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Planning Your Research The research plan is the main part of a grant application describing a principal investigator's proposed research, stating its importance and how it will be conducted. A typical research plan has four main sections: A. Specific Aims B. Background and Significance C. Preliminary Studies and Progress Report D. Research Design and Methods The research plan should be written to address the following questions: What do you intend to do? Why is the work important? What has already been done? How are you going to do the work? Specific Aims The specific aim is a formal statement of the objectives and milestones of a research project in a grant application. The purpose of this section is to clearly and concisely describe what the proposed research is intended to accomplish. Should include specific research objectives. Should be hypothesis-based. Objectives should be obtainable within the proposed timeframe. Study aims should fit together in an overall framework. Study should be well-focused rather than broad and diffuse. One page is recommended for the specific aims section. Background and Significance The background and significance section states the research problem including the proposed rationale, current state of knowledge and potential contributions and significance of the research to the field. Critically evaluate existing knowledge, including background literature and relevant data. References should reflect an updated knowledge of the field. Specify existing gaps that the project is intended to fill. Discussion should convey the importance and relevance of the research aims. Highlight potential policy or practice impacts. Highlight why research findings are important beyond the confines of the specific research project (e.g., significance; how research results can be applied). Two to three pages is recommended for the background and significance section. Preliminary Studies and Progress Reports The preliminary results section describes prior work by the investigators relevant to the proposed project. In a new application, the preliminary results are important to establish the experience and competence of the applicant to pursue the proposed research project and to provide support for the study hypotheses and research design. In a competing renewal application, this section becomes a progress report, describing studies performed during the last grant period. The progress report should include a summary of the previous application's specific aims and importance of the findings. Discuss how previous work leads to the current proposal. Emphasize how the previous work demonstrates feasibility of proposed methods. If you do not have the required expertise for a specific methodology, enlist a collaborator or consultant (include a letter of support or agreement—Section J of the Research Plan). Accuracy and overall presentation are important in figures, tables and graphs. Six to eight pages is recommended for the narrative portion of the preliminary studies and progress report section. Research Design and Methods The purpose of the research design and methods section is to describe how the research will be carried out. This section is critical for demonstrating that the applicant has developed a clear, organized and thoughtful study design. Should provide an overview of the proposed design and conceptual framework. Study goals should relate to proposed study hypotheses. Include details related to specific methodology; explain why the proposed methods are the best to accomplish study goals. Describe any novel concepts, approaches, tools or techniques. Include details of how data will be collected and results analyzed. Consider required statistical techniques. Include proposed work plan and timeline. Consider and discuss potential limitations and alternative approaches to achieve study aims. Do not exceed 25 pages for Items A-D, including all table and figures. A common, and costly, mistake is to leap in and begin working without designing what it is you will do and planning how to carry it out. Spend time on working this out and discussing it with your supervisor and any available experts. After this, you will most likely need to submit for approval a brief proposal providing details of your intended studies. You should provide information about: topic; aims of the research, or the problem to be investigated; relevance to your discipline; and the central concepts of the study. Identifying the central concepts of your study often means considering possible attitudes, experiences, behaviours, social processes, reactions whatever is interesting and possible to examine. Take into account such factors as your own personality, age, gender, interests and work load; the participants, their available roles, the activities that will take place, the times at which things happen and the places in which they happen; the accessibility and availability of material, of members of a group or an organisation, of individuals to be interviewed or documentary sources. Methods to be used Many of these remarks apply across the board; and not to just one method. Indeed, it is difficult, and usually fruitless, to compartmentalise research methods. As with most aspects of PhD work, you arrive at the best method to use by asking questions. Experimental and quasi-experimental studies. What design is most appropriate? What factors are to be controlled by you in the experimental design? What factors are to be knowingly ignored, or dealt with by randomisation? How is random allocation of treatments to experimental units to be achieved? Where are the experimental units coming from? Survey research What form of survey is most appropriate for the task at hand: mailout, face-to-face interview, telephone? Who are the intended respondents? How will the respondents be chosen-by a randomisation process, by a quota, by purposive selection, from administrative records, from an organisational hierarchy? If randomisation has a role, how will it be introduced - by your, by a private survey organisation, by a governmental survey organisation? Interview based studies How many members of a group would you attempt to interview? How would you approach them initially? What form will the interviews take - semi-structured, unstructured? What would be the approximate duration of the interviews? Would you use a single interview per person or a series of interviews? What topics would you attempt to cover in the interviews? Participant observation What role or roles would you adopt in the setting? What level of participation would you employ - complete, participant as observer, observer as participant? What would be the best activities in the setting in which to participate? What would be the best physical locations from which to observe? What use, if any, should be made of informants? How would you go about selecting them and establishing a relationship with them? Textual analysis What sort of textual material will you use - printed, graphical, audio or visual? How will you obtain the texts to be analysed? What other aspects of the text will you examine, eg, origins of the material? How will you select a sample of texts to be analysed from the range of available material? Conversation analysis Will you record conversations for the analysis or use conversations recorded for other purposes? If you record conversations for the analysis, how will you manage your role as observer? How will you obtain existing recordings? How will you gain the consent of the participants? If you use conversations recorded for other purposes, how will you obtain existing recordings? For each methodology, ask yourself how should the data be recorded? analysed? These may not be simple decisions to make. But, you need to clarify the steps involved in each part of the study, and establish a timetable for each part. Of course, it is also important to recognise that you may well bring personal biases to the study. Examine how these might affect the data collection process and your interpretation of the results of your research. There are invariable ethical implications to proposed research programs. If possible, seek professional advice before setting about data collection, especially on statistical matters that you may be unfamiliar with. Most universities employ professional statisticians within their mathematics, economics, agricultural, biological and social science departments. These people have to be experienced in the real-life issues of data collection and data analysis relevant to their discipline. Use them. What you want to study and how to study it go hand in hand, though there is rarely one method that is uniquely best for any one aim. Often there will be competing methods, or designs, that can address a given aim, and, especially in the social sciences and humanities, a multi-method approach combining qualitative and quantitative techniques can be stimulating and rewarding. The most appropriate research designs usually emerge when operationalising the aims of the research, that is, during the process of transforming the research question in its most general form, to a doable focused task with clear inputs and manageable outcomes. Look at the correspondence, then, between your operationalised aims and available methods. By justifying to yourself why it is the best method, by sitting down and writing about it, you can examine the fit between aims and research design. You will save yourself a lot of heartache by seeking help on dealing with data before collecting your data. This applies across the entire spectrum of data collection, from qualitative studies (eg, single case studies, textual analysis), through to planned laboratory experimentation with clear, numerical outcomes. Expert help on qualitative data techniques is usually available in social science departments, including sociology, psychology, and education. Most universities employ professional statisticians within their mathematics, economics, agricultural, biological and social science departments. It is their job to advise postgraduate students on how to proceed with their quantitative analyses. Overall, your supervisor should be able to help, or at least point you in the direction of help. Think carefully about the structure of your data, regardless of which method you use. Organise your data in a structured way that reflects the intended method, and the analyses that will follow the data collection phase. Which are your independent variables, which are the dependent? How have you operationalised the aims and concepts of your study? The answers to questions such as these are what you look at to tackle the structure. Once you have collected your data, you may need to seek professional advice, especially if such advice was not sought before you collected your data. If the analysis has a statistical component - which can be as true of textual data as of survey outcomes and laboratory experimentation - organise it so that it is easily accessed by a range of software. Organisation within spreadsheets is often a good way to proceed. They can deal with textual as well as numeric data in a structured way, and be accessed in a straightforward manner from good qualitative and quantitative software analysis packages. The same is true of tables modules in sophisticated word processors; they assist organisational structure which simplifies later analysis. A great deal of invaluable qualitative material ends up unanalysed because it was never transferred to machine readable form. Transferring to machine readable form also drastically reduces error rates on data entry from pencil and paper approaches. There is any amount of good statistical software available nowadays. Elementary analyses can be carried out within spreadsheets and good word processors. There are also software packages to conduct qualitative data analysis, for example NUDIST (Published by Qualitative Solutions and Research Pty Ltd, at Latrobe University; their website is referenced below. Software such as BMDP, SAS, SPSS, NUDIST, etc. and many other exemplars can carry out most of the analyses required in numerical research - which also covers much categorical data collection. SPSS (Statistics Package for the Social Sciences) is one of the best-known statistical software packages; see the main website referenced below. SAS is another very well-known package, it is sold by the SAS Institute and has versions available for mainframes and PCs. The PC version, for Macintosh or Windows, is called JMP; the website link is referenced below. Seek advice on access to analytic software. Most universities maintain licences on popular software and make it available at a reasonable cost; they also usually provide introductory courses that get you started on effectively using the software. After that, courses on individual methods are often available within universities and, in the social sciences, are always available at the summer schools run by the Australian Consortium for Social and Political Research (ACSPRI) in Canberra, and the winter ACSPRI school run in state capitals. It's certainly a good feeling to have so much 'in the bag'. But there is also a temptation now to think that it's just a matter of assembling it. However, your data are of no real use alone. Their value is only in how they can answer your research question, and demonstrate the significance of your work and the contribution it makes to knowledge in your discipline. So….. The first thing is to revisit your initial research question. Then stand back and think what it is you've actually discovered (often it is useful to write a few paragraphs to pin this down) and start to think how you would answer this question using your data. Although you may have gathered your data in various ways at different times - for example, through different experiments, questionnaires, interviews, the literature - this is the place to combine and integrate it all in the best way to make your point and answer your question. If you cannot see how the material you've gathered helps you to answer your question, then one way to see the thread is to tell yourself a story about it. For example: Story of a Thesis Once upon a time researchers believed that …………………….. (literature review). But then I thought that maybe ……………………… (aims), so, what I did was ………………………………………… (method), and I've discovered that …………………………. (findings), which changed the way we …………………. (contribution to knowledge). Often your question now seems inadequate to express what it is you've found and, at the very least, you need to sharpen its focus. Or you may find you've only answered part of the original question. You need to decide whether you are going to answer the rest, i.e. gather more material, or whether you will reformulate and limit the question. Sometimes you need to process the data from many different angles to fully exploit the potential there could be hidden surprises; but also sometimes it becomes apparent that some of your data are irrelevant and, even though it's painful, you may have to discard. Once you have your sharpened research question, a clear picture of what it is you've found and its significance, you can put it together in a story, your next consideration is how best to present it to do justice to your thesis argument or overall theme. How you are going to present your discoveries in detail (which may even involve tables, graphs, diagrams, photos) requires a lot of thought and some trial and error. Here your possible alternative ideas need to be discussed with your supervisor. It's mostly through face-to-face discussion that such things get resolved. Why am I doing it? Introduction Significance What is known? What is unknown? Review of research Identifying gaps What do I hope to discover? Aims How am I going to discover it? Methodology What have I found? Results What does it mean? Discussion So what? What are the possible applications or recommendations? What contribution does it make to knowledge? What next? Conclusions