Mixed methods research involves using both quantitative and qualitative research methods in a single study to provide a more complete understanding of the research problem. It started in the 1950s and has become widely used in educational research. There are different types of mixed methods designs including exploratory, explanatory, and triangulation designs that vary in their sequencing and prioritization of quantitative and qualitative data collection and analysis. Key considerations in mixed methods research include sampling strategies, research designs, and ensuring ethical treatment of participants.
This document provides an overview of mixed-methods research. It defines mixed-methods research as involving both quantitative and qualitative research methods in a single study to provide a more complete understanding than either method alone. It discusses the history and examples of mixed-methods research in education. Key aspects covered include different research designs like exploratory, explanatory, and triangulation; sampling strategies; steps in conducting mixed-methods research; and evaluating and ensuring ethics in mixed-methods studies. The document aims to explain what mixed-methods research entails at a high-level.
This document discusses research design and provides an overview of different types of research designs including quantitative, qualitative, and mixed methods designs. It defines key aspects of research design such as causality, validity, and bias. It also explains different categories of designs like experimental, quasi-experimental, descriptive, correlational, and qualitative designs as well as features of each. The document provides examples of specific designs like randomized control trials, time series, case studies and tips for choosing an appropriate research design.
This document provides an overview of mixed methods research. It defines mixed methods research as combining quantitative and qualitative research techniques in a single study. The document discusses the purposes of mixed methods research, compares qualitative and quantitative research, and examines the philosophical basis of pragmatism in mixed methods. It also outlines various mixed methods research designs, procedures for planning a mixed methods study, and strengths and weaknesses of the approach.
The document discusses different approaches to mixing qualitative and quantitative research methods, specifically focusing on the concept of triangulation. It outlines some of the debates around combining methods, including arguments that the paradigms are incompatible and integrating them risks ignoring underlying assumptions. The document then describes various types of triangulation and mixed methods strategies, including how and when quantitative and qualitative data and findings can be integrated. Examples of sequential, concurrent and explanatory mixed methods designs are provided.
A mixed methods approach involves collecting, analyzing, and integrating both quantitative and qualitative data within a single study or series of studies. While some argue it results in invalid studies, others believe quantitative and qualitative approaches can be compatible if used to complement each other's strengths. Mixed methods research can provide stronger evidence through triangulation, answer a broader range of questions, and increase generalizability, but it is also more complex, resource-intensive, and time-consuming than single method designs. There are different ways to sequence the quantitative and qualitative elements, such as explanatory or exploratory designs.
Quantitative, qualitive and mixed research designsAras Bozkurt
This document provides an overview of quantitative method design, specifically experimental design. It discusses key concepts in experimental design including random assignment, control over extraneous variables, manipulation of treatment conditions, outcome measures, and threats to validity. It also describes different types of experimental designs including between-group designs like true experiments, quasi-experiments, and factorial designs as well as within-group designs like time series experiments, repeated measures experiments, and single subject experiments. The document provides examples and explanations of how to implement these different experimental designs.
Mixed methods research involves using both quantitative and qualitative research methods in a single study to provide a more complete understanding of the research problem. It started in the 1950s and has become widely used in educational research. There are different types of mixed methods designs including exploratory, explanatory, and triangulation designs that vary in their sequencing and prioritization of quantitative and qualitative data collection and analysis. Key considerations in mixed methods research include sampling strategies, research designs, and ensuring ethical treatment of participants.
This document provides an overview of mixed-methods research. It defines mixed-methods research as involving both quantitative and qualitative research methods in a single study to provide a more complete understanding than either method alone. It discusses the history and examples of mixed-methods research in education. Key aspects covered include different research designs like exploratory, explanatory, and triangulation; sampling strategies; steps in conducting mixed-methods research; and evaluating and ensuring ethics in mixed-methods studies. The document aims to explain what mixed-methods research entails at a high-level.
This document discusses research design and provides an overview of different types of research designs including quantitative, qualitative, and mixed methods designs. It defines key aspects of research design such as causality, validity, and bias. It also explains different categories of designs like experimental, quasi-experimental, descriptive, correlational, and qualitative designs as well as features of each. The document provides examples of specific designs like randomized control trials, time series, case studies and tips for choosing an appropriate research design.
This document provides an overview of mixed methods research. It defines mixed methods research as combining quantitative and qualitative research techniques in a single study. The document discusses the purposes of mixed methods research, compares qualitative and quantitative research, and examines the philosophical basis of pragmatism in mixed methods. It also outlines various mixed methods research designs, procedures for planning a mixed methods study, and strengths and weaknesses of the approach.
The document discusses different approaches to mixing qualitative and quantitative research methods, specifically focusing on the concept of triangulation. It outlines some of the debates around combining methods, including arguments that the paradigms are incompatible and integrating them risks ignoring underlying assumptions. The document then describes various types of triangulation and mixed methods strategies, including how and when quantitative and qualitative data and findings can be integrated. Examples of sequential, concurrent and explanatory mixed methods designs are provided.
A mixed methods approach involves collecting, analyzing, and integrating both quantitative and qualitative data within a single study or series of studies. While some argue it results in invalid studies, others believe quantitative and qualitative approaches can be compatible if used to complement each other's strengths. Mixed methods research can provide stronger evidence through triangulation, answer a broader range of questions, and increase generalizability, but it is also more complex, resource-intensive, and time-consuming than single method designs. There are different ways to sequence the quantitative and qualitative elements, such as explanatory or exploratory designs.
Quantitative, qualitive and mixed research designsAras Bozkurt
This document provides an overview of quantitative method design, specifically experimental design. It discusses key concepts in experimental design including random assignment, control over extraneous variables, manipulation of treatment conditions, outcome measures, and threats to validity. It also describes different types of experimental designs including between-group designs like true experiments, quasi-experiments, and factorial designs as well as within-group designs like time series experiments, repeated measures experiments, and single subject experiments. The document provides examples and explanations of how to implement these different experimental designs.
This document discusses mixed method research design. It defines mixed methods research as collecting and analyzing both quantitative and qualitative data within a single or series of studies. It outlines the basic characteristics of mixed methods research, including collecting both types of data, considering priority and sequence, and matching analysis to design. The document then discusses various aspects of mixed methods research such as when to conduct it, reasons for using it, types of designs, steps to carry out a mixed methods study, and criteria for evaluating it. It also notes some strengths as being able to describe findings easily but some weaknesses as taking more time.
Qualitative research uses words rather than numbers to understand phenomena through interviews, observations and documents. It is useful when little is known about a condition or environment. Some key characteristics of qualitative research include studying things in their natural settings, using the researcher as the instrument of data collection, collecting multiple sources of data, and analyzing data inductively to identify themes. Mixed-methods research combines qualitative and quantitative approaches by collecting and analyzing both types of data sequentially or concurrently.
Mixed method research involves using both quantitative and qualitative methods in a single study. There are four basic designs: convergent parallel design, explanatory sequential design, exploratory sequential design, and embedded design. The convergent design collects both types of data simultaneously and merges the results, while the sequential designs implement the methods in phases to build on each other. The embedded design incorporates one method within a study using the other method predominantly. Key decisions in choosing a design are the level of interaction between methods, priority, timing, and mixing strategies.
Definition
A procedure used to collect both qualitative and quantitative data.
This is done due to the fact that it is believed that both types of studies will provided a clearer understanding of what is being studied.
“It consists of merging ,integrating ,linking ,or embedding the two “strands””(Ceswell,2012).
This document discusses mixed methods research. It provides an overview of why researchers use mixed methods, addressing criticisms of combining qualitative and quantitative research. It also challenges the distinction between these paradigms by analyzing seven common assumptions. Considerations for mixed methods designs include the timing, weighting, and mixing of qualitative and quantitative data. Key mixed methods designs are triangulation, embedded, explanatory, and exploratory approaches. Practical issues like research politics, costs, skills, and team organization are also covered.
This document discusses a study on the use of mixed methods research in applied linguistics. It aims to identify the types of research designs and sampling designs used in mixed methods studies in AL. The study analyzed 205 articles from 7 journals over 14 years. It found that concurrent triangulation design was most common, used in 66% of studies to provide supplementary data through multiple sources or methods. Common sampling designs included identical, multilevel, and parallel samples. The conclusion discusses how mixed methods research can integrate qualitative and quantitative findings to develop meta-inferences, though few studies in the sample explicitly did this.
Mixed method research involves collecting and analyzing both qualitative and quantitative data. It is guided by a pragmatic worldview that focuses on practical solutions to research problems. Mixed method designs provide an overview of both qualitative and quantitative approaches to gain a broader and more complete understanding than a single method can provide. They allow for both objective measurement and subjective understanding to uncover processes and outcomes.
Research Methodology (The Transformative Design)Kamal Baharom
This document discusses transformative mixed methods procedures, which aim to address social issues and promote change for marginalized groups. It defines transformative designs as using a basic mixed methods design (convergent, explanatory, exploratory, or embedded) within a theoretical framework oriented towards issues like inequality. Transformative designs are value-based and ideological. The sequential transformative strategy uses two phases guided by a theoretical lens addressing problems like discrimination. The goal is to facilitate reform through understanding issues faced by underrepresented communities.
This document provides an overview of mixed methods research, including definitions, characteristics, strengths/weaknesses of quantitative and qualitative methods, reasons for using mixed methods, and major mixed methods designs. It discusses the convergent parallel design, which collects and analyzes quantitative and qualitative data concurrently and equally. It also covers the explanatory sequential design, in which qualitative data is used to help explain initial quantitative results. Examples of published studies using each design are provided.
Mixed methods research combines quantitative and qualitative data collection and analysis in a single study. It allows researchers to gain a deeper understanding of a phenomenon by using the strengths of both quantitative and qualitative research. There are three main types of mixed methods designs: qualitative-quantitative, quantitative-qualitative, and concurrent quantitative-qualitative. Mixed methods research provides an opportunity for quantitative and qualitative data to inform and enhance each other.
Mixed methods research combines both qualitative and quantitative research approaches and methods. There are four main types of mixed methods designs: triangulation design, embedded design, explanatory design, and exploratory design. The triangulation design concurrently collects and analyzes quantitative and qualitative data to compare or validate results. The embedded design has one data type play a supportive role to the other. The explanatory design uses qualitative data to explain initial quantitative results, while the exploratory design uses qualitative data to develop instruments for a subsequent quantitative phase. Mixed methods research provides a more comprehensive understanding of research problems than a single method alone.
This document discusses a lecture on mixed research methods. The lecture aims to address the relationship between sociological imagination and investigation, prospects for integrating qualitative and quantitative methods, challenges of using mixed methods approaches, and how mixed methods can help understand research topics. The lecture objectives are to distinguish research designs, identify when methods complement each other, and explain mixed methods designs. Key points covered include triangulation, action research, parallel versus sequential mixed methods, and reconciling different paradigms.
This document discusses quantitative and qualitative research approaches. It outlines the key objectives, features and limitations of each. Quantitative research aims to measure predetermined variables and examine relationships statistically, using methods like surveys and experiments. It focuses on objectivity and generalizability. Qualitative research explores phenomena through flexible, interactive methods like interviews to understand experiences. It provides contextual understanding but findings may not generalize. The document advocates sometimes combining both approaches to overcome individual limitations.
Mixed methods research involves collecting and analyzing both quantitative and qualitative data within a single study or series of studies. This approach allows researchers to understand research problems more fully than using either quantitative or qualitative methods alone. Researchers can collect quantitative data through methods like questionnaires, surveys, and attendance records, and qualitative data through interviews, observations, and document analysis. The mixed methods design considers the priority and sequence of quantitative and qualitative data collection and analysis. Reasons for using a mixed methods approach include explaining and interpreting results, exploring phenomena, and developing and testing new instruments.
Qualitative research involves gathering narrative data through observation and interviews to understand human behavior. It is subjective. Quantitative research determines relationships between variables through objective surveys and statistical analysis. Mixed methods research combines qualitative and quantitative approaches, using both words and figures to analyze collected information and reach conclusions.
A mixed research design uses both quantitative and qualitative data and methods to conduct research. It has two main types - mixed method, which uses quantitative data for one stage and qualitative for another, and mixed model, which uses both quantitative and qualitative data in one or two stages. The advantages include providing context behind numbers, allowing triangulation, and compensating for weaknesses. However, mixed research also requires more resources, expertise, time, and can be more difficult to interpret.
No, analyzing the same qualitative data both qualitatively and quantitatively would not constitute a mixed methods study on its own. A mixed methods approach requires the intentional collection and analysis of both qualitative and quantitative data.
A presentation about the added value of combining qualitative and quantitative methods. It begins with a brief discussion of qualitative research and how it is distinct from yet shares basic principles with quantitative research, followed by a discussion of four important ways mixed methods -- integrating qualitative and quantitative -- adds value to our research efforts, and then a discussion of mixed methods research -- what it is, typologies, alternatives to typologies, and the use of diagrams.
This document provides an overview of mixed methods research. It discusses the three main types of research designs: qualitative, quantitative, and mixed methods. It explains the differences between qualitative and quantitative research in terms of purpose, group studied, variables, data collection/analysis, and results. The document also discusses pragmatism as the philosophy behind mixed methods research and reasons for combining methods. It outlines various ways that qualitative and quantitative methods can be mixed, such as through timing, weighting, and mixing of data. The document concludes by describing six main mixed methods designs and recommending further readings on the topic.
Why use mixed methods? Webinar with Dr. SchuttSAGE Publishing
The document summarizes a mixed methods study on housing outcomes for individuals with chronic mental illness. It compares outcomes for those living in group homes versus independent apartments. Data was collected through surveys, clinician assessments, ethnographic observation, and neuropsychological testing. Key findings include: (1) group housing was associated with better housing retention and cognition compared to independent living, especially for those with substance abuse issues or rejection of needed support; (2) consumer preferences did not predict optimal placement as clinicians could better assess need for support; (3) positive social processes in group homes helped some regain stability while negative experiences interfered with outcomes. The study demonstrates how mixed methods can provide a more authentic and nuanced understanding of social phenomena than a
This document discusses key aspects of qualitative case study research. It outlines that case studies allow for an in-depth exploration of a phenomenon within its real-life context. The document discusses different approaches to case studies by researchers like Yin, Stake and Creswell. It also addresses important considerations for case study research like purposefully defining the case, collecting multiple sources of data, ensuring validity and ethics, and producing engaging written reports for academic audiences.
This document discusses mixed method research design. It defines mixed methods research as collecting and analyzing both quantitative and qualitative data within a single or series of studies. It outlines the basic characteristics of mixed methods research, including collecting both types of data, considering priority and sequence, and matching analysis to design. The document then discusses various aspects of mixed methods research such as when to conduct it, reasons for using it, types of designs, steps to carry out a mixed methods study, and criteria for evaluating it. It also notes some strengths as being able to describe findings easily but some weaknesses as taking more time.
Qualitative research uses words rather than numbers to understand phenomena through interviews, observations and documents. It is useful when little is known about a condition or environment. Some key characteristics of qualitative research include studying things in their natural settings, using the researcher as the instrument of data collection, collecting multiple sources of data, and analyzing data inductively to identify themes. Mixed-methods research combines qualitative and quantitative approaches by collecting and analyzing both types of data sequentially or concurrently.
Mixed method research involves using both quantitative and qualitative methods in a single study. There are four basic designs: convergent parallel design, explanatory sequential design, exploratory sequential design, and embedded design. The convergent design collects both types of data simultaneously and merges the results, while the sequential designs implement the methods in phases to build on each other. The embedded design incorporates one method within a study using the other method predominantly. Key decisions in choosing a design are the level of interaction between methods, priority, timing, and mixing strategies.
Definition
A procedure used to collect both qualitative and quantitative data.
This is done due to the fact that it is believed that both types of studies will provided a clearer understanding of what is being studied.
“It consists of merging ,integrating ,linking ,or embedding the two “strands””(Ceswell,2012).
This document discusses mixed methods research. It provides an overview of why researchers use mixed methods, addressing criticisms of combining qualitative and quantitative research. It also challenges the distinction between these paradigms by analyzing seven common assumptions. Considerations for mixed methods designs include the timing, weighting, and mixing of qualitative and quantitative data. Key mixed methods designs are triangulation, embedded, explanatory, and exploratory approaches. Practical issues like research politics, costs, skills, and team organization are also covered.
This document discusses a study on the use of mixed methods research in applied linguistics. It aims to identify the types of research designs and sampling designs used in mixed methods studies in AL. The study analyzed 205 articles from 7 journals over 14 years. It found that concurrent triangulation design was most common, used in 66% of studies to provide supplementary data through multiple sources or methods. Common sampling designs included identical, multilevel, and parallel samples. The conclusion discusses how mixed methods research can integrate qualitative and quantitative findings to develop meta-inferences, though few studies in the sample explicitly did this.
Mixed method research involves collecting and analyzing both qualitative and quantitative data. It is guided by a pragmatic worldview that focuses on practical solutions to research problems. Mixed method designs provide an overview of both qualitative and quantitative approaches to gain a broader and more complete understanding than a single method can provide. They allow for both objective measurement and subjective understanding to uncover processes and outcomes.
Research Methodology (The Transformative Design)Kamal Baharom
This document discusses transformative mixed methods procedures, which aim to address social issues and promote change for marginalized groups. It defines transformative designs as using a basic mixed methods design (convergent, explanatory, exploratory, or embedded) within a theoretical framework oriented towards issues like inequality. Transformative designs are value-based and ideological. The sequential transformative strategy uses two phases guided by a theoretical lens addressing problems like discrimination. The goal is to facilitate reform through understanding issues faced by underrepresented communities.
This document provides an overview of mixed methods research, including definitions, characteristics, strengths/weaknesses of quantitative and qualitative methods, reasons for using mixed methods, and major mixed methods designs. It discusses the convergent parallel design, which collects and analyzes quantitative and qualitative data concurrently and equally. It also covers the explanatory sequential design, in which qualitative data is used to help explain initial quantitative results. Examples of published studies using each design are provided.
Mixed methods research combines quantitative and qualitative data collection and analysis in a single study. It allows researchers to gain a deeper understanding of a phenomenon by using the strengths of both quantitative and qualitative research. There are three main types of mixed methods designs: qualitative-quantitative, quantitative-qualitative, and concurrent quantitative-qualitative. Mixed methods research provides an opportunity for quantitative and qualitative data to inform and enhance each other.
Mixed methods research combines both qualitative and quantitative research approaches and methods. There are four main types of mixed methods designs: triangulation design, embedded design, explanatory design, and exploratory design. The triangulation design concurrently collects and analyzes quantitative and qualitative data to compare or validate results. The embedded design has one data type play a supportive role to the other. The explanatory design uses qualitative data to explain initial quantitative results, while the exploratory design uses qualitative data to develop instruments for a subsequent quantitative phase. Mixed methods research provides a more comprehensive understanding of research problems than a single method alone.
This document discusses a lecture on mixed research methods. The lecture aims to address the relationship between sociological imagination and investigation, prospects for integrating qualitative and quantitative methods, challenges of using mixed methods approaches, and how mixed methods can help understand research topics. The lecture objectives are to distinguish research designs, identify when methods complement each other, and explain mixed methods designs. Key points covered include triangulation, action research, parallel versus sequential mixed methods, and reconciling different paradigms.
This document discusses quantitative and qualitative research approaches. It outlines the key objectives, features and limitations of each. Quantitative research aims to measure predetermined variables and examine relationships statistically, using methods like surveys and experiments. It focuses on objectivity and generalizability. Qualitative research explores phenomena through flexible, interactive methods like interviews to understand experiences. It provides contextual understanding but findings may not generalize. The document advocates sometimes combining both approaches to overcome individual limitations.
Mixed methods research involves collecting and analyzing both quantitative and qualitative data within a single study or series of studies. This approach allows researchers to understand research problems more fully than using either quantitative or qualitative methods alone. Researchers can collect quantitative data through methods like questionnaires, surveys, and attendance records, and qualitative data through interviews, observations, and document analysis. The mixed methods design considers the priority and sequence of quantitative and qualitative data collection and analysis. Reasons for using a mixed methods approach include explaining and interpreting results, exploring phenomena, and developing and testing new instruments.
Qualitative research involves gathering narrative data through observation and interviews to understand human behavior. It is subjective. Quantitative research determines relationships between variables through objective surveys and statistical analysis. Mixed methods research combines qualitative and quantitative approaches, using both words and figures to analyze collected information and reach conclusions.
A mixed research design uses both quantitative and qualitative data and methods to conduct research. It has two main types - mixed method, which uses quantitative data for one stage and qualitative for another, and mixed model, which uses both quantitative and qualitative data in one or two stages. The advantages include providing context behind numbers, allowing triangulation, and compensating for weaknesses. However, mixed research also requires more resources, expertise, time, and can be more difficult to interpret.
No, analyzing the same qualitative data both qualitatively and quantitatively would not constitute a mixed methods study on its own. A mixed methods approach requires the intentional collection and analysis of both qualitative and quantitative data.
A presentation about the added value of combining qualitative and quantitative methods. It begins with a brief discussion of qualitative research and how it is distinct from yet shares basic principles with quantitative research, followed by a discussion of four important ways mixed methods -- integrating qualitative and quantitative -- adds value to our research efforts, and then a discussion of mixed methods research -- what it is, typologies, alternatives to typologies, and the use of diagrams.
This document provides an overview of mixed methods research. It discusses the three main types of research designs: qualitative, quantitative, and mixed methods. It explains the differences between qualitative and quantitative research in terms of purpose, group studied, variables, data collection/analysis, and results. The document also discusses pragmatism as the philosophy behind mixed methods research and reasons for combining methods. It outlines various ways that qualitative and quantitative methods can be mixed, such as through timing, weighting, and mixing of data. The document concludes by describing six main mixed methods designs and recommending further readings on the topic.
Why use mixed methods? Webinar with Dr. SchuttSAGE Publishing
The document summarizes a mixed methods study on housing outcomes for individuals with chronic mental illness. It compares outcomes for those living in group homes versus independent apartments. Data was collected through surveys, clinician assessments, ethnographic observation, and neuropsychological testing. Key findings include: (1) group housing was associated with better housing retention and cognition compared to independent living, especially for those with substance abuse issues or rejection of needed support; (2) consumer preferences did not predict optimal placement as clinicians could better assess need for support; (3) positive social processes in group homes helped some regain stability while negative experiences interfered with outcomes. The study demonstrates how mixed methods can provide a more authentic and nuanced understanding of social phenomena than a
This document discusses key aspects of qualitative case study research. It outlines that case studies allow for an in-depth exploration of a phenomenon within its real-life context. The document discusses different approaches to case studies by researchers like Yin, Stake and Creswell. It also addresses important considerations for case study research like purposefully defining the case, collecting multiple sources of data, ensuring validity and ethics, and producing engaging written reports for academic audiences.
Presentation for the HEA-funded workshop ‘Teaching Research Methods in Business and Management’.
Drawing on a mixture of practice and evidence, this one-day event provided an opportunity for those interested in the teaching of research methods in Business and Management – including qualitative, quantitative and mixed methods – to share experiences, insights, and good practice, and to discuss challenges and explore potential solutions.
This presentation forms part of a blog post reporting on the event which can be accessed via: http://bit.ly/1fcTwna
For further details of HEA Social Sciences work relating to teaching research methods in the Social Sciences please see http://bit.ly/15go0mh
Quantitative and qualitative data, questionnaires, interviewsleannacatherina
Quantitative data involves numbers and statistics while qualitative data involves words and opinions. Quantitative research gathers numerical data through things like questionnaires with closed-ended questions that can be statistically analyzed. Qualitative research gathers non-numerical information through open-ended questions and focuses on experiences and feelings, with analysis through summarization. The type of data collection and analysis used depends on the aims and purpose of the research.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms.
Computer Games in Education - Unlocking LearningOllie Bray
This document discusses the potential benefits of using computer games in education. It argues that games can promote learning through play, challenge, progression and reward in a personalized and competitive environment. The document also suggests that games can serve as "contextual hubs" to engage both students and teachers across different subject areas. Several case studies show improvements in math test scores and student motivation when using educational games. The document concludes by discussing how games can be designed and incorporated into teaching to foster literacy, problem solving and exploration of complex tasks while maintaining appropriate boundaries.
The document discusses how tutor blogs can help both students and teachers. It defines a blog as an online diary that allows easy publishing of text, graphics, and other media on the web. There are three types of educational blogs: class blogs, learner blogs, and tutor blogs. A tutor blog is useful for students as it houses all needed documents, serves as a communication tool for parents, and reminds students of deadlines. A tutor blog also helps teachers by requiring lesson planning, providing a record of course development, and promoting parental involvement. Creating and using a blog is easy.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms.
The document shares 11 lessons learned from Design Mind Salon events. Some of the key lessons include:
- Technology brings opportunities to connect with others worldwide but can also reduce uniqueness and underground culture.
- It is important to thoroughly prepare for projects and opportunities instead of hoping they will instantly succeed.
- Most creative work involves reusing 80% of past processes but making the beginnings and endings different for each project.
- Networking is crucial to the success of projects and creative work.
Changing the learning culture the impact of ict and digitalisationKai Pata
Tallinn University has taken a cross-cutting approach to teaching digital competences across subject-specific courses according to established digital competence frameworks. The School of Digital Technologies in particular facilitates this approach through tools like eDidaktikum, which supports tracking student competencies, and through open learning practices using blogs and social media. This work aims to change learning cultures by promoting collaboration, problem-based learning, and developing digital skills in real-world contexts.
The document discusses the Renaissance period in Europe, which began in Italy in the late 1300s and spread north over the next 200 years. The Renaissance focused on rediscovering classical knowledge in arts, literature, and architecture from ancient Greece and Rome. This movement was known as humanism and emphasized that individual humans are important and that life on Earth is significant. Key figures like Leonardo Da Vinci, Michelangelo, and Niccolo Machiavelli helped drive changes through their art, sculpture, architecture, and political writings that represented a shift away from traditional religion and the focus on the afterlife towards reason and emphasizing this life.
The document outlines a promotional campaign for the Architecture Library at the University of Oklahoma. The overall goal is to increase the library's visibility within the College of Architecture. Key objectives include creating a cohesive image for the library, increasing faculty involvement through bibliographic instruction sessions, and increasing understanding of the library's resources and special collections. The campaign will be evaluated through surveys and by monitoring various metrics like instruction sessions and material usage.
Great Plains Diesel Technologies InjectorDoug Mitchell
The document proposes developing a new type of fuel injector for diesel engines using terbium alloy. It summarizes the key issues with current injector technologies and regulations requiring cleaner combustion. A terbium alloy actuator could enable much faster and more precisely controlled injection, improving efficiency and reducing emissions. The proposal outlines milestones to design and test a prototype injector, develop the necessary terbium metallurgy and electronic control capabilities, and conduct engine tests. Success could open a large market and disrupt current injector technologies.
The document discusses strategies for building cross-platform mobile web applications using web technologies like HTML5, jQuery Mobile, and W3C widgets. It provides steps for creating a basic mobile web app with pages, headers, content, dialog boxes, lists, and themes. It also covers packaging the app as a widget and distributing it across various platforms.
This document provides guidance for clinicians on critically evaluating new medical studies and literature. It outlines key questions to consider in order to determine if a study's findings are likely to be true, important, and applicable to patients. Some areas to focus on include the study design, methods, results, conclusions, relevance and applicability of the population and time period studied. Considering these factors can help clinicians decide if new research is worth incorporating into their practice. The document emphasizes analyzing new findings in the context of existing knowledge.
The document provides an overview of qualitative and quantitative research methods. It defines qualitative research as exploring meanings, experiences and views to understand problems, while quantitative research tests relationships between variables and looks for patterns using statistical analysis. The document outlines different types of each approach, including phenomenology, ethnography, grounded theory, case studies and narrative for qualitative, and descriptive, correlational, quasi-experimental and experimental for quantitative. It highlights that qualitative research is subjective and focuses on why, while quantitative measures variables objectively and examines causal relationships.
This document discusses the importance and applications of quantitative research across various fields including anthropology, communication, sports medicine, medical education, behavioral sciences, education/psychology, and social sciences. It provides examples of quantitative research questions and methods used in these fields, including experiments, surveys, and correlational studies. The key aspects of experimental design are outlined, including the need for treatment and control groups, random assignment, pre-and post-testing, and how field experiments differ from lab experiments.
This document provides an overview of qualitative research methods. It discusses what qualitative research is, how to get the right sample, important aspects of qualitative research design such as research questions and comparisons. It also covers organizing a qualitative study, ethics, and designing for different qualitative methods like interviews, focus groups, and ethnography. Key considerations for each method are outlined.
This document discusses research in health and social care. It begins by defining research and explaining why it is needed to systematically build knowledge and test treatments. The document then outlines three basic characteristics of research in this field - that it must be logical, understandable, and useful. Next, it describes the overall research process and some common research philosophies and methodologies, including quantitative, qualitative and mixed methods approaches. Examples of different types of research projects are also provided.
Pengantar Metode Penelitian Kualitatif (Qualitative Research-An Introduction)NajMah Usman
Belajar apa itu metodologi Penelitian Kualitatif
Mengenal istilah-istilah Ontologi, Epistomologi, Methodologi, Metode dll
Happy Learning
Video:
https://www.youtube.com/watch?v=TaPugvOnCRQ
Qualitative And Quantitative Approach To Research QuestionsAshley Jean
The key attributes of Kraft's primary target market segment are millennial mothers. Millennial mothers represent the largest demographic cohort of new mothers. They are well-educated and family-oriented, seeking products that protect their family's financial well-being. As digital natives, millennial mothers are heavy social media users and influencers. They utilize multiple social networks daily to research products and parenting issues online.
This document provides an overview of qualitative research. It defines qualitative research as focusing on understanding human behavior and reasons for behavior through words rather than numbers. The document outlines different qualitative research approaches like phenomenology, grounded theory, ethnography, biographical studies, and case studies. It compares qualitative and quantitative research and discusses qualitative research purposes, methods of data collection including interviews, observations, documents, and focus groups. The document also covers qualitative sampling strategies, designing a qualitative study, and concerns of qualitative researchers.
Sampling for Quantities & Qualitative Research Abeer AlNajjar.docxanhlodge
Sampling for Quantities & Qualitative Research
Abeer AlNajjar
1
Population
Target group (universe in texts)
Census (to study every member of a population)
because measuring every member of a population usually is not feasible most researchers employ a Sample
Sample ( a subgroup of the population)
2
Communication researchers are interested in a population (also called a universe when applied to texts) of communicators, all the people who posses a particular characteristic, or, in the case of those who study texts, all the messages that share a characteristic of interest.
The population of interest to researchers (often called the target group) might be members of a business, communication majors at a university, all students at a university, all people living in a city, all eligible voters in a country.
Texts ( editorials published in a specific newspaper for a week, or a large universe such as every editorial published In every newspaper in the UAE, or even larger such as all persuasive messages).
The best way to generalize to a population is to study every member of a population (Census)
If every member is studied, we know, by definition, the population’s response at the point in time the study was done
Sample
The results from the sample are then generalized back to (used to represent) the population
Representative sample ( population validity)
Its similarity to its parent population
3
The results from the sample are then generalized back to (used to represent) the population). For such generalization to be valid (demonstrate population validity), the sample must be representative of its population. That is, it must accurately approximate the population.
Types of sampling
Random sampling (probability sampling)
Involves selecting a sample in such a way that each person in the population of interest has an equal chance of being included
Nonrandom sampling (nonprobability sampling)
Is what ever researchers do instead of using procedures that ensure that each member of a population has an equal chance of being selected
Sampling error
Is a number that express how much the characteristic of a sample probably differ from the characteristics of a population
5
There are 2 different types of sampling procedures, and differ in terms of how confident we are about the ability of the selected sample to represent the population from which it is drawn
Random sampling (probability sampling)
Involves selecting a sample in such a way that each person in the population of interest has an equal chance of being included
By giving everyone an equal chance , random sampling eliminates the danger of researchers biasing the selection process because of their own opinions or desires. By eliminating bias, random sampling provides the best assurance that the same characteristics of the population exist in the sample, and, therefore, that the sample represents the population.
Nonrandom sampling: it sometimes is .
This document provides an overview of research methods and designs. It discusses qualitative and quantitative research methods, with qualitative focusing on lived experiences and meanings and quantitative focusing on numerical data. It also discusses different types of study designs, including observational studies like cross-sectional and longitudinal, and experimental designs like clinical and community trials. Experimental research allows investigators to actively alter variables to evaluate relationships, while considering factors like the purpose of the study, strength of evidence desired, time and resources available, and ethics.
This document discusses different types of study designs used in medical research, including qualitative and quantitative methods. It covers observational studies like cohort and case-control studies, as well as experimental designs like randomized controlled trials. For each study type, it outlines their purpose, strengths, weaknesses and the types of research questions they can help answer. The goal is to help researchers choose the most appropriate design based on their specific research question and aims.
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Define and explain the significance of qualitative research methodology.
Qualitative research is defined as an interpretive naturalistic approach to the world. This means that qualitative researchers study things in their natural settings, attempting to make sense of or interpret phenomena in terms of the meanings people bring to them. The goal when applying qualitative research methods, the emphasis is put on the natural setting and the points of views of the research participants.
Discuss the different types of qualitative research design.
The qualitative research design is a formal, objective, systematic process for obtaining information about the world. A method used to describe, test relationships, and examine cause and effect relationships. To gain insight; explore the depth, richness, and complexity inherent in the phenomenon (Hansen,
Draborg
&
Kristensen
, 2011). There five different types of qualitative research design methods: ethnography, narrative, phenomenological, grounded theory, and case study. In ethnography, the researcher immerses themselves in the target participants and the environment to understand the goals, cultures, challenges, motivations, and themes. The narrative approach weaves together a sequence of events, usually from just one or two individuals to form a cohesive story. The researcher will conduct in-depth interviews, read documents, and look for themes. In a phenomenological study, you use a combination of methods, such as conducting interviews, reading documents, watching videos, or visiting places and events, to understand the meaning participants place on whatever’s being examined. The grounded theory looks to provide an explanation or theory behind the events. Finally, a case study involves a deep understanding through multiple types of data sources. Case studies can be explanatory, exploratory, or describing an event.
Identify and describe a minimum of two types of sampling techniques used in qualitative research.
Two different types of sampling techniques in qualitative research are Purposeful Sampling and Quota Sampling. The most common sampling strategy is Purposeful sampling. In this type of sampling, participants are selected or sought after based on pre-selected criteria based on the research question. For example, the study may be attempting to collect data from lymphoma patients in a city or county. The sample size may be predetermined or based on theoretical saturation, which is the point at which the newly collected no longer provides additional insights. Quota Sampling is a sampling technique whereby participant quotas are
prior to sampling. Typically, the researcher is attempting to gather data from a certain number of participants that meet certain characteristics that may include things such as age, sex, class, marital status, HIV status.
Describe methods for collecting ...
There are two main types of research: quantitative and qualitative. Quantitative research uses numerical data and statistical analysis to test hypotheses, while qualitative research uses descriptive data like words to develop theories and explore phenomena. Some key differences are that quantitative research has clearly defined variables, aims to test theories, uses large representative samples and statistical analysis, while qualitative research has a rough idea of variables, aims to develop theories, uses small samples and descriptive analysis like coding and narratives. There are also various research designs that differ based on whether they manipulate variables experimentally, use control groups, collect data prospectively or retrospectively, and in quantitative versus qualitative traditions.
This document provides an overview of different types of research methods. It discusses the meaning of research and outlines key steps in the research methodology process. It then describes the main types of research by purpose (basic/pure vs applied) and by method (quantitative vs qualitative). For quantitative research, it details four types: descriptive, correlational, causal-comparative, and experimental. For qualitative research, it outlines three main types: historical research, ethnographic research, and case study research.
1) The document summarizes key aspects of evaluating clinical trials, including types of trials and potential biases.
2) Clinical trials aim to test interventions in a controlled manner to determine safety and effectiveness. Randomized controlled trials (RCTs) are considered the gold standard for limiting biases.
3) However, biases can still influence trials in many ways, such as through selection of participants, administration of interventions, measurement of outcomes, and reporting/publication of results. It is important to critically appraise trials to assess risk of biases.
This document discusses regulations for human subject research and the IRB review process. It provides an overview of the ethical principles from the Belmont Report including respect for persons, beneficence, and justice. It also reviews key events in research ethics history. The document outlines the steps for developing a research study including distinguishing research from quality improvement. It discusses the MSU reliance process and IRB submission requirements such as elements of a consent form and HIPAA authorization documentation.
Doing sociological research involves applying the sociological perspective, being curious and asking questions objectively. There are different types of truths and ways of knowing, including scientific knowledge based on empirical evidence. Sociological research methods include positivist, interpretive, and critical sociology. Key aspects of research are concepts, variables, measurement, validity, reliability, and the relationship between variables. The scientific method involves collecting data through observation and experimentation. Common data collection methods are participant observation, interviews, surveys, existing sources, and experiments. It is important for sociological research to be objective and consider how factors like gender can influence results. Ethical standards help ensure research protects participants.
Qualitative Research Basic Introduction.pptxdhruvibagaria
Qualitative research aims to understand complex human and social processes through naturalistic and interpretive methods like interviews and focus groups. It explores issues in depth to understand psychological and social factors behind health and illness. Some key strengths are that it provides an in-depth and holistic understanding of issues from an insider's perspective, and is flexible and versatile. However, it typically requires more time, the findings cannot be generalized, and it is not intended to test hypotheses. Qualitative research uses emergent design and inductive analysis to understand issues that are new or not well understood.
This document discusses grounded theory and constructivist grounded theory as qualitative research methodologies. It explains that grounded theory is used to develop a theory grounded in data using an inductive approach. Constructivist grounded theory is presented as an extension of grounded theory that incorporates a constructivist perspective, where theories are co-constructed by the researcher and participants based on their shared experiences. The document provides an example of how constructivist grounded theory would be applied in a research study exploring how poor, working class clients' experiences of counseling may affect their perspectives and participation in individual counseling.
Arsenic and bladder cancer variation in estimatesDr Arindam Basu
This document discusses how estimates of cancer risk from arsenic exposure vary across populations due to differences in arsenic prevalence and levels of exposure. A meta-analysis of 19 studies from various countries found larger risk estimates for bladder cancer in populations with higher arsenic exposure, such as Bangladesh and Chile, compared to smaller effects in countries like the United States with lower exposure. Factors like smoking, diet, micronutrient intake and genetics may help explain discrepancies in risk estimates between populations. The document calls for more data on arsenic-caused cancers from highly exposed regions and a revision of acceptable arsenic levels in drinking water in light of new evidence showing risks even at low doses.
Development of polygenic risk scores for ambulatory care sensitive hospitalis...Dr Arindam Basu
This document outlines a proposal to estimate a polygenic risk score (PRS) for ambulatory sensitive conditions using genome-wide association studies (GWAS). It describes identifying common genetic variants associated with conditions like asthma through a meta-analysis of GWAS data. A PRS would then be constructed from these variants and applied to a target population to study its association with access to primary care and predict risk. Interpreting the PRS could provide insight into genetic and gene-environment effects on preventive healthcare access. The goal is to advance precision public health by identifying groups that could benefit most from targeted prevention interventions.
This document discusses using principles of software and data carpentry teaching models to teach epidemiology and data analysis skills to public health students. It describes using a module on the GRADE evidence appraisal method in a classroom setting. By applying techniques like live coding demonstrations and frequent feedback, the instructor was able to spend less time on one-on-one coaching while improving student satisfaction, grades, and understanding of evidence appraisal compared to previous years of regular classroom teaching.
Arsenic and bladder cancer variation in estimatesDr Arindam Basu
This document summarizes research on the health effects of exposure to inorganic arsenic through drinking water. Key points include:
- Exposure to inorganic arsenic through contaminated drinking water is widespread globally and poses risks of various cancers and skin lesions.
- Studies in West Bengal and Bangladesh found high prevalences of exposure through tubewells extracting groundwater with high arsenic levels.
- Research identified strong dose-response relationships between average and peak arsenic exposure levels in drinking water and risks of developing arsenic-related skin lesions.
- Subsequent studies examined how diet, nutrition, and micronutrient levels may influence susceptibility to arsenic-induced skin lesions, with some evidence found for roles of certain nutrients.
The document provides an overview of various research methods used in health sciences, including case series, cross-sectional surveys, case-control studies, cohort studies, and randomized controlled trials. It describes the key features and appropriate uses of each study design. Examples are given of studies conducted using each design. The document emphasizes that the appropriate study design depends on the research question, available resources, and desired results.
This document discusses mixed methods research and provides examples of issues that can be examined using mixed methods approaches. It addresses measuring the effectiveness of interprofessional training from different stakeholder perspectives. It also discusses strategies for measuring the effectiveness of colorectal cancer screening tests and telehealth physician training. Mixed methods are presented as a way to capture subjective qualitative perspectives alongside more objective quantitative data to obtain a fuller picture of "the truth."
The Ibis Effect: The Migrant Indian Health EffectDr Arindam Basu
This is a lecture on the status of health of migrant Indians and their public health services utilisation. We propose that this has to do with migration patterns and there is a need to systematically study in the context of health of Indian migrants across the Pacific
A Lecture on Sample Size and Statistical Inference for Health ResearchersDr Arindam Basu
This document discusses concepts related to statistical inference and sample size. It begins by introducing statistical inference, estimation, and hypothesis testing. It then covers concepts of probability, including independence, mutually exclusive events, and addition. It discusses random variables and different types of variables. The document also introduces the normal distribution and central limit theorem. It provides examples of how to calculate confidence intervals and discusses interpretations of confidence intervals. Finally, it outlines the steps of hypothesis testing.
The document discusses the Andersen Model of health care access. The model conceptualizes access as being determined by population characteristics (contextual and individual factors) that predispose people to use services or enable/impede their use. These include demographic, social, health beliefs, and enabling resources factors. The model also considers people's need (perceived and evaluated by professionals) and how this influences health behaviors and outcomes. It provides a framework for examining equitable access to care based on need rather than social characteristics or enabling resources.
This document discusses health culture and practices among Indian immigrants. It outlines that India has a large and diverse population facing major health challenges like infectious and cardiovascular diseases. When Indians immigrate to New Zealand, they initially display healthier profiles than locals due to selection biases, though health declines over time with reduced physical activity and diet changes. Barriers to healthcare include language issues and unfamiliarity with the New Zealand system. Developing cultural competence among providers, understanding traditional Indian practices, employing visual communication methods, and involving family can help improve healthcare for Indian immigrants.
This is my lecture presentation slide decks on albinism I gave at New Zealand Albinism Society Meeting on 29th November, 2014. It provides a basic introduction to albinism and is meant more as an invitation to discuss and invite questions and comments from a "lay" audience.
Priority setting in healthcare is necessary to allocate limited resources to maximize health benefits. It involves ranking diseases, health conditions, and interventions based on criteria like burden of disease, cost-effectiveness, equity, and existing delivery capacity. While controversial, priority setting can be made legitimate through transparent processes that consider community needs and engage stakeholders. Frameworks provide structures to conduct priority setting exercises and address ethical challenges through criteria like accountability, participation, and appeals mechanisms. Identifying who loses out in the system through analyses like benefit incidence assessments is also important.
This document discusses social determinants of health and access to healthcare. It presents models showing that access to care is determined by biological/need variables, demographic variables, socioeconomic status, place of living, and social variables. It also discusses the concepts of equity versus equitability of access, and how inequitable access can lead to unjust health outcomes and violations of people's right to health and access to care. The document analyzes components like access, socioeconomic status, and social justice as principles of social determinants of health.
This document provides an introduction to measuring population health using the Disability-Adjusted Life Year (DALY) as a single metric. It describes how DALYs are calculated by adding Years of Life Lost (YLL) due to premature mortality and Years Lived with Disability (YLD) for prevalent cases of disease and injury. The Global Burden of Disease (GBD) study, led by several organizations, estimates DALYs for 291 diseases, 1160 sequelae, and 220 health states in 187 countries to quantify population health gaps compared to an ideal standard. This allows comparison of disease burden over time, between locations, and for different diseases and risk factors.
This document provides information about health systems in India. It notes that India has a population of over 1.2 billion people spread across 35 states with wide disparities in wealth. The ratio of health professionals to population is low at around 2 per 1000 people. It discusses the evolution of health systems from ancient times focusing on Ayurveda and the establishment of modern allopathic medicine by the British. It highlights some pioneering Indian medical innovations and researchers. It also notes the fragmented private healthcare sector in India which spends a lower percentage of GDP on healthcare compared to other countries. It argues that New Zealand and India have a longstanding friendship and opportunities to partner in areas like public health.
Using Visual Methods and Social Network Analysis to Explore Relationships in ...Dr Arindam Basu
The purpose of this presentation is to lay out thoughts ad generate discussions and ideas about using inter-disciplinary principles of visual research methods applied to images stored in social media, as well as social network analysis on groups, individuals, images, and documents. Then blend the two to identify hard to find problems or build agenda for investigation and actually investigate significant environmental and occupational health issues. In addition to laying out thoughts, some indicative images and instances of social network analyses have been provided in this description.
Presentation on UDHC for UC Tertiary Engagement Summit (Draft Slides)Dr Arindam Basu
Set of slide decks for the UDHC related presentation at the University of Canterbury Tertiary Engagement Summit where the purpose of discussion is to share ideas how students and trainees in tertiary education can engage with the community to bring about real world change. I chose to focus on UDHC and the excellent work the project has brought about.
Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) CurriculumMJDuyan
(𝐓𝐋𝐄 𝟏𝟎𝟎) (𝐋𝐞𝐬𝐬𝐨𝐧 𝟏)-𝐏𝐫𝐞𝐥𝐢𝐦𝐬
𝐃𝐢𝐬𝐜𝐮𝐬𝐬 𝐭𝐡𝐞 𝐄𝐏𝐏 𝐂𝐮𝐫𝐫𝐢𝐜𝐮𝐥𝐮𝐦 𝐢𝐧 𝐭𝐡𝐞 𝐏𝐡𝐢𝐥𝐢𝐩𝐩𝐢𝐧𝐞𝐬:
- Understand the goals and objectives of the Edukasyong Pantahanan at Pangkabuhayan (EPP) curriculum, recognizing its importance in fostering practical life skills and values among students. Students will also be able to identify the key components and subjects covered, such as agriculture, home economics, industrial arts, and information and communication technology.
𝐄𝐱𝐩𝐥𝐚𝐢𝐧 𝐭𝐡𝐞 𝐍𝐚𝐭𝐮𝐫𝐞 𝐚𝐧𝐝 𝐒𝐜𝐨𝐩𝐞 𝐨𝐟 𝐚𝐧 𝐄𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫:
-Define entrepreneurship, distinguishing it from general business activities by emphasizing its focus on innovation, risk-taking, and value creation. Students will describe the characteristics and traits of successful entrepreneurs, including their roles and responsibilities, and discuss the broader economic and social impacts of entrepreneurial activities on both local and global scales.
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
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How to Setup Warehouse & Location in Odoo 17 InventoryCeline George
In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
2. Three Scenarios
• Inter-professional Training
• Colorectal Cancer Screening
• Teaching of Telehealth to Physicians
How Can Qualitative alone, Quantitative Research alone, or a combination meet
the needs of research questions pursued?
3. Interprofessional Education
• Different Professions, Same Trainees
• Different Professionals Train the Same People
• How does one learn about effectiveness of the
education process?
• Whose Perspective? (Trainers? Trainees?
External Stakeholders?)
• How Do We Measure Outputs?
• Can Everything Be Measured?
4. How Does One Measure the Effectiveness of Inter-professional Training?
5. Screening For Colorectal Cancer
• Colorectal Cancer is a
leading cause of cancer and
kill people
• If this cancer can be
detected when it the
tumour is very small and
localized, then it can be
safely removed
• That detection is done
using a stool test called
guaiac test.
• What’s the best strategy?
Source: http://www.medicinenet.com/colon_cancer/article.htm
6. What Does One Measure?
The Patient (Suffering, Convenience, How Easy)
Ministry of Health (Payer)
How Economical?
How Many False Cases
for reasons of logistics
How Many People should
be Screened To Identify
One case?
The Physician (Provider)
How best will the
screening test perform?
Sensitivity? Specificity?
7. What is the Effectiveness of Telehealth
Training for Physicians?
Trainees (Physicians)
Stakeholders (MoH)
Trainers (Teaching Physicians)
8. The Truth Out There (Descriptive
Data, Relationships)
The Participants Who
Contribute to the Truth
Seeking Process
* Patients
•Members. Public
• Preconceptions
• Life Story ...
The Investigator Who
Investigates “The Truth”
• Belief
• Previous Ideas
• “Need” for “Positive” Findings
9. The Truth Out There (Descriptive
Data, Relationships)
1. Rule Out Chance
2. Control for
Confounding
3. Eliminate Bias
4. Test for
Causality (where
Needed)
Quantitative Research
Dissociates the Investigator
from His “Biases”
The Participants Who
Contribute to the Truth
Seeking Process
* Patients
•Members. Public
• Preconceptions
• Life Story ...
The Investigator Who
Investigates “The Truth”
• Belief
• Previous Ideas
• “Need” for “Positive” Findings
10. The Truth Out There (Descriptive
Data, Relationships)
The Participants Who
Contribute to the Truth
Seeking Process
* Patients
•Members. Public
• Preconceptions
• Life Story ...
Qualitative
Research:
integration
between the
Researcher, Resear
chee , Researched
The Investigator Who
Investigates “The Truth”
• Belief
• Previous Ideas
• “Need” for “Positive” Findings
11. The Truth Out There (Descriptive
Data, Relationships)
Quantitative Research
The Participants Who
Contribute to the Truth
Seeking Process
* Patients
•Members. Public
• Preconceptions
• Life Story ...
Qualitative Research
The Investigator Who
Investigates “The Truth”
• Belief
• Previous Ideas
• “Need” for “Positive” Findings
12. The Reality (Interprofessional Education
Improves Student Outcomes )
Survey of trainees
Items on
questionnaires
Tallying Numbers
Quantitative Research
The Participants Who
Contribute to the Truth
Seeking Process
* Students narrate their
experiences
Qualitative Research
The Investigator Who
Investigates “The Truth”
• Belief
• Previous Ideas
• “Need” for “Positive” Findings
13. The Reality (Telehealth Education
through distance improves care
process)
Pass/Fail Statistics
Student
Performance
Carbon Saving
Quantitative Research
Trainees tell their
Stories on how well
They did and what they
felt
Qualitative Research
The Investigator Who
Investigates “The Truth”
• Belief
• Previous Ideas
• “Need” for “Positive” Findings
14. The Reality (Telehealth Education
through distance improves care
process)
Pass/Fail Statistics
Student
Performance
Carbon Saving
Quantitative Research
Trainees tell their
Stories on how well
They did and what they
felt
Qualitative Research
The Investigator Who
Investigates “The Truth”
• Belief
• Previous Ideas
• “Need” for “Positive” Findings
These Diverse Views of the World Are Reconciled in Mixed Methods Research
22. Conclusion
•
•
•
•
•
•
•
Qualitative + Quantitative = Mixed Methods
Qualitative: subjective, perspective dependent
Quantitative: objective, neutral view of truth
Mixed: Captures “Truth” both ways
Sequential or Concurrent
Full or Partial
Dominant or Non-dominant
23. References
Borkan, J. M. (2004). Mixed Methods Studies : A Foundation, 4–6.
doi:10.1370/afm.111.wo
Onwuegbuzie, A. J., & Turner, L. A. (2007). Toward a Definition of Mixed Methods
Research. Journal of Mixed Methods Research, 1(2), 112–133.
doi:10.1177/1558689806298224
Leech, N. L., & Onwuegbuzie, A. J. (2007). A typology of mixed methods research designs.
Quality & Quantity, 43(2), 265–275. doi:10.1007/s11135-007-9105-3
Lingard, L., Albert, M., & Levinson, W. (2008). Grounded theory , mixed methods , and
action research, 337(August), 459–461. doi:10.1136/bmj.39602.690162.47
O’Cathain, A., Murphy, E., & Nicholl, J. (2007). Why, and how, mixed methods research is
undertaken in health services research in England: a mixed methods study. BMC health
services research, 7, 85. doi:10.1186/1472-6963-7-85
Sale, J. E. M., & Brazil, K. (2002). Revisiting the Quantitative-Qualitative Debate :
Implications for Mixed-Methods Research, 43–53.