Bishop Anyolo in Uriri Parish

Social survey/questionnaire

What is the method? Social surveys are a questionnaire-based method of research that can produce both qualitative and quantitative information depending on how they are structured and analysed. This section focuses on the use of surveys to collect and analyse qualitative data. Many of the issues and considerations are the same as for the quantitative use of surveys, and more detail can be found in the earlier section of this handbook. When should it be used? Questionnaire surveys can be used in a wide range of settings and to gather a variety of different types of information. You may be evaluating a programme in which a wide range of projects have been commissioned, and want to gather the views of a wide range of project managers, or you may be measuring the impact of an initiative on the business community in a specific geographical area. A small-scale qualitative survey may be conducted to explore in more detail the findings of qualitative research. What do I need to consider? Many of the considerations for a social survey are the same as for a quantitative survey, however we define a social survey as one where less statistical rigour is required, where sample sizes are not as large, and with results not expected to be significant of the wider population. A social survey may have a greater focus on collecting rich and detailed qualitative data. Population A number of questions about the proposed population for a social survey need to be considered. Such as are there language issues? And Qualitative Research Methods Is this the real life? yes/no If no, please answer question 2 2. Is it just fantasy? yes/no Please provide reasons for your answer .................................................. .................................................. .................................................. .................................................. ..................................................what are the geographic restrictions? These are the same issues as for quantitative surveys. Sampling The sample is the section of the wider population that will be engaged in the survey. Detailed consideration of sampling still needs to be made even when not striving for statistical significance. It is still important to understand who the respondent is and what your sampling frame is going to be. Format A social survey will usually be a cross-sectional survey used to gather information on a small sample population at a single point in time. An example of a cross-sectional survey would be a questionnaire that collects data on peoples’ experiences of a particular initiative. However, a qualitative survey could equally be used in a longitudinal study, perhaps returning to particular individuals over time to measure the impact of an intervention on the direction of someone’s life. Questions There are a whole range of questions to be asked in relation to survey design, such as: What types of questions can be asked? How complex will the questions be? Will screening questions be needed? Can question sequence be controlled? Will lengthy questions be asked? Will long response scales be used? A social survey will be more interested in qualitative findings, in recording peoples’ opinions and perceptions, and therefore will make more use of open questions where respondents can give their own responses to a set question. Open questions will begin with what, why, how, or describe, to elicit rich qualitative information. Open questions can be used in a variety of ways: Usage Example As a follow-on from closed questions, to develop a more detailed response. ‘If answering yes to question 7, please provide the reasons for this’ To find out more about a person, their thoughts, needs, problems, etc. Why is that so important to you? To get people to realise the extent of their problems. What effect does this have on your family life? To get people to reflect on the impact of something or some change. How has this made a difference to you? Administration The costs, required facilities, time, and personnel needed to conduct an effective survey are often underestimated, even when it is not on a large scale. There should be an administrative system in place to deal with the questionnaires for when they are returned/completed. This may include numbering the questionnaires, recording what action has been taken with them, entering the results into a spreadsheet/database etc. How should it be used? Surveys can be carried out by phone, post, email, website or face-toface, for detailed pros and cons of these delivery methods see the earlier section on qualitative surveys. In collecting rich qualitative survey data, the most effective method would be via face to face, administered surveys, as the researcher would be able to use prompts to encourage people to give more detailed answers. This does however introduce a bias, which needs to be understood and controlled as much as possible, i.e. by using standard prompts. In qualitative surveys, it is necessary that the interviewer conduct the interview with total objectivity, so that respondents are not influenced by any outside source in their responses. For this reason, interviews should be conducted by welltrained and qualified interviewers. What is the output? The data that a social survey can produce is very much dependent on how the questionnaire is constructed. However, the data can be very useful for providing an overall picture of the way in which a project or programme is being implemented and how effectively it is impacting upon its target audience. Qualitative data output will be in a text, audio or picture format, and each answer may be very different from another. This can make collection of data more difficult, and a way of collating data needs to be considered early in the process. How should it be analysed ? The Quantification of Qualitative Survey Data Surveys can be analysed by collating the frequency of responses to each of the questions on the survey form. This can be done manually using a “frequency table”, which can be easily set up on an Excel spreadsheet to analyse descriptive statistics. QSR NUD*IST and NVIVO are qualitative data analysis packages, which enable non-statistical information from interviews, group work, observations, audio, video, pictures or documents to be analysed according to chosen criteria. For example, it is possible to use the package to ‘pull out’ all material relating to key words or phrases (e.g. neighbourhood renewal) and then sub-divide the data into more specific areas of analysis (e.g. statement of use, problems, projects). This is a powerful piece of software that can provide clarity to wide range of often complicated written or media materials. Case study: Using surveys to evaluate a project A programme targeted on helping young people back into work through training wants to evaluate how well it is achieving its objectives. It uses a survey to canvas the views of young people who have been on the programme to date. The survey asks them closed questions about what training they have attended and how useful they have found the training (on a scale of 1:4). The survey also uses open questions to ask young people about what their plans are for the future as a result of the training (i.e. has it helped them to consider applying for full time work? Or further education opportunities?). The qualitative data is analysed and this shows that the young people have gained in confidence, are looking to go into further education or training or have already secured job interviews in a range of occupational fields, however there is a distinct focus on work in the field of construction. The results of the survey are analysed and this provides conclusions about overall success of the programme, which allows the programme manager to draw conclusions and consider design issues for making the programme more effective in the future. Interviews What is the method? One of the most popular and frequently used methods of gathering information from people about anything is by interviewing them. It is also the most popular method used within the social sciences. There is a continuum of formality around interviewing and it covers a multitude of techniques, from informal “chats” maybe arranged as “vox-pops” right through to highly structured, formal interviews, taped and transcribed. The different types and styles of interview elicit very different types of information. Conducting interviews is an interpersonal process and as an investigator you must be very aware of your own behaviours and assumptions in the context. Interviews are not “neutral” social spaces and you must be respectful and maintain appropriate boundaries at all times. What do I need to consider ? Interviews are a qualitative method of research often used to obtain the interviewees’ perceptions and attitudes to the issues. The key issue with interviewing is making decisions about who are the key people to talk to and what type of interview are you going to use. Interview Style There are three clearly identifiable styles of interview- structured, semistructured and unstructured: Structured - Follows a set of specific questions, which are worked through systematically. This type of interview is used when the researcher wishes to acquire information where the responses are directly comparable. Semi-structured - This is a more commonly used interview technique that follows a framework in order to address key themes rather than specific questions. At the same time it allows a certain degree of flexibility for the researcher to respond to the answers of the interviewee and therefore develop the themes and issues as they arise. Unstructured - This method of interview does not follow any predetermined pattern of questions or themes. Rather, the interviewer will address the issues as they emerge in the interview. The method is useful when the researcher wishes to explore the full breadth of a topic. Interview Type These are some of the types of interviews: Fact finder - This type of interview is used to obtain specific information from an interviewee and usually includes structured or standardised interview questions (the wording of the questions and the order in which they are asked is the same). It is used when some information is already known and there is a need to gain a more in-depth insight. An example of when a fact finder interview would be appropriate is when interviewing a project officer as part of an evaluation of their project. Quantitative (or ‘hard’) information is usually already known (such as outputs and funding data), therefore the interview could be used to discover qualitative information that the hard data cannot portray, such as the ‘softer’ outcomes of the project. Idea generator - In many respects, this type of interview is the opposite of the fact finder interview. It is used when the interviewer has no preconceptions about what might be discovered over the course of the interview and results can be used to set the parameters or framework for the study. Interview questions are loosely structured allowing maximum flexibility to explore a range of issues. Idea generator interviews are usually applied at the start of a research project in order to discover and explore issues from a particular group or community. For example, in order to develop a community cohesion strategy, idea generator interviews may be used to find out what community cohesion means to different groups in the community. Exploratory - These are the most frequently used type of interview as they are relevant to most types of research project. They are usually conducted with representatives that have a strategic role to play in the research. These types of interview require some degree of prior knowledge about the research subject as they are about testing hypotheses, making connections between other elements of the research, ensuring the strategic fit and progressing the findings of the research forward (e.g. senior officials from a local authority may be interviewed using this method in order to find out future plans and priorities and how they fit in with others’ plans and priorities). Experiential - This type of interview aims to draw out people’s feelings, perceptions and experiences over a specific period of time (e.g. the duration of a regeneration programme or project). This provides rich, in-depth material about how the subject under investigation has affected an individual’s life on a personal level. Experiential interviews may be used to elicit information from people who have benefited from a community project or who live in an area that has received regeneration monies.

A Case Study

It is an understatement that there is confusion among students, teachers, researchers, and methodologists about the definition and the main characteristics of case study research. Case study research is presented by some as a strictly exploratory research strategy in which nothing can be proven, most often by referring to the alleged impossibility to “generalize”. Others, such as Yin (1984, 1994, 2003), have claimed that the problem of “generalization” can be solved and that, therefore, theories can also be tested in (preferably) “multiple case studies”. A major difficulty for students and novice case study researchers is that proponents of these different perspectives give different meanings to similar methodological terms without clearly defining these meanings, making it almost impossible to grasp the nature of the debate and to infer solutions to problems in designing their own research. Ragin (1992) has argued that the work of any given case study researcher often is characterized by some hybrid of various approaches, which are usually difficult to disentangle. Most definitions of case study research, as found in the literature, are statements about the most frequently used measurement techniques (such as using “multiple sources of evidence”, or “qualitative methods”) and research objectives (such as “exploration”). Such definitions are attempts to capture in one statement the most important practical characteristics of a diverse array of studies that present themselves 1.1as case studies. Yin’s (2003: 13–14) definition is an example of such an all-inclusive descriptive definition: “A case study is an empirical inquiry that investigates a contemporary phenomenon within its real-life context, especially when the boundaries between object of study and context are not clearly evident. It copes with the technically distinctive situation in which there will be many more variables of interest than data points, and as one result relies on multiple sources of evidence, with data needing to converge in a triangulating fashion, and as another result benefits from the prior development of theoretical propositions to guide data collection and analysis”. But one methodological characteristic by which a case study is distinct from other research strategies such as the survey is not captured in Yin’s work, or most other definitions found in the literature, namely the fact that a case study basically is an inquiry of only one single instance (the case), or sometimes a small number of instances, of the object of study. Yin’s and others’ definitions only highlight another distinctive characteristic of the case study, namely that in a case study the object of study or its environment are not manipulated (“real life context”).This definition wants to capture both, and the two really distinctive features of the case study in comparison to the survey and the experiment create our definition of the case study: A case study is a study in which (a) one case (single case study) or a small number of cases (comparative case study) in their real life context are selected, and (b) scores obtained from these cases are analysed in a qualitative manner. With “study” we mean a research project in which a practice-oriented or theory-oriented research objective is formulated and achieved. With a case we mean an instance of an object of study. (We will explain our concept of “object of study” in Chapter 3.) With “real life context” we mean the object of study as it occurs (or has occurred) in reality, without manipulation. With “analysis in a qualitative manner” we mean an analysis based on visual inspection of the scores of the case (in contrast to a statistical analysis). We distinguish two main types of case study: the single case study, a case study in which data from one instance is enough to achieve the research objective, and the comparative case study, a case study that requires data from two or more instances to achieve the research objective. The difference between the experiment and the case study is that the experiment manipulates instances, whereas the case study does not. An experiment is a study in which one or more variable characteristics of an object of study are manipulated in one or multiple (“experimental”) instances of an object of study and in which scores obtained in the experimental instance or instances are analysed. The survey also studies instances in their real life context. A survey is a study in which (a) a single population in the real life context is selected, and (b) scores obtained from this population are analysed in a quantitative (statistical) manner. Our definition of the case study reflects our idea that the survey and the case study are different in two aspects; (a) the number of instances from which data are collected for the analysis, and, consequently, (b) the method of data analysis. The instances and data can be available from earlier studies (allowing for a secondary analysis) or it may be necessary to select new instances and collect new data. The case study draws conclusions on the basis of a “qualitative” analysis (“visual inspection”) of scores from one single instance (single case study) or from a small number of instances (comparative case study), whereas the survey draws conclusions on the basis of a quantitative (statistical) analysis of data from a population with a large number of instances.The definition of the case study does not include statements on data collection or measurement techniques. In our view research strategies do not differ, in principle, in terms of methods of measurement. For all three research strategies discussed here, the data analysed can be quantitative or qualitative! Measurement methods that are usually associated with case studies, such as the “qualitative” interview and using “multiple sources of evidence”, could also be used in the other research strategies. Similarly, measurement methods that are usually associated with other research strategies, such as standardized questionnaires in surveys and quantitative measurements in experiments, could also be used in case studies. Principles of measurement and the quality criteria that apply to it, such as reliability and validity, apply to any measurement in any research strategy. Although in a case study quantitative data can be used to generate the scores to be analysed, the interpretation of scores of the (small number of) cases in order to generate the outcome of the study is done qualitatively (by visual inspection) and not statistically. The definition of the case study is applicable also to the study of instances (cases) of objects of study that existed or occurred in the past. Therefore, the study of instances of an object of study as occurring “in its real-life context” (as formulated in our definition) includes both the study of contemporary instances and of past instances. In this book, thus, we discuss the case study as a research strategy defined by the number of instances (N 1 or N small) that is studied as well as the “qualitative” or non-statistical method of analysis of all kinds of (quantitative and qualitative) data.

DATA ANALYSIS, INTERPRETATION AND PRESENTATION

OVERVIEW Qualitative and quantitative Simple quantitative analysis Simple qualitative analysis Tools to support data analysis Theoretical frameworks: grounded theory, distributed cognition, activity theory Presenting the findings: rigorous notations, stories, summaries WHY DO WE ANALYZE DATA 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 • forecast outcomes SCALES OF MEASUREMENT Many people are 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 and numerical. Nominal scale A nominal scale is where: the data can be classified into a nonnumerical or named categories, and the order in which these categories can be written or asked is arbitrary. Ordinal scale An ordinal scale is where: the data can be classified into non-numerical or named categories an inherent order exists among the response categories. Ordinal scales are seen in questions that call for ratings of quality (for example, very good, good, fair, poor, very poor) and agreement (for example, strongly agree, agree, disagree, strongly disagree). Numerical scale A numerical scale is: where numbers represent the possible response categories there is a natural ranking of the categories zero on the scale has meaning there is a quantifiable difference within categories and between consecutive categories. When using a quantitative methodology, you are normally testing theory through the testing of a hypothesis. In qualitative research, you are either exploring the application of a theory or model in a different context or are hoping for a theory or a model to emerge from the data. In other words, although you may have some ideas about your topic, you are also looking for ideas, concepts and attitudes often from experts or practitioners in the field. QUALITATIVE ANALYSIS "Data analysis is the process of bringing order, structure and meaning to the mass of collected data. It is a messy, ambiguous, timeconsuming, creative, and fascinating process. It does not proceed in a linear fashion; it is not neat. Qualitative data analysis is a search for general statements about relationships among categories of data." Marshall and Rossman, 1990:111 Hitchcock and Hughes take this one step further: "…the ways in which the researcher moves from a description of what is the case to an explanation of why what is the case is the case." Hitchcock and Hughes 1995:295 Simple qualitative analysis • Unstructured - are not directed by a script. Rich but not replicable. • Structured - are tightly scripted, often like a questionnaire. Replicable but may lack richness. • Semi-structured - guided by a script but interesting issues can be explored in more depth. Can provide a good balance between richness and replicability. Simple qualitative analysis • Recurring patterns or themes – Emergent from data, dependent on observation framework if used • Categorizing data – Categorization scheme may be emergent or pre-specified • Looking for critical incidents – Helps to focus in on key events TOOLS TO SUPPORT DATA ANALYSIS • Spreadsheet – simple to use, basic graphs • Statistical packages, e.g. SPSS • Qualitative data analysis tools – Categorization and theme-based analysis, e.g. N6 – Quantitative analysis of text-based data

Hypothesis

A statement temporarily accepted as true : Barr and Scates define as, “A hypothesis is a statement temporarily accepted as true in the light of what is, at the time, known about a phenomena, and it is employed as a basis for action in the search for new truth, when the hypothesis is fully established, it may take the form of facts, principles and theories.” Hypothesis A testable proposition or assumption. George, J. Mouly defines that, “Hypothesis is an assumption or proposition whose testability is to be tested on the basis of the computability of its implications with empirical evidence with previous knowledge.” Hypothesis Tentative relationship of two or more variables either normative or casual: “A hypothesis is defined as a statement for the tentative relationship of two or more variables. The relationship of the variables may either be normative or causal relationship. It should be based on some rationale.” ASSUMPTION, POSTULATE AND HYPOTHESIS The terms assumption. postulate and hypothesis occur most frequently in the research literature, but are often confused by research scholars. Hence these terms need clear explanation. (a) Assumption: Assumption means taking things for granted so that the situation is simplified for logical procedure. Assumptions are not the very ground of our activity as the postulates are. They merely facilitate the progress of an agreement a partial simplification by introducing restrictive conditions. For example, the formulas of Statistics and measurement are based on number of assumptions. Assumption means restrictive conditions before the argument can become valid. Assumptions are made on the basis of logical insight and their truthfulness can be observed on the basis of data or evidences. The postulates are the basis and form the original point of an argument whereas assumptions are a matter of choice and less use, we make them more free will and our argument be a general proposition or convention. (b) Postulate: Postulates are the working beliefs of most scientific activity. The mathematician begins by postulating a system of numbers which range from 0 to 9 and can permute and combine only thereafter. Similarly ‘Hull’s Theory of Reinforcement’s is based on eight postulates of behaviour of an organism. With many people God and Spirit is a postulate of the good life or godly life. Postulates are not proven; they are simply accepted at their face value so that their basic work for the discovery of other facts of nature can begin. (c) Hypothesis: A hypothesis is different from both of these. It is the presumptive statement of a proposition which the investigator seeks to prove. It is a condensed generalization. This generalization requires a knowledge of principles of things or essential characteristics which pertain to entire class of phenomena. The theory when stated as a testable proposition formally and clearly and subjected to empirical or experimental verification is known as hypothesis. The hypothesis furnishes the germinal basis of the whole investigation and remains to test it out by facts. The hypothesis is based on some earlier theory and some rationale whereas postulates are taken as granted true. An assumption is the assumed solution of a major problem. It may be partially true. The scientific research process is based on some hypotheses. The nature sciences and mathematics are based on postulates. The statistic is based on some assumptions which are considered approximate science. The assumptions are helpful in conducting a research work in behavioural sciences. OBSERVATION VERSUS SPECIFIC LAND GENERAL HYPOTHESIS Hypotheses are often confused with observation. These terms refer to quite different things. An observation refers to what is….that is to what is seen. From observation researcher may infer. For example a researcher may go into a school and after looking around. Observe that most of the students are back. From that observation he may infer that the school is located in a poor neighbourhood. Though the researcher does not know that the neighbourhood is poor, he expects that the majority of people living there are poor. Then he has formulated a specific hypothesis setting forth an anticipated relationship between two variables like race and income level. For the test of this hypothesis researcher could walk around the neighbourhood, observes the home and the income levels. After observation he provides support for this specific hypothesis for this researcher might make a general hypothesis. The second hypothesis represents a generalization and must be tested by making observation as was the specific hypothesis. Since it would be impossible to observe all universe or population, thus, the researches will take a sample and reach conclusion on a probability basis for the verification of hypothesis being true or not. There is some difference between specific and general hypothesis. Specific hypothesis requires fewer observations for testing than the general hypothesis. For testing purpose a general hypothesis is reformulated to a more specific one. NATURE OF HYPOTHESIS The following are the main features of a hypothesis: 1. It is conceptual in nature. Some kind of conceptual elements in the framework are involved in a hypothesis. 2. It is a verbal statement in a declarative form. It is a verbal expression of ideas and concepts, it is not merely idea but in the verbal form, the idea is ready enough for empirical verification. 3. It has the empirical referent. A hypothesis contains some empirical referent. It indicates the tentative relationship between two or more variables. 4. It has a forward or future reference. A hypothesis is future oriented. It relates to the future verification not the past facts and informations. 5. It is the pivot of a scientific research. All the research activities are designed for its verification. The nature of hypothesis can be well understood by differentiating it with other terms like assumption and postulate. FUNCTIONS OF HYPOTHESIS The following are the main functions of hypothesis in the research process suggested by H.H. Mc. Ashan : 1. It is a temporary solution of a problem concerning with some truth which enables an investigator to start his research work. 2. It offers a basis in establishing the specifics what to study for and may provide possible solutions to the problem. 3. Each hypothesis may lead to formulate another hypothesis. 4. A preliminary hypothesis may take the shape of final hypothesis. 5. Each hypothesis provides the investigator with definite statement which may be objectively tested and accepted or rejected and leads for interpreting results and drawing conclusions that is related to original purpose. The functions of a hypothesis may be condensed into three. The following are the threefold functions of a hypothesis: (a) To delimit the field of the investigation. (b) To sensitize the researcher so that he should work selectively, and have very realistic approach to the problem. (c) To offer the simple means for collecting evidences to the verification. IMPORTANCE OF A HYPOTHESIS 1. Hypothesis as the Investigator’s “Eyes”: Carter V. Good thinks that by guiding the investigator in further investigation it serves as the investigator’s “Eyes” in seeking answers to tentatively adopted generalization. 2. It Focuses Research: Without it, research is unfocussed research and remains like a random empirical wandering. It serves as necessary link between theory and the investigation. 3. It Places Clear and Specific Goals: A well thought out set of hypothesis is that they place clear and specific goals before the research worker and provide him with a basis for selecting sample and research procedure to meet these goals. 4. It Links Together: “It serves the important function of linking together related facts and information and organizing them into wholes.” – Good Barr and Scates 5. It Prevents Blind Research: “The use of hypothesis prevents a blind search and indiscriminate gathering of masses of data which may later prove irrelevant to the problem under study.” – P. V. Young 6. As a Sort of Guiding Light: A hypothesis serves as a powerful beacon that lights the way for the research work. George J. Mouley thinks that Hypotheses serve the following purposes: 1. They provide direction to research and prevent the review of irrelevant literature and the collection of useful or excess data. 2. They sensitize the investigator certain aspects of situation which are irrelevant from the standpoint of the problem at hand. 3. They enable the investigator to understand with greater clarity his problem and its ramification. 4. They serve as a framework for the conclusive-in short a good hypothesis: (a) Gives help in deciding the direction in which he has to proceed. (b) It helps in selecting pertinent fact. (c) It helps in drawing conclusions. D.B. Van Dalen advocates the Importance of Hypothesis in the following ways: 1. Hypotheses are indispensable research instrument, for they build a bridge between the problem and the location of empirical evidence that may solve the problem. 2. A hypothesis provides the map that guides and expedites the exploration of the phenomena under consideration. 3. A hypothesis pin points the problem. The investigator can examine thoroughly the factual and conceptual elements that appear to be related to a problem. 4. Using hypothesis determines the relevancy of facts. A hypothesis directs the researcher’s efforts into a productive channels. 5. The hypothesis indicates not only what to look for is an investigation but how to obtain data. It helps in deciding research design. It may suggest what subjects, tests, tools, and techniques are needed. 6. The hypothesis provides the investigator with the most efficient instrument for exploring and explaining the unknown facts. 7. A hypothesis provides the framework for drawing conclusions. 8. These hypotheses simulate the investigator for further research studies. Bruce W. Tuckman presents the importance of Hypothesis in the Research Spectrum : Research begins with a problem and utilization of both theories and findings in arriving at hypothesis. These hypotheses contain variables which must be labelled and then operationally defined to construct predictions. These steps might be considered the logical stages of the research. These stages are followed by methodological stages, which culminate in the development of research design and development of measures and finally in the finding themselves.

Data Collection

In dealing with any real life problem it is often found that data at hand are inadequate, and hence, it becomes necessary to collect data that are appropriate. There are several ways of collecting the appropriate data which differ considerably in context of money costs, time and other resources at the disposal of the researcher. Primary data can be collected either through experiment or through survey. If the researcher conducts an experiment, he observes some quantitative measurements, or the data, with the help of which he examines the truth contained in his hypothesis. But in the case of a survey, data can be collected by any one or more of the following ways: (i) By observation: This method implies the collection of information by way of investigator’s own observation, without interviewing the respondents. The information obtained relates to what is currently happening and is not complicated by either the past behaviour or future intentions or attitudes of respondents. This method is no doubt an expensive method and the information provided by this method is also very limited. As such this method is not suitable in inquiries where large samples are concerned. (ii) Through personal interview: The investigator follows a rigid procedure and seeks answers to a set of pre-conceived questions through personal interviews. This method of collecting data is usually carried out in a structured way where output depends upon the ability of the interviewer to a large extent. (iii) Through telephone interviews: This method of collecting information involves contacting the respondents on telephone itself. This is not a very widely used method but it plays an important role in industrial surveys in developed regions, particularly, when the survey has to be accomplished in a very limited time. (iv) By mailing of questionnaires: The researcher and the respondents do come in contact with each other if this method of survey is adopted. Questionnaires are mailed to the respondents with a request to return after completing the same. It is the most extensively used method in various economic and business surveys. Before applying this method, usually a Pilot Study for testing the questionnaire is conduced which reveals the weaknesses, if any, of the questionnaire. Questionnaire to be used must be prepared very carefully so that it may prove to be effective in collecting the relevant information. (v) Through schedules: Under this method the enumerators are appointed and given training. They are provided with schedules containing relevant questions. These enumerators go to respondents with these schedules. Data are collected by filling up the schedules by enumerators on the basis of replies given by respondents. Much depends upon the capability of enumerators so far as this method is concerned. Some occasional field checks on the work of the enumerators may ensure sincere work. Research Methodology The researcher should select one of these methods of collecting the data taking into consideration the nature of investigation, objective and scope of the inquiry, finanical resources, available time and the desired degree of accuracy. Though he should pay attention to all these factors but much depends upon the ability and experience of the researcher. In this context Dr A.L. Bowley very aptly remarks that in collection of statistical data commonsense is the chief requisite and experience the chief teacher. Execution of the project: Execution of the project is a very important step in the research process. If the execution of the project proceeds on correct lines, the data to be collected would be adequate and dependable. The researcher should see that the project is executed in a systematic manner and in time. If the survey is to be conducted by means of structured questionnaires, data can be readily machine-processed. In such a situation, questions as well as the possible answers may be coded. If the data are to be collected through interviewers, arrangements should be made for proper selection and training of the interviewers. The training may be given with the help of instruction manuals which explain clearly the job of the interviewers at each step. Occasional field checks should be made to ensure that the interviewers are doing their assigned job sincerely and efficiently. A careful watch should be kept for unanticipated factors in order to keep the survey as much realistic as possible. This, in other words, means that steps should be taken to ensure that the survey is under statistical control so that the collected information is in accordance with the pre-defined standard of accuracy. If some of the respondents do not cooperate, some suitable methods should be designed to tackle this problem. One method of dealing with the non-response problem is to make a list of the non-respondents and take a small sub-sample of them, and then with the help of experts vigorous efforts can be made for securing response. Analysis of data: After the data have been collected, the researcher turns to the task of analysing them. The analysis of data requires a number of closely related operations such as establishment of categories, the application of these categories to raw data through coding, tabulation and then drawing statistical inferences. The unwieldy data should necessarily be condensed into a few manageable groups and tables for further analysis. Thus, researcher should classify the raw data into some purposeful and usable categories. Coding operation is usually done at this stage through which the categories of data are transformed into symbols that may be tabulated and counted. Editing is the procedure that improves the quality of the data for coding. With coding the stage is ready for tabulation. Tabulation is a part of the technical procedure wherein the classified data are put in the form of tables. The mechanical devices can be made use of at this juncture. A great deal of data, specially in large inquiries, is tabulated by computers. Computers not only save time but also make it possible to study large number of variables affecting a problem simultaneously. Analysis work after tabulation is generally based on the computation of various percentages, coefficients, etc., by applying various well defined statistical formulae. In the process of analysis, relationships or differences supporting or conflicting with original or new hypotheses should be subjected to tests of significance to determine with what validity data can be said to indicate any conclusion(s). For instance, if there are two samples of weekly wages, each sample being drawn from factories in different parts of the same city, giving two different mean values, then our problem may be whether the two mean values are significantly different or the difference is just a matter of chance. Through the use of statistical tests we can establish whether such a difference is a real one or is the result of random fluctuations. If the difference happens to be real, the inference will be that the two samples come from different universes and if the difference is due to chance, the conclusion would be that the two samples belong to the same universe. Similarly, the technique of analysis of variance can help us in analysing whether three or more varieties of seeds grown on certain fields yield significantly different results or not. In brief, the researcher can analyse the collected data with the help of various statistical measures. Hypothesis-testing: After analysing the data as stated above, the researcher is in a position to test the hypotheses, if any, he had formulated earlier. Do the facts support the hypotheses or they happen to be contrary? This is the usual question which should be answered while testing hypotheses. Various tests, such as Chi square test, t-test, F-test, have been developed by statisticians for the purpose. The hypotheses may be tested through the use of one or more of such tests, depending upon the nature and object of research inquiry. Hypothesis-testing will result in either accepting the hypothesis or in rejecting it. If the researcher had no hypotheses to start with, generalisations established on the basis of data may be stated as hypotheses to be tested by subsequent researches in times to come. Generalisations and interpretation: If a hypothesis is tested and upheld several times, it may be possible for the researcher to arrive at generalisation, i.e., to build a theory. As a matter of fact, the real value of research lies in its ability to arrive at certain generalisations. If the researcher had no hypothesis to start with, he might seek to explain his findings on the basis of some theory. It is known as interpretation. The process of interpretation may quite often trigger off new questions which in turn may lead to further researches. Preparation of the report or the thesis: Finally, the researcher has to prepare the report of what has been done by him. Writing of report must be done with great care keeping in view the following: 1. The layout of the report should be as follows: (i) the preliminary pages; (ii) the main text, and (iii) the end matter. In its preliminary pages the report should carry title and date followed by acknowledgements and foreword. Then there should be a table of contents followed by a list of tables and list of graphs and charts, if any, given in the report. The main text of the report should have the following parts: (a) Introduction: It should contain a clear statement of the objective of the research and an explanation of the methodology adopted in accomplishing the research. The scope of the study along with various limitations should as well be stated in this part. (b) Summary of findings: After introduction there would appear a statement of findings and recommendations in non-technical language. If the findings are extensive, they should be summarised. (c) Main report: The main body of the report should be presented in logical sequence and broken-down into readily identifiable sections. (d) Conclusion: Towards the end of the main text, researcher should again put down the results of his research clearly and precisely. In fact, it is the final summing up. At the end of the report, appendices should be enlisted in respect of all technical data. Bibliography, i.e., list of books, journals, reports, etc., consulted, should also be given in the end. Index should also be given specially in a published research report. 2. Report should be written in a concise and objective style in simple language avoiding vague expressions such as ‘it seems,’ ‘there may be’, and the like. 3. Charts and illustrations in the main report should be used only if they present the information more clearly and forcibly. 4. Calculated ‘confidence limits’ must be mentioned and the various constraints experienced in conducting research operations may as well be stated. Criteria of Good Research Whatever may be the types of research works and studies, one thing that is important is that they all meet on the common ground of scientific method employed by them. One expects scientific research to satisfy the following criteria 1. The purpose of the research should be clearly defined and common concepts be used. 2. The research procedure used should be described in sufficient detail to permit another researcher to repeat the research for further advancement, keeping the continuity of what has already been attained. 3. The procedural design of the research should be carefully planned to yield results that are as objective as possible. 4. The researcher should report with complete frankness, flaws in procedural design and estimate their effects upon the findings. 5. The analysis of data should be sufficiently adequate to reveal its significance and the methods of analysis used should be appropriate. The validity and reliability of the data should be checked carefully. 6. Conclusions should be confined to those justified by the data of the research and limited to those for which the data provide an adequate basis. 7. Greater confidence in research is warranted if the researcher is experienced, has a good reputation in research and is a person of integrity. 1. Good research is systematic: It means that research is structured with specified steps to be taken in a specified sequence in accordance with the well defined set of rules. Systematic characteristic of the research does not rule out creative thinking but it certainly does reject the use of guessing and intuition in arriving at conclusions. 2. Good research is logical: This implies that research is guided by the rules of logical reasoning and the logical process of induction and deduction are of great value in carrying out research. Induction is the process of reasoning from a part to the whole whereas deduction is the process of reasoning from some premise to a conclusion which follows from that very premise. In fact, logical reasoning makes research more meaningful in the context of decision making. 11 James Harold Fox, Criteria of Good Research, Phi Delta Kappan, Vol. 39 (March, 1958), pp. 285–86. 12 See, Danny N. Bellenger and Barnett, A. Greenberg, “Marketing Research—A Management Information Approach”, p. 107–108. 3. Good research is empirical: It implies that research is related basically to one or more aspects of a real situation and deals with concrete data that provides a basis for external validity to research results. 4. Good research is replicable: This characteristic allows research results to be verified by replicating the study and thereby building a sound basis for decisions.

Research Paper Publication in Refereed/Unpaid /Scopus Indexed Journals i...

What is (and what is NOT) A Project

A Project From the perspective of project management, any series of activities that go through the project cycle ARE projects. The project cycle consists of project phases. An organisation should already have a well-defined organisational strategy from which it can begin to assess relevant needs and opportunities in its field. Several ideas will then come to light, from which an organisation may choose. The project phases then follow logically through design, financing, implementation and evaluation stages. NGOs often perform activities that do not fall into the category of projects. It is also important to recognise that a project is not: • past activities that are repeated in exactly the same way on a periodic basis • activities with no clearly defined goals • activities which can be repeated or transplanted anywhere at any moment; or • ongoing (regular) organisational activities (e.g. board meetings) What is the Project Design ? The project design is one phase of the project cycle. It consists of two elements: • project planning (formulation of project elements); and • project proposal writing (converting the plan into a project document). Project design is a result of both project planning and the project proposal. Both steps are essential to forming a solid project design. Project Planning — Formulation of Project Elements Before the project is written, its individual elements need to be developed. Addressing the planning considerations helps develop the project elements, Another way to break down planning questions is to take into consideration the project design stage at which these questions are asked. On the basis of these criteria the project planning questions could be classified as to whether they are made during project planning or proposal writing. Regardless of the project planning model presented , quality proposal writing is not possible without proper planning. Planning Considerations What is the Project Design? The project design is one phase of the project cycle. It consists of two elements: • project planning (formulation of project elements); and • project proposal writing (converting the plan into a project document). Project design is a result of both project planning and the project proposal. Both steps are essential to forming a solid project design. Project Planning — Formulation of Project Elements Before the project is written, its individual elements need to be developed. Addressing the planning considerations helps develop the project elements, as. Another way to break down planning questions is to take into consideration the project design stage at which these questions are asked. On the basis of these criteria the project planning questions could be classified as to whether they are made during project planning or proposal writing. Regardless of the project planning model presented, quality proposal writing is not possible without proper planning.

Project Proposal Writing for Non Governmental Organisations

Once the groundwork has been completed, proposal writing can commence. The key decision to be made at this stage is the structure of the project proposal (including the content and length). The structure is determined by the nature of the project as well as by the funding agency’s requirements. In the variety of formats, application forms, project design outlines, and grant application guidelines, it is possible to detect some common elements. Proposed Format Title page A title page should appear on proposals longer than three to four pages. The title page should indicate the project title, the name of the lead organisation (and potential partners, if any), the place and date of project preparation and the name of the donor agency to whom the proposal is addressed. Project title The project title should be short, concise, and preferably refer to a certain key project result or the leading project activity. Project titles that are too long or too general fail to give the reader an effective snapshot of what is inside. Contents page If the total project proposal is longer than 10 pages it is helpful to include a table of contents at the start or end of the document. The contents page enables readers to quickly find relevant parts of the document. It should contain the title and beginning page number of each section of the proposal. Abstract Many readers lack the time needed to read the whole project proposal. It is therefore useful to insert a short project summary — an abstract. The abstract should include: • the problem statement • the project’s objectives • implementing organisations • key project activities; and • the total project budget. Theoretically, the abstract should be compiled after the relevant items already exist in their long form. For a small project the abstract may not be longer than 10 lines. Bigger projects often provide abstracts as long as two pages. Context This part of the project describes the social, economic, political and cultural background from which the project is initiated. It should contain relevant data from research carried out in the project planning phase or collected from other sources. The writer should take into consideration the need for a balance between the length of this item and the size of the overall project proposal. Large amounts of relevant data should be placed in an annex. TOPIC MATERIAL Project justification Rationale should be provided for the project. Due to its importance usually this section is divided into four or more sub-sections. Problem statement The problem statement provides a description of the specific problem(s) the project is trying to solve, in order to “make a case” for the project. Furthermore, the project proposal should point out why a certain issue is a problem for the community or society as a whole, i.e. what negative implications affect the target group. There should also be an explanation of the needs of the target group that appear as a direct consequence of the described problem. Priority needs The needs of the target group that have arisen as a direct negative impact of the problem should be prioritised. An explanation as to how this decision was reached (i.e. what criteria was used) must also be included. For example, if the problem is stated as “… poor infrastructure in the community ” the list of needs associated with this problem may be: • improved water supply in quality and quantity; • better roads; and • improved solid waste collection. These three needs would then be given higher or lower priority according to the level of importance for the community, and a description would be given of how that decision was reached (e.g. a poll taken from the local population, costs associated with project intervention, etc.). This procedure provides credibility to the selected intervention. The proposed approach (type of intervention) The project proposal should describe the strategy chosen for solving the problem and precisely how it will lead to improvement. One way to describe the approach related to the need previously stated as improved water supply could be: “ intervention to provide basic water supply facilities in the community, ” with some description of the specific features of the solution proposed. ■ Never use language that could be perceived as an attack towards any other organisation or institution. ■ Carry out an analysis of your organisation’s strengths prior to preparing the proposal and then showcase these strengths. ■ Show that your planning process is participatory and takes into consideration the opinions of the target group. ■ Prepare a short document that presents your past experience (organisational record) and attach it Before Writing a Proposal Interview past and prospective beneficiaries. Though feedback was likely received when the previous project ended, new benefits and conditions may have arisen since that time. Speak to prospective beneficiaries to ensure that what you are planning to offer is desired and needed. ■ Review past project proposals. Avoid repeating mistakes and offering to reproduce results that have already been achieved. Donors will be unlikely to provide more funding for something that should already have been done. ■ Review past project evaluation reports. Don’t count on project members to remember all the mistakes and areas for improvement from previous efforts. ■ Organise focus groups. Make sure that the people you need are willing and able to contribute. ■ Check statistical data. Don’t let others discover gaps and inaccuracies in the data you are relying on. ■ Consult experts. Outside opinions will give you ideas and credibility. ■ Conduct surveys, etc. Gather as much preliminary information as possible to demonstrate commitment to the project and to refine the objectives. ■ Hold community meetings or forums. When the public feels that they have been consulted on an issue, they will be much more likely to cooperate and support the project.to the project proposal.

Quantitative Research Methods

Quantitative methods are research techniques that are used to gather quantitative data, data that can be sorted, classified, measured. This following section outlines the core quantitative research methods used in social research. Quantitative survey What is the method? Surveys are a popular method of collecting primary data. The broad area of survey research encompasses any measurement procedures that involve asking questions of respondents. They are a flexible tool, which can produce both qualitative and quantitative information depending on how they are structured and analysed. In this section we focus on the quantitative use of surveys, and in later sections we explore the more qualitative use of survey methods. When should it be used? When you need to generate primary data from a large number of sources to answer your research question. Surveys are a useful a means of gathering data from businesses, community organisations and residents, and survey research is one of the most important areas of measurement in applied social research. However, health warnings need to be attached to the use of quantitative surveys and careful consideration needs to be taken before embarking on any large-scale survey. What do I need to consider? In undertaking a survey it is important to understand who you want to survey, how you are going to select them, how you are going to survey them, what you want to ask them and how you are going to organise the task. The following section outlines some key considerations that need to be made before embarking on a large-scale survey. Population – A number of questions about the proposed population for a survey need to be considered. Such as: Can the population be counted? Some populations will be easy to count, in a given geographical area there will be secondary data sources that will give you a population count (Census), in a membership organisation there may be a list of all members, however in a newly arrived ethnic community such as the recent arrivals of Polish and Eastern European communities there is less chance that you can obtain a reliable count of the population. A bias in your survey results can occur if the survey sample does not accurately represent the population. Having a count of the population is also important in order to establish the significance of your results to allow a generalisation to the population as a whole. Are there language issues? Respondents may have varying capacities for being able to complete written surveys or questionnaires. While telephone and street surveys do not require the respondent to be able to read or write in English, postal surveys involve respondents completing the survey or questionnaire themselves. You should consider the offer of help in self-administered surveys for respondents to complete a form either in person or over the telephone, this will help address potential language or basic skills issues. If surveying an ethnic minority population you may wish to translate questionnaires into community languages, or have people who speak the communities’ language to assist where necessary. What are the geographic restrictions? The geographic spread of the population to be surveyed will determine the method used for collecting your data. If you are surveying people from a particular location or organisation it may be possible to conduct a survey using an interviewer, however if you have a population sample that is geographically dispersed then you would look to use a different method, such as a telephone or postal survey. Sampling The sample is the section of the wider population that will be engaged in the survey and sampling is the process of identifying who you will aim to contact from that population. The word ‘population’ is used to describe the target group, and while this may be the national population as a whole, it may also be a smaller group such as lone parents, or business members of a Chambers of Commerce in a particular location. Detailed consideration of sampling needs to be made to ensure the validity of your results, and the following issues need consideration: Who is the respondent? The first thing you need to understand is who your respondent is going to be. This is the person that will provide the data you are asking for. If the survey is distributed amongst households, who in particular will be filling in the survey? Do you want to specify who the survey is to be completed by? And do you understand why you are specifying this person? The same is true when surveying organisations or groups. A survey will have much greater success if it is directed to the right respondent. Identifying the person best suited to completing a survey will help to increase the response rate and generate more accurate data. What is your sampling frame? A sampling frame is a list of members of a population from which members of a sample are then selected. A sampling frame needs to be accurate, complete, up-to-date and relevant to the purposes of the survey for which it is to be used. Once you have an established sampling frame, depending on its size you may need to adopt a sampling technique to extract your final sample. For example random sampling, simple random sampling or stratified sampling (see further reading for more details on sampling techniques). Are response rates likely to be a problem? With any survey, you need to look at the profile of the people who did responded and satisfy yourself that they are about the same as the people who didn’t respond – and also, that they’re about the same as the overall population that you’re sampling. If you send out a survey to a population, which is 50% male, and 50% female, but your responses are 80% from females then your findings will not represent your target population. Response rates can be low for surveys, under 20% for a postal survey is not uncommon. However, all the considerations in this section can help to improve your response rate . Statistical significance: Understanding your population, sample size, and response rates are important for calculating interval and confidence levels, which are vital in determininghow many people you need to interview in order to get results that reflect the target population as precisely as needed. You can use online calculators to establish this type of information, but it is important to understand the terms and the reasons for doing this (see section on statistical analysis for more detail). Format It is important to understand what format of survey you are looking to undertake. There are broadly two survey formats that you may use and it is important to understand which you are using: Cross-sectional surveys are used to gather information on a population at a single point in time. An example of a crosssectional survey would be a questionnaire that collects data on peoples’ experiences of a particular initiative or event. A crosssectional survey questionnaire might try to determine the relationship between two factors, like the impact of a programme of activity on the level of benefits claims for example. Longitudinal surveys gather data over a period of time. This would allow analysis of changes in the population over time and attempt to describe and/or explain them. The three main types of longitudinal surveys are trend studies, cohort studies, and panel studies (for more details see further reading). A longitudinal study will also seek to determine the relationship between factors, but the difference is that the examination will be of a change in factors over time, so for example the relationship between health and employment. Questions There are a whole range of questions to be asked in survey design, such as: What types of questions can be asked? How complex will/can the questions be? Will screening questions be needed? Can question sequence be controlled? Will lengthy questions be asked? Will long response scales be used? Here we outline the main types of questions used in quantitative surveys: Closed questions – these have a number of possible answers in a list for respondents to choose from (e.g. a closed question about the sources of funding for a community project would ask respondents to choose from a list of categories, such as New Deal for Communities, Neighbourhood Renewal Funding and so on). Usually, closed questions include an ‘other’ option to enable respondents to add any categories that have been omitted; Ranking scales – these are most commonly used when trying to ascertain the level of importance of a number of items. A list of choices are provided and respondents are asked to put them in order (e.g. when undertaking a feasibility study for a new town centre, a question using a ranking scale may show a list of items that are commonly found in town centres and ask respondents to rank which ones are most important to them); Sliding scales – these are used to discover respondents’ strength of feeling towards an issue. Respondents are given a series of statements and asked how much they agree or disagree with the statement by using a sliding scale where numbers represent different strengths of feelings. For example, 1 = strongly agree and 5 = strongly disagree. Write questions that are clear, precise, and relatively short Because every question is measuring something, it is important for each to be clear and precise. Your goal is for each respondent to interpret the meaning of each survey question in exactly the same way. If your respondents are not clear on what is being asked in a question, their responses may result in data that cannot or should not be applied in your survey findings. Do not use “loaded” or “leading” questions A loaded or leading question biases the response given by the respondent. A loaded question is one that contains loaded words. Loaded or leading questions may hint to the respondent how you expect the question answered, for example ‘Do you think your neighbourhood is still run down?’, by including the word ‘still’ a bias is introduced as it presupposes that the respondent thought the area was previously run down. Ambiguous or compound questions can be confusing, leaving respondents unsure as to how to answer. Compound questions are ones that ask several things which might require different answers, for example ‘Would you like to see more community support officers on the streetsallowing a reduction in investment in CCTV?’. The respondent may wish to provide multiple answers to this question, answering yes to having more community support officers, but disagreeing with the reduction in investment for CCTV. See the section on further reading for more information on question types and constructing survey questions. Administration The costs, required facilities, time, and personnel needed to conduct an effective survey are often underestimated. The most common resource underestimated is time. You need to factor in time to pilot or test your survey, time to deliver your survey, time to give respondents to complete surveys and then have them returned (this may be via mail and therefore take time to return), and you also need to factor in the time required to analyse surveys. When conducting a large scale survey, inputting data to generate your analysis can be very time consuming. The best approach is to often work up your timeline backwards from when you need your results, calculating the time required for each step, this way you can establish when things need to start by. How should it be used? Selecting the type of survey you are going to use is one of the most critical decisions in many social research contexts. In a similar way to interviews, surveys can be delivered in a variety of ways: • postal surveys; • telephone surveys; • email/internet surveys; • street surveys/administered surveys. The delivery method for any survey should be carefully considered, and in many ways will be decided by consideration of factors listed above, such as population, sample size and respondent. Having a good understanding of these will inform the best method of delivery. For example, if the survey is to be distributed to a particular local authority officer role across the country, then a postal or email survey would work best, as it is likely there will be over 350 in the population, geographically dispersed and literate. It is vitally important to conduct a trial run or pilot of any survey, as those that have designed a survey and are close to its subject, may take for granted that the questions and layout will work as a survey with the wider intended population. A survey may be piloted with colleagues or friends that have the same level of involvement in the subject you are surveying as the wider intended population. Feedback should be sought on the ease upon which the survey can be followed and completed. A pilot survey may also be conducted with a subset of the selected sample. This would give opportunities to detect and resolve problems before they obscure or distort the result of the wider survey.

POSITIVISTIC METHODOLOGIES

SURVEYS Surveys involve selecting a representative and unbiased sample of subjects drawn from the group you wish to study. The main methods of asking questions are by face-to-face or telephone interviews, by using questionnaires or a mixture of the two. There are two main types of survey: a descriptive survey: concerned with identifying & counting the frequency of a particular response among the survey group, or an analytical survey: to analyse the relationship between different elements (variables) in a sample group. EXPERIMENTAL STUDIES Experimental studies are done in carefully controlled and structured environments and enable the causal relationships of phenomena to be identified and analysed. The variables can be manipulated or controlled to observe the effects on the subjects studied. For example, sound, light, heat, volume of work levels etc can be managed to observe the effects.Studies done in laboratories tend to offer the best opportunities for controlling the variables in a rigorous way, although field studies can be done in a more ‘real world’ environment. LONGITUDINAL STUDIES These are studies over an extended period to observe the effect that time has on the situation under observation and to collect primary data (data collected at first hand) of these changes. Longitudinal studies are often conducted over several years, which make them unsuitable for most relatively short taught post-graduate courses. However, it is possible to base short time scale research on primary data collected in longitudinal studies by, for example, government agencies, and focusing research on a close analysis of one or more aspect or elements of this data. CROSS-SECTIONAL STUDIES This is a study involving different organisations or groups of people to look at similarities or differences between them at any one particular time, e.g. a survey of the IT skills of managers in one or a number of organisations at any particular time. Cross-sectional studies are done when time or resources for more extended research, e.g. longitudinal studies, are limited. It involves a close analysis of a situation at one particular point in time to give a ‘snap-shot’ result. PHENOMENOLOGICAL METHODOLOGIES CASE STUDIES A case study offers an opportunity to study a particular subject, e.g. one organisation, in depth, or a group of people, and usually involves gathering and analysing information; information that may be both qualitative and quantitative. Case studies can be used to formulate theories, or be: Descriptive (e.g. where current practice is described in detail) Illustrative (e.g. where the case studies illustrate new practices adopted by an organisation Experimental (e.g. where difficulties in adopting new practices or procedures are examined) Researchers are increasingly using autobiography as a means of collecting information from small groups of respondents to seek patterns, underlying issues and life concerns. This method could be used, for example, to trace the influences of variables, such as social class, gender and educational experiences on career development and career progression, or lack of it, within an organisation. It can be, however a time consuming process as it requires trust to be built between researcher and the people concerned. ACTION RESEARCH Action research involves an intervention by a researcher to influence change in any given situation and to monitor and evaluate the results. The researcher, working with a client, identifies a particular objective, e.g. ways of improving telephone responses to ‘difficult’ clients, and explores ways this might be done. The researcher enters into the situation, e.g. by introducing new techniques, and monitors the results. This research requires active co-operation between researcher and client and a continual process of adjustment to the intervention in the light of new information and responses to it from respondents. ETHNOGRAPHY (PARTICIPANT OBSERVATION) This form of research evolved from anthropology and the close study of societies. Ethnography is more usually described as participant observation, and this is where the researcher becomes a working member of the group or situation to be observed. The aim is to understand the situation from the inside: from the viewpoints of the people in the situation. The researcher shares the same experiences as the subjects, and this form of research can be particularly effective in the study of small groups/small firms.Participant observation can be overt (everyone knows it is happening) or covert (when the subject(s) being observed for research purposes are unaware it is happening). PARTICIPATIVE ENQUIRY This is about research within one’s own group or organisation and involves the active involvement and co-operation of people who you would normally work and associate with on a daily basis. The whole group may be involved in the research and the emphasis is on sharing, agreeing, cooperating and making the research process as open and equal as possible.Clearly this type of research can work when the student is already an active and known member of any organisation and may therefore be a particularly suitable approach for part-time employed students in their own workplaces. FEMINIST PERSPECTIVES Research, from a feminist perspective, focuses on knowledge grounded in female experiences and is of benefit to everyone, but particularly women. In a business context, for example, research might centre on the role of women in an organisation and on their views, roles, influence and concerns. Feminist research perspectives have a number of common starting points. First, that women and their contributions to social and cultural life have been marginalized and that this is reflected in past research practice. Second, that men and male perspectives or norms have dominated previous research. And third, that gender, as a significant factor in understanding the world, has been absent from understandings and interpretations of social phenomena, in favour of other categories, e.g. social class. Feminist perspectives draw attention therefore, to how women or women’s concerns may in previous research have been excluded, ignored or relegated to the periphery. It also raises questions therefore about why some forms of knowledge become or are perceived as more valid than others. GROUNDED THEORY Grounded theory reverses approaches in research that collected data in order to test the validity of theoretical propositions, in favour of an approach that emphasises the generation of theory from data.Theory is generated from observations made, rather than being decided before the study. This approach seeks to challenge research approaches that unwittingly or wittingly look for evidence in the data to confirm or deny established theories or practices; the feeling behind this is that you will often find out in research what you are looking for! But if an open mind is kept, new ways of perceiving a subject or new ways of categorising or applying data gathered may be discovered or advanced. The aim of grounded theory is then, to approach research with no preconceived ideas about what might be discovered or learned. Silverman (1993) summarises the main features and stages of grounded theory: 1. An attempt to develop categories which derive from the data; 2. Attempting then to give as many examples as possible in the categories developed in order to demonstrate their importance 3. Then developing these categories into more general and broader analytical frameworks (or theories) with relevance to other situations outside the research subject.

What you can do with Research

So what can we use research to do in order to gain this new knowledge? Some of the ways it can be used one to: x Categorise. This involves forming a typology of objects, events or concepts, i.e. a set of names or ‘boxes’ into which these can be sorted. This can be useful in explaining which ‘things’ belong together and how. x Describe. Descriptive research relies on observation as a means of collecting data. It attempts to examine situations in order to establish what is the norm, i.e. what can be predicted to happen again under the same circumstances. x Explain. This is a descriptive type of research specifically designed to deal with complex issues. It aims to move beyond ‘just getting the facts’ in order to make sense of the myriad other elements involved, such as human, political, social, cultural and contextual. x Evaluate. This involves making judgements about the quality of objects or events. Quality can be measured either in an absolute sense or on a comparative basis. To be useful, the methods of evaluation must be relevant to the context and intentions of the research. x Compare. Two or more contrasting cases can be examined to highlight differences and similarities between them, leading to a better understanding of phenomena. x Correlate. The relationships between two phenomena are investigated to see whether and how they influence each other. The relationship might be just a loose link at one extreme or a direct link when one phenomenon causes another. These are measured as levels of association. x Predict. This can sometimes be done in research areas where correlations are already known. Predictions of possible future behaviour or events are made on the basis that if there has been a strong relationship between two or more characteristics or events in the past, then these should exist in similar circumstances in the future, leading to predictable outcomes. x Control. Once you understand an event or situation, you may be able to find ways to control it. For this you need to know what the cause and effect relationships are and that you are capable of exerting control over the vital ingredients. All of technology relies on this ability to control. You can combine two or more of these objectives in a research project, with sometimes one objective needing to be successfully achieved before starting the next, for example you usually need to be able to explain how something happens before you can work out how to control it. RESEARCH DESIGNS There are numerous types of research design that are appropriate for the different types of research projects. The choice of which design to apply depends on the nature of the problems posed by the research aims. Each type of research design has a range of research methods that are commonly used to collect and analyse the type of data that is generated by the investigations.

Qualitative Vs Quantitative Research: Difference between them with examp...

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How to Write a Literature Review in 30 Minutes or Less

Study Conceptual Framework

General research concepts

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TANGA TANGA IN SHOCK! MAINA KAMANDA & DENNIS WAWERU POWERFUL SPEECH IN K...

WOMAN EMPOWERMENT IN KENYA SAMPLE SURVEY

WOMAN EMPOWERMENT BASELINE SURVEY PROPOSED METHODOLOGY In the Technical Proposal for Consultancy Services for Women empowerment in Kenya Baseline Survey ,I present a typical approach, methodology and work plan we normally use in Baseline Survey assignments, we present our proposed Approach, Technical Methodology and Work Plan for this in this assignment. These are presented in the following sequence: i. Our Approach ii. Proposed Methodology iii. Work Plan We shall use a participatory, collaborative and all inclusive approach to undertake the proposed consultancy Services for Women empowerment research project. This approach is part of our training and capacity building program to ensure that internal capacity in Baseline and the sustainability of the implementation of our recommendations as well as greater acceptability of the results of the baseline survey exercise. Advantages of Participatory & Collaborative Approach The proposed participatory and collaborative approach has the following advantages: 1.Training & Capacity building A participatory collaboration and all-inclusive approach has an inbuilt ability to transfer knowledge to the client and build thier capacity to undertake future impact assessment survey when they become necessary. Furthermore, all the tools and instruments manuals (questionnaires and training manuals), which are jointly developed with the client, shall remain in the custody and ownership of the client. 2.In this approach the Assignment shall benefit from the talents, energies and creative wisdom of the client and their staff 3.The Approach ensures greater client and staff ownership of the Baseline Survey and final products or deliverables. 4.It leads to more realistic results, which will help to logically and rationally solve some of the Implementation challenges currently faced by the client Desk/documents Review The overall objective of this task is to get an in-depth understanding of the project. The literature review will enable the consultant understand all the survey components and its implementation logical frame work. At this stage, the information gaps will be identified and addressed jointly with the client 1. An Inception Report acceptable to the client 2. Clearly identified information gaps and 3. Draft Baseline Survey Instrument(s) Development of Data Collection Tool After a comprehensive desk/documents review, the consultants shall prepare and pre-test survey instrument/questionnaire to be used for gathering relevant survey data. This will be developed to facilitate capturing of all the details of project interventions. The Draft standard questionnaire shall be presented to the client for comments and suggestions before a final Questionnaire is prepared and submitted for final approval and use. Other Data Collection Methods In baseline surveys, no single method is sufficient enough on its own to gather all the relevant information and data. Our consultants shall use the TRIANGULATION method to collect additional survey data and information. These methods shall supplement the data collected using a standard questionnaire, and they shall include the following: Secondary data such as District l reports for target districts/divisions, District Reports from Ministry of Planning and National Development, Reports from local Authorities Focus Group Discussions (FGDs). Face to face interviews with beneficiaries and key stakeholders Expert opinions from those tasked by government with implementation of women empowerment projects, Non government organizations working with women . Sampling Procedure, Sampling Frame AND Survey Design In order to correctly assess the impact of Women empowerment Programs , we shall follow sampling procedure presented below: Sampling Frame The sampling frame: The survey will be conducted in all the 47 Counties in Kenya Sampling Procedure Sampling Procedures used. , shall involve random sampling using simple random sampling procedures. Recruitment and Training of Enumerators and Field Supervisors The consultants shall collaborate with the client to recruit and train a number of field enumerators and supervisors for data collection from the target. At this stage, the minimum qualification requirements for the enumerators and their supervisors shall be discussed and adopted. For now, we propose a minimum of undergraduate degree level of education. The enumerators and the supervisors shall be thoroughly trained to administer the questionnaire throughout the field work. The questionnaire(s) shall be pre-tested and refined by the trained enumerators before going to the field. Data Collection The questionnaires and other data collection methods mentioned above shall be used to collect the relevant information/data from the staff within the sampled project PAs. The enumerators shall be grouped into teams and each team shall be assigned an experienced supervisor. Each supervisor shall work under a consultant who shall be responsible for monitoring the accuracy and reliability of data from the field. Appropriate number of enumerators and field supervisors shall be recruited and trained to ensure speed and timely collection of field data. Data Entry and Cleaning The instrument that shall be developed shall be as closed ended as possible. Data from the field shall be cleaned and all open ended questions shall be first coded. The data shall then be entered into computer using SPPSS and or MS Excel Platforms. The cleaned data shall then be ready for analysis. Data analysis and Report Writing The data shall be analyzed on SPSS and MS Excel platforms. The data will be reported in terms of charts and tables. Advanced statistical analyzes shall be done to determine any correlations and reliability of the data collected. The consultants shall then prepare and present to the client a Draft Baseline Survey Report for comments and suggestions. The comments and suggestions shall be incorporated in the Draft Report and a Draft Final Report shall be prepared by the consultant Stakeholders workshop The client shall organize a stakeholders’ workshop in an appropriate place to be identified jointly with the consultants. The consultants shall present the Draft final report for purposes of validation by the selected stakeholders. After this the comments and suggestions of the stakeholders shall be incorporated in the draft final report. Final Report After incorporating the stakeholders comment and suggestions, the consultants shall prepare and submit to the client a Final Report in required number of hard copies and soft copies in CD ROM in MS Word (and PDF) format. A graphical and iterative process model of our technical methodology is presented in the next page. This is followed by a presentation of our proposed Work Plan for undertaking the baseline survey assignment. WORK PLAN for the Baseline Survey Exercise Our Work Plan for the proposed Baseline Survey consultancy follows an activity based process. A summary of this process model would suffice here. ACTIVITY NO. 1. Preliminary activities: contract signing, resource mobilization, stakeholder briefings, communication and familiarization 2. Documents/Literature Review 3. Inception Report preparations and submission 4. Preparations and Pre-testing of Survey Instrument(s)/Questionnaire 5. Sampling activities 6. Recruitment and Training of field enumerators and supervisors 7. Field Data collection 8. Data cleaning, coding and entry 9. Data Analysis and Interpretations 10. Draft Report Preparations and submission to client for comments and suggestions 11. Preparation of Draft Final Report 12. Stakeholders Validations Workshop and incorporation of stakeholders comments/suggestions 13. Final Report preparation and submission to the client

Nyathi Kano