Book•
Qualitative research & evaluation methods
01 Jan 2002-Iss: 1
TL;DR: In this paper, conceptual issues and themes on qualitative research and evaluaton methods including: qualitative data, triangulated inquiry, qualitative inquiry, constructivism, constructionism, complexity (chaos) theory, qualitative designs and data collection, fieldwork strategies, interviewing, tape-recording, ethical issues, analysis, interpretation and reporting, observations vs. perceived impacts and utilisation-focused evaluation reporting.
Abstract: This book explains clearly conceptual issues and themes on qualitative research and evaluaton methods including: qualitative data, triangulated inquiry, qualitative inquiry, constructivism, constructionism, Complexity (chaos) theory, qualitative designs and data collection, fieldwork strategies, interviewing, tape-recording, ethical issues, analysis, interpretation and reporting, observations vs. perceived impacts and utilisation-focused evaluation reporting.
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TL;DR: In this article, the authors analyze the generation, development and use of AM technologies in Germany from a dynamic innovation system perspective and suggest opportunities for systemic interventions to further innovations in AM and in the German animal production sector and in other countries.
52 citations
Cites methods from "Qualitative research & evaluation m..."
...The sample for the first interviews was generated based on the literature review and then further amplified by the snowball method (Patton, 2002)....
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TL;DR: In this paper, the authors investigated perceptions toward REDD+ based on interviews with 60 Indonesia-based key-informants influencing REDD+, and highlighted the underlying causes of these problems and the implication for REDD+.
Abstract: Reducing Emissions from Deforestation and Forest Degradation (REDD+) represents the strategic linkage between a climate change regime and international forest policy. But the future success of REDD+ will depend, in part, on how policy makers perceive the challenges and opportunities it offers stakeholders. This study investigated perceptions toward REDD+ based on interviews with 60 Indonesia-based key-informants influencing REDD+ policy. Interviewees cited “governance reform,” “network building,” “conservation,” and “economic development” as opportunities. The perceived challenges included “REDD+’s complexity,” “uncertainty of REDD+ decisions,” “REDD+ is a tool of developed countries,” and problems inherent within existing forest governance related to coordination, lack of capacity, ambiguity of legal system, and corruption. Adopting a clientelist perspective we draw attention to the underlying causes of these problems and the implication for REDD+. Despite highlighting significant challenges, most inform...
52 citations
Cites background or methods from "Qualitative research & evaluation m..."
...A purposive sampling method was employed to identify key individuals influencing REDD+ policy making or implementation based on their level of engagement, expertise and standing (Patton, 2002)....
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...It takes its inspiration from Brown, Smit, Sonwa, Somorin, and Nkem’s (2011) study of perceptions of opportunities and challenges in implementing the REDD+ (Reducing Emissions from Deforestation and Forest Degradation) mechanism in the Congo Basin of Africa....
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TL;DR: A parental sense of ambiguity of school officials’ roles and procedures related to school reporting and intervention is highlighted, which has implications in the development and use of school-wide bullying protocols and parental advocacy.
Abstract: Current research offers a limited understanding of parental experiences when reporting bullying to school officials. This research examines the experiences of middle-school parents as they took steps to protect their bullied youth. The qualitative tradition of interpretive phenomenology was used to provide in-depth analysis of the phenomena. A criterion-based, purposeful sample of 11 parents was interviewed face-to-face with subsequent phone call follow-ups. Interviews were taped, transcribed, and coded. MAX qda software was used for data coding. In analyzing the interviews, paradigm cases, themes, and patterns were identified. Three parent stages were found: discovering, reporting, and living with the aftermath. In the discovery stage, parents reported using advice-giving in hopes of protecting their youth. As parents noticed negative psychosocial symptoms in their youth escalate, they shifted their focus to reporting the bullying to school officials. All but one parent experienced ongoing resistance fro...
52 citations
Cites background from "Qualitative research & evaluation m..."
...The process of inquiry demands the researcher listen closely, question, reflect, recheck, and interpret important dimensions that emerge from the narratives of participants’ experiences (Creswell, 2003; Patton, 2002)....
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...The interpretive phenomenological approach sought to understand participants’ experiences in a new way, questioning the narrative, holding open the possibilities, and letting phenomena emerge (Diekelmann & Ironside, 2005; Patton, 2002)....
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...Therefore, we sought to interpret parents’ experiences of reporting and to stay close to the experience itself (Patton, 2002; Smythe, Ironside, Sims, Swenson, & Spence, 2008)....
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TL;DR: In this paper, a case study of law enforcement rangers' perceptions of occupational stress in a protected area in Uganda has been conducted using an ethnographic case study approach based on interviews and participant observation.
Abstract: In many countries law enforcement rangers are frontline guardians responsible for the management, monitoring and protection of protected areas and wildlife species. To date, little research has been conducted on law enforcement rangers and their perceptions of stress. This exploratory study contributes to both the criminological and conservation literature by exploring an important human dimension often neglected in conservation science research: law enforcement rangers. Similar to previous research on police occupational stress, it is expected that law enforcement rangers experience stressors unique to their profession. Utilizing an ethnographic case study approach based on interviews and participant observation, this research examines ranger perceptions of occupational stress in a protected area in Uganda. Findings indicate that law enforcement rangers are exposed to various occupational/task-related, external, internal, and occupation-related personal strains. Results from the study have implications in understanding, reducing and preventing occupational stress in rangers, as well as in capacity building for park management.
52 citations
TL;DR: With minimal help from data scientists, health care researchers can use Auto-ML to quickly build high-quality models, and this will boost wider use of machine learning in health care and improve patient outcomes.
Abstract: Background: To improve health outcomes and cut health care costs, we often need to conduct prediction/classification using large clinical datasets (aka, clinical big data), for example, to identify high-risk patients for preventive interventions. Machine learning has been proposed as a key technology for doing this. Machine learning has won most data science competitions and could support many clinical activities, yet only 15% of hospitals use it for even limited purposes. Despite familiarity with data, health care researchers often lack machine learning expertise to directly use clinical big data, creating a hurdle in realizing value from their data. Health care researchers can work with data scientists with deep machine learning knowledge, but it takes time and effort for both parties to communicate effectively. Facing a shortage in the United States of data scientists and hiring competition from companies with deep pockets, health care systems have difficulty recruiting data scientists. Building and generalizing a machine learning model often requires hundreds to thousands of manual iterations by data scientists to select the following: (1) hyper-parameter values and complex algorithms that greatly affect model accuracy and (2) operators and periods for temporally aggregating clinical attributes (eg, whether a patient’s weight kept rising in the past year). This process becomes infeasible with limited budgets. Objective: This study’s goal is to enable health care researchers to directly use clinical big data, make machine learning feasible with limited budgets and data scientist resources, and realize value from data. Methods: This study will allow us to achieve the following: (1) finish developing the new software, Automated Machine Learning (Auto-ML), to automate model selection for machine learning with clinical big data and validate Auto-ML on seven benchmark modeling problems of clinical importance; (2) apply Auto-ML and novel methodology to two new modeling problems crucial for care management allocation and pilot one model with care managers; and (3) perform simulations to estimate the impact of adopting Auto-ML on US patient outcomes. Results: We are currently writing Auto-ML’s design document. We intend to finish our study by around the year 2022. Conclusions: Auto-ML will generalize to various clinical prediction/classification problems. With minimal help from data scientists, health care researchers can use Auto-ML to quickly build high-quality models. This will boost wider use of machine learning in health care and improve patient outcomes. [JMIR Res Protoc 2017;6(8):e175]
52 citations