Research is a careful and detailed study into a specific problem, concern, or issue using the scientific method.
Research may be very broadly defined as systematic gathering of data and information and its analysis for advancement of knowledge in any subject.
Characteristics of research
Characteristics of research include the following:
Empirical – research is based on direct experience or observation by the researcher.
Logical – research is based on valid procedures and principles.
Cyclical – research starts with a problem and ends with a problem.
Analytical – research utilizes proven analytical procedures in gathering data, whether historical, descriptive, experimental, and case study.
Critical – research exhibits careful and precise judgment.
Methodical – research is conducted in a methodical manner without bias using systematic method and procedures.
Replicability – research design and procedures are repeated to enable the researcher to arrive at valid and conclusive results.
Types of research
There are three main types of research as described below:-
Basic research
Basic research, also called pure research or fundamental research, is a scientific research which seeks to discover basic truths or principles. This type of research is driven purely by curiosity and a desire to expand our knowledge. It tends not to be directly applicable to the real world in a direct way, but enhances our understanding of the world around us.
Applied research
Applied research involves seeking new applications of scientific knowledge to the solution of a problem such as the development of new system or procedure, new device, or new method, in order to solve an immediate problem.
Therefore, applied research is used to answer a specific question that has direct applications to the world. This is the type of research that solves a problem as it produces knowledge of practical use to man.
Developmental research
Developmental research, also known as evaluative research, is a decision-oriented research involving the application of the steps of the scientific method in response to an immediate need to improve existing practices. It attempts to assess statistics of something in order to determine its level of worth. If need arises, an improvement on it is made.
The Importance of Research in Daily Life
- Knowledge generated by research is the basis of sustainable development, which requires that knowledge be placed at the service of development, be converted into applications, and be shared to ensure widespread benefits. Some benefits of research include the following:
- Research is essential to economic and social development of our globalized society. For example, research can lead to improvement in the quality of life when, for instance, the findings show that fast population growth does not match the government’s efforts to provide comprehensive social services such water supply, health and education. In this case, family planning methods can be used to check population growth.
- Research enables the development of knowledge or generation of a new knowledge. For example, a researcher can establish the reason why malaria cases are on the increase despite supply of mosquito nets to every household. The information obtained can be used to tackle the problem in a different approach rather than insistence on the use of nets.
- Research can be used to test viabilities of theories and possibly develop new theories and laws.
- Knowledge generated from research can improve farming schemes or any other aspect related to life.
Research Stages in Conducting a Research
Scientific research involves a systematic process that focuses on being objective and gathering a multitude of information for analysis so that the researcher can come to a conclusion. In this process, the study is documented in such a way that another individual can conduct the same study again. This is referred to as replicating the study.
Any research done without documenting the study so that others can review the process and results is not an investigation using the scientific research process. The scientific research process is a multiple-step process where the steps are interlinked with the other steps in the process. If changes are made in one step of the process, the researcher must review all the other steps to ensure that the changes are reflected throughout the process. The stages or steps of research are explained below:
Problem identification
The first stage of research work is to identify a problem or develop a research question. The research problem may be something the researcher identifies as a problem. This serves as the focus of the study.
A research problem is a definite or clear statement about an area of concern, a condition to be improved upon, a difficulty to be eliminated, or a troubling question which should be answered through data collection and analysis. A research problem does not state how to do something, offer a vague or broad proposition, or present a value question.
The purpose of a problem statement is to:
introduce the reader to the importance of the topic being studied. The reader is oriented to the significance of the study and the research questions, hypotheses, or assumptions to follow;
place the topic into a particular context that defines the parameters of what is to be investigated; and
provide the framework for reporting the results and indicate what is probably necessary to conduct the study and explain how the findings will present this information.
The problem to be studied must be clear, accurate and meaningful. In identifying the problem, two basic steps explained below are followed:
Identifying the problem which is related to the subject of interest such as soil erosion, agriculture, climate, weather, etc. In agriculture, for example, the problem can be “Do mining activities pollute water sources in Tarime District?”
Narrowing down the problem so as to make it specific and easy to answer through data collection. For example, “Do mining activities like those undertaken in Nyamongo Gold Mine pollute water sources such as River Tigite in Tarime District?”
The information of a problem provides the context or scope and framework for the study. Sources of a problem include personal experiences, conclusions from theories, literature reviews, practical issues, deductive reasoning and inductive reasoning.
A research problem must be researchable or verifiable (both theoretically and practically), clear and ethical. The research contains variables. A variable is a factor or characteristic that a researcher would like to handle, measure, observe or manipulate in the research. A researcher must determine which variable needs to be manipulated to generate quantifiable results.
The key to designing any experiment is to look at what research variables could affect the outcome. There are many types of variable but the most important, for the vast majority of research methods, are the independent and dependent variables.
The independent variable is also known as the manipulated variable, is the factor manipulated by the researcher, and it produces one or more results, known as dependent variables. An independent variable is the one whose effect the researcher would like to establish in a study. The variable is used to ascertain whether or not the result one gets is due to it.
Any factor that can take on different values in an experiment is a scientific variable. For example, in an experiment investigating the effect farmers’ level of education on environmental degradation, the variables might be farmer’s age, level farmer’s of education, number of training the farmer has attended, the number of times the farmer has been visited and advised by agricultural or environmental officers, farmer’s gender, etc.
In an experiment, the independent variable is manipulated and the effects observed. These observed effects are called dependent variables. They are often the hypothesized outcome of manipulating the independent variable. A dependent variable, therefore, is a change or outcome which occurs as a result of the independent variable.
A change in the dependent variable depends on the independent variable, hence the name. The dependent variable responds to the independent variable, and it’s this relationship that researchers attempt to measure when conducting experiments. For example, a researcher might wish to establish the effect of fertilizer on the rate of plant growth; amount of fertilizer is the independent variable. The researcher could regard growth as height, weight, number of fruits produced, or all of these. These are dependent variables because they depend on the amount (or type) of fertilizer applied. A whole range of dependent variables arises from one independent variable.
Literature review
Now that the problem has been identified, the researcher must learn more about the topic under investigation. To do this, the researcher must review the literature related to the research problem. This stage provides foundational knowledge about the problem area. The review of literature also educates the researcher about what studies have been conducted in the past, how these studies were conducted, and the conclusions in the problem area.
Literature review involves collection of ideas and information presented by different scholars in books, journals, or reports. This stage guides a researcher to do a research on what other researchers have not gone through so as to
avoid repetition. It also helps a researcher find out more information about the problem at hand. For example, in the study of the effects of education level on the rate of environmental degradation, the researcher can go through books, journals, or reports to find out what other researchers say or recommend about this study, usually by focusing on the study in question.
Formulation of hypothesis
A hypothesis is a tentative, testable answer to a scientific question. Once a scientist has a scientific question she is interested in, the scientist reads up to find out what is already known on the topic. Then she uses that information to form a tentative answer to her scientific question. Sometimes people refer to the tentative answer as “an educated guess.” Keep in mind, though, that the hypothesis also has to be testable since the next step is to do an experiment to determine whether or not the hypothesis is right.
If one’s interest is to test “the effect high population growth on deforestation”, she may state the hypothesis as “Fast population growth accelerates deforestation”.
A hypothesis leads to one or more predictions that can be tested by experimenting. A hypothesis is tested by drawing conclusions from it. If observation and experimentation show a conclusion to be false, the hypothesis must be false. For example, it may be assumed that the problem of environmental degradation through agriculture is due to lack of education among farmers. A research can be conducted by interviewing sample farmers about their level of education and whether or not they are receiving the necessary training on environmental pollution. If the collected data confirms the case to be true, then the hypothesis is true. If not true, the hypothesis is wrong.
It is important to note that a good hypothesis is one which is simple, clear but not obvious; precise, testable, and able to indicate the relationship between variables.
Establishment of a study design
This involves the people who will participate in the research study, specifying who will participate in the study; how, when, and where data will be collected. It also focuses on how best the data will be collected and the tools that will be used. This requires the researcher to know the kind of information needed, who has the information and where to find the respondents.
The people whom the researcher intends to get the information from or the number of individuals to be experimented upon are called the population. For example if the researcher wants to find out about the effect of local seeds on crop yields in Tarime District, the possible population will be peasants in selected wards or villages of the named district. The farmers in selected wards or villages represent want we call target population. This is because it is difficult to research all farmers in the district, in which case a representative population is selected randomly.
However, due to one reason or another, not all the target population can be reached. This makes the researcher select the accessible population out of the target population, that is, the population that can be reached easily.
Another difficulty often arises that not all members in the target population can participate. The researcher, therefore, should select even a smaller population to deal with. The process of selecting the participants (respondents) is called sampling and the sampled out population is called sample population or sample size. For example, if the target population consists of 500 peasants, a research may select just 200 peasants to participate in the study. This is the sample population or sample size. The reason behind sampling is that it is impossible to reach everyone in the population due to several limitations such as time and financial constraints, long distances or remoteness, human factor, etc.
The use of samples assumes that the sample is a representative of the population. All members are given an equal and independent chance to be selected through application of different sampling techniques (which are beyond the scope of this study).
Reconnaissance
This is a pilot study which is conducted in the study area before the actual data collection is done. The researcher subjects to testing a small area with equivalent features needed for research, especially the tools of research before the actual study is conducted. Thereafter, the actual data collection is conducted after ensuring that tools are in the best condition to bring the expected results.
Data collection
Once the reconnaissance is completed, the actual study begins with the collection of data. The collection of data is a critical step in providing the information needed to answer the research question. Every study includes the collection of some type of data—whether it is from the literature or from subjects—to answer the research question. Data can be collected in the form of words on a survey (interview), with a questionnaire, through observations, or from the literature. These methods of data collection, also called research instruments or research tools, are discussed below:
Observation
Observation is a way of gathering data by watching behaviour, events, or noting physical characteristics in their natural setting. Observations can be overt (everyone knows they are being observed) or covert (no one knows they are being observed and the observer is concealed). The benefit of covert observation is that people are more likely to behave naturally if they do not know they are being observed. However, you will typically need to conduct overt observations because of ethical problems related to concealing your observation.
Observations can also be either direct or indirect. Direct observation is when you watch interactions, processes, or behaviours as they occur; for example, observing a teacher teaching a lesson to determine whether she/he is delivering it with fidelity. Indirect observations are when you watch the results of interactions, processes, or behaviours; for example, measuring the amount of food waste left by students in a school cafeteria to determine whether a new food is acceptable to them.
Observation is most commonly used in qualitative research. There are two types of observations namely, unstructured and structured observation.
Unstructured observation is a type observation where there is no checklist (a list of items to be noted, checked, or remembered) so all behaviours seen are written down in as much detail as possible.
Structured observation is a type observation that involves the recording of events of predefined types occurring at particular points in time, or within particular intervals. Structured observation typically produces quantitative data (information about the frequency of different sorts of events or of the proportion of time spent on different types of activity).
Advantages of observation
- Data is collected where and when an event or activity is occurring.
- It does not rely on people’s willingness or ability to provide information. This is because people are not always willing to write their true views on a questionnaire or tell a stranger what they really think at interview.
- It allows the researcher to directly see what people do rather than relying on what people say they did.
- It is the only appropriate tool for certain cases. For example, in the case of animals, infants, deaf and dumb persons, mad persons, non-cooperative persons, too shy persons and for persons who do not understand the language of researcher, observation will be the only appropriate tool.
Disadvantages of observation
- It is susceptible to observer bias.
- It is susceptible to the “hawthorne effect,” that is, people usually perform better when they know they are being observed, although indirect observation may decrease this proble.
- It can be expensive and time-consuming compared to other data collection methods. It does not increase researcher’s understanding of why people behave as they do.Some of the occurrences, such as sexual activities by couples, may not be open to observation.
- Not all occurrences open to observation can be observed when observer is at hand. For example, the quarrel and fight between two individuals or groups is never certain. Nobody knows when such an event will take place.Not all occurrences lend themselves to observational study: For example, love, affection, feeling and emotion of parents towards their children are not open to our senses and also cannot be quantified by observational techniques. The researcher may employ other methods like case study; interview etc. to study such phenomena.
Interview
Interviewing is one of the most common methods of collecting information from individuals. The technique involves oral or vocal questioning or discussion. It often involves two people – the researcher (interviewer) and the respondent (interviewee). The interviewer asks questions or initiates the discussion while the interviewee answers the questions or responds to the discussion.
There are various types of interviews that are used to collect data. These include structured, semi-structured and unstructured interviews.
Structured interviews: These are more or less like questionnaires since they consist of closed ended items. In this kind of interview, the respondents must choose from a limited number of answers that have been written in advance.
Example 1
The following are examples of structured interview questions:
Which human activity do you think pollutes the environment a great deal? [Tick your choice] (A)Agriculture (B) Mining (C) Transportation.
Do you think family planning controls population growth? YES/NO; TRUE/FALSE; etc.
emi-structured interviews: These are flexible kind of interviews in which the interviewer asks important questions in the same way each time but is free to alter the sequence of the questions and to probe for more information. Some items are structured while others are open. The respondents are free to answer the questions in any way they choose.
Example 2
Examples of semi-structured interview questions: (1). How do you dispose off the kitchen waste? (2). For how long have you been cultivating your land with a tractor?
Unstructured interviews: These are wholly open ended instrument in which interviewers have a list of topics they
want respondents to talk about but are free to phrase the questions as they wish. The respondents are free to answer in any way they choose.
Example 3
Examples of unstructured interview questions: (1). Why do you think it is important to boil and filter drinking water? (2). In your own views, what should be done to improve agricultural production in the country?
Interviews can be conducted in a variety of ways; for example, by telephone or as a face-to-face interview using an
interview schedule to guide your questions. Usually, combinations of structured, semi-structured and unstructured interview questions are used to collect data. It is important to do so in order to capture as much data as possible
Interview is one of the best methods of data collection. However, language barriers, biasness, shyness and discomfort may prevent the researcher to get the intended information.
Advantages of interviews
- They are useful to obtain detailed information about personal feelings, perceptions and opinions.
- They allow more detailed questions to be asked.
- They usually achieve a high response rate.
- Respondents’ own words are recorded.
- Ambiguities can be clarified and incomplete answers followed up.
- Precise wording can be tailored (modified) to the respondent and precise meanings of questions clarified.
- Interviewees are not influenced by others in the group. Some interviewees may be less self-conscious in a one-to-one situation.
Disadvantages of interviews
- They can be very time-consuming in terms of setting up, interviewing, recording, analysing, feedback, and reporting.
- They can be costly.
- Different interviewers may understand and record interviews in different ways.
Questionnaire
A questionnaire is a research instrument consisting of a series of questions for the purpose of gathering information from respondents. This is the most common type of research instrument. It involves the use of written down items to which the respondent individually responds in writing. The items are in the form of questions or statements.
Although questionnaires are often designed for statistical analysis of the responses, this is not always the case.
Questionnaires have advantages over some other types of surveys in that they are cheap, do not require as much effort from the questioner as verbal or telephone surveys, and often have standardized answers that make it simple to compile data. However, such standardized answers may frustrate users. Questionnaires are also sharply limited by the fact that respondents must be able to read the questions and respond to them. Thus, for some groups of people, conducting a survey by questionnaire may not be concrete.
It is important that the questions and statements for each item are clear, easy to read and interpret by the interviewee. Each item should contain one idea. Avoid long, complicated and ambiguous statements.
The use of a questionnaire in data collection is advantageous because there is a possibility of reaching distant respondents; it has well-planed questions as they are prepared and tested beforehand and can always be modified and adapted. This technique however is costly. Also, there is possibility of loss of material on transit, late filling and returning of the questionnaires and illiteracy as a barrier.
Advantages of a questionnaire
- It is a relatively simple method of obtaining data.
- Less time is consumed.
- Researcher is able to gather data from a widely scattered sample.
- It is suitable for distant respondents. Disadvantages of a questionnaire
- Responses to a questionnaire lack depth.
- Respondents may omit or disregard any item they choose.
- Some items may force the respondents to select responses that are not their actual choices
- Length of the questionnaire is limited according to the respondent’s interest.
- Printing may be costly especially if it is lengthy.
- Data are limited to the information that is voluntarily supplied by the respondents.
- Some items may be misunderstood, especially where clarity is not observed.
- The sample is limited to those who are literate.
- Questionnaires may either get lost on the way or some pages detached.
Data analysis
Data analysis, also known as analysis of data or data analytics, is a process of inspecting, cleansing, transforming, and modelling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making. It is a messy, ambiguous, time-consuming, creative, and fascinating process.
The researcher has to analyze the data so that the research question can be answered. The results of this analysis are then reviewed and summarized in a manner directly related to the research questions. The stage involves some mathematics, description, organization and interpretation.
A researcher produces data of various kinds such as crop yields, people’s behaviour, farming systems, level of poverty in the rural community, etc. The analysis of this data should be well organized to make sense.
The purpose of analysing data is to obtain usable and useful information. The analysis, irrespective of whether the data is qualitative or quantitative, may:
describe and summarise the data;
identify relationships between variables;
compare variables;
identify the difference between variables; or
forecast outcomes.
Scales of measurement
People are often confused about what type of analysis to use on a set of data and the relevant forms of pictorial presentation or data display. The decision is based on the scale of measurement of the data. These scales are nominal, ordinal, interval, and ratio.
Nominal
Let’s start with the easiest one to understand. Nominal scales are used for labelling variables, without any quantitative value. “Nominal” scales could simply be called “labels.” Notice that all of these scales are mutually exclusive (no overlap) and none of them has any numerical significance. A good way to remember all of this is that “nominal” sounds a lot like “name” and nominal scales are kind of like “names” or labels.
Examples of nominal scale are given in the chart below.
Note: a sub-type of nominal scale with only two categories (e.g. male/female) is called “dichotomous.” Ordinal
With ordinal scales, it is the order of the values that is important and significant, but the differences between each one is not really known. Take a look at the example below. In each case, we know that a number 4 is better than a number 3 or number 2, but we don’t know–and cannot quantify–how much better it is. For example, is the difference between “OK” and “Unhappy” the same as the difference between “Very Happy” and “Happy?” We can’t say.
Ordinal scales are typically measures of non-numeric concepts like satisfaction, happiness, discomfort, etc.
“Ordinal” is easy to remember because is sounds like “order” and that’s the key to remember with “ordinal scales”– it is the order that matters, but that’s all you really get from these.
The best way to determine central tendency on a set of ordinal data is to use the mode or median; the mean cannot be defined from an ordinal set.
Examples of ordinal scale are given in the chart below.
Interval
Interval scales are numeric scales in which we know not only the order, but also the exact differences between the values. The classic example of an interval scale is Celsius temperature because the difference between each value is the same. For example, the difference between 60 and 50 degrees is a measurable 10 degrees, as is the difference between 80 and 70 degrees. Time is another good example of an interval scale in which the increments are known, consistent, and measurable.
The central tendency in interval data can be measured by mode, median, or mean; standard deviation can also be calculated.
Ratio
This is a type of scale that is used to make comparisons between values or quantities. For example, Wangwe harvested 50 sacks of maize which is twice the quantity harvested by Wambura from the same acreage because the former applied fertilizer and good farming practices while the latter did not. This gives a ratio is of 50:25 = 2:1.
Data interpretation
This is a stage at which data is organized, and assembled to permit drawing of conclusion and actions. Data interpretation is part of daily life for most people. Interpretation is the process of making sense of numerical data that has been collected, analyzed, and presented.
Assume a research was conducted to find out the rate (weigh per plant) at which a new fertilizer, X, can be applied to get the maximum yield of maize. The results obtained were tabulated as follows:
Table 1.1 Rate of application of fertilizer X versus yield (hypothetical data)
| Fertilizer rate (g/plant) | 0.25 | 0.50 | 0.75 | 1.00 | 1.25 | 1.5 | 1.75 | 2.00 | 2.25 | 2.50 | 2.75 | 3.00 |
| Harvest (tonnes/per hectare) | 20 | 24 | 25.4 | 35.2 | 40.9 | 65 | 76.5 | 80.3 | 79.0 | 78.6 | 77.1 | 76.2 |
The data shows that any increase in fertilizer from 0.25 grams to 2.00 grams leads to an increase in yield. The maximum yield is attained at an application rate of about 2.00 g of fertilizer per plant. However, beyond this fertilizer rate, any added input (fertilizer) leads to a decreasing output (maize). This means that, to get maximum yield, fertilizer application should not exceed 2.00 grams per plant, possibly because too much fertilizer is toxic to plants.
Testing hypothesis
After data presentation, the researcher is able to answer questions asked in each step during data analysis. This is done through hypothesis testing where the question statement is proved or disproved.
Report wring/presentation
Research report is a condensed form or brief description of the research work done by the researcher. This is the last stage of research where a researcher communicates his/her findings to the public or other researchers.
Report writing in research is very important because of the following reasons:
- It reveals the researched problems and their implications.
- It fully represents the outcomes of the research data.
- It interprets the data.
- It provides the data around the problem.
- The report format
As you read through the large number of published studies, you will likely notice that the reports tend to follow both a topical pattern and a style of writing. Normally, research a reports have three main parts – preliminary pages, main body of the report, and conclusion and recommendations.
Preliminary pages
These pages serve as a guide to the leader. Page one carries the title of the research. An example of a research title is: “An assessment of the factors affecting oil palm production in Kigoma region”.
Page two carries declaration. This is an oath and confirmation that the work belongs to the named researcher and that it has not been produced by any researcher before.
Page 3 contains an acknowledgement. Here the researcher thanks people who, in one way or another, assisted him/her to accomplish his/her research work.
The next page contains a table of contents, followed by the page carrying the list of tables (if any).
Thereafter, the list of diagrams or figures (if any) follows. Next to the list of figures is the abstract. The abstract summarizes the outcome of the research in a few words.
The main body
The chapters contained in the main body of the research report include the following:
Chapter 1: Introduction
The main body of the paper has five chapters, with the introduction being the first. The purpose of the introduction is to introduce the reader to the topic and discuss the background of the problem at hand. The chapter consists of the background statements of the problems, the purpose and objectives of study, scope of the study and significance of the study.
Chapter 2: Literature review
This chapter contains a review on what other readers and scholars have reported about the problem under investigation. For example, if the research investigates about the reason for a drop in maize production in the study area, then the literatures reviewed should talk about maize production. The information reviewed could include land preparation, planting, harvesting, yield and any other relevant information.
Chapter 3: Methods
Methods refer to the actual procedures used to perform the research. The methods section is often the most systematic section in that small details are typically included in order to help others analyse, evaluate, and/or replicate the research process if desired.
The chapter explains about the methods used to collect, handle and analyse data and the model of data analysis used. It also includes an explanation about the study area, research design, population and sampling, survey instruments used, and objectives of the study.
The methods of investigation described in this chapter include where, by whom and how the study was conducted in a named study area. It also discusses about sample population and how it was sampled, location of the study area and other demographic characteristics such as sex, age, and socio-economic status of the population under study.
The procedures used to collect data spells out the actual steps taken to collect data. It involves mentioning the procedure and problems encountered during data collection.
Data analysis is one of the information explained in this chapter. Details on data treatments and the statistical techniques employed to analyse data are fully explained.
Limitations that could have influenced the study and were beyond the researcher’s control are also discussed.
Chapter 4: Results
This chapter shows the results obtained from the research. Results can be presented in the form of tables, diagrams, charts, figures, lines, etc.
Chapter 5: Discussion
Discussion of the results is done in this chapter. This section allows the researcher to scrutinize the research, discuss how the results are applicable to real life or even how they don’t support the original theory. The discussion section gives the researcher an opportunity to discuss, in a less formal manner, the results and implications of the research.
Chapter 5: Conclusion and recommendations
This is the final chapter in a research. In this chapter, the researcher draws his/her conclusion based on what has been observed in the whole study. The conclusion touches all issues observed from chapter one to the final chapter. Observations and suggestions from other authors and researchers can also be included in this chapter.
Recommendations are often used to suggest the needs for additional research on specific areas related to the current study. What remains to be done in the study at hand is also put forward. This gives room to other researchers, and serves as a starting point, for further studies on the same topic. The researcher also suggests to the government or any institution on the best way to tackle the research problem.
After conclusions and recommendations, follows the references and appendices.
Conducting Research
Research needs to be conducted in a clear and organized manner so as to obtain answers to the stated problem.The preparation of research proposal should be done before conducting it. Sometimes it may be hard to get data from the targeted population. Sampling should be used to obtain a representative population and save time as well as utilize resources economically.
The use of Research Output and Recommendations
The result obtained from any research is what we call research output. Ideally, the purpose of conducting any research is to come out with an output that can be used to solve a given problem, which probably hinders human development, in one ways or another. Uses of research output and recommendation include the following:
Research can improve people’s knowledge, for example, the discovery of a new knowledge in combating mosquitoes that spread malaria.
Recommendations suggested by researchers can be used by the governments or any institutions to solve the problems inflicting the society such as disease, drought, thuggery, famine and social amenities. Solutions to these problems are obtained by conducting research which comes with suggestions on how to solve them successfully.
Research results can be used to improve economic activities and community welfare. For example, the discovery of a new variety of maize that resists diseases and produces high yields can make farmers self-sufficient in food. Likewise, discovery of a new breed of cattle which produces more milk can serve a similar purpose.
Research can lead to sustainable exploitation of natural resources. For example, research on use of improved and energy-serving charcoal burners and kilns has helped reduce the cutting of trees for firewood. Likewise, mining is preceded by exploration and feasibility studies which provide guidelines on how to exploit the minerals sustainably. Establishment of hydroelectric power projects are due to successful research work on the feasibility studies and environmental impact assessment.
Research findings are useful in formulating government policies. Policies are enacted after a thorough research has been conducted so as to avoid any complaints during implementation.
Research results are useful in protecting and conserving the environment. For example, a research has been conducted to find out alternative activities for people engaged in charcoal burning for sale. The solution was to introduce dairy goat husbandry as an alternative economic activity to keep people off forests. This has helped to conserve trees and the environment in general.
Research results can be used to curb unemployment problem. For example, it may be found that the best way to solve unemployment problem is to provide soft loans to youths after graduating instead of just allowing them search for employment opportunities which is very scarce nowadays.
Research improves the marketability of goods and commodities. Formerly, water sellers used to sell unboiled and unbottled water. After research, it was found that water can be marketed very well if it is purified and bottled.
