Research report

Research report Report writing is the last step in the research process. In this step the researcher has to write a complete report of scientific research undertaken. Research report is the process of communicating the results and the care that has been exercised throughout the study. In general, research report is a detailed account of the study conducted or systematic report of the findings of a research which describes the process and the data used in the study. Components of a research report Normally, the research report should have the following format as shown in the Table below;

Section	Description
Preliminaries
Title Page	Contains the title of the research, researcher’s name, institution, and date of submission.
Abstract	A concise summary of the research, including the research problem, methodology, key findings, and conclusions.
Table of Contents	Lists all the chapters and sections in the report with their page numbers.
List of Figures and Tables	Provides a list of all figures and tables used in the report along with their page numbers.
Certification	A statement confirming the originality and authenticity of the research, signed by the researcher and supervisor.
Declaration	A declaration by the researcher stating the originality of the work and confirming it is their own.
Dedication	A brief statement where the researcher dedicates the report to someone or something important.
Acknowledgements	Expresses gratitude to individuals, institutions, and others who contributed or supported the research.
Acronyms/Abbreviations Used	A list of all abbreviations and acronyms used in the report, with their full meanings.
Chapter 1: Introduction
Background to the Research Problem	Provides context and background information on the research topic.
Statement of the Research Problem	Clearly defines the research problem, outlining the issue or challenge the research aims to address.
Research Hypotheses or Questions	Lists the hypotheses or research questions that guide the study.
Objectives of the Study	Defines the specific goals the research aims to achieve.
Significance of the Study	Explains the importance and potential impact of the research on the field or society.
Scope of the Study	Describes the boundaries and limitations of the research.
Chapter 2: Literature Review
Related Works	Discusses previous research and studies that are relevant to the research topic.
Key Ideas and Theories	Presents the theoretical framework and key concepts related to the study, helping to position the current research in the context of existing knowledge.
Chapter 3: Methodology
Research Procedures	Describes the methods and procedures used in conducting the research, such as qualitative or quantitative approaches.
Data Collection	Explains how data was gathered, including tools, instruments, and techniques used (e.g., surveys, interviews, experiments).
Data Organization, Analysis, and Presentation	Outlines how data was organized, processed, and analyzed, including any software or statistical tools used.
Chapter 4: Results and Discussion
Results	Presents the research findings, often using tables, graphs, and charts.
Discussion	Interprets the meaning of the results, comparing them with findings from other sources and research. It also highlights any significant patterns, trends, or conclusions.
Conclusion of Each Subsection	Provides conclusions based on each part of the discussion, summarizing key findings and their implications.
Chapter 5: Summary, Conclusion, and Recommendations
Summary	A brief overview of the major findings and the key points discussed in the report.
Conclusion	Interprets the research findings, answering the research questions and explaining their significance.
Recommendations	Offers suggestions for action based on the research findings, highlighting who should take action and how.
Suggestions for Further Study	Identifies areas that require further investigation or research.
References	A list of all sources cited in the report, such as books, articles, and websites, arranged alphabetically.
Appendices	Includes additional materials such as research tools (surveys, interview questions), raw data, tables, photographs, and any other relevant information that supports the study.

Research process In order to study and solve a problem, a research has to undergo several stages in a well regulated and systematic manner. Failure in any stage is likely to affect the whole research process. In order to work systematically, a research process or stages goes through a series of actions which are:

1. formulation of research problem
2. Review of the literature
3. Hypothesis formulation and research questions
4. Research design
5. Target population, sample and sampling techniques
6. Sampling techniques
7. Data collection
8. Data analysis and presentation
9. Hypothesis testing
10. Generalizations and Interpretation

Formulating the research problemFormulating of a research problem is an important step that will uncover what problem is worthy studying by explaining clearly what has been documented, what has not been documented and what needs to be documented. The main function of a research problem is to determine what needs to be researched. Basically, the main sources of a research problem include conversation with people you can gain insight and find out the existing imbalances, research gaps and issues to be researched. Moreover, a research problem can be identified by exploring the interventions and programs that have been in place. Therefore, through critical studying in such areas one may decide to evaluate the effectiveness of one of those interventions. Another way of establishing a research problem is based on experiences evaluating some existing phenomena and establishing some areas worth to be researched. As a starting point in thinking how to develop a research problem the following sample of a research problem can be useful guides to you: Sample : It is an acceptable fact that the impact of climate change is affecting all people equally but different in different parts of the world with slightly variations across gender differences. Most of the studies have documented on how women have been affected by the impact of climate change and associated adaptation measures. However, there are limited studies on the extent of impact of climate change to the elderly population and the adaptation measures to this social age group. Failure to document this area means that the vulnerability to the impact of climate change and social disturbance will keep on increasing and many of the elderly in society will be negatively affected. Therefore, this study is an attempt to that end. Considerations in selecting a research problem For manageable and sustainable motivation, a researcher should consider the following when selecting a research area or a research problem.

1. Firstly, interest in the area make the researcher to be motivated throughout the research process.
2. Secondly, it is important to consider the magnitude of the selected topic. This will enable the researcher to balance time and resources for completing the study on time. Therefore, a researcher is required to narrow down the topic hence make it manageable, specific and clear.
3. Thirdly, the researcher should make sure that the indicators and concepts studied are measurable and verifiable.
4. Fourthly, the researcher should have adequate and appropriate research knowledge and skills to address the problem to be studied.
5. Fifthly, the researcher should focus on a relevant research problem that is likely to fill the existing knowledge gap, add new knowledge and improve practices in the researched area. This will be an additional aspect to sustain the interest of the study.
6. Sixthly, consideration of ethical issues in relation to the area the researcher plans to study is of great importance. This item requires the researcher’s professionalism and flexibility especially when the previous plans affected the research ethics.

Criteria for a good research problem There are a number of criteria that need to be considered in writing a research problem. A good research problem is likely to adhere to the following qualities:

1. Firstly, it should be novel that, the problem should come up with a new process, product or principle that can help in improving practices.
2. Secondly, it should be interesting in the sense that it draws attention and interest to other people.
3. Thirdly, it should be innovative meaning that it improves the current or existing state of affairs and possibly technology.
4. Fourthly, it should be cost effective in such a way that it  produces good value for money, time and resources. It should be addressing the problem of the community.

Challenges of Writing a Research Problem

1. Lack of Understanding Many people may not fully understand what a research problem is. They may confuse it with a general topic instead of focusing on a specific issue to solve.
2. Choosing a Clear Topic people often struggle to narrow down a broad subject into a clear and manageable research problem. For example, instead of studying "climate change," they might need to focus on "the effects of climate change on rice farming in Tanzania."
3. Limited Knowledge people may not know enough about their topic to identify a meaningful problem. This makes it hard to find something worth researching.
4. Finding Relevant Information It can be challenging to find enough background information or data about the problem, especially when resources like books or internet access are limited.
5. Connecting to Real-Life Issues Some people find it hard to link their research problem to real-life situations in their community, which can make their research less impactful.
6. Overthinking or Oversimplifying people may either overcomplicate the research problem or choose something too simple that doesn’t require much investigation.
7. Language Barriers Writing the research problem in clear, formal language can be difficult, especially when English is not their first language.
8. Lack of Guidance Without proper guidance from teachers or supervisors, students may feel unsure about how to frame their research problem correctly.
9. Fear of Making Mistakes Some people worry that their problem might not be "good enough," which can make them hesitant to start.
10. Time Constraints Writing a good research problem requires time to think, read, and plan. people often feel rushed and may not give it the attention it needs.

Research objectives A good literature review can be distinguished by several criteria.

1. First of all, a literature review should be capable of outlining the important study trends showing the current situation, information and documentation done in the area being studied.
2. The second criterion is that, literature review needs to assess the strengths and weaknesses of the existing researches in different orientations including whether methodological approaches used in the existing studies they were relevance or not. Furthermore, literature review should assess the strengths and weaknesses of arguments, conclusions and assumptions made by the existing studies.
3. The third criterion is that, literature review should be capable of identifying knowledge gaps from the existing studies. In other words, literature review should not be written plainly that is, agreeing with most of the past literature in their entire dimension. In this case there would be no need of conducting another one because it will be a duplication of the research unnecessarily and wastage of resources and time.
4. The fourth criterion is that, a good literature review should be based on most recent existing literature of which one can establish research gap and position their work among other related studies.

Review of the literature Once the problem is formulated, a brief critical review and summary of it should be written down. At this point, the researcher should undertake extensive literature survey connected with the problem. Literature review is concerned with reading of various previously related publications in order to enable a researcher to be aware of how other researchers have addressed the same or related research problem. Literature review helps to avoid unnecessary repetition of studies which have already been conducted. It helps the researcher to redefine his or her research problem, to select appropriate sample, appropriate tools and the research design. Generally, literature review is important in clarifying and focusing the research problem; and in sharpening the research methods that you will use in your study by looking at how others have used them. Literature review will also enable the researcher to broaden knowledge in the selected area to situate the study against other related research to avoid duplication. Furthermore, it helps to identify the research gap and challenges likely to face the research process. A good literature review can be distinguished by several criteria.

1. First of all, a literature review should be capable of outlining the important study trends showing the current situation, information and documentation done in the area being studied.
2. The second criterion is that, literature review needs to assess the strengths and weaknesses of the existing researches in different orientations including whether methodological approaches used in the existing studies they were relevance or not. Furthermore, literature review should assess the strengths and weaknesses of arguments, conclusions and assumptions made by the existing studies.
3. The third criterion is that, literature review should be capable of identifying knowledge gaps from the existing studies. In other words, literature review should not be written plainly that is, agreeing with most of the past literature in their entire dimension. In this case there would be no need of conducting another one because it will be a duplication of the research unnecessarily and wastage of resources and time.
4. The fourth criterion is that, a good literature review should be based on most recent existing literature of which one can establish research gap and position their work among other related studies

To sum up literature review acts as a lock and key that well specifies the research gap. In this part you will be in a better position to know what is needed in the research you are conducting, where to conduct it, and how your findings fill in the gap you have established. Hypothesis formulation and research questions After extensive literature survey, a researcher should state in clear terms the working hypothesis. Hypothesis is a tentative assumption made in order to draw out and test its logical or empirical consequences. It is a tentative statement about the relationship between two or more variables. It provides the focal point for research, guide the researcher by delimiting the areas of research and keep him/her on the right track. Hypothesis also indicates type of data required, methods of data analysis and draws conclusion. Basically, there are two types of hypotheses;

1. null hypothesis
2. alternative hypothesis

Null hypothesis is stated in a negative way or by using negative statement for example, there  is no relationship between population  growth and development; rate of survival  will not increase after surgery; a high  cholesterol intake is not associated with  development (risk) of cancer; smoking  is not a cause of cancer; existence of  informal institutions is not associated  with minimal conflicts in project areas Alternative hypothesis is stated to indicate the actual expectation or relationship. It is usually a positive statement about certain variables, for example, there is a relationship between  truancy in schools and poor performance  in academics; Other examples, the rate of survival will increase after surgery; a high cholesterol intake is associated with the development of heart disease; cigarette smoking is a cause of cancer; existence of informal institutions in water projects is associated with minimal conflicts in the project areas. Generally, there are many sources that can enable a researcher to formulate a hypothesis. The main sources of hypothesis formulation include personal experiences, imagination and thinking, observation of phenomena, scientific theories, reviewing previous studies and cultural disposition. A good stated hypothesis can be identified by observing the following criteria:

1. it should be stated in the simplest terms which ensure easy understanding by others
2. it should not conflict with any law of nature which is known to be true
3. it permits the application of desirable reasoning.
4. it should be limited in scope
5. must be specific
6. it should be capable of being tested within specific time
7. should allow the application of deductive reasoning.

Research questions Research questions are the specific issues that the study wants to investigate from data collection and that data will answer them. In writing research questions, one can replace the first words used in the hypothesis “There is” with the words “Is there”  and also replacing the period with question mark. For examples, Is there  any relationship between population growth and development? Types of research questions There are three types of research questions which are;

1. Firstly**,** a descriptive research question; this seeks to identify and describe some phenomenon. Will the rate of survival increase after surgery?
2. Secondly, a For example differences : research question; this asks if there are differences between groups on some phenomenon. For example: do students who engage in remedial classes perform better than students who engage in sports activities?
3. Thirdly, a relationship research question; this asks if two or more phenomena are related in some systematic manner. For instance, Is the existence of informal institutions associated with minimal conflicts in the areas?

Research design Research design is concerned with a systematic and well-planned means for conducting a research. It is a systematic way of finding out new knowledge. A research design is a conceptual structure for conducting the research. Preparation of the research design will smoothen the processes of sampling, methods and tools for data collection, analysis, interpretation and reporting. It will also reduce unnecessary expenditure by having predefined activities and resources. Usually, research designs vary with varying nature of studies. The commonly used research design are, ‘snap-shot’ or baseline sometimes called case-study, cross-sectional, longitudinal and experimental research design. Snap-shot or baseline is concerned with in-depth studies aimed at searching of the current and past behaviors and experiences for a single person, family, group, or organization. Usually, the findings from this kind of design cannot be generalized. Cross-sectional research design is a survey design in which data are collected at one point in time from a predetermined population. Data from this design is normally used to describe the characteristics of the studied sample with regard to the population when data were collected. Longitudinal research design is a form of survey in which data from the same area is collected at different time interval for the sake of investigating the changes of a studied population over time. It can be after several months or years. experimental research design can be used to establish cause - effect relationships between the independent and dependent variables by means of manipulating the variables studied through controlling them or randomization. Alternatively, the studies conducted by using this design can compare groups that are closely related or introduce an intervening variable from which a researcher can examine changes among the groups. For example, studying two groups in which one of the two was intervened with an activity or project and the other not subjected to an activity. Target population, sample and sampling techniques In statistical geography, sampling is concerned with the selection of a subset of elements or individuals from a population to estimate characteristics of the whole population (also, known as target population or universe). Each observation measures one or more properties (such as weight, location or colour) of observable bodies distinguished as independent objects or individuals. Below are important definitions of the commonly terminologies used in studies dealing with population.

1. Target populationThis is entire population that the results of the survey should be representing. The target population can be the entire country, region, district, intervened villages, cropland or rivers or cattle. Normally, the sample is selected from the target population. For the case of smaller population, it is advised to study the entire population.
2. ElementsThese include individual persons, objects, or units about which information is collected. Thus, totality of elements forms population.
3. SampleThe sample is also known as the subset of the target population because it is selected from the population. It is also referred to as the composition of the set of elements from the population. It must be selected according to principles of sampling and this will make it a more representative of the total population.
4. Sample Size: is a proportional set of elements selected from the target population. Often in probability studies it is recommended that sample to be optimal enough for data collection. Too small size is likely to increase errors in the data collected while too large sample size will have implications on time and cost. However it is generally recommended that sample size should be proportional to the size of population in case of finite universe. That is the larger the population, the larger the sample and the smaller the population the smaller the sample. In probability studies sample size can be estimated by using scientific methods as shown in the formula
   • • • • • For the finite populationThe formula is:
         $$$$

n = \frac{N}{1 + N(e)^2}

Where; *n* = sample size, *N* = population size (for example total households), and *e* = the level of precision (desired margin of error) - For infinite populationThe formula is: $$ n = \frac{Z^2 \times p (1 - p)}{e^2}

 Where;
 *Z*= the area under the normal curve corresponding to the defined level of confidence;
 p*=* the true share of the population that displays a certain characteristic (for example, female population)
 *e* = the desired margin of error

5. Sampling frameis a list of units in the population, for example a register of workers at an X secondary school in Mwanza, students’ enrollment from the attendance register, group members in sports and list of pastoralists in ward or village Y. The sampling frame should be checked from time to time to avoid people who were not in the list to be counted. The list should also be updated as required. For instance, it is better to get the sampling frame from the studied village rather than depending on the census survey which may sometimes be out of date.

Sampling techniques Sampling is a process of selecting a representative of a population from which the data will be drawn on behalf of the entire population. Carefulness is crucial at this stage as the researcher narrows the data source to the sample. Dealing with a sample is rewarding in many ways. The appropriately selected sample will save resources and time; ensure accuracy and produce manageable data. A well-designed sample can represent the intended population. The major categories of sampling techniques are

1. probability sampling
2. non-probability sampling

Probability sampling It is a method of selecting sample whereby every individual in the population has equal chance of being selected. Probability methods include;

1. simple random sampling
2. systematic sampling
3. stratified sampling
4. cluster sampling
5. multistage sampling

Simple random sampling technique It is the basic sampling technique whereby each member from the population has an equal chance of being chosen. Each individual is chosen entirely by chance and each member of the population has an equal chance of being included in the sample. Systematic sampling technique Systematic sampling is a random sampling technique in which members from a larger population are selected based on regular interval and systematic order. Thus, a sampling interval is required. Stratified sampling technique This is a probability sampling technique whereby the researcher divides the entire population into different sub-groups or strata, then randomly selects the final proportionally from different strata. The population is based on strata. Stratification is the process of dividing members of the population into homogeneous subgroups before sampling. Every element in the population must be assigned to only one stratum; then simple random sampling or systematic sampling is applied within each stratum. Cluster sampling technique It is a method of sampling used when the total area of interest is large. The sample is obtained by dividing the area into a number of small non- overlapping areas and then samples are selected randomly from these smaller areas called clusters .This is applied when the entire population is unclear or unknown and the sample clusters are geographically convenient. When the clusters are natural in a population, cluster sampling is less expensive and quicker. Cluster sample permits each accumulation of large samples. The loss of precision per individual case is compensated by the possibility of studying larger samples without extra cost. A cluster sampling procedure enables obtaining information from one or more areas. In a cluster sampling, each cluster may be composed of unit that are not similar. This pattern has a likelihood of producing large sampling error and reduce the representatives of the sample. In cluster sampling, when unequal size of some of the subsets is selected, an element of sample bias will rise. This type of sampling does not allow generalization of its findings to another area example in the diagram below there are six clusters; A, B, C, D, E, and F where two clusters C and F have been randomly picked. Multi-stage sampling technique Multi-stage sampling is concerned with taking samples of preceding random samples. This sampling technique is more complex than cluster sampling which contains two or more stages in a sample selection. In simple terms in multi-stage sampling large clusters of population are divided into smaller clusters in several stages in order to make primary data collection more manageable . This technique is effective in primary data collection from geographically dispersed population when face-to-face contact is required. It is also time and cost effective and has high level of flexibility. However, it has limitations such as, high level of subjectivity, lack representation of a population and complex planning and administrative issues are required to accomplish. Non probability sampling This is a type of sampling in which members of the population have equal chance of being included in the sample. Members to be included in a sample are chosen from the population in some non-random manner. Non probability sampling consists of

1. quota sampling,
2. convenience sampling
3. purposive sampling
4. snowball sampling
5. voluntary (self-selected) sampling

Quota sampling technique Under quota sampling the interviewers are simply given quotas to be filled from different strata with some restrictions on how they are to be filled. In other words, the actual selection of the item for the sample is left to the interviewer’s discretion. For example, the researcher may be asked to draw a sample of 35 females and 45 males aged between 45 and 60 from a certain population. The technique lacks the representativeness and it is biased. Convenience sampling technique This is the type of non-probability sampling method which is applied when the members of the population are convenient to the sample. Convenience sampling is also known as grab or opportunity sampling or accidental. In this technique, most of the elements in a population that happens to be present at the time of conducting research are selected for study. The researcher opts for it when he/she is interested in obtaining information cheaply. Like many other non-probability sampling it faces the limitation of lacking representativeness and it is subjected to biasness. Purposive sampling technique This is the type of non-probability sampling where a researcher selects only those cases, thought to be typical characteristics of the population. Purposive sampling is also known as judgmental sampling. The researcher selects the samples based purely on the self knowledge and credibility. In other words, researchers choose only those people whom they deem fit to participate in the study. It is one of the most cost and time-effective sampling methods available. However, the technique has the following limitations: vulnerability to errors in judgment by researcher, low level of reliability and high level of biasness which subjects the research to inability to generalize research findings. Snowball sampling technique Snowball sampling is a special non probability method used when the desired sample characteristic is rare. It may be extremely difficult or cost prohibitive to locate respondents in these situations. It relies on referrals from initial subjects to identify additional subjects. This technique is preferable in sensitive areas like drug abuse, domestic violence and investigative studies on sex workers. Though the costs of conducting research are lowered; however, it introduces biasness because the technique itself reduces the likelihood that the sample will be representative of the entire population. Data collection Proper planned methods and tools for data collection is one among the means for increasing accuracy, correctness, precision and validity of data to be collected. Data collection is a fieldwork where the researcher goes to the field and collects facts expected to answer the identified problem. Data collection methods Data may be collected from

1. primary sources.
2. secondary sources.

Primary data are the data collected directly from the field by the researcher using his or her own sense organs such as, mouth, eye, ear, skin and nose. They are first-hand data collected through the use of various methods such as survey, observation, interview, focus group discussion and documentary review or measurement. Secondary data refers to data collected by the researcher from existing sources such as books, magazines, pamphlets, journal articles and other unpublished documents. These are second hand information obtained from already made material or documents. Methods for data collection are defined depending on mode of conducting research and types of data collected. Data collection tools also known as instruments for data collection stands for various pre-designed means for capturing data in the field. The research tools are classified with respect to the data collection methods. The following are data collection methods:

1. household survey
2. interview
3. Focus group discussion (FGD)
4. observation
5. Transect walk

Household survey Household survey is a method of collecting data achieved by asking a sample of participants questions in order to get information about a population represented by the sample. Usually, it has slightly different names depending on the type and extent of data required. The data collection instrument in the household surveys is called questionnaire. The questionnaire can be divided into

1. structured
2. unstructured.

Structured questionnaire refers to systematically prepared questions in a written form with a range of pre-determined response (options/answer) that the respondent can select. The prepared questions with answers are called closed-ended questions unstructured questionnaire the same questions are composed but mostly dominated with open-ended questions.   Survey Questionnaire Sample

Question	Response Options
1. Are you the head of the household?	☐ Yes ☐ No
2. Total number of members in your household:	Male: _______________ Female: _______________ Grown-ups (>18 years): _______________ Children (<18 years): _______________
3. Level of education of the household members:	☐ 1. Illiterate ☐ 2. Primary ☐ 3. Secondary ☐ 4. Above
4. How many members have been employed?	_______________
5. Information on employment of the household head:	☐ 1. Unemployed ☐ 2. Petty trade ☐ 3. Civil servant ☐ 4. Own business ☐ 5. Private employee ☐ 6. Other (please specify): _______________
6. The average monthly income in the household:	☐ 1. Less than Tsh 50,000 ☐ 2. Tsh 50,001 - 100,000 ☐ 3. Tsh 100,001 - 500,000 ☐ 4. Tsh 500,001 - 1,000,000 ☐ 5. Greater than Tsh 1,000,000
7. How often do family members watch Television?	☐ 1. > 3 hours daily ☐ 2. Every day ☐ 3. Once a week ☐ 4. Once a month ☐ 5. Almost never
8. Do you think the media has raised awareness on solid waste management?	☐ 1. Yes ☐ 2. No (If yes, continue to Question 9, if not, continue to Question 10)
9. Which mass media has been most useful for you in raising awareness?	☐ 1. Radio ☐ 2. Television ☐ 3. Newspaper ☐ 4. Social media (WhatsApp/Facebook/Instagram/Twitter) ☐ 5. Mobile short message service (SMS)
10. Where do you normally store your household waste?	Storage Type: ☐ Pit/rubbish halls: _______________ (Number of days per week) ☐ Plastic bags: _______________ (Number of days per week) ☐ Other (please specify): _______________ _______________

  Usually, structured questionnaires are tedious to prepare but easy to fill in. They are easy to analyze and more efficient when dealing with large sample. On the contrary, unstructured questionnaires are easy to construct since they are dominated with open ended questions but difficult for the respondents to fill in cases when they are required to do it on their own time. The questionnaire can be administered to the respondents in different ways commonly through face-to-face interaction which is helpful in overcoming language barriers and influencing good response rates. However, it is time and resource consuming. Other methods are phone call and mailing or posting questionnaires in websites but the methods are more challenging in terms of response rates and managing language barrier which has additional limitation related to the unguaranteed turn-up of answered questionnaire. Interview Key informant interview is mainly concerned with collecting qualitative data from skilled people on the topic not based on their educational knowledge and level but their stake on the topic investigated. For example, if the research is about assessing the effectiveness of a given project, the research should involve people from the government or private institutions who in one way or another were involved in some activities during implementation of the project. When dealing with the key informant interview, the interview guides are the main instruments used in collecting data from experienced people in the field with regard to the study conducted. Through in this method, data will solely be qualitative, challenging to analyze and cannot be generalized. The following is an example of the key informant interview guide for assessing the effectiveness of the project. Focus group discussion (FGD) Focus group discussion is concerned with collecting qualitative data from a small sample, often homogeneous group of people within the studied population to explore their ideas on a particular topic based on their life experiences. The group should not be too large to allow everyone to have a chance to participate and should not take long time. The group should also not be very small to allow wide range of ideas from group members. The method is recommended when the researcher aims at not only collecting interesting information, but also identifying issues and themes that are related to the objectives of the research be conducted. Generally, the focus group discussion is impractical in situations where the language barriers cannot be controlled, the researcher has little control over the situation; trust among the participants cannot be established; and free expressions and confidentiality cannot be ensured. In this method, checklist is used in data collection. The following is an example of focus group discussion checklist. Focus Group Discussion Checklist

Focus Group Discussion Checklist
1. What are your opinions about the ongoing water project management practices in your village?
2. Are you satisfied with the way village water project management is done?
3. What is going well in the village with the project management?
4. What is not going well in the project management that you are dissatisfied with?
5. What kind of things would you like to see happening?
6. How about the issue of transparency among the water committee leader entrusted with overseeing the project and collecting revenue? How about accountability? What do you think about these?
7. Some people have said that one way to improve X is to do Y. Do you agree with this? (Or, how do you feel about that?)
8. Are there other recommendations that you would like to make?
9. Are there any other things you would like to say before we wind up?
Follow-up Prompts for Discussion:
- Can you say more about that?
- Can you give an example?
- Jane says X. What is your opinion on that?

Interview Guide for the Key Informant

Question	Response Options/Guidelines
1. Name of institution	_______________________________ Date: ___________________
2. What is your current position?	_______________________________
3. Are you a focal person in the climate change adaptation implemented in village X?	☐ Yes ☐ No
4. Based on your participation in the project, what is your opinion on the impact of the project on livelihood and the environment?	_______________________________
5. With respect to your response in question 4, what is the most important factor that motivated people in the project area to participate in the associated activities?	_______________________________
6. Did the project sustainably empower the community? If so, how?	_______________________________
7. In your opinion, what are the main reasons for some villagers to drop the activities in the project?	_______________________________
8. What should be done to sustain the project activities?	_______________________________
9. In your opinion, was the project gender-responsive?	☐ Yes ☐ No Please explain: __________________________

Observation method Observation is a data collection method in which a researcher collects information in the field-based on visualization. Tools used for data collection are observation guide, recording sheet and field notes. The observation guide can be divided into

1. semi-structured observations guides.
2. structured observations guides.

Normally, observation method and the associated tools are opted when there is a need for direct information, to understand the ongoing behavior. There is physical evidence, products, activities or outputs that can be observed and need for alternative data in cases other means of data collection seem to be impractical. The following is an example of semi-structured observation guide for forest surveillance activity in a given forest studied; Semi-Structured Observation Guide

Semi-Structured Observation Guide
1. Who is taking part? List the participants involved in the activity (e.g., community members, environmental staff, volunteers, etc.).
2. Number of participants Total number of participants: __________
3. Nature of the activity and forest surveillance Describe the type of activity being conducted, such as patrols, monitoring wildlife, collecting data, etc.
4. Time and location of the activity Time: __________ Location: __________
5. How is the activity organized? Describe how the activity is structured (e.g., roles, stages of the activity, schedule).
6. What are the roles of participants and responsibilities? Outline specific roles (e.g., lead surveillor, data recorder, patrol member) and responsibilities (e.g., report findings, monitor specific areas).
7. Who makes decisions and for whom? Identify who is in charge of decision-making (e.g., project leader, community leader) and the group that follows the decisions.
8. Are the resources made available to the environmental surveillance team? List the resources provided, such as special equipment (e.g., GPS devices), mobile phones, and means of transport (e.g., vehicles, motorcycles).

beneficial in collecting direct and real time data still it has some limitations such as it is observer biased, potentially unreliable, interpretation and coding challenges; sampling can be a problem and it can be labor intensive. Transect walk Transect walk is a team-based field walk along a defined path (transect) across the community or project area together with the local people often for the sake of collecting geographical data on various aspects by observing, asking, listening, watching and at the end producing a transect map or diagram. The data collection tools in this method include observation guide, recording sheet and field notes. Transect walks are usually preferred when the researcher is interested in collecting direct data by observing people, surroundings and resources in their natural settings. However, this data collection method demands good observation skills. Data analysis and presentation After the data has been collected, the researcher has to do analysis. The researcher should classify and organize the raw data into some purposeful and usable categories. Data analysis involves recording and storage of data in a computer. For quantitative data will be followed by computing mean, mode, median, range and standard deviation where required. The analyzed data are presented in various formats such as tables, graphs, charts and maps, while qualitative data are grouped in themes or topics. However, in case of qualitative data, this can be analyzed through thematic and content analysis. Thematic analysis emphasizes on identifying, analyzing and interpreting the pattern of meaning of themes within qualitative data. Content analysis examines patterns in communication in a systematic manner. The purpose of data presentation is to display the results in a presentable manner to enable easy interpretation and report writing. Hypothesis testing In this stage the researcher finds out whether the facts from the field support the formulated hypothesis. Meaning that, research results obtained from the field are used to make decisions whether they support the hypothesis or not. On testing the hypothesis, two possible outcomes are expected, that is, the findings may support or not support the hypothesis. In case the findings do not support the hypothesis, new hypotheses can be formulated, restarted basing on the findings and re-tested. In case the results are supported by the hypothesis you can go directly to generalization. Generalizations and Interpretation If a hypothesis is tested and supported several times, it can increase confidence to the researcher in arriving to generalization and building a theory. As a matter of fact, the real value of research lies in its ability to arrive at certain generalizations. As researcher who has no hypothesis to test might seek to explain the findings on the basis of some relevant theory or theories that underpinned the study. Finally, the researcher has to prepare the report of the findings.