Gather Data In Order Research Articles

Understanding patient experience in the emergency room using multiple methods

This paper discusses a multi-method approach of gathering data in order to understand how variables within a high stress environment, such as a hospital emergency room, can affect user experience. The challenges facing emergency departments in Alberta can be summarized as a lack of understanding of what happens in an emergency room, inadequate communication between staff and the public, and challenges with the physical design of these departments. Through this study we were able to understand the patient experience and to identify gaps in service, gain insights into issues that are negatively impacting patients and suggests artefacts and processes in order to better deliver patient care.

The walk-and-talk methodology – researching place and people

The article focuses on walk-and-talk interviews, which are yet a little-used research method in Latvia. The term is used in the social sciences and humanities and is an appropriate method for gathering data in order to determine the relationship of an individual or a social group with a specific place. The method in a pilot project was used to listen to life experiences in Tūja, a village along the Baltic coast in Latvia. The study focused on social change in Tūja and the influence of the economic and political changes of the 1990s on the living conditions and lifestyle of the local inhabitants. The pilot project was conducted by the researchers from the Institute of Philosophy and Sociology of University of Latvia.

Fuzzy FMEA Application Combined with Fuzzy Cognitive Maps to Manage the Risks of a Software Project

Abstract The failure rate of an Information Technologies (IT) software project is pretty high because of their uncertain and risky structure. Managing well this kind of projects becomes important. Failure Mode and Effect Analysis (FMEA) is an extensive method that is used for identifying the importance level of risks in a project by using risk priority numbers (RPN). This method is based on experts’ experience and cognitive skills at gathering data in order to make risk assessment. This situation causes inaccurate conclusions in the final risk ranking. Fuzzy logic is widely integrated into FMEA to handle these inaccuracies and inconsistencies in the literature while making assessment and calling Fuzzy FMEA method that we proposed. In this study, we explored another uncovered weaknesses of the proposed method. FMEA and Fuzzy FMEA do not consider the relationships among the risks of a project. To overcome this disadvantage, we proposed to integrate the idea of cognitive maps into these two methods (FMEA w/FCMs and Fuzzy FMEA w/FCMs). Finally, we got a comprehensive risk assessment methodology by considering the relationships among the risks under ambiguous circumstances.

An overview of realist evaluation for simulation-based education

This article describes the key features of realist (realistic) evaluation and illustrates their application using, as an example, a simulation-based course for final year medical students. The use of simulation-based education (SBE) is increasing and so too is the evidence supporting its value as a powerful technique which can lead to substantial educational benefits. Accompanying these changes is a call for research into its use to be more theory-driven and to investigate both ‘Did it work?’ and as importantly ‘Why did it work (or not)?’ An evaluation methodology that is capable of answering both questions is realist evaluation.Realist evaluation is an emerging methodology that is suited to evaluating complex interventions such as SBE. The realist philosophy positions itself between positivist and constructivist paradigms and seeks to answer the question ‘What works for whom, in what circumstances and why?’ In seeking to answer this question, realist evaluation sets out to identify three fundamental components of an intervention, namely context, mechanism and outcome. Educational programmes work (successful outcomes) when theory-driven interventions (mechanisms) are applied to groups under appropriate conditions (context). Realist research uses a mixed methods (qualitative and quantitative) approach to gathering data in order to test the proposed context-mechanism-outcome (CMO) configurations of the intervention under investigation.Realist evaluation offers a valuable methodology for researchers investigating interventions utilising simulation-based education. By investigating and understanding the context, mechanisms and outcomes of SBE interventions, realist evaluation can provide the deeper level of understanding being called for.

Fuzzy FMEA Application Combined with Fuzzy Cognitive Maps to Manage the Risks of a Software Project

The failure rate of an Information Technologies (IT) software project is pretty high because of their uncertain and risky structure. Managing well this kind of projects becomes important. Failure Mode and Effect Analysis (FMEA) is an extensive method that is used for identifying the importance level of risks in a project by using risk priority numbers (RPN). This method is based on experts’ experience and cognitive skills at gathering data in order to make risk assessment. This situation causes inaccurate conclusions in the final risk ranking. Fuzzy logic is widely integrated into FMEA to handle these inaccuracies and inconsistencies in the literature while making assessment and calling Fuzzy FMEA method that we proposed. In this study, we explored another uncovered weaknesses of the proposed method. FMEA and Fuzzy FMEA do not consider the relationships among the risks of a project. To overcome this disadvantage, we proposed to integrate the idea of cognitive maps into these two methods (FMEA w/FCMs and Fuzzy FMEA w/FCMs). Finally, we got a comprehensive risk assessment methodology by considering the relationships among the risks under ambiguous circumstances.

Fuzzy FMEA Application Combined with Fuzzy Cognitive Maps to Manage the Risks of a Software Project

The failure rate of an Information Technologies (IT) software project is pretty high because of their uncertain and risky structure. Managing well this kind of projects becomes important. Failure Mode and Effect Analysis (FMEA) is an extensive method that is used for identifying the importance level of risks in a project by using risk priority numbers (RPN). This method is based on experts’ experience and cognitive skills at gathering data in order to make risk assessment. This situation causes inaccurate conclusions in the final risk ranking. Fuzzy logic is widely integrated into FMEA to handle these inaccuracies and inconsistencies in the literature while making assessment and calling Fuzzy FMEA method that we proposed. In this study, we explored another uncovered weaknesses of the proposed method. FMEA and Fuzzy FMEA do not consider the relationships among the risks of a project. To overcome this disadvantage, we proposed to integrate the idea of cognitive maps into these two methods (FMEA w/FCMs and Fuzzy FMEA w/FCMs). Finally, we got a comprehensive risk assessment methodology by considering the relationships among the risks under ambiguous circumstances.

The Relationship between Emotional Intelligence and Perceived Social Support

Abstract The studty aims at examining and understanding the relation between Emotional Intelligence and Perceived social support in a sample of 525 students of the University of Prishtina. Great number of studies in the field of Emotional Intelligence, have shown that that this new construct of Intelligence, (EI), operates within the social context, therefore the examination of socially relevant variables is crucial for personal and social context. It has been hypothesised that Emotional Intelligence and it’s dimensions correlate positively with the Perceived Social Support and the relation between these two variables is a great predictor of positive interactions, interpersonal relationships and is very relevant for the educational context as well. The study is based on the ability and competency based model of the Emotional Intelligence construct. Emotional Intelligence Scale (Schutte, N. S., Malouff, J. M., Hall, L. E., Haggerty, D. J., Cooper, J. T., Golden, C. J., & Dornheim, L. (1998) and the Multidimensional Scale of Perceived Social Support (Zimet, Dahlem, Zimet & Farely, 1998) were administered to gather data in order to test the hypotheisis. The preliminary findings support theoretical and empirical perspective, and appear to be promising by emphasizing the Emotional Intelligence consutruct as an added value for the educational context, in specific for youth interactions and their wellbeing.

Exploring children’s perspectives: Multiple ways of seeing and knowing the child

This article focuses on human development in the early years, and the challenges for teachers and researchers in seeking to explore young children’s perspectives. The current interest in listening to children’s voices sits within competing developmental discourses about infants, toddlers and young children, which emphasise both their capability and confidence as well as their immaturity, especially with regard to oral language. Their “voice” can be heard and seen differently by teachers, researchers and families, who filter it according to their own perspectives and their image of the child. Drawing on a range of contemporary New Zealand studies, we discuss some key issues such as whether children need speech to have a voice? And in what ways can we gather children’s perspectives in research and education? To explore children’s perspectives and hear their voices requires skilled and flexible researchers and teachers, who watch and listen carefully whilst being mindful of their filtering/interpretive gazes. This takes time and patience and requires multiple ways of gathering data in order that the child is heard authentically.

Erratum to: Civil society research and Marcellus Shale natural gas development: results of a survey of volunteer water monitoring organizations

This paper reports the results of a survey of civil society organizations that are monitoring surface water for impacts of Marcellus Shale development in Pennsylvania and New York. We argue that enlisting volunteers to conduct independent monitoring is one way that civil society organizations are addressing knowledge gaps and the “undone science” of surface water quality impacts related to gas extraction. The survey, part of an ongoing 2-year study, examines these organizations' objectives, monitoring practices, and financial, technical, and institutional support networks. We find that water monitoring organizations typically operate in networks of two main types: centralized networks, with one main “hub” organization connecting many chapter groups or teams, and decentralized networks, consisting primarily of independent watershed associations and capacity building organizations. We also find that there are two main orientations among water monitoring groups. Roughly, half are advocacy-oriented, gathering data in order to improve regulation, support litigation, and change industry behavior. We characterize the other half as knowledge-oriented, gathering data in order to protect natural resources through education and awareness. Our analysis finds that many monitoring programs function relatively independently of government and university oversight supported instead by a number of capacity building organizations in the field. We argue that this reflects neoliberal tendencies toward increased public responsibility for environmental science. We also find that new participants in the field of water monitoring, mainly large environmental NGOs integral to the operations of centralized networks, are shifting monitoring programs towards more advocacy-oriented objectives. We believe this shift may impact how civil society water monitoring efforts interact with regulatory bodies, such as by taking normative positions and using volunteer-collected data to advocate for policy change.

Assessment of Knowledge Acquired in an Organic Chemistry Course

A model for the evaluation of students' knowledge using a multiple-choice type exercise was presented and used as an instrument for gathering data in order to make general assessment of students' strengths and weaknesses in organic chemistry after having taken the course. The results obtained allowed us to clarify and research more thoroughly those areas that need to be reinforced in order to improve the quality of the teaching/learning process.This data will be applied in the pre-planning stage in subsequent semesters of the same course.