This document provides an overview of research design and methodology. It discusses key components of methodology including selecting the overall research method, data collection approaches, and sampling strategy. Both quantitative and qualitative research methods are described, as well as mixed methods. Common data collection techniques are explained for structured, semi-structured, and mixed methods approaches. Considerations for selecting an appropriate research method based on objectives, resources, and other factors are also outlined. The document aims to help researchers design a methodology that will feasibly achieve their intended research scope and objectives.
Here are some data collection methods that can be used if you don't have direct access to the population of interest:
- Remote key informant interviews: Conduct interviews over the phone or online platforms with people who have knowledge about the population/area but are not directly part of it, such as local leaders, aid workers, journalists etc.
- Secondary data review: Analyze existing data from government, UN agencies, NGO reports, media articles, academic studies etc. to understand the situation without primary data collection.
- Remote household surveys: Use phone surveys to interview households. This requires having a sample frame of phone numbers for the population.
- Online/mobile surveys: Distribute surveys virtually through websites/apps if the
This document provides an overview of research design methodology, including different types of research methods, data collection approaches, and frequently asked questions. It discusses quantitative, qualitative, and mixed methods approaches. Specifically, it describes structured surveys, semi-structured discussions, observations, and sequential or concurrent mixed methods. Considerations for selecting a methodology include the research objectives, available time and resources, and required scope and quality of findings. The document aims to help researchers design the overall strategy for data collection and analysis.
This document provides an overview of research design methodology, including different types of research methods, data collection approaches, and frequently asked questions. It discusses quantitative, qualitative, and mixed methods approaches. Specifically, it describes structured surveys, semi-structured discussions, observations, and sequential or concurrent mixed methods. Considerations for selecting a methodology include the research objectives, available time and resources, and required scope and quality of findings. The document aims to help researchers design a methodology that effectively addresses their research questions.
This document provides an overview of different approaches to data sampling, collection, and testing. It discusses various units of measurement that can be used and describes structured, semi-structured, and mixed methods for data collection. Structured approaches use close-ended tools like surveys to collect quantifiable data, while semi-structured use open-ended questions in interviews and discussions to gather qualitative insights. Mixed methods combine approaches. The document provides examples of when each approach would be most applicable and addresses common questions about differences between methods.
This document provides an overview of quantitative and qualitative research methods. It distinguishes between quantitative and qualitative research, describing how they differ in terms of data collection methods, sampling strategies, and analysis approaches. Quantitative research uses structured and closed-ended questioning, probability sampling, and statistical analysis to generalize to populations. Qualitative research employs semi-structured interviews, non-probability sampling, and inductive analysis to understand perspectives without generalization. Mixed methods combines quantitative and qualitative data collection and analysis to provide a comprehensive understanding of research problems.
Quantitative and Qualitative Approaches.pdfssuser504dda
This document provides an overview of quantitative and qualitative research approaches. It defines quantitative research as deductive, using numeric data from large samples to test hypotheses and analyze relationships between variables objectively. Qualitative research is defined as inductive, relying on words from smaller samples to understand participant experiences subjectively and identify themes in the data. The key differences between the two approaches are described in terms of identifying research problems, reviewing literature, specifying research purposes and questions, collecting and analyzing data, and reporting results. The document also discusses research design and types of quantitative, qualitative, and mixed methods designs.
This document discusses research methods and designs. It defines quantitative and qualitative research methods. Quantitative methods use numerical data and statistics, while qualitative methods focus on patterns and human experiences. The document also outlines different types of research designs, including descriptive, experimental, quasi-experimental, correlational, narrative, phenomenological, grounded theory, historical, case study and ethnographic. It provides examples of how to create a research method and an example research method related to constraint identification and classification.
Qualitative research is a scientific method of investigation that seeks to understand and explain social phenomena through analysis of people's experiences. It involves collecting data in natural settings through methods like interviews, observations and focus groups. The data collected consists of words and images rather than numbers. Three common qualitative methods are participant observation, in-depth interviews, and focus groups. Qualitative research is characterized by its inductive approach, focus on meanings and experiences, flexible design, and interpretation of findings. It aims to gain an in-depth understanding of issues rather than generalizing to a population.
Here are some data collection methods that can be used if you don't have direct access to the population of interest:
- Remote key informant interviews: Conduct interviews over the phone or online platforms with people who have knowledge about the population/area but are not directly part of it, such as local leaders, aid workers, journalists etc.
- Secondary data review: Analyze existing data from government, UN agencies, NGO reports, media articles, academic studies etc. to understand the situation without primary data collection.
- Remote household surveys: Use phone surveys to interview households. This requires having a sample frame of phone numbers for the population.
- Online/mobile surveys: Distribute surveys virtually through websites/apps if the
This document provides an overview of research design methodology, including different types of research methods, data collection approaches, and frequently asked questions. It discusses quantitative, qualitative, and mixed methods approaches. Specifically, it describes structured surveys, semi-structured discussions, observations, and sequential or concurrent mixed methods. Considerations for selecting a methodology include the research objectives, available time and resources, and required scope and quality of findings. The document aims to help researchers design the overall strategy for data collection and analysis.
This document provides an overview of research design methodology, including different types of research methods, data collection approaches, and frequently asked questions. It discusses quantitative, qualitative, and mixed methods approaches. Specifically, it describes structured surveys, semi-structured discussions, observations, and sequential or concurrent mixed methods. Considerations for selecting a methodology include the research objectives, available time and resources, and required scope and quality of findings. The document aims to help researchers design a methodology that effectively addresses their research questions.
This document provides an overview of different approaches to data sampling, collection, and testing. It discusses various units of measurement that can be used and describes structured, semi-structured, and mixed methods for data collection. Structured approaches use close-ended tools like surveys to collect quantifiable data, while semi-structured use open-ended questions in interviews and discussions to gather qualitative insights. Mixed methods combine approaches. The document provides examples of when each approach would be most applicable and addresses common questions about differences between methods.
This document provides an overview of quantitative and qualitative research methods. It distinguishes between quantitative and qualitative research, describing how they differ in terms of data collection methods, sampling strategies, and analysis approaches. Quantitative research uses structured and closed-ended questioning, probability sampling, and statistical analysis to generalize to populations. Qualitative research employs semi-structured interviews, non-probability sampling, and inductive analysis to understand perspectives without generalization. Mixed methods combines quantitative and qualitative data collection and analysis to provide a comprehensive understanding of research problems.
Quantitative and Qualitative Approaches.pdfssuser504dda
This document provides an overview of quantitative and qualitative research approaches. It defines quantitative research as deductive, using numeric data from large samples to test hypotheses and analyze relationships between variables objectively. Qualitative research is defined as inductive, relying on words from smaller samples to understand participant experiences subjectively and identify themes in the data. The key differences between the two approaches are described in terms of identifying research problems, reviewing literature, specifying research purposes and questions, collecting and analyzing data, and reporting results. The document also discusses research design and types of quantitative, qualitative, and mixed methods designs.
This document discusses research methods and designs. It defines quantitative and qualitative research methods. Quantitative methods use numerical data and statistics, while qualitative methods focus on patterns and human experiences. The document also outlines different types of research designs, including descriptive, experimental, quasi-experimental, correlational, narrative, phenomenological, grounded theory, historical, case study and ethnographic. It provides examples of how to create a research method and an example research method related to constraint identification and classification.
Qualitative research is a scientific method of investigation that seeks to understand and explain social phenomena through analysis of people's experiences. It involves collecting data in natural settings through methods like interviews, observations and focus groups. The data collected consists of words and images rather than numbers. Three common qualitative methods are participant observation, in-depth interviews, and focus groups. Qualitative research is characterized by its inductive approach, focus on meanings and experiences, flexible design, and interpretation of findings. It aims to gain an in-depth understanding of issues rather than generalizing to a population.
Practical Research 1 about quantitative and qualitative methodsAndoJoshua
Quantitative methods involve collecting and analyzing numerical data using statistical techniques. This may include polls, questionnaires, and manipulating existing statistical data. Quantitative techniques provide systematic and powerful analysis based on quantitative data. Quantitative data can be counted or measured numerically, while qualitative data includes non-numerical responses. The role of the researcher is to design rigorous quantitative studies and ensure valid and reliable results.
Quantitative search and_qualitative_research by mubarakHafiza Abas
The document discusses quantitative and qualitative research methods. Quantitative research aims to quantify data by using structured tools like questionnaires to collect numerical data from large samples that can be statistically analyzed. It focuses on objectively testing hypotheses. Qualitative research collects non-numerical data like descriptions through methods such as interviews and observations to understand peoples' experiences. It focuses on exploring topics in-depth. The document also compares surveys and questionnaires, describing their differences and advantages and disadvantages of various survey methods.
The document provides an overview of research methodology. It discusses key aspects of the research process including developing research questions and hypotheses, research design, data collection methods, and data analysis. Some common data collection methods described are surveys, experiments, case studies, observations, interviews, and focus groups. The document also covers qualitative and quantitative research approaches, as well as descriptive, explanatory, and exploratory research.
Qualitative & Quantitative Research Methods.docxSobiaAlvi
Content List
Topic: Concept of Qualitative & Quantitative Research Design
1. Quantitative Research
2. Qualitative Research
Topic: Comparison of Qualitative & Quantitative Research
1. Qualitative Vs. Quantitative Research – A Comparison
References
Data Collection and Sampling Techniques Demo ppt.pptxChristianAlcaide2
This document discusses data collection and sampling techniques used in research. It defines primary and secondary data, as well as qualitative and quantitative data. Several primary data collection methods are described, including surveys, interviews, focus groups, observation, experiments, diaries, and case studies. Secondary data collection involves obtaining published information from sources like books, journals, and government records. The document also explains probability sampling techniques like simple random sampling, systematic sampling, stratified random sampling and cluster sampling. Non-probability sampling techniques include quota sampling, snowball sampling, convenience sampling, and purposive sampling.
This document discusses different methods of data collection. It defines data collection as the process of systematically gathering and measuring information on variables of interest in order to answer research questions and test hypotheses. The two main types of data are qualitative and quantitative. Qualitative data is non-numerical, descriptive data often in the form of words, while quantitative data is numerical and can be mathematically computed. Common qualitative methods include interviews and focus groups, while quantitative methods include surveys, experiments, and observational studies. The document also discusses mixed methods research, which combines qualitative and quantitative approaches.
This document discusses various methods of data collection for research. It begins by defining data collection as the process of systematically gathering and measuring information to answer research questions and test hypotheses. It then covers the main types of data (qualitative, quantitative, and mixed methods) and their characteristics. A number of specific primary and secondary data collection methods are outlined, including questionnaires, interviews, observations, experiments, and existing records/documents. Key points about ensuring high quality data collection through appropriate instruments and instructions are also made.
PR1 M5 Understanding Data and Ways how to Systematically Collect Data.pdfLEONILAMIRANDA2
This document discusses qualitative research methods for systematically collecting data. It describes various non-probability sampling techniques like convenience sampling, purposive sampling, quota sampling, and snowball sampling. Sample size in qualitative research typically continues until information redundancy or saturation occurs, with rules of thumb based on the research approach, data collection method, and length of interviews. Qualitative data collection methods are time-consuming so samples are usually smaller, but the information is richer with deeper insight into the phenomenon studied. Data analysis involves examining, categorizing, and recombining evidence to address the study's initial propositions.
PR1 M5 Understanding Data and Ways how to Systematically Collect Data.pdfLEONILAMIRANDA2
This document discusses qualitative research methods for systematically collecting data. It describes various non-probability sampling techniques like convenience sampling, purposive sampling, quota sampling, and snowball sampling. Sample size in qualitative research typically continues until information redundancy or saturation occurs, with rules of thumb based on the research approach, data collection method, and length of interviews. Qualitative data collection methods are time-consuming so samples are usually smaller, but the information is richer with deeper insight into the phenomenon studied. Data analysis involves examining, categorizing, and recombining evidence to address the study's initial propositions.
This document provides an overview of key concepts related to marketing research and the marketing research process. It discusses the components of a marketing information system and how it can provide valuable consumer behavior insights. The 6 steps of marketing research are defined as problem definition, research design, data collection, data analysis, report presentation, and decision making. Various research methods like observation, interviews, questionnaires, and experiments are described. Different sampling techniques including probability and non-probability sampling are also summarized.
The document discusses key aspects of research design including:
1) Research design determines the framework and methods for a study including data collection and analysis.
2) Key decisions in research design include determining primary or secondary data sources, qualitative or quantitative data, specific methods for data collection like surveys or experiments, and approaches for data analysis.
3) A strong research design considers reliability, validity, neutrality, and generalizability and sets up a study for success through a coherent plan.
Understanding ways to collect data, group 4 presentation. Understanding ways to collect data, group 4 presentation. Understanding ways to collect data, group 4 presentation. Understanding ways to collect data, group 4 presentation. Understanding ways to collect data, group 4 presentation. Understanding ways to collect data, group 4 presentation. Understanding ways to collect data, group 4 presentation. Understanding ways to collect data, group 4 presentation. Understanding ways to collect data, group 4 presentation. Understanding ways to collect data, group 4 presentation.
Research Methodology Of The Research ApproachJessica Howard
This section discusses the research methodology used in the study. It outlines two main types of research methods: quantitative and qualitative. Quantitative research uses numerical data that can be mathematically analyzed, while qualitative research uses non-numerical data to understand experiences. The study will use qualitative methods as the research involves many social variables best explored through qualitative approaches. Data will be collected through interviews and analyzed thematically to understand perceptions.
Qualitative research seeks to understand a research problem from the perspectives of the local population involved. It provides information about the human side of issues by identifying factors like social norms, beliefs, and relationships. When used with quantitative methods, qualitative research can help interpret complex realities and data. Valid qualitative research comprehensively collects data through methods like interviews and observation from participants selected through strategies such as purposive and snowball sampling. It analyzes data appropriately and corroborates findings through techniques including member checking and triangulation.
This document outlines and compares quantitative and qualitative research methods. Quantitative methods focus on measuring responses from large sample sizes using tools like surveys and statistical analysis, while qualitative methods use descriptive data collection like interviews and observations to understand differing perspectives on reality. It also discusses participatory methods which involve workshops and diagrams to collaboratively understand issues. Examples of each method type are provided. The document then outlines the typical phases of research including idea generation, problem definition, design, data collection, analysis, interpretation, and communication of results.
Class 6 research quality in qualitative methods 3 2-17tjcarter
This document discusses key ethical issues and methodological considerations for conducting Scholarship of Teaching and Learning (SoTL) research. It outlines assumptions of qualitative research designs, including that they seek to understand meaning and experience rather than generate generalized knowledge. It also discusses eight stages of formative research to generate options and assess interventions. The document emphasizes rigor in qualitative research through credibility, transferability, dependability, and confirmability. It explores mixed methods approaches and priorities for integrating qualitative and quantitative methods.
Project Monitorig and Evaluation_Data Collection Methods is a Presentation by William Afani Paul for a Project MEAL Masterclass by Excellence Foundation for South Sudan
This session is designed to equip participants with essential knowledge and skills in monitoring and evaluating projects effectively.
During this masterclass, participants will delve into the fundamental concepts, tools, and techniques of project monitoring and evaluation. Through interactive discussions, case studies, and practical exercises, attendees will gain a comprehensive understanding of MEAL principles and their application in diverse project contexts.
Key Objectives
Understand the importance of project monitoring and evaluation in ensuring project success.
Learn how to develop and implement effective monitoring and evaluation frameworks.
Explore various data collection methods and analysis techniques for monitoring and evaluation purposes.
Gain insights into utilizing monitoring and evaluation findings to inform decision-making and improve project outcomes.
Learning Outcomes: By the end of the masterclass, participants will able to:
Define key concepts related to project monitoring and evaluation.
Develop a monitoring and evaluation plan tailored to specific project requirements.
Apply appropriate data collection methods and tools for monitoring and evaluation activities.
Utilize monitoring and evaluation findings to enhance project performance and impact.
Concept of Qualitative and Quantitative Research Design.pptxSobiaAlvi
Topic: Concept of Qualitative and Quantitative Research Design
Content List
1. Quantitative Research Design
Definition
What is Quantitative Research
Characteristics of Quantitative Research
Quantitative Research: Key Advantages
Quantitative Research Methodology
7 Best Practices to Conduct Quantitative Research
Basic Research Design for Quantitative Studies
Strengths of Using Quantitative Methods
Limitations of Using Quantitative Methods
2. Qualitative research design
Definition
What is Qualitative Research?
Characteristics of Qualitative Research
Three Key Elements of Qualitative Research
Quantitative Research: Key Advantages
Basic Research Design for Qualitative Studies
Strengths of Using Qualitative Methods
Limitations of Using Qualitative Methods
5 Key Types of Qualitative Research
Qualitative Research Methods: The Top 4 Techniques
Qualitative Research Best Practices
References
https://libguides.usc.edu/writingguide/quantitative#:~:text=Quantitative%20research%20deals%20in%20numbers,%2C%20free%2Dflowing%20manner%5D
https://www.scribbr.com/methodology/qualitative-quantitative-research/
https://www.enago.com/academy/qualitative-vs-quantitative-research/
https://www.investopedia.com/terms/q/quantitativeanalysis.asp
https://ideascale.com/blog/what-is-quantitative-research/
https://ideascale.com/blog/what-is-qualitative-research/
This document discusses qualitative research methods. Qualitative research seeks to understand a research problem from the perspectives of the local population. It provides information about human behaviors, beliefs, opinions and relationships. When used with quantitative methods, qualitative research can help interpret complex realities and data. Some key aspects of qualitative research include unstructured response options, no statistical tests, and less generalizable but more valid and reliable results depending on the researcher's skill.
Part 2 Deep Dive: Navigating the 2024 Slowdownjeffkluth1
Introduction
The global retail industry has weathered numerous storms, with the financial crisis of 2008 serving as a poignant reminder of the sector's resilience and adaptability. However, as we navigate the complex landscape of 2024, retailers face a unique set of challenges that demand innovative strategies and a fundamental shift in mindset. This white paper contrasts the impact of the 2008 recession on the retail sector with the current headwinds retailers are grappling with, while offering a comprehensive roadmap for success in this new paradigm.
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Practical Research 1 about quantitative and qualitative methodsAndoJoshua
Quantitative methods involve collecting and analyzing numerical data using statistical techniques. This may include polls, questionnaires, and manipulating existing statistical data. Quantitative techniques provide systematic and powerful analysis based on quantitative data. Quantitative data can be counted or measured numerically, while qualitative data includes non-numerical responses. The role of the researcher is to design rigorous quantitative studies and ensure valid and reliable results.
Quantitative search and_qualitative_research by mubarakHafiza Abas
The document discusses quantitative and qualitative research methods. Quantitative research aims to quantify data by using structured tools like questionnaires to collect numerical data from large samples that can be statistically analyzed. It focuses on objectively testing hypotheses. Qualitative research collects non-numerical data like descriptions through methods such as interviews and observations to understand peoples' experiences. It focuses on exploring topics in-depth. The document also compares surveys and questionnaires, describing their differences and advantages and disadvantages of various survey methods.
The document provides an overview of research methodology. It discusses key aspects of the research process including developing research questions and hypotheses, research design, data collection methods, and data analysis. Some common data collection methods described are surveys, experiments, case studies, observations, interviews, and focus groups. The document also covers qualitative and quantitative research approaches, as well as descriptive, explanatory, and exploratory research.
Qualitative & Quantitative Research Methods.docxSobiaAlvi
Content List
Topic: Concept of Qualitative & Quantitative Research Design
1. Quantitative Research
2. Qualitative Research
Topic: Comparison of Qualitative & Quantitative Research
1. Qualitative Vs. Quantitative Research – A Comparison
References
Data Collection and Sampling Techniques Demo ppt.pptxChristianAlcaide2
This document discusses data collection and sampling techniques used in research. It defines primary and secondary data, as well as qualitative and quantitative data. Several primary data collection methods are described, including surveys, interviews, focus groups, observation, experiments, diaries, and case studies. Secondary data collection involves obtaining published information from sources like books, journals, and government records. The document also explains probability sampling techniques like simple random sampling, systematic sampling, stratified random sampling and cluster sampling. Non-probability sampling techniques include quota sampling, snowball sampling, convenience sampling, and purposive sampling.
This document discusses different methods of data collection. It defines data collection as the process of systematically gathering and measuring information on variables of interest in order to answer research questions and test hypotheses. The two main types of data are qualitative and quantitative. Qualitative data is non-numerical, descriptive data often in the form of words, while quantitative data is numerical and can be mathematically computed. Common qualitative methods include interviews and focus groups, while quantitative methods include surveys, experiments, and observational studies. The document also discusses mixed methods research, which combines qualitative and quantitative approaches.
This document discusses various methods of data collection for research. It begins by defining data collection as the process of systematically gathering and measuring information to answer research questions and test hypotheses. It then covers the main types of data (qualitative, quantitative, and mixed methods) and their characteristics. A number of specific primary and secondary data collection methods are outlined, including questionnaires, interviews, observations, experiments, and existing records/documents. Key points about ensuring high quality data collection through appropriate instruments and instructions are also made.
PR1 M5 Understanding Data and Ways how to Systematically Collect Data.pdfLEONILAMIRANDA2
This document discusses qualitative research methods for systematically collecting data. It describes various non-probability sampling techniques like convenience sampling, purposive sampling, quota sampling, and snowball sampling. Sample size in qualitative research typically continues until information redundancy or saturation occurs, with rules of thumb based on the research approach, data collection method, and length of interviews. Qualitative data collection methods are time-consuming so samples are usually smaller, but the information is richer with deeper insight into the phenomenon studied. Data analysis involves examining, categorizing, and recombining evidence to address the study's initial propositions.
PR1 M5 Understanding Data and Ways how to Systematically Collect Data.pdfLEONILAMIRANDA2
This document discusses qualitative research methods for systematically collecting data. It describes various non-probability sampling techniques like convenience sampling, purposive sampling, quota sampling, and snowball sampling. Sample size in qualitative research typically continues until information redundancy or saturation occurs, with rules of thumb based on the research approach, data collection method, and length of interviews. Qualitative data collection methods are time-consuming so samples are usually smaller, but the information is richer with deeper insight into the phenomenon studied. Data analysis involves examining, categorizing, and recombining evidence to address the study's initial propositions.
This document provides an overview of key concepts related to marketing research and the marketing research process. It discusses the components of a marketing information system and how it can provide valuable consumer behavior insights. The 6 steps of marketing research are defined as problem definition, research design, data collection, data analysis, report presentation, and decision making. Various research methods like observation, interviews, questionnaires, and experiments are described. Different sampling techniques including probability and non-probability sampling are also summarized.
The document discusses key aspects of research design including:
1) Research design determines the framework and methods for a study including data collection and analysis.
2) Key decisions in research design include determining primary or secondary data sources, qualitative or quantitative data, specific methods for data collection like surveys or experiments, and approaches for data analysis.
3) A strong research design considers reliability, validity, neutrality, and generalizability and sets up a study for success through a coherent plan.
Understanding ways to collect data, group 4 presentation. Understanding ways to collect data, group 4 presentation. Understanding ways to collect data, group 4 presentation. Understanding ways to collect data, group 4 presentation. Understanding ways to collect data, group 4 presentation. Understanding ways to collect data, group 4 presentation. Understanding ways to collect data, group 4 presentation. Understanding ways to collect data, group 4 presentation. Understanding ways to collect data, group 4 presentation. Understanding ways to collect data, group 4 presentation.
Research Methodology Of The Research ApproachJessica Howard
This section discusses the research methodology used in the study. It outlines two main types of research methods: quantitative and qualitative. Quantitative research uses numerical data that can be mathematically analyzed, while qualitative research uses non-numerical data to understand experiences. The study will use qualitative methods as the research involves many social variables best explored through qualitative approaches. Data will be collected through interviews and analyzed thematically to understand perceptions.
Qualitative research seeks to understand a research problem from the perspectives of the local population involved. It provides information about the human side of issues by identifying factors like social norms, beliefs, and relationships. When used with quantitative methods, qualitative research can help interpret complex realities and data. Valid qualitative research comprehensively collects data through methods like interviews and observation from participants selected through strategies such as purposive and snowball sampling. It analyzes data appropriately and corroborates findings through techniques including member checking and triangulation.
This document outlines and compares quantitative and qualitative research methods. Quantitative methods focus on measuring responses from large sample sizes using tools like surveys and statistical analysis, while qualitative methods use descriptive data collection like interviews and observations to understand differing perspectives on reality. It also discusses participatory methods which involve workshops and diagrams to collaboratively understand issues. Examples of each method type are provided. The document then outlines the typical phases of research including idea generation, problem definition, design, data collection, analysis, interpretation, and communication of results.
Class 6 research quality in qualitative methods 3 2-17tjcarter
This document discusses key ethical issues and methodological considerations for conducting Scholarship of Teaching and Learning (SoTL) research. It outlines assumptions of qualitative research designs, including that they seek to understand meaning and experience rather than generate generalized knowledge. It also discusses eight stages of formative research to generate options and assess interventions. The document emphasizes rigor in qualitative research through credibility, transferability, dependability, and confirmability. It explores mixed methods approaches and priorities for integrating qualitative and quantitative methods.
Project Monitorig and Evaluation_Data Collection Methods is a Presentation by William Afani Paul for a Project MEAL Masterclass by Excellence Foundation for South Sudan
This session is designed to equip participants with essential knowledge and skills in monitoring and evaluating projects effectively.
During this masterclass, participants will delve into the fundamental concepts, tools, and techniques of project monitoring and evaluation. Through interactive discussions, case studies, and practical exercises, attendees will gain a comprehensive understanding of MEAL principles and their application in diverse project contexts.
Key Objectives
Understand the importance of project monitoring and evaluation in ensuring project success.
Learn how to develop and implement effective monitoring and evaluation frameworks.
Explore various data collection methods and analysis techniques for monitoring and evaluation purposes.
Gain insights into utilizing monitoring and evaluation findings to inform decision-making and improve project outcomes.
Learning Outcomes: By the end of the masterclass, participants will able to:
Define key concepts related to project monitoring and evaluation.
Develop a monitoring and evaluation plan tailored to specific project requirements.
Apply appropriate data collection methods and tools for monitoring and evaluation activities.
Utilize monitoring and evaluation findings to enhance project performance and impact.
Concept of Qualitative and Quantitative Research Design.pptxSobiaAlvi
Topic: Concept of Qualitative and Quantitative Research Design
Content List
1. Quantitative Research Design
Definition
What is Quantitative Research
Characteristics of Quantitative Research
Quantitative Research: Key Advantages
Quantitative Research Methodology
7 Best Practices to Conduct Quantitative Research
Basic Research Design for Quantitative Studies
Strengths of Using Quantitative Methods
Limitations of Using Quantitative Methods
2. Qualitative research design
Definition
What is Qualitative Research?
Characteristics of Qualitative Research
Three Key Elements of Qualitative Research
Quantitative Research: Key Advantages
Basic Research Design for Qualitative Studies
Strengths of Using Qualitative Methods
Limitations of Using Qualitative Methods
5 Key Types of Qualitative Research
Qualitative Research Methods: The Top 4 Techniques
Qualitative Research Best Practices
References
https://libguides.usc.edu/writingguide/quantitative#:~:text=Quantitative%20research%20deals%20in%20numbers,%2C%20free%2Dflowing%20manner%5D
https://www.scribbr.com/methodology/qualitative-quantitative-research/
https://www.enago.com/academy/qualitative-vs-quantitative-research/
https://www.investopedia.com/terms/q/quantitativeanalysis.asp
https://ideascale.com/blog/what-is-quantitative-research/
https://ideascale.com/blog/what-is-qualitative-research/
This document discusses qualitative research methods. Qualitative research seeks to understand a research problem from the perspectives of the local population. It provides information about human behaviors, beliefs, opinions and relationships. When used with quantitative methods, qualitative research can help interpret complex realities and data. Some key aspects of qualitative research include unstructured response options, no statistical tests, and less generalizable but more valid and reliable results depending on the researcher's skill.
Part 2 Deep Dive: Navigating the 2024 Slowdownjeffkluth1
Introduction
The global retail industry has weathered numerous storms, with the financial crisis of 2008 serving as a poignant reminder of the sector's resilience and adaptability. However, as we navigate the complex landscape of 2024, retailers face a unique set of challenges that demand innovative strategies and a fundamental shift in mindset. This white paper contrasts the impact of the 2008 recession on the retail sector with the current headwinds retailers are grappling with, while offering a comprehensive roadmap for success in this new paradigm.
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[To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
This presentation is a curated compilation of PowerPoint diagrams and templates designed to illustrate 20 different digital transformation frameworks and models. These frameworks are based on recent industry trends and best practices, ensuring that the content remains relevant and up-to-date.
Key highlights include Microsoft's Digital Transformation Framework, which focuses on driving innovation and efficiency, and McKinsey's Ten Guiding Principles, which provide strategic insights for successful digital transformation. Additionally, Forrester's framework emphasizes enhancing customer experiences and modernizing IT infrastructure, while IDC's MaturityScape helps assess and develop organizational digital maturity. MIT's framework explores cutting-edge strategies for achieving digital success.
These materials are perfect for enhancing your business or classroom presentations, offering visual aids to supplement your insights. Please note that while comprehensive, these slides are intended as supplementary resources and may not be complete for standalone instructional purposes.
Frameworks/Models included:
Microsoft’s Digital Transformation Framework
McKinsey’s Ten Guiding Principles of Digital Transformation
Forrester’s Digital Transformation Framework
IDC’s Digital Transformation MaturityScape
MIT’s Digital Transformation Framework
Gartner’s Digital Transformation Framework
Accenture’s Digital Strategy & Enterprise Frameworks
Deloitte’s Digital Industrial Transformation Framework
Capgemini’s Digital Transformation Framework
PwC’s Digital Transformation Framework
Cisco’s Digital Transformation Framework
Cognizant’s Digital Transformation Framework
DXC Technology’s Digital Transformation Framework
The BCG Strategy Palette
McKinsey’s Digital Transformation Framework
Digital Transformation Compass
Four Levels of Digital Maturity
Design Thinking Framework
Business Model Canvas
Customer Journey Map
Understanding User Needs and Satisfying ThemAggregage
https://www.productmanagementtoday.com/frs/26903918/understanding-user-needs-and-satisfying-them
We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.
In this webinar, we won't focus on the research methods for discovering user-needs. We will focus on synthesis of the needs we discover, communication and alignment tools, and how we operationalize addressing those needs.
Industry expert Scott Sehlhorst will:
• Introduce a taxonomy for user goals with real world examples
• Present the Onion Diagram, a tool for contextualizing task-level goals
• Illustrate how customer journey maps capture activity-level and task-level goals
• Demonstrate the best approach to selection and prioritization of user-goals to address
• Highlight the crucial benchmarks, observable changes, in ensuring fulfillment of customer needs
At Techbox Square, in Singapore, we're not just creative web designers and developers, we're the driving force behind your brand identity. Contact us today.
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3. Session
Contents
1. Overview of research methods
2. Distinction between quantitative
& qualitative research
3. Types & applicability of different
research methods
4. Q&A
5. Research methodology
The methodology is an outline of the overall data collection and analysis strategy that
will be used to implement the research cycle
The methodology should:
Be compatible with the preliminary data analysis plan
Be designed in a way that ensures the intended scope of the research (i.e. objectives and
research questions) can be feasibly achieved to the required quality, given the time,
resources and access available
Designing a methodology involves three key components:
Selecting the overall research method
Selecting the appropriate data collection approach(es)
Designing the sampling strategy
6. Categories of research methods
Research methods are broadly distinguished between the following categories:
Quantitative
Measure prevalence of
issues, verify hypotheses
and establish causal
relations between
variables
Large samples,
structured data collection,
and predominantly
deductive analysis
Qualitative
Explore and discover
themes, develop
theories, rather than verify
hypotheses and measure
occurrences
Smaller samples, semi-
structured data collection,
inductive analysis
Mixed Methods
Combines both
qualitative and
quantitative to (1) collect
and analyse both types of
data and (2) use both
approaches in tandem
8. Selecting your research method
What factors to consider when choosing one research method over another?
Overall applicability to meet research objectives
Time i.e. key planning and decision-making milestones to inform
Resources available
Material resources
Financial resources
Human resources
Access to population of interest
10. Differences between quantitative & qualitative research
The distinction between quantitative and qualitative research is not always as clear-cut:
Individual and household surveys
o Commonly associated with quantitative, large sample research
o Could also be used for a qualitative case study
Key Informant interviews and community discussions
o Commonly associated with qualitative, semi-structured data collection & analysis
o Could also be used for quantitative data collection & analysis where time and resources do not
allow a large, representative sample
Focus Group Discussions
o Perhaps the most distinctly qualitative research method, always administered using a semi-
structured data collection tool
o Often analysed using content analysis i.e. a somewhat quantitative approach counting the
number of times a theme or set of words appear with the discussion transcripts
o This content analysis can then inform the more in-depth qualitative analysis.
11. Differences between quantitative & qualitative research
Distinction between the two can be made based on the following three criteria:
Quantitative Qualitative
1. Type of data collection Structured, close-ended data
collection tools
Semi-structured (but not
unstructured) data collection tools
2. Type of analysis Measuring prevalence,
quantifying issues, and
primarily involves deductive
analysis
Exploratory, and primarily involves
inductive analysis
3. Type of sampling strategy Can use both probability or
non-probability sampling
generalisation to the wider
population possible
Non-probability sampling
generalisation to the wider population
not possible
13. Types of research methods (1)
Category Type of research
methods
Description When to use this method
Quantitative Structured, probability
sampling/ census
Structured, close-ended data
collection;
Quantitative analysis;
Data collected from a census or
through large samples, with
sample size calculated based on
probability theory
To measure prevalence and make
generalizable claims,
To conduct deductive analysis
(relationship tests, verify hypothesis)
To identify key factors that influence a
particular outcome or understand the best
predictors of a specific outcome
Quantitative Structured, non-
probability sampling
Structured, close-ended data
collection;
Quantitative analysis;
Can be small or large sizes; non-
probability sampling
To measure prevalence (indicative only)
but contextual and/ or logistical
constraints do not allow for large,
repressentative samples
To draw indicative inferences from a
sample to a population
14. Types of research methods (2)
Category Type of research
methods
Description When to use this method
Qualitative Semi-structured, non-
probability sampling
Semi-structured data collection;
Qualitative analysis;
Relatively small sample sizes;
non-probability sampling
No measurement of prevalence or
verification of hypothesis needed;
No or limited prior understanding of the
situation to be studied and the specific
variables to be assessed;
To conduct inductive analysis i.e.
explore and develop a theory or pattern
of meaning, based on experiences,
observations and perspectives of the
situation being studied
Mixed
Methods
N/A Combines both qualitative and
quantitative methods, both in
terms of collecting and analyzing
both types of data but also using
both in tandem to enhance the
overall strength of the study
Quantitative or qualitative methods by
themselves inadequate to understand
the research problem;
To use all methods possible to obtain an
in-depth, comprehensive understanding
of the research problem.
15. The most powerful research method?
Mixed methods research – if time, access, resources allow!
Common misnomer that quantitative research is the strongest – not always!
Not all issues need to explained in a quantifiable way
Some issues are over-simplified if only explored in numeric terms
In-depth explanation and contextualisation is useful
Ultimately depends on the research objectives
17. Session
Contents
1. Unit of measurement
2. Types of data collection approaches
(structured)
3. Types of data collection approaches (semi-
structured)
4. Types of data collection approaches (mixed
methods)
5. Frequently Asked Questions (FAQs)
6. Overview of remote data collection
7. Q&A
8. Task for the week
19. What is it?
The unit that will be used to record,
measure and analyse observations/
information collected
Examples?
Individual
Family
Household
Community/ group
Town/ village
Facility
20. Remember…
Unit will impact the time, resources needed to collect and analyse information
Unit will define the depth of information possible and scope of analysis
Depth
of
information
Location level
Household level
Individual level
Community/Group level
Time / Cost / Access
22. 1. The structured survey approach
Information collected through an interview, a discussion, a conversation
Using structured, close-ended data collection tools
Collection of quantifiable information
Cross-sectional or longitudinal
Types of data collection methods?
Household (HH) survey – collecting data at HH level, to understand experiences and characteristics of HHs within population of interest
Individual survey – collecting data at individual level, to help understand situation and characteristics of individuals within the population of
interest can include some HH level indicators if needed
Key informant interview – collecting data at community. location or group level from a key informant (KIs) i.e. an individual whose informal/
formal position gives him specific knowledge about other people, processes, or events that is more extensive, detailed, or privileged than
other individuals in their group/ community/ location
Group discussion – collecting data at community, location or group level from a group of representatives e.g. KIs
23. 1. The structured survey approach- Applicability
When should you use this approach?
To measure prevalence provide a quantifiable, numeric description of
the trends, behaviours, experiences, attitudes or opinions of a population
To generalize findings to a wider population probability sample
statistically representative information
Need prevalence data, understanding of scale of crisis but probability
sampling not possible non-probability sample indicative information
Types of research cycles this approach is commonly used for?
Multi-sector needs assessments
In-depth thematic needs assessments e.g. WASH Cluster needs assessment
Longitudinal studies (correlational studies)
Third party monitoring (impact evaluation, outcome monitoring, post-
distribution monitoring, etc.)
24. 2. The structured experimental approach
What is it?
Similar to survey approach
But relies on experimental survey design
control vs. treatment group
Types of data collection methods?
Household (HH) survey – collecting data at HH level, to understand experiences and
characteristics of HHs within population of interest
Individual survey – collecting data at individual level, to help understand situation and
characteristics of individuals within the population of interest can include some HH level
indicators if needed
25. 2. The structured experimental approach - Applicability
When should you use this approach?
To measure prevalence and evaluate the outcomes or impact of a medium to large-scale
intervention on the population of interest
Generalize findings to a wider population probability sample statistically
representative information
Types of research cycles this approach is commonly used for?
Outcome monitoring
Impact evaluations
Etc.
26. 3. The structured observation approach (Description)
What is it?
Information collected through observation rather than
conversation
Using structured, close-ended checklists to collect
quantifiable information
Looking for specific object, behaviour or event against a
checklist e.g. Household using soap? Damage to health
center? Students participating in classroom?
Can be used as part of experimental approach
Types of data collection methods?
Participant observation – researcher participates in
context (e.g. anthropologists)
Direct observation – researchers observes context (e.g.
psychologists or clinical research)
27. 3. The structured observation approach - Applicability
When should you use this approach?
Serves similar purpose as survey approach
Depends on research objectives observation vs.
conversation?
Types of research cycles this approach is commonly used for?
Could be same as survey approach
Could be same as experimental approach
29. 4. The semi-structured discussion approach
What is it?
Information collected through detailed, narrative interviews, group discussions
Using semi-structured (NOT UNSTRUCTURED) data collection tools
open-ended questions, probes
Purposefully selected participants
Types of data collection methods?
Individual interview – collecting data at individual level, to help understand situation and characteristics of individuals within the population
of interest can include some HH level indicators if needed
Key informant interview – collecting data at community. location or group level from a key informant (KIs) i.e. an individual whose informal/
formal position gives him specific knowledge about other people, processes, or events that is more extensive, detailed, or privileged than
other individuals in their group/ community/ location
Group discussion – collecting data at community, location or group level from a group of representatives e.g. Kis
Focus group discussion – bringing together people from similar backgrounds or experiences to discuss a specific topic of interest; data
collected at community, location or group level
30. 4. The semi-structured discussion approach - Applicability
When should you use this approach?
To gather detailed insights about the
experiences, perspectives of specific population
group or location
To provide a qualitative description of the
experiences, trends, attitudes or opinions of a
population
Types of research cycles this approach is
commonly used for?
In-depth assessments where there is limited
prior understanding of a situation e.g. access to
cash among refugees & migrants in Libya
Participatory mapping exercises (mapping FGDs
(focus group disc.) or KI interviews)
31. ‘Most Significant Change’ data collection technique
A very specific type of participatory,
discussion-based data collection
method used for monitoring &
evaluation
Invites participants (through KI
interviews, individual interviews or
FGDs) to explain the most significant
changes brought about in their lives
by a project over a given period of time,
in key domains of change
Useful for third party monitoring or
impact evaluation research cycles
32. ‘Most Significant Change’ data collection technique
The stories, anecdotes you collect from beneficiaries/ project partners,
broken down by «domain» of interest
The stories, anecdotes you select to qualitatively analyse change per
«domain», in consultation with project team
33. 5. The semi-structured observation approach
Similar to structured observation approach
But two key differences:
Structured observation Semi-structured observation
1. Differences in data
collection methods
Information collected using a
structured set of questions,
usually to identify specific object,
behaviour or event against a
checklist
Information collected based on a
short set of open-ended
questions for observations e.g.
movement patterns of refugees
in and out of camps during a
sustained period of time
2. Differences in purpose Provide a quantifiable, numeric
description of the trends,
behaviours, experiences, etc. of
a population
Gather detailed insights about
the behaviours, experiences of
a specific population group or
location, and to understand, by
observation, how things are
done and what issues exist
35. 6. Sequential mixed methods data collection
Method used to sequentially elaborate or expand on the findings of one type of
research method with another
• Identify coping
strategies
Qualitative
• Measure
prevalence of
identified coping
strategies
Quantitative
1. Exploratory sequential approach
• Measure
prevalence of
known coping
strategies
Quantitative
• Understand and
contextualize
observed trends
in prevalence
Qualitative
2. Explanatory sequential approach
• Identify coping
strategies
Qualitative
• Measure
prevalence of
identified coping
strategies
Quantitative
• Understand and
contextualize
observed trends
in prevalence
Qualitative
3. The “ideal” sequential approach
36. 7. Concurrent mixed methods approach
Method used to merge or converge the findings from different research methods collected at the
same time
Alternative to sequential approach if time constraints sequential better practice if time and
resources allow
Concurrent mixed methods serves two key purposes:
Triangulation strategy
Convergence
of information
collected?
Divergence of
information
collected?
Embedded strategy
Primary
method:
quant
(What?
Where?)
Secondary
method:
qual (How?
Why?)
Key findings &
conclusions
37. Case study data collection technique
Using a combination of different data
collection methods to zoom in to a
specific issue, area or group
A component within a research
cycle, not a research cycle by itself
Useful to collect detailed information
on an event, activity, process, group
e.g. zoom in to one specific type of
intervention in an area within a larger
DFID-funded humanitarian programme
39. FAQs (1)
What is the difference between a key informant interview and an individual
interview? Isn’t the key informant also technically an individual?
The differences lies in the unit of measurement individual experiences
(individual interview) vs. community/ village/ institution experiences (KI interview)
For semi-structured data collection, when is it recommended to use FGDs
over KI or individual interviews?
This depends on two things
Research objectives and type of information needed e.g. Variety of
opinions and experiences useful? Specific information needed from an
expert? Topics sensitive to discuss in group setting?
Logistical constraints e.g. Large number of individuals to be reached within
a short timeframe?
40. FAQs (2)
Is it possible to have two different units of measurement in the same questionnaire?
Ideally, should be avoided, but there are some exceptions:
Individual information within a household survey (e.g. child attendance roster)
Household information within an individual survey (e.g. household size or income indicators)
Individual information within a village/ community/ location level interview (e.g. KI’s displacement status
and experiences, if KI also part of the affected population)
Household information within a village/ community/ location level interview (e.g. KI estimates # or % of
households affected by a specific situation in a village)
What if my population of interest includes minors (i.e. individuals <18 years of age)?
Can I collect data from minors?
Only if absolutely necessary to meet objectives of the research
Only if required information cannot be collected from adult respondents e.g. parents or caregivers
Ideally, only from respondents >15 years
Only if the required protocols are being followed
Will de discussed later in this training
42. What is remote data collection?
Remote data collection is a means of gathering data without a
physical presence in the data collection location and without
direct, in-person contact with the population of interest
When is it useful?
When it is not possible to conduct in-person visits to the
locations / populations of interest because of reasons such as:
Disease outbreak (e.g. COVID-19)
Time or resource constraints (e.g. not enough budget to hire
enumerators to cover all areas for face to face interviews)
Access constraints due to:
Security concerns
COVID-19 travel restrictions
Physical access barriers such as lack of infrastructure
Severe weather conditions which limits travel
possibilities, etc.
Etc.
43. Pros and cons of remote data collection
Pros Cons
Planning efficiency
More time and resource efficient; if
necessary logistics already in place,
could be fairly straightforward to
deploy
Challenging and time consuming to
set up correctly (e.g. identifying
respondents, organizing necessary
logistics, etc.), difficult to apply
stratification in sampling; challenging
to monitor progress
Implementation efficiency
Easier to implement even with
limited time, access and resources
(assuming planning and design is
done robustly)
Higher likelihood of low response
rates; limited means of verifying
responses/ data quality assurance;
more challenging to build trust with the
respondents; difficult to deploy long
or complicated questionnaires
Coverage
Ensures maximum possible
coverage of areas and population of
interest despite access constraints
Difficult to have the “full picture” as it
could introduce potential sampling
biases (e.g. based on phone network
coverage) and results in exclusions/
oversight of certain population
groups or areas
44. Some types of remote data collection methods (1)
1. Phone-based (individual, household, community level)
Most relevant for: needs assessments, post distribution monitoring (PDMs),
humanitarian situation monitoring (HSM)
Representative sampling could be possible
2. REACH “Area of Knowledge” methodology (face-to-
face data collection in alternate location)
Most relevant for: community-level needs assessments or HSM
Representative sampling not relevant (requires identifying the
respondent most likely to have the required knowledge)
3. Internet-based data collection
Tools include: social media, web-based surveys, online discussion
platforms, chatbots (WFP mVAM), etc.
Most relevant for: community-level needs assessments HSM (KI
interviews or group discussions), PDMs (individual perception surveys)
Representative sampling could be possible (but extremely difficult to
implement e.g. would need email address database and usually low
response rates)
45. Some types of remote data collection methods (2)
4. Remote sensing
Only relevant if aim is to gain an understanding based on specific physical
characteristics of an area (e.g. agriculture and vegetation health analysis, shelter
damage assessment, flood impact assessment, etc.)
Representative sampling or even census could be possible
5. Secondary data review and “expert” consultations
Most relevant for: needs analysis or HSM
Only feasible if relevant and «reliable» data sources already exist
6. Paper form submissions
Only applicable if respondents have no movement restrictions and are able to
send paper forms back through required means
Logistically difficult, not the most time and resource efficient
Most relevant for: community-level needs assessments or HSM (KI
interviews), PDMs (individual perception surveys)
Representative sampling could be possible (but extremely difficult to
implement e.g. would need postal address database and expect very low
response rates)
46. Post-distribution
monitoring (PDM) of cash
assistance and core relief
items to refugees and
IDPs across Iraq
Project began in 2016
and remains ongoing
Data collected through
two call centres: Erbil and
Baghdad
Household level data
collection, providing at
least a 90% confidence
level and 10% margin of
error at Governorate level
Phone-based data collection example: Iraq UNHCR
Cash Assistance PDM (2017-now)
Project background
To improve time and cost
efficiency, since most of
the data collected would
not be verifiable by
enumerators in the field
Access to beneficiary
contact lists ensures time-
efficient data collection
The project has a wide
geographical spread, so
the call centre allows for
rapid, far reaching data
collection
Why was it remote? What worked well? Challenges?
A team of enumerators
have been well trained and
dedicated to this
assessment continuously
Availability of anonymised,
comprehensive beneficiary
lists for sampling purposes
Remote data collection
helps ensure data privacy
Typically the call centre
remains functional,
regardless of changing
access constraints
Building trust among
respondents
Ensuring respondents
understand the role of this
assessment
Potential for duplication as
beneficiary lists were at the
individual level while
sampling was at the
household level
Space constraints within
the call centre during
multiple ongoing
assessments
47. Humanitarian Situation
Monitoring in ‘hard to
reach areas’ of ‘3 border’
area between Mali, Niger
and Burkina Faso
Since November 2019
Remote data collection
through face to face
interviews with KIs who
travel between accessible
and inaccessible areas
Collect information about
humanitarian situation in
each country / areas with
same tool to allow for
comparability
AoK data collection example: 3-border HSM in Sahel
(December 2019- now)
Project background
To gather information
about areas where
humanitarian access is low
or unreliable
To ensure supply of
information about these
areas is regular and not
contingent on access,
allowing for trends
monitoring
Less resource intensive –
good compromise to
gather indicative data in
complement to existing,
more robust data collection
systems
Why was it remote?
Once knowledge of
population movements
within a region is clear,
easy to set up data
collection to ‘capture’
information about
different areas
Ability to cover data
across a vast territory
from a handful of static
bases.
Ability to monitor trends
on situation in hard to
reach areas and to
compare and contrast
between severity levels.
What worked well?
Reliability is not high and
ability to verify validity of
data collected is low – it’s
indicative only
KIs reporting on overall
situation at settlement
level can hide inequalities
While it is less
challenging finding KIs
from relevant geographic
areas, it can be difficult to
find a balance of KI
profiles (men, women,
age groups, vulnerable
groups etc), impacting
comparative analysis.
Challenges?
HH survey has two components: (1) a short background and demographics module (which includes a detailed roster of each household member’s age, sex, marital status and relationship status to the head of household) and (2) a detailed module exploring the key indicators and variables relevant to the topic of research. In some cases, a third module is also included which records individual-level data within the household, for e.g. information on education background and current status of each child member of school-going age within the household.
FGDs are useful to:
gain insight into how a specific group thinks about an issue
collect anecdotal evidence
gather a wide range of opinions and ideas through a few discussions only, and
identify and understand inconsistencies and variations that exist in a particular community in terms of perceptions, experiences and practices.
What is the project?
Post-distribution monitoring of cash assistance and core relief items to refugees and IDPs across Iraq
PDM activities have been conducted for in-kind, cash, and seasonal assistance in the KR-I and neighbouring areas from 2016, and for cash-based assistance nationwide since 2017.
Two call centres- in Erbil and Baghdad
Once we have the beneficiary lists, we stratify them by governorate and conduct HH interviews. We do a census for any governorate under 100 people and randomly sample the rest to get 90/10 governorate level and 95/5 overall
Why was a call centre used?
Most of the data collected is not verifiable by in-person enumerators anyway (i.e. use of cash assistance, use of household coping strategies)
Geographic spread – some assessments under this project cover the whole of Iraq. In some governorates we have 500+ beneficiaries, but sometimes we only have 4 or 5 beneficiaries in a governorate. This would make it challenging to do in-person data collection.
What works well?
We’ve built a strong team of core enumerators who are primarily dedicated to this project. Some have worked on the team for years and really understand the methodology and questions.
Good for data privacy- all phones and beneficiary lists stay within the office at all times.
When access is limited, call-centre data collection is usually unaffected.
What challenges were faced?
Building trust of beneficiaries – we’ve written robust introduction statements at the start of our surveys to ensure that enumerators are fully explaining who they are, why they’re calling, etc. For in person data collection enumerators are identifiable as REACH employees, but on the phone it has to be explained much more thoroughly.
Duplication - we were potentially duplicating households in our survey since the contact lists we had could often have more than one household member in them (i.e. multiple beneficiaries within the same household). Since our unit of measurement was the household (i.e. most of the questions we were asking were at household level), we had to find some ways to overcome this. One very simple measure for example we took was to ask right at the start of the survey if someone else within their household (defining clearly what the household was) had already been contacted in the past x period for a similar survey. There was another measure we took which was matching unique case registration IDs, but this isn’t always possible
Space constraints- when we have simultaneous data collection for multiple assessments it’s often very crowded in the call centre. Makes it hard for enumerators to hear and for people to hear them on the call.