Joel Suto
I am an accomplished Research Scientist, Trainer and Qualitative Data Analyst. My research interests include governance, education, health, gender, women empowerment, and population dynamics. Over the years I have participated in cutting edge research studies that have informed policy in the areas of interest. I have also facilitated and conducted practical competence and skills-based training in data analysis, ethics and governance, strategic leadership and management and project management. I am an innovative and creative thinker and flexible in my approach to issues. I possess excellent organizational skills and a clear, logical mind with a practical approach to problem solving and a drive to see things through to completion. With excellent interpersonal skills, I am a team player with the ability to motivate others. My professional experience to date has provided a wealth of specialist skills and expertise in research, training, writing and project management. I am committed to facing fresh challenges and to pursuing my future career goals.
Supervisors: Prof. Salome Bukachi, Dr. Frederick Wekesah, Dr. Daniel Muindi, Prof. Ben Mulemi, and Dr. Millicent Liani
Phone: +254720272325
Address: P. O. Box 1008 - 00902, Kikuyu - Kenya
Supervisors: Prof. Salome Bukachi, Dr. Frederick Wekesah, Dr. Daniel Muindi, Prof. Ben Mulemi, and Dr. Millicent Liani
Phone: +254720272325
Address: P. O. Box 1008 - 00902, Kikuyu - Kenya
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Thesis Chapters
The violence witnessed in Kenya in the aftermath of the 2007 disputed presidential elections shook
Kenyans into the realization that Kenya had remained a highly polarized nation since independence.
Brother turned against brother resulting in the loss of more than 1,300 lives and the displacement of more than
300,000 people. International agencies stepped in with the AU taking the lead in a bid to seek a
cessation to the violence. An agreement was finally sealed on February 28, 2008 through the KNDRC
process mediated by former UN Secretary General Kofi Annan. The agreement led to inter alia the
cessation of violence and formation of a coalition government. However, the mediation efforts could
have only done so much. There were long-term issues that needed specialized agencies to fully resolve.
With this understanding the KNDRC agreed on a number of commissions to be formed to handle these
issues.
The Commission of Inquiry into the Post-Election Violence (Waki Commission), the National Cohesion
and Integration Commission – the only permanent commission – and finally the TJRC were among
commissions formed to handle the long-term issues of the conflict. The Waki Commission in its report
recommended the formation of a Special Tribunal for Kenya to try the people suspected to bore criminal
responsibility for the PEV. However, the Special Tribunal of Kenya never saw the light of day.
Consequently, the ICC stepped in and took up the cases after the then ICC Prosecutor Moreno Ocampo
received the names of people suspected to bear criminal responsibility for the PEV from Kofi Annan.
The TJRC was finally established in 2009 to among others promote justice, healing and reconciliation in
Kenya. It was formed at a time when the ICC was in the process of confirming charges against six
Kenyans in relation to the 2007 / 2008 PEV. At the time many Kenyans viewed the TJRC as a ploy by
those in government to shield the merchants of impunity from criminal prosecution.
The TJRC problems were further compounded by the credibility crisis that faced its’ chairperson –
Ambassador Bethuel Kiplagat. The issues surrounding the chairperson threatened to tear the commission
apart and derail the truth seeking process. The crisis led to the resignation of the then vice-chairperson –
Ms. Betty Murungi. This left the TJRC with only seven commissioners when the chairperson finally
stepped aside. Throughout its’ work the commission was further plagued by financial challenges as well
as lack of political will in the truth seeking process.
The TJRC worked for four years and finally handed in its’ report in May 2013. The commissioners
noted that reconciliation is not an event but a process. Consequently, the TJRC interpreted its mandate
as being to initiate the process of reconciliation. The TJRC held a number of public hearings and
reconciliation forums to aid in the initiation of reconciliation between and among the different Kenyan
ethnic groups. The research concludes that despite the many challenges experienced by the TJRC, it did
actually lay the foundation for reconciliation. It is imperative that the government endeavours to
implement the commission’s recommendations if reconciliation is to be fully realized in the country. It
is equally important that the rule of law is observed so that the citizens can rest assured that justice and
fairness will prevail.
Books
Teaching Documents
As a part of this PMP Certification training, you will improve your leadership skills and understand how to use standard tools & techniques to ensure all communications are clear. You will acquire skills to create an accurate project schedule and identify, access, and control project risks. You will be guided through the program by globally-renowned project management experts to earn a PMP Certification that prepares you to face the emerging new normal.
Our training courses help both individual participants hone their individual expertise and entire organizations grow continue making an impact in their different sectors of operations. Our short courses are not run-of the-mill, because we do things a little differently than other training companies you may have worked with in the past. We research skills gaps and from there we then design and develop all of our training courses in great detail with one aim in mind - to help take Course
Participants and your company to the next level. Having this capability in-house allows us to conduct an in-depth training needs analysis, pinpoint urgent skills gaps and design practical learning modules
which are highly relevant to the client’s specific working environment.
The course surveys some of the foundational topics in data science, such as data analysis, data visualization, machine Learning, and time series forecasting. The course is intended for students who wish to learn about the powerful Python data science ecosystem in order to apply data analysis techniques, information visualization, and inferential statistical analyses to gain new insights into the data. Through this course participants will learn how to manipulate, process, and clean data with Python, using its data-oriented library ecosystem and tools that will lay the foundations to allow participants become effective data analysts. Participants will learn how to conduct data science by learning how to analyze data. That includes knowing how to import data, explore it, analyze it, learn from it, visualize it, and ultimately generate easily shareable reports. The course will run with a mix of theoretical classes and hands-on sessions.
This course aims to provide participants with the strategic understanding and applied skills in planning, conducting, analyzing, and reporting findings from quantitative research. At the end of the course, participants will be able to plan, conduct, and critically assess the quality of the quantitative data gathered during their data collection process. Specifically, participants will learn how to use SPSS in Quantitative Data Analysis.
Participants will learn how to identify problems to study, develop hypotheses and research questions, specify independent and dependent variables, check for the validity and reliability of studies and design research projects. Participants will be exposed to the broad range of designs used in social science research from laboratory and field experiments, surveys, content analysis, focus groups and in-depth interviewing.
This course aims to facilitate the participant's first steps in R and equip them with the tools and understanding to expand their technical know-how according to the needs of their specific research. It is neither a computer science nor a methodological course, but aimed at the practical needs of empirically working researchers. Participants' will learn how to programme in R and how to use R for effective data analysis and visualization. The course begins with developing a basic understanding of the R working environment. Then participants are introduced to the necessary arithmetic and logical operators, salient functions for manipulating data, and getting help using R. Next, the common data structures, variables, and data types used in R, are demonstrated and applied. Participants also learn to write R scripts and build R markdown documents to share their code with others. Further, participants utilize the various packages available in R for visualization, reporting, data manipulation, and statistical analysis.
This course aims to provide participants with the strategic understanding and applied skills in planning, conducting, and analyzing, reporting findings from qualitative research. At the end of the course, participants will be able to plan, conduct, and critically assess the quality of the qualitative data gathered during their data collection process. Participants will also learn how to use NVivo 12 in Qualitative Data Analysis.
The course provides participants with a strong foundation in monitoring and evaluation, programme design and implementation. Participants will explore the variety of tools and techniques used to measure project progress and to report outcomes to the appropriate internal and external stakeholders-including donors, funders, supervisors, or the population being served. Participants will design relevant and effective frameworks, and learn the required methods to conduct effective data collection, statistical analysis, and reporting. Through the interactive sessions and through exposure to real case studies drawn from relevant organizations, participants will gain the skills needed to conduct a monitoring and evaluation programme for development organizations, NGOs, or private organizations in the development, peacebuilding, energy, gender studies, transnational security sectors among other sectors. The course introduces participants to MEAL concepts and practices. It will stimulate ideas on how to design and implement monitoring and evaluation processes that strengthen accountability and learning, and so promote project, programme and strategy effectiveness.
This course will introduce the participants to data management, data visualization and basic statistical analysis in Stata. The course requires no prior experience with Stata and would be suitable for beginners or participants wanting to refresh the core concepts. Stata is an interactive data management program and is used for the statistical analysis by statisticians, epidemiologists, economists, demographers and by researchers from most disciplines. The course will start with an introduction to Stata using the Graphical User Interface and then work using command syntax. The course will introduce Stata syntax and procedures to manage data. The course will also cover data visualizations and statistical analysis with several practical sessions. Commands for creating new variables and for modifying existing variables will also be covered. Through hand-on training, participants will be familiar with the ways to import data from different formats to Stata, export Stata to other formats, and combine several datasets. Moreover, the course will cover data visualization (E.g. histogram, bar diagram, pie-chart, scatter plot, line graph etc.) and basic analysis including descriptive statistics, correlation and regression.
through the final steps of a project - documenting lessons learned. The course underlines the importance of understanding the relationship between projects and organization’s strategic goals. It also discusses the technical, cultural, and interpersonal skills necessary to successfully manage projects from initiation to closure. It emphasises that project management is a professional discipline with its own tools, body of knowledge, and skills. Concepts are reinforced by case studies covering a wide variety of project types and industries.
Course Objectives
By the end of this program, participants should be able to:
Understand the fundamentals of qualitative research
Understand qualitative data collection and analysis methods
Appreciate the role of Atlas.ti in the research process
Set up a project in Atlas.ti and explore the function of Atlas.ti
Upload primary documents into the hermeneutic units
Undertake deductive and inductive qualitative data coding using Atlas.ti
Distinguish among open, axial and selective coding
Identify specific methods that enhance rigor in qualitative data analysis
Use Atlas.ti in data analysis following an approach emphasizing data integration, organization, and constant documentation of the process
Justify decision making with sound findings and evidence-based recommendations
Write a qualitative research report
This course aims to provide participants with the strategic understanding and applied skills in planning, conducting, and analyzing, reporting findings from qualitative research. At the end of the course, participants will be able to plan, conduct, and critically assess the quality of the qualitative data gathered during their data collection process. Participants will also learn how to use NVivo 12 in Qualitative Data Analysis.
Course Objectives
By the end of this program, participants should be able to:
Understand the fundamentals of qualitative research
Understand qualitative data collection and analysis methods
Set up a project in NVivo and explore the function of NVivo
Create, import and work with codes and nodes in NVivo
Undertake deductive and inductive qualitative data coding using NVivo
Manage all project materials conveniently in one project file.
Deliver quality outputs backed by a transparent discovery and analysis process
Justify decision making with sound findings and evidence-based recommendations
Revisit data easily, build up the big picture perspective
Write a qualitative research report
Course Objectives
By the end of the course, participants should be able to:
Understand key aspects of project design, planning, implementation, administration and Monitoring and Evaluation
Understand approaches to design, implement, monitor and evaluate projects
Link a logical framework and translate it into a concise and transparent budget and a simple work plan
Understand best practices techniques for project management, monitoring and evaluation
Understand and appreciate the use of Microsoft Project in project planning and monitoring
Many research scientists nowadays collect data through a mixed methods approach. Consequently, our world is exploding with data – text from interviews and FGDs transcripts, videos, social media and more. Making sense of it without the right research tools is like looking for a needle in a haystack. Qualitative data analysis is that process of bringing order, structure and meaning to the mass of collected data. If you are planning to conduct KIIs, IDIs or FGDs during your data collection, do participant observation or collect policy papers, press releases or Internet data from online surveys, soon or later you will have volumes of data and field notes for analysis.
This course aims to provide participants with the strategic understanding and applied skills in planning, conducting, and analyzing, reporting findings from qualitative research. At the end of the course, participants will be able to plan, conduct, and critically assess the quality of the qualitative data gathered during their data collection process. Participants will also learn how to use NVivo 12 in Qualitative Data Analysis.
Target Audience
This course targets research scientist and practitioners with basic knowledge in qualitative research but keen on updating their skills and competence in qualitative data analysis. Beginners as well as specialists in the fields of Social Sciences, Anthropology, Sociology, Community Development, Project Management, Monitoring and Evaluation, Market Research, Agriculture, Economics, Food Security and Livelihoods, Nutrition, Education, Clinical Medicine, Public Health, Health Economics, Epidemiology, Demography, Population Studies and anyone with an interest in qualitative research will benefit immensely from undertaking the course.
Course Objectives
By the end of this program, participants should be able to:
1. Understand qualitative analysis approaches
2. Understand different qualitative data collection methods
3. Set up a project in NVivo
4. Explore the function of NVivo
5. Import and create sources – PDFs, media files data sets, documents, and social media
6. Create and use classifications
7. Create, import and work with codes and nodes in NVivo
8. Undertake deductive and inductive qualitative data coding using NVivo
9. Manage all project materials conveniently in one project file, easily work with material in their own language
10. Effortlessly share their work with others
11. Easily manage their information and enhance their internal workflow and reporting processes
12. Deliver quality outputs backed by a transparent discovery and analysis process
13. Justify decision making with sound findings and evidence-based recommendations
14. Revisit data easily, build up the big picture perspective
15. Write a qualitative research report
Training Methodology
The course is designed to be highly interactive, challenging and stimulating. It will be an instructor led training and will be delivered using a blended learning approach comprising of presentations, discussions, guided sessions of practical exercise, web based tutorials, group work and exploration of relevant issues. Our facilitators are seasoned industry experts with years of experience, working as professional and trainers in these fields. All facilitation and course materials will be offered in English.
Many research scientists nowadays collect data through a mixed methods approach. Consequently, our world is exploding with data – text from interviews and FGDs transcripts, videos, social media and more. Making sense of it without the right research tools is like looking for a needle in a haystack. Qualitative data analysis is that process of bringing order, structure and meaning to the mass of collected data. If you are planning to conduct KIIs, IDIs or FGDs during your data collection, do participant observation or collect policy papers, press releases or Internet data from online surveys, soon or later you will have volumes of data and field notes for analysis.
This course aims to provide participants with the strategic understanding and applied skills in planning, conducting, and reporting findings from qualitative research. At the end of the course, participants will be able to plan, conduct, and critically assess the quality of the qualitative data gathered during their data collection process. Participants will also learn how to use NVivo 12 in Qualitative Data Analysis.
Target Audience
This course targets research scientist and practitioners with basic knowledge in qualitative research but keen on updating their skills and competence in qualitative data analysis. Beginners as well as specialists in the fields of Social Sciences, Anthropology, Sociology, Community Development, Project Management, Monitoring and Evaluation, Market Research, Agriculture, Economics, Food Security and Livelihoods, Nutrition, Education, Clinical Medicine, Public Health, Health Economics, Epidemiology, Demography, Population Studies and anyone with an interest in qualitative research will benefit immensely from undertaking the course.
Course Objectives
By the end of this program, participants should be able to:
Understand qualitative analysis approaches
Understand different qualitative data collection methods
Set up a project in NVivo
Explore the function of NVivo
Import and create sources – PDFs, media files data sets, documents, and social media
Create and use classifications
Create, import and work with codes and nodes in NVivo
Undertake deductive and inductive qualitative data coding using NVivo
Manage all project materials conveniently in one project file, easily work with material in their own language
Effortlessly share their work with others
Easily manage their information and enhance their internal workflow and reporting processes
Deliver quality outputs backed by a transparent discovery and analysis process
Justify decision making with sound findings and evidence-based recommendations
Revisit data easily, build up the big picture perspective
Write a qualitative research report
Training Methodology
The course is designed to be highly interactive, challenging and stimulating. It will be an instructor led training and will be delivered using a blended learning approach comprising of presentations, discussions, guided sessions of practical exercise, web based tutorials, group work and exploration of relevant issues. Our facilitators are seasoned industry experts with years of experience, working as professional and trainers in these fields. All facilitation and course materials will be offered in English.
Papers
The violence witnessed in Kenya in the aftermath of the 2007 disputed presidential elections shook
Kenyans into the realization that Kenya had remained a highly polarized nation since independence.
Brother turned against brother resulting in the loss of more than 1,300 lives and the displacement of more than
300,000 people. International agencies stepped in with the AU taking the lead in a bid to seek a
cessation to the violence. An agreement was finally sealed on February 28, 2008 through the KNDRC
process mediated by former UN Secretary General Kofi Annan. The agreement led to inter alia the
cessation of violence and formation of a coalition government. However, the mediation efforts could
have only done so much. There were long-term issues that needed specialized agencies to fully resolve.
With this understanding the KNDRC agreed on a number of commissions to be formed to handle these
issues.
The Commission of Inquiry into the Post-Election Violence (Waki Commission), the National Cohesion
and Integration Commission – the only permanent commission – and finally the TJRC were among
commissions formed to handle the long-term issues of the conflict. The Waki Commission in its report
recommended the formation of a Special Tribunal for Kenya to try the people suspected to bore criminal
responsibility for the PEV. However, the Special Tribunal of Kenya never saw the light of day.
Consequently, the ICC stepped in and took up the cases after the then ICC Prosecutor Moreno Ocampo
received the names of people suspected to bear criminal responsibility for the PEV from Kofi Annan.
The TJRC was finally established in 2009 to among others promote justice, healing and reconciliation in
Kenya. It was formed at a time when the ICC was in the process of confirming charges against six
Kenyans in relation to the 2007 / 2008 PEV. At the time many Kenyans viewed the TJRC as a ploy by
those in government to shield the merchants of impunity from criminal prosecution.
The TJRC problems were further compounded by the credibility crisis that faced its’ chairperson –
Ambassador Bethuel Kiplagat. The issues surrounding the chairperson threatened to tear the commission
apart and derail the truth seeking process. The crisis led to the resignation of the then vice-chairperson –
Ms. Betty Murungi. This left the TJRC with only seven commissioners when the chairperson finally
stepped aside. Throughout its’ work the commission was further plagued by financial challenges as well
as lack of political will in the truth seeking process.
The TJRC worked for four years and finally handed in its’ report in May 2013. The commissioners
noted that reconciliation is not an event but a process. Consequently, the TJRC interpreted its mandate
as being to initiate the process of reconciliation. The TJRC held a number of public hearings and
reconciliation forums to aid in the initiation of reconciliation between and among the different Kenyan
ethnic groups. The research concludes that despite the many challenges experienced by the TJRC, it did
actually lay the foundation for reconciliation. It is imperative that the government endeavours to
implement the commission’s recommendations if reconciliation is to be fully realized in the country. It
is equally important that the rule of law is observed so that the citizens can rest assured that justice and
fairness will prevail.
As a part of this PMP Certification training, you will improve your leadership skills and understand how to use standard tools & techniques to ensure all communications are clear. You will acquire skills to create an accurate project schedule and identify, access, and control project risks. You will be guided through the program by globally-renowned project management experts to earn a PMP Certification that prepares you to face the emerging new normal.
Our training courses help both individual participants hone their individual expertise and entire organizations grow continue making an impact in their different sectors of operations. Our short courses are not run-of the-mill, because we do things a little differently than other training companies you may have worked with in the past. We research skills gaps and from there we then design and develop all of our training courses in great detail with one aim in mind - to help take Course
Participants and your company to the next level. Having this capability in-house allows us to conduct an in-depth training needs analysis, pinpoint urgent skills gaps and design practical learning modules
which are highly relevant to the client’s specific working environment.
The course surveys some of the foundational topics in data science, such as data analysis, data visualization, machine Learning, and time series forecasting. The course is intended for students who wish to learn about the powerful Python data science ecosystem in order to apply data analysis techniques, information visualization, and inferential statistical analyses to gain new insights into the data. Through this course participants will learn how to manipulate, process, and clean data with Python, using its data-oriented library ecosystem and tools that will lay the foundations to allow participants become effective data analysts. Participants will learn how to conduct data science by learning how to analyze data. That includes knowing how to import data, explore it, analyze it, learn from it, visualize it, and ultimately generate easily shareable reports. The course will run with a mix of theoretical classes and hands-on sessions.
This course aims to provide participants with the strategic understanding and applied skills in planning, conducting, analyzing, and reporting findings from quantitative research. At the end of the course, participants will be able to plan, conduct, and critically assess the quality of the quantitative data gathered during their data collection process. Specifically, participants will learn how to use SPSS in Quantitative Data Analysis.
Participants will learn how to identify problems to study, develop hypotheses and research questions, specify independent and dependent variables, check for the validity and reliability of studies and design research projects. Participants will be exposed to the broad range of designs used in social science research from laboratory and field experiments, surveys, content analysis, focus groups and in-depth interviewing.
This course aims to facilitate the participant's first steps in R and equip them with the tools and understanding to expand their technical know-how according to the needs of their specific research. It is neither a computer science nor a methodological course, but aimed at the practical needs of empirically working researchers. Participants' will learn how to programme in R and how to use R for effective data analysis and visualization. The course begins with developing a basic understanding of the R working environment. Then participants are introduced to the necessary arithmetic and logical operators, salient functions for manipulating data, and getting help using R. Next, the common data structures, variables, and data types used in R, are demonstrated and applied. Participants also learn to write R scripts and build R markdown documents to share their code with others. Further, participants utilize the various packages available in R for visualization, reporting, data manipulation, and statistical analysis.
This course aims to provide participants with the strategic understanding and applied skills in planning, conducting, and analyzing, reporting findings from qualitative research. At the end of the course, participants will be able to plan, conduct, and critically assess the quality of the qualitative data gathered during their data collection process. Participants will also learn how to use NVivo 12 in Qualitative Data Analysis.
The course provides participants with a strong foundation in monitoring and evaluation, programme design and implementation. Participants will explore the variety of tools and techniques used to measure project progress and to report outcomes to the appropriate internal and external stakeholders-including donors, funders, supervisors, or the population being served. Participants will design relevant and effective frameworks, and learn the required methods to conduct effective data collection, statistical analysis, and reporting. Through the interactive sessions and through exposure to real case studies drawn from relevant organizations, participants will gain the skills needed to conduct a monitoring and evaluation programme for development organizations, NGOs, or private organizations in the development, peacebuilding, energy, gender studies, transnational security sectors among other sectors. The course introduces participants to MEAL concepts and practices. It will stimulate ideas on how to design and implement monitoring and evaluation processes that strengthen accountability and learning, and so promote project, programme and strategy effectiveness.
This course will introduce the participants to data management, data visualization and basic statistical analysis in Stata. The course requires no prior experience with Stata and would be suitable for beginners or participants wanting to refresh the core concepts. Stata is an interactive data management program and is used for the statistical analysis by statisticians, epidemiologists, economists, demographers and by researchers from most disciplines. The course will start with an introduction to Stata using the Graphical User Interface and then work using command syntax. The course will introduce Stata syntax and procedures to manage data. The course will also cover data visualizations and statistical analysis with several practical sessions. Commands for creating new variables and for modifying existing variables will also be covered. Through hand-on training, participants will be familiar with the ways to import data from different formats to Stata, export Stata to other formats, and combine several datasets. Moreover, the course will cover data visualization (E.g. histogram, bar diagram, pie-chart, scatter plot, line graph etc.) and basic analysis including descriptive statistics, correlation and regression.
through the final steps of a project - documenting lessons learned. The course underlines the importance of understanding the relationship between projects and organization’s strategic goals. It also discusses the technical, cultural, and interpersonal skills necessary to successfully manage projects from initiation to closure. It emphasises that project management is a professional discipline with its own tools, body of knowledge, and skills. Concepts are reinforced by case studies covering a wide variety of project types and industries.
Course Objectives
By the end of this program, participants should be able to:
Understand the fundamentals of qualitative research
Understand qualitative data collection and analysis methods
Appreciate the role of Atlas.ti in the research process
Set up a project in Atlas.ti and explore the function of Atlas.ti
Upload primary documents into the hermeneutic units
Undertake deductive and inductive qualitative data coding using Atlas.ti
Distinguish among open, axial and selective coding
Identify specific methods that enhance rigor in qualitative data analysis
Use Atlas.ti in data analysis following an approach emphasizing data integration, organization, and constant documentation of the process
Justify decision making with sound findings and evidence-based recommendations
Write a qualitative research report
This course aims to provide participants with the strategic understanding and applied skills in planning, conducting, and analyzing, reporting findings from qualitative research. At the end of the course, participants will be able to plan, conduct, and critically assess the quality of the qualitative data gathered during their data collection process. Participants will also learn how to use NVivo 12 in Qualitative Data Analysis.
Course Objectives
By the end of this program, participants should be able to:
Understand the fundamentals of qualitative research
Understand qualitative data collection and analysis methods
Set up a project in NVivo and explore the function of NVivo
Create, import and work with codes and nodes in NVivo
Undertake deductive and inductive qualitative data coding using NVivo
Manage all project materials conveniently in one project file.
Deliver quality outputs backed by a transparent discovery and analysis process
Justify decision making with sound findings and evidence-based recommendations
Revisit data easily, build up the big picture perspective
Write a qualitative research report
Course Objectives
By the end of the course, participants should be able to:
Understand key aspects of project design, planning, implementation, administration and Monitoring and Evaluation
Understand approaches to design, implement, monitor and evaluate projects
Link a logical framework and translate it into a concise and transparent budget and a simple work plan
Understand best practices techniques for project management, monitoring and evaluation
Understand and appreciate the use of Microsoft Project in project planning and monitoring
Many research scientists nowadays collect data through a mixed methods approach. Consequently, our world is exploding with data – text from interviews and FGDs transcripts, videos, social media and more. Making sense of it without the right research tools is like looking for a needle in a haystack. Qualitative data analysis is that process of bringing order, structure and meaning to the mass of collected data. If you are planning to conduct KIIs, IDIs or FGDs during your data collection, do participant observation or collect policy papers, press releases or Internet data from online surveys, soon or later you will have volumes of data and field notes for analysis.
This course aims to provide participants with the strategic understanding and applied skills in planning, conducting, and analyzing, reporting findings from qualitative research. At the end of the course, participants will be able to plan, conduct, and critically assess the quality of the qualitative data gathered during their data collection process. Participants will also learn how to use NVivo 12 in Qualitative Data Analysis.
Target Audience
This course targets research scientist and practitioners with basic knowledge in qualitative research but keen on updating their skills and competence in qualitative data analysis. Beginners as well as specialists in the fields of Social Sciences, Anthropology, Sociology, Community Development, Project Management, Monitoring and Evaluation, Market Research, Agriculture, Economics, Food Security and Livelihoods, Nutrition, Education, Clinical Medicine, Public Health, Health Economics, Epidemiology, Demography, Population Studies and anyone with an interest in qualitative research will benefit immensely from undertaking the course.
Course Objectives
By the end of this program, participants should be able to:
1. Understand qualitative analysis approaches
2. Understand different qualitative data collection methods
3. Set up a project in NVivo
4. Explore the function of NVivo
5. Import and create sources – PDFs, media files data sets, documents, and social media
6. Create and use classifications
7. Create, import and work with codes and nodes in NVivo
8. Undertake deductive and inductive qualitative data coding using NVivo
9. Manage all project materials conveniently in one project file, easily work with material in their own language
10. Effortlessly share their work with others
11. Easily manage their information and enhance their internal workflow and reporting processes
12. Deliver quality outputs backed by a transparent discovery and analysis process
13. Justify decision making with sound findings and evidence-based recommendations
14. Revisit data easily, build up the big picture perspective
15. Write a qualitative research report
Training Methodology
The course is designed to be highly interactive, challenging and stimulating. It will be an instructor led training and will be delivered using a blended learning approach comprising of presentations, discussions, guided sessions of practical exercise, web based tutorials, group work and exploration of relevant issues. Our facilitators are seasoned industry experts with years of experience, working as professional and trainers in these fields. All facilitation and course materials will be offered in English.
Many research scientists nowadays collect data through a mixed methods approach. Consequently, our world is exploding with data – text from interviews and FGDs transcripts, videos, social media and more. Making sense of it without the right research tools is like looking for a needle in a haystack. Qualitative data analysis is that process of bringing order, structure and meaning to the mass of collected data. If you are planning to conduct KIIs, IDIs or FGDs during your data collection, do participant observation or collect policy papers, press releases or Internet data from online surveys, soon or later you will have volumes of data and field notes for analysis.
This course aims to provide participants with the strategic understanding and applied skills in planning, conducting, and reporting findings from qualitative research. At the end of the course, participants will be able to plan, conduct, and critically assess the quality of the qualitative data gathered during their data collection process. Participants will also learn how to use NVivo 12 in Qualitative Data Analysis.
Target Audience
This course targets research scientist and practitioners with basic knowledge in qualitative research but keen on updating their skills and competence in qualitative data analysis. Beginners as well as specialists in the fields of Social Sciences, Anthropology, Sociology, Community Development, Project Management, Monitoring and Evaluation, Market Research, Agriculture, Economics, Food Security and Livelihoods, Nutrition, Education, Clinical Medicine, Public Health, Health Economics, Epidemiology, Demography, Population Studies and anyone with an interest in qualitative research will benefit immensely from undertaking the course.
Course Objectives
By the end of this program, participants should be able to:
Understand qualitative analysis approaches
Understand different qualitative data collection methods
Set up a project in NVivo
Explore the function of NVivo
Import and create sources – PDFs, media files data sets, documents, and social media
Create and use classifications
Create, import and work with codes and nodes in NVivo
Undertake deductive and inductive qualitative data coding using NVivo
Manage all project materials conveniently in one project file, easily work with material in their own language
Effortlessly share their work with others
Easily manage their information and enhance their internal workflow and reporting processes
Deliver quality outputs backed by a transparent discovery and analysis process
Justify decision making with sound findings and evidence-based recommendations
Revisit data easily, build up the big picture perspective
Write a qualitative research report
Training Methodology
The course is designed to be highly interactive, challenging and stimulating. It will be an instructor led training and will be delivered using a blended learning approach comprising of presentations, discussions, guided sessions of practical exercise, web based tutorials, group work and exploration of relevant issues. Our facilitators are seasoned industry experts with years of experience, working as professional and trainers in these fields. All facilitation and course materials will be offered in English.