge required to solve current problems and after learning the knowledge worker returns into the business process. In that perception learning processes are directly linked to business processes.
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Thalmann, S.; Enoksson, F. (2007): An approach for on-demand e-learning to support knowledge work. In: Maurer, H. et al. (eds.): in: Tochtermann, K. & Maurer, H. (eds.): Proceedings of I-KNOW ´07. 7th International Conference on Knowledge Management, Graz, Austria, September 5-7, 2007. Journal of Universal Computer Science, 289-296.
Consequently, for knowledge work with its high variety often unforeseeable tasks and thus unforeseeable required knowledge [Maier, 05] learning support by current EL approaches are not ensured. Therefore, in the following the requirements from KM at learning support as well as the current situation in EL are regarded. Building on that a model for supporting learning in knowledge work is introduced. In the following chapters the proposed approach is to use application profiles for describing the resources and arranging learning and knowledge resources to learning arrangements are described.
Learning support of knowledge work From a KM perspective competencies and general knowledge applicable in numerous situations are highly relevant. But because of the scare time in the daily work life, long-lasting learning processes brokering general knowledge appear unworkable. The prior transfer of the required knowledge seems not practicable, because on the one hand the demand of knowledge work is mostly unforeseeable and with a high variance [Maier, 05] and on the other hand the transfer of all potentially valuable knowledge is very time-consuming and expensive. EL is understood as learning, a continuous, life-long process resulting from acting in situations [Brown, 89], that is supported by information and communication technology. Typically, learning material is offered as web-based training (WBT), which can be characterized either as monolithic, static courses or as more or less predefined compositions of learning objects (LO). The result is in both cases a static WBT that should fit all knowledge workers in all situations, irrespective of their personal attributes and that of their current context. If the knowledge worker’s context and needs are not considered, motivation, success and acceptance may decline [Dagger, 05]. In order to solve this problem, it is necessary to consider the concrete situation of the knowledge worker and to compose resources during run-time into learning arrangements. Therefore, a detailed and processable description of the situation must be available. Building on the theory of task-technology fit [Goodhue, 95], a better fit between the knowledge worker’s situation (task) and the proposed WBT (technology) should improve knowledge worker’s performance. Generally, it seems improbable that the predefined, static and bulky courses of current EL can ensure the fit to the knowledge worker’s current task. However, none of the current approaches clearly focuses on considering typical situations in which employees encounter an opportunity to learn which is at the centre of just-intime KM [Davenport, 02], workplace learning [Illeris, 03] or on-demand KM [Sampson, 02]. Here, knowledge services are triggered by a situation in which the user switches to a learning-oriented action, in this case knowledge elements are selected, composed and delivered considering as much context as possible [Maier, 07b]. Educational Adaptive Hypermedia Systems (EAHS) are an established approach to adapt learning material to the learners’ situation. But in contrast to the proposed approach it strongly focuses on learners characteristics, like previous knowledge or learning styles, and not at work situations, primary focused here. In the rest of this paper we propose an approach for on-demand EL supporting knowledge work considering requirements from KM and EL depictured in figure 1. Despite the fact that knowledge work and KM requires more flexible
approaches for learning, traditional solutions developed by course authors [1] are still necessary. Didactically refined courses can be used to transfer more general knowledge and competencies identified as generally applicable in a multiplicity of business processes by learning processes before [2]. In the case of insufficient knowledge in the business process [3] situation-oriented arrangements are assembled by resources from the organizational knowledge base in order to compensate the knowledge gap. Therefore, the organizations whole knowledge base (including external material) should be used. Thus, knowledge elements in different stages of maturity, like lessons learned, best practice or patents, [Maier, 07a], as well as contact information, like blue or yellow pages for proposing people helpful for the problem can be considered. By system-let adaptivity [4] a set of knowledge elements appropriate for the knowledge workers specific situation will be arranged [5]. In contrast to the traditional EL the composed course is not didactically designed or prepared. Finally, the knowledge worker can adopt the codified knowledge into the current work situation and apply in the business process [6].
Figure 1: learning support for knowledge work
Application profiles to support on-demand e-Learning In the last couple years, many organizations have applied concepts of business process re-engineering and numerous methods and techniques to support business process modeling have been proposed in the literature. Recently, a number of authors have proposed extensions to business process modeling techniques that model (some of the) specifics of KM (for a comparison see [Maier, 2007c]). Main extensions are on one hand additional object types, e.g., knowledge object, i.e. topics of interest, documented knowledge, employees, and skills, and on the other additional model types, e.g., knowledge structure- or communication diagram and knowledge map. Even though the added concepts describe a portion of the context of knowledge work, they are not suited to model the often unstructured and creative learning practices in knowledge work and particularly their link to business processes (for a detailed comparison see [Maier, 05]). To overcome this obstacle [Maier, 07b]
proposed an approach for on-demand EL based on the concept of activity theory. The activity-theoretic perspective [Engström, 87], [Blackler, 95] focuses creative, dynamic, and communication-intensive tasks, unstructured problems, membership in communities, self-organizing teams and demand for learning. In contrast to the clearly defined sequence of events and functions, there is no predetermined flow of knowledge-oriented actions. Nevertheless, deriving a learning need from the mentioned extended modeling approaches seems also realizable. In order to reuse knowledge elements from the organisational knowledge base (see figure 1) contextual information, i.e. metadata, represented in a semantically described specification is needed [Pawlowski, 06]. For LO the IEEE LOM [IEEE, 02] is regarded as the dominant standard in the field [Duval, 04], the standard is rather extensive standard that covers many of relevant aspects in order to mark up any LO. Depending on the intention of the use of the LOs and a cost/benefit analysis the set of metadata chosen can either be local to the organisation or from an established standard, in order to prepare for interoperability with other organisations. Some of the common problems with using a standard in practice are that they are sometimes very extensive and a lot of the elements are never used, even if the standard chosen is extensive it might not have enough elements to cover the need to describe a LO needed within an organisation [Godby, 04]. One solution to both apply to standards and describing the resources the way needed is to use application profiles [Heery, 00]. They are defined as: "schemas which consists of data elements drawn from one or more name-spaces, combined together by implementers, and optimised for a particular local application" [Heery, 00]. The application profile can furthermore restrict each of it elements further than it was originally intended, however the opposite is however not possible in order to be consistent with the standard. This means that an organisation can choose which metadata elements to use from one or more standards and also from locally developed used elements. Some guidelines in order to create an application profile are given in [Duval, 06] where the starting point is to analyze organizational requirements. With the requirements it is also recommended to start from a certain standard that covers most of the needs and start from those elements of the standard. From there it is possible to further make the selection of appropriate metadata elements from other standards. In [Maier, 07b] the requirements for a knowledge worker in a business process has been analysed and the paper further discusses what metadata elements from that standard can be used for different contexts aspects for a knowledge worker in a business process. The context dimensions taken into consideration are: process, person, group, product, location, time, technology and they are mapped against the elements of IEEE LOM. In [Maier, 07b] it is concluded that IEEE LOM can generally be mapped to these context dimensions. However, In organization specific parts and in the description of media types, usage descriptions and educational descriptions is not totally covered. The solution is to extend these description by using application profiles with IEEE LOM as base schema. An example of an application profile for Learning Objects in form of video or audio content would use the IEEE LOM in combination with elements from the MPEG-7 standard, that is used to describe the technical aspects of video and audio content.
Arranging Knowledge Elements for on-demand e-learning In order to create situation-oriented learning arrangements for realizing on-demand EL arranging knowledge elements, is proposed in the following. Starting point for ondemand learning systems is a learning need arise by situations in business processes. Learning activities are triggered by an opportunity in a business process in which an employee with a certain learner profile can, should or must learn in order to be able to complete the present task. A learning system then delivers knowledge elements according to the worker’s situation [Maier, 07b]. The situation can be described by the seven context dimensions mentioned in previous chapter, and the description is derived from basic systems, like ERP Systems or learning management systems. Table 1 presents the seven context dimensions with a short description of what they are and also how they can be found and gathered from the basic systems. context description dimensions process sequence of tasks
direct takeover of elements
applying rules or ontologies to gain usable metadata
- parts of the process description like keywords
- attributes from modelling language Æ required knowledge - granularity level from roles - personal attributes from learner profiles - derive metadata from user behaviour, e.g. click stream data - user feedback to calibrate the deriving process - evaluate system usage of the other group members in similar situations
person
individual engagement in the learning process
- entered keywords - input from defined input fields
group
teams or communities the knowledge worker is engaged in electronic resources which the knowledge worker use
- elements from group description
product
location
geographic location, points of interest
time
available time, current time technical attributes of devices and applications
technol ogy
-non-varying attributes from - analyzing relationships defined the metadata of content in use in the metadata to identify typical attributes that fits - analyze the LO history to find typical successors - predefined points of - derive metadata from points of interests directly entered by interest (assign points to the user, e.g. by using select geographic coordinates) , e.g. lists keywords, degree of interruption - information directly entered - deriving from schedules or by the user process descriptions - technical specifications - derive technical requirements from the devices stored in from the device information device profiles, e.g. (CC/PP) model
Table 1: deriving metadata from context dimensions Providing situation-oriented learning arrangements can be realized in the following steps. Firstly, context data needs to be gathered which can be implemented by sensor services that provide context from basic systems such as repositories, ERP or HR systems. Those systems containing a huge amount of data about resources and their usage, the knowledge worker itself and his engagement with the systems.
Because of the heterogeneous data formats used in the multifaceted amount of basic systems and this raw data represents isolated views on the situation they must be aggregated, filtered and related in a separate consolidation process for describing the entire situation and to ensure processing in the next levels. For example, raw data in form of a geographic coordinate must be linked to a point of interest, the description of which in form of metadata can be processed in the next levels. The methods depictured in Table 1 can be used in order gain valuable metadata stored in application profiles used in the organisation. After preparing the input data, the context is available as processable metadata stored with an application profile schema. This data is the basis for automatic query generation. The generated query is used for querying one or more repositories, in which knowledge resources and their metadata are stored. [Maier, 07b] showed that descriptions of the proposed context dimensions (see Table 1) match to metadata elements from existing metadata standards, e.g. IEEE LOM. Thus selection of suitable resources by using context information and practices described in table 1 is enabled. A way to structure and support the search of knowledge elements would be to attach each of them to a learning process, this process would in turn correspond to a “learning need” that the knowledge worker has in the business process. In order the find the “learning need” for a knowledge worker, i.e. what a knowledge worker needs to learn in order to fulfil the part of the business process that are currently lacking. To derive this in an automatic way the description of the business process had to include roles in the process with some kind of competency description. It would also require a competency description of the knowledge worker, from those descriptions a learning need will be derived by comparing the two descriptions, the competency gap is then the learning need. To automatically find the learning need is rather complex unless all information already exist in advance. To manually find out a learning need it would first need to be recognized by the knowledge worker that such a need exist. This learning process needs to be found by the knowledge worker and from a selected learning process the attached LOs can be selected with the context dimensions taken into consideration in order to further personalise the selection. In order to be interoperable over several repositories some kind of common infrastructure between the systems are needed. A way of searching for resources that is quite common in the library world is the Z39.50-protocol standard [Hammer, 96]. The protocol is client/server based and both sides have to implement a Z39.50 interface. Furthermore it needs to be decided what kind of data that can be searched for. Z39.50 can be used for non-semantic described resources, traditionally stored in databases or document management systems [Hammer, 96]. In the case of semantically described resources, e.g. described in RDF, searching can be made quite easy by using a query language like SPARQL specially designed for RDF. The outcome of the query is a set of metadata describing knowledge elements that fulfil the criteria specified in the query. Therefore, the corresponding knowledge elements fit in the knowledge worker’s current situation to a certain degree. Knowledge elements are selected from the return set and arranged into learning chunks. The size of the learning arrangements can vary from atomic knowledge elements to complex sets. The decision is placed by a personal software agent or by a rule-based approach based on a fitness function as benchmark for evaluation [Goodhue, 95].
Finally, the resources identifiers are used to retrieve them from the repository and to present them to the knowledge worker. The endpoint of a so-defined learning activity would not be passing a test, but completing the original task in the business process. By adopting the absorbed knowledge into the current work situation in a business process and applying the knowledge in order to solve a certain task the on-demand learning process is finished and the knowledge worker turns back into the business process.
Conclusion and outlook The paper identifies the requirements of learning support for knowledge work and presented an approach to consider these requirements. The need for acquiring new knowledge arises directly from acting in business process. Because of the high variance and unstructured processes of knowledge work [Maier, 05] the demand for knowledge cannot be identified before running the business process. Therefore, a flexible, situation-oriented reaction of a demand for knowledge arising from acting in a business process is necessary (see figure 1). In order to ensure this support an approach for on-demand EL was proposed. What needs to be taken into consideration when searching for and arranging knowledge elements are the context-dimension as described in the paper. This information needs to be gathered and consolidated, perhaps from different systems in order to detect the learning need and afterwards query repositories in order to receive a personalised set of knowledge elements. Resource descriptions with the LOM standard fits with the context dimensions [Maier, 07b], but could be extended with the help of application profiles in order to make a better description for a particular organisation. Problematically are interoperability aspects between different metadata descriptions. The idea behind application profiles is rather simple, but when implementing such a solution problems can occur that is caused by differences in the abstract model behind different metadata standards. It is usually possible to be interoperable with one standard when using several in an application profile, but that is not really what is wanted. This problem is described in more detail in [Nilsson, 05]. In further research empirical studies to evaluate proper application profiles and a prototypical implementation of the presented approach are planned. Interesting questions here would be how to derive the necessary information needed to describe the seven contexts described here and then also how to keep it in a format that would be interoperable with each other.
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