34,866 research outputs found

    Lessons learned: structuring knowledge codification and abstraction to provide meaningful information for learning

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    Purpose – To increase the spread and reuse of lessons learned (LLs), the purpose of this paper is to develop a standardised information structure to facilitate concise capture of the critical elements needed to engage secondary learners and help them apply lessons to their contexts. Design/methodology/approach – Three workshops with industry practitioners, an analysis of over 60 actual lessons from private and public sector organisations and seven practitioner interviews provided evidence of actual practice. Design science was used to develop a repeatable/consistent information model of LL content/structure. Workshop analysis and theory provided the coding template. Situation theory and normative analysis were used to define the knowledge and rule logic to standardise fields. Findings – Comparing evidence from practice against theoretical prescriptions in the literature highlighted important enhancements to the standard LL model. These were a consistent/concise rule and context structure, appropriate emotional language, reuse and control criteria to ensure lessons were transferrable and reusable in new situations. Research limitations/implications – Findings are based on a limited sample. Long-term benefits of standardisation and use need further research. A larger sample/longitudinal usage study is planned. Practical implications – The implementation of the LL structure was well-received in one government user site and other industry user sites are pending. Practitioners validated the design logic for improving capture and reuse of lessons to render themeasily translatable to a new learner’s context. Originality/value – The new LL structure is uniquely grounded in user needs, developed from existing best practice and is an original application of normative and situation theory to provide consistent rule logic for context/content structure

    S-COL: A Copernican turn for the development of flexibly reusable collaboration scripts

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    Collaboration scripts are usually implemented as parts of a particular collaborative-learning platform. Therefore, scripts of demonstrated effectiveness are hardly used with learning platforms at other sites, and replication studies are rare. The approach of a platform-independent description language for scripts that allows for easy implementation of the same script on different platforms has not succeeded yet in making the transfer of scripts feasible. We present an alternative solution that treats the problem as a special case of providing support on top of diverse Web pages: In this case, the challenge is to trigger support based on the recognition of a Web page as belonging to a specific type of functionally equivalent pages such as the search query form or the results page of a search engine. The solution suggested has been implemented by means of a tool called S-COL (Scripting for Collaborative Online Learning) and allows for the sustainable development of scripts and scaffolds that can be used with a broad variety of content and platforms. The tool’s functions are described. In order to demonstrate the feasibility and ease of script reuse with S-COL, we describe the flexible re-implementation of a collaboration script for argumentation in S-COL and its adaptation to different learning platforms. To demonstrate that a collaboration script implemented in S-COL can actually foster learning, an empirical study about the effects of a specific script for collaborative online search on learning activities is presented. The further potentials and the limitations of the S-COL approach are discussed

    Ontology-based patterns for the integration of business processes and enterprise application architectures

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    Increasingly, enterprises are using Service-Oriented Architecture (SOA) as an approach to Enterprise Application Integration (EAI). SOA has the potential to bridge the gap between business and technology and to improve the reuse of existing applications and the interoperability with new ones. In addition to service architecture descriptions, architecture abstractions like patterns and styles capture design knowledge and allow the reuse of successfully applied designs, thus improving the quality of software. Knowledge gained from integration projects can be captured to build a repository of semantically enriched, experience-based solutions. Business patterns identify the interaction and structure between users, business processes, and data. Specific integration and composition patterns at a more technical level address enterprise application integration and capture reliable architecture solutions. We use an ontology-based approach to capture architecture and process patterns. Ontology techniques for pattern definition, extension and composition are developed and their applicability in business process-driven application integration is demonstrated

    Reuse patterns in adaptation languages : creating a meta-level for the LAG adaptation language

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    A growing body of research targets authoring of content and adaptation strategies for adaptive systems. The driving force behind it is semantics-based reuse: the same strategy can be used for various domains, and vice versa. Whilst using an adaptation language (LAG e.g.) to express reusable adaptation strategies, we noticed, however, that: a) the created strategies have common patterns that, themselves, could be reused; b) templates based on these patterns could reduce the designers' work; c) there is a strong preference towards XML-based processing and interfacing. This has leaded us to define a new meta-language for LAG, extracting common design patterns. This paper provides more insight into some of the limitations of Adaptation Languages like LAG, as well as describes our meta-language, and shows how introducing the meta-level can overcome some redundancy issues
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