Research methods and methodologies for studying organisational learning

The purpose of this paper is to compare and evaluate the main research methods and methodologies for studying organisational learning (OL), and propose a framework for their selection. It presents a comprehensive review of literature on OL, learning organisation (LO) and research methods and reports evidence on recent developments in research methods for studying OL. The paper highlighted on the purists and pragmatists’ views of research methodologies as basis of the study. The results revealed that the research methods and methodologies for studying OL do not reflect on the differing views of the purists and pragmatists’ debate but rather conform to the convergence ideologies of the two camps. Particularly, the outcomes augment the use of triangulation and suggest that the choice of method(s) should be consistent with research aims and epistemological philosophy of OL. Consequently, the study recommends OL Research Methods Framework as a useful guide for selecting a suitable approach in the area. The paper recommends ethnography for future research consideration

An evaluation of Simventure

This paper discusses the value of providing a simulated experience of how organisations work enabling skills and knowledge from disparate subject areas to be synthesised and assimilated in solving complex business proble

An empirical learning-based validation procedure for simulation workflow

Simulation workflow is a top-level model for the design and control of simulation process. It connects multiple simulation components with time and interaction restrictions to form a complete simulation system. Before the construction and evaluation of the component models, the validation of upper-layer simulation workflow is of the most importance in a simulation system. However, the methods especially for validating simulation workflow is very limit. Many of the existing validation techniques are domain-dependent with cumbersome questionnaire design and expert scoring. Therefore, this paper present an empirical learning-based validation procedure to implement a semi-automated evaluation for simulation workflow. First, representative features of general simulation workflow and their relations with validation indices are proposed. The calculation process of workflow credibility based on Analytic Hierarchy Process (AHP) is then introduced. In order to make full use of the historical data and implement more efficient validation, four learning algorithms, including back propagation neural network (BPNN), extreme learning machine (ELM), evolving new-neuron (eNFN) and fast incremental gaussian mixture model (FIGMN), are introduced for constructing the empirical relation between the workflow credibility and its features. A case study on a landing-process simulation workflow is established to test the feasibility of the proposed procedure. The experimental results also provide some useful overview of the state-of-the-art learning algorithms on the credibility evaluation of simulation models

Enhancing Care Transitions for Older People through Interprofessional Simulation: A Mixed Method Evaluation

Introduction: The educational needs of the health and social care workforce for delivering effective integrated care are important. This paper reports on the development, pilot and evaluation of an interprofessional simulation course, which aimed to support integrated care models for care transitions for older people from hospital to home. Theory and methods: The course development was informed by a literature review and a scoping exercise with the health and social care workforce. The course ran six times and was attended by health and social care professionals from hospital and community (n=49). The evaluation aimed to elicit staff perceptions of their learning about care transfers of older people and to explore application of learning into practice and perceived outcomes. The study used a sequential mixed method design with questionnaires completed pre (n=44) and post (n=47) course and interviews (n=9) 2-5 months later. Results:Participants evaluated interprofessional simulation as a successful strategy. Post-course, participants identified learning points and at the interviews, similar themes with examples of application in practice were: Understanding individual needs and empathy; Communicating with patients and families; Interprofessional working; Working across settings to achieve effective care transitions. Conclusions and discussion:An interprofessional simulation course successfully brought together health and social care professionals across settings to develop integrated care skills and improve care transitions for older people with complex needs from hospital to home

CBR and MBR techniques: review for an application in the emergencies domain

The purpose of this document is to provide an in-depth analysis of current reasoning engine practice and the integration strategies of Case Based Reasoning and Model Based Reasoning that will be used in the design and development of the RIMSAT system. RIMSAT (Remote Intelligent Management Support and Training) is a European Commission funded project designed to: a.. Provide an innovative, 'intelligent', knowledge based solution aimed at improving the quality of critical decisions b.. Enhance the competencies and responsiveness of individuals and organisations involved in highly complex, safety critical incidents - irrespective of their location. In other words, RIMSAT aims to design and implement a decision support system that using Case Base Reasoning as well as Model Base Reasoning technology is applied in the management of emergency situations. This document is part of a deliverable for RIMSAT project, and although it has been done in close contact with the requirements of the project, it provides an overview wide enough for providing a state of the art in integration strategies between CBR and MBR technologies.Postprint (published version

Assessing mobile mixed reality affordances as a comparative visualization pedagogy for design communication

Spatial visualisation skills and interpretation are critical in the design professions but are difficult for novice designers. There is growing evidence that mixed reality visualisation improves learner outcomes, but often these studies are focused on a single media representation and not on a comparison between media and the underpinning learning outcomes. Results from recent studies highlight the use of comparative visualisation pedagogy in design through learner reflective blogs and pilot studies with experts, but these studies are limited by expense and designs familiar to the learner. With increasing interest in mobile pedagogy, more assessment is required in understanding learner interpretation of comparative mobile mixed reality pedagogy. The aim of this study is to do this by evaluating insights from a first-year architectural design classroom through studying the impact and use of a range of mobile comparative visualisation technologies. Using a design-based research methodology and a usability framework for accessing comparative visualisation, this paper will study the complexities of spatial design in the built environment. Outcomes from the study highlight the positives of the approach but also the improvements required in the delivery of the visualisations to improve on the visibility and visual errors caused by the lack of mobile processing

Mining Heterogeneous Multivariate Time-Series for Learning Meaningful Patterns: Application to Home Health Telecare

For the last years, time-series mining has become a challenging issue for researchers. An important application lies in most monitoring purposes, which require analyzing large sets of time-series for learning usual patterns. Any deviation from this learned profile is then considered as an unexpected situation. Moreover, complex applications may involve the temporal study of several heterogeneous parameters. In that paper, we propose a method for mining heterogeneous multivariate time-series for learning meaningful patterns. The proposed approach allows for mixed time-series -- containing both pattern and non-pattern data -- such as for imprecise matches, outliers, stretching and global translating of patterns instances in time. We present the early results of our approach in the context of monitoring the health status of a person at home. The purpose is to build a behavioral profile of a person by analyzing the time variations of several quantitative or qualitative parameters recorded through a provision of sensors installed in the home