A framework to analyze argumentative knowledge construction in computer-supported collaborative learning

Computer-supported collaborative learning (CSCL) is often based on written argumentative discourse of learners, who discuss their perspectives on a problem with the goal to acquire knowledge. Lately, CSCL research focuses on the facilitation of specific processes of argumentative knowledge construction, e.g., with computer-supported collaboration scripts. In order to refine process-oriented instructional support, such as scripts, we need to measure the influence of scripts on specific processes of argumentative knowledge construction. In this article, we propose a multi-dimensional approach to analyze argumentative knowledge construction in CSCL from sampling and segmentation of the discourse corpora to the analysis of four process dimensions (participation, epistemic, argumentative, social mode)

A video life-world approach to consultation practice: The relevance of a socio-phenomenological approach

This article discusses the [development and] use of a video life-world schema to explore alternative orientations to the shared health consultation. It is anticipated that this schema can be used by practitioners and consumers alike to understand the dynamics of videoed health consultations, the role of the participants within it and the potential to consciously alter the outcome by altering behaviour during the process of interaction. The study examines health consultation participation and develops an interpretative method of analysis that includes image elicitation (via videos), phenomenology (to identify the components of the analytic framework), narrative (to depict the stories of interactions) and a reflexive mode (to develop shared meaning through a conceptual framework for analysis). The analytic framework is derived from a life-world conception of human mutual shared interaction which is presented here as a novel approach to understanding patient-centred care. The video materials used in this study were derived from consultations in a Walk-in Centre (WiC) in East London. The conceptual framework produced through the process of video analysis is comprised of different combinations of movement, knowledge and emotional conversations that are used to classify objective or engaged WiC health care interactions. The videoed interactions organise along an active or passive, facilitative or directive typical situation continuum illustrating different kinds of textual approaches to practice that are in tension or harmony. The schema demonstrates how practitioners and consumers interact to produce these outcomes and indicates the potential for both consumers and practitioners to be educated to develop practice dynamics that support patient-centred care and impact on health outcomes

Towards a scope management of non-functional requirements in requirements engineering

Getting business stakeholders’ goals formulated clearly and project scope defined realistically increases the chance of success for any application development process. As a consequence, stakeholders at early project stages acquire as much as possible knowledge about the requirements, their risk estimates and their prioritization. Current industrial practice suggests that in most software projects this scope assessment is performed on the user’s functional requirements (FRs), while the non-functional requirements (NFRs) remain, by and large, ignored. However, the increasing software complexity and competition in the software industry has highlighted the need to consider NFRs as an integral part of software modeling and development. This paper contributes towards harmonizing the need to build the functional behavior of a system with the need to model the associated NFRs while maintaining a scope management for NFRs. The paper presents a systematic and precisely defined model towards an early integration of NFRs within the requirements engineering (RE). Early experiences with the model indicate its ability to facilitate the process of acquiring the knowledge on the priority and risk of NFRs

Knowledge modeling for software design

This paper develops a modeling framework for systems engineering that encompasses systems modeling, task modeling, and knowledge modeling, and allows knowledge engineering and software engineering to be seen as part of a unified developmental process. This framework is used to evaluate what novel contributions the 'knowledge engineering' paradigm has made and how these impact software engineering

Where do uncertainties reside within environmental risk assessments? Expert opinion on uncertainty distributions for pesticide risks to surface water organisms

A reliable characterisation of uncertainties can aid uncertainty identification during environmental risk assessments (ERAs). However, typologies can be implemented inconsistently, causing uncertainties to go unidentified. We present an approach based on nine structured elicitations, in which subject-matter experts, for pesticide risks to surface water organisms, validate and assess three dimensions of uncertainty: its level (the severity of uncertainty, ranging from determinism to ignorance); nature (whether the uncertainty is epistemic or aleatory); and location (the data source or area in which the uncertainty arises). Risk characterisation contains the highest median levels of uncertainty, associated with estimating, aggregating and evaluating the magnitude of risks. Regarding the locations in which uncertainty is manifest, data uncertainty is dominant in problem formulation, exposure assessment and effects assessment. The comprehensive description of uncertainty described will enable risk analysts to prioritise the required phases, groups of tasks, or individual tasks within a risk analysis according to the highest levels of uncertainty, the potential for uncertainty to be reduced or quantified, or the types of location-based uncertainty, thus aiding uncertainty prioritisation during environmental risk assessments. In turn, it is expected to inform investment in uncertainty reduction or targeted risk management action