(b) Ethical behaviour of assistants
Researchers should require ethical compliance from team members just as sponsors expect ethical behaviour from the researcher. Assistants are expected to carry out the sampling plan, to interview or observe respondents without bias and to accurately record all necessary data. Unethical behaviour such as filling in an interview sheet without having asked the respondent the questions cannot be tolerated. The behaviour of the assistants is under the direct control of the responsible researcher or field supervisor. If an assistant behaves improperly in an interview or shares a respondents interview sheet with unauthorized person, it is the researcher’s responsibility. All researchers’ assistants should be well trained and supervised.
(c) Protection of anonymity
Researchers and assistants protect the confidentiality of the sponsor’s information and the anonymity of the respondents. Each researcher handling data should be required to sign a confidentiality and nondisclosure statement.
1. DEFINITION OF LOGISTICS
Scientific research is a process that needs careful planning. This is very necessary considering that research is a very expensive undertaking in terms of time, financial and human resources. Careful planning before starting the research process minimizes the problems often encountered by the researcher in the field as well as enhances the reliability and validity of data.
Logistics in research refers to all those processes that a researcher must address or carry out to ensure successful completion of a research project. The researcher must be aware of the logistical issues before starting the research as such awareness and subsequent preparation will save the researcher a great deal of resources and will also ensure high quality research.
2. LOGISTICAL ISSUES IN RESEARCH
a) Pre-field work logistics
This encompasses those activities that a researcher must carry out before embarking on data collection in the field. The main items to consider in pre-field work logistics are:
i. Terms of reference; These are necessary when a consultant is to be contracted to carry out a research project. The client, an individual or firm, draws up the term of reference and may either invite bids from several consultants or negotiate the cost of the project with one consultant. The terms must be comprehensive as they define the scope of the research and document in detail what the client expects the consultant to do. The first section of the terms of reference should describe the research project including the background, purpose and objectives while the second section should enumerate specific activities that the consultant should carry out.
ii. Obtaining a research permit; As soon as the research proposal is ready, or if necessary, a formal agreement between the researcher and the client is drawn, the researcher must obtain authority to conduct research from the Office of the President. However this requirement may not apply to some institutions particularly those engaged in research on a regular basis or where the client is a donor or a government institution. If the client is a donor or a government institution, it is always advisable to request a letter of approval from the institution or government department certifying that the researcher has approval to carry out the research. It is a government requirement that once the researcher has completed writing the report, a copy of that report should be deposited with the office of the president.
iii. Establishing a work plan; a work plan refers to a plan of action and gives details of various tasks that need to be done during the research process as well as the time frame for each task. The work plan should specify other parties that might be involved in the project and what their tasks should be.
iv. Training research assistants; It is often impossible for one person to collect all the data required in a research project and as a result the researcher relies greatly on research assistants. The quality of collected data depends to a great deal on the ability of the enumerators to collect accurate data. It is therefore very important to identify good enumerators and train them on the use of instruments. The training will also help standardize data collection so as to minimize variations in data collection procedures that may bias the results.
A researcher can identify good enumerators by asking other known researchers to recommend enumerators those researchers have used in similar studies. Alternatively, the researcher might have several enumerators from prior acquaintances or he/she could approach private or public institutions that often have enumerators on the ground to assist in identifying good enumerators.
Depending on the scope of the research project, the researcher should engage enough enumerators to collect data within the specific period. An interview with each enumerator is always recommended before making the decision to engage that person. A contract must then be drawn with each of the enumerators identified.
The researcher should identify a few experienced researchers to help with training the assistants. During training, enumerators must cover a number of things which should include: understanding the background, purpose and objectives of the study, population from which the sample is drawn, geographical location of the respondents and the methodology of data collection. The enumerators must also be thoroughly drilled on the use of instruments. The training should also include other basic principles of data collection such as how to establish rapport with respondents, checking through questionnaires to identify errors and omissions and how to handle completed instruments to avoid loss or misplacement. A researcher may engage as supervisor to oversee data collection.
v. Pre-testing the instrument; This is done to ensure that items in the instrument are stated clearly and have the same meaning to all respondents. The respondents on which the instrument is pre-tested should not be part of the selected sample. It is during the pre-testing of the instrument that the researcher is able to assess the clarity of the instrument and the ease of use of the instrument as well as the time taken to administer the instrument. Also the researcher is able to identify sensitive or annoying items and items identified as sensitive, confusing or biased in any way should be modified or omitted.
Information obtained during pre-testing should be used to revise the instrument. The data obtained during pre-testing is also important and should be analyzed.
vi. Sampling; There are various sampling techniques that a researcher may adopt when selecting a sample. Quantitative research relies heavily on the randomness of the sample. One assumption in identifying a random sample is that a sampling frame exists or will be developed. The randomness of a sample affects the degree to which results from the sample can be generalized to the population. The randomness of the sample is as accurate as the sampling frame from which it is drawn. Where no sampling frame exists, the researcher can construct one.
Following a brief discussion of what constitutes an effective political cartoon and a quick review of the major Iraq news stories in the first months of 2005, the paper analyzes specific cartoons published in the two newspapers.
The exponential technology growth, improved international private rights and improved use of human capital are some of those key terms what the theory is all about....
However, Bateson & Hinde argue that the periods of increased sensitivity are not sharply defined, and consequently they suggested the use of the term ‘sensitive period,’ which is now widely (but by no means universally) used.
CHRONOLOGICAL SNOBBERY: C. S. Lewis's term for what he describes as "the uncritical acceptance of . . . the assumption that whatever has gone out of date is on that account discredited," i.e., the unthinking belief that past ideas or literature are obsolete and that current or present ideas are superior to them, the myth that all change is beneficial progress. Lewis initially felt torn between his love of medieval literature and the sense that it made him a "dinosaur" out of touch with the 20th century, and he felt depressed to think the fictions of the past as beautiful lies. In a fierce philosophical debate ("") with Owen Barfield, Barfield convinced him that such a view was wrong, and Lewis states Barfield "made short work of my chronological snobbery" (qtd. in Duriez 45).
a passing impulse or
potency."9 Her prescient understanding of these critical
periods is now confirmed by scientists and even the popular
culture, with Time magazine calling it "Windows of Opportunity"10
Regardless of what they are called, the sensitive periods are
critical to the child's self development.
Characteristics of a good hypothesis
A good hypothesis should have the following properties:
? Hypotheses should be constructed in such a way that they lend themselves to the Scientific Method.
? They should be empirical statements; never normative or value statements about what should or should not be.
? A hypothesis should describe a general phenomena not a particular occurrence.
? A good hypothesis should be plausible. There should be some logical reason for thinking it possible.
? A good hypothesis is specific. The concepts used are clearly defined. An example of a bad hypothesis is to say that there is a relationship between personality and political attitudes. Which personality type? What attitudes? A good hypothesis is more specific, e.g., People who feel alienated are not likely to have a strong trust in government.
? A good hypothesis is testable. There must be evidence that is obtainable which will indicate whether the hypothesis is correct or not.
? The type of product produced and sold determines the inventory control technique used by a firm.
? Instability of demand and Supplier unreliability inhibits the effective application of Just in time technique.
b) Field work logistics
This is the most important part of the research process. A researcher can develop a good proposal and instrument but if data collection is poor, the results of the study are inaccurate and therefore of no use. It is therefore important for a researcher to ensure that all the mechanics of data collection are efficient. This can be achieved by sticking to guidelines during field work such as:
i. The researcher, supervisor and enumerators should familiarize themselves as much as possible with the geographical area in which the research is to take place.
ii. Enumerators should create a rapport with the respondents. This helps the respondents to see themselves as contributing positively to the outcome of the study.
iii. Researchers should take precaution against common diseases such as malaria.
iv. Researchers and enumerators should be courteous.
v. Enumerators should not be over inquisitive; otherwise they will be viewed with suspicion.
vi. Enumerators must be familiar with the instruments so that they do not appear unsure and confused.
Researchers and enumerators may encounter problems while working in the field which could lead to inefficient data collection. These problems may include:
i. Suspicion from respondents as they may be viewed as strangers. If possible, data collectors should be from the study areas respondents are more likely to trust somebody they know and therefore share information more freely.
ii. Diseases whereby many areas are prone to various diseases such as malaria, cholera typhoid which are all killer diseases.
iii. Harsh climate could at times make it difficult to collect data.
iv. High cost of transport which may lead to enumerators walking over long distances to get to respondents.
v. Language barrier as not all enumerators and researchers are conversant with local languages.
Post-field work logistics
This includes the process of getting the completed instruments from the field to the centre where data coding and analysis will be done. During data collection, the researcher must establish an efficient system of collecting completed instruments on a regular basis. This may be done by setting up centres in the field where enumerators take completed instruments and the supervisor checks through to ensure that instruments are completed properly before dispatching them to the main centre where data analysis and coding will be done
Data coding and entry should start as soon as completed instruments start coming in if this is possible. This reduces time needed to code and enter data. Complete instruments should not be destroyed until a certain period of time has elapsed as they might be required for reference.
If a study is valid then it truly represents what it was intended to represent. Experimental validity refers to the manner in which variables that influence both the results of the research and the generalizability to the population at large. It is broken down into two groups: (1) Internal Validity and (2) External Validity.
Internal Validity. Internal validity refers to a study’s ability to determine if a causal relationship exists between one or more independent variables and one or more dependent variables. In other words, can we be reasonably sure that the change (or lack of change) was caused by the treatment? Researchers must be aware of aspects that may reduce the internal validity of a study and do whatever they can to control for these threats. These threats, if left ignored, can reduce validity to the point that any results are meaningless rendering the entire study invalid. There are eight major threats to internal validity that are discussed below and summarized in Table 1
History. History refers to any event outside of the research study that can alter or effect subjects’ performance. Since research does not occur within a vacuum, subjects often experience environmental events that are different from one another. These events can play a role in their performance and must therefore be addressed. One way to assure that these events do not impact the study is to control them, or make everyone’s experience identical except for the independent variable(s). Since this is often impossible, using randomization procedures can often minimize this risk, assuring that outside events that occur in one group are also likely to occur in the other.
Maturation. While not a major concern in very short studies such as a survey study, maturation can play a major role in longer-term studies. Maturation refers to the natural physiological or psychological changes that take place as we age. This is especially important in childhood and must be addressed through subject matching or randomization. For instance, an episode of major depression typically decreases significantly within a six-month period even without treatment. Imagine we tested a new medication designed to treat depression. If our results showed that subjects who took this medication showed a significant decrease in depressive symptoms within six months, could we truly say that the medication caused the decrease in symptoms? Probably not, especially since maturation alone would have shown similar results.
Testing. People tend to perform better at any activity the more they are exposed to that activity. Testing is no exception. When subjects, especially in single group studies, are given a test as a pretest and then the same test as a posttest, the chances that they will perform better the second time due merely to practice is a concern. For this reason, two group studies with a control group are recommended.
Statistical Regression. Statistical regression, or regression to the mean, is a concern especially in studies with extreme scores. It refers to the tendency for subjects who score very high or very low to score more toward the mean on subsequent testing. If you get a 99% on a test, for instance, the odds that your score will be lower the second time are much greater than the odds of increasing your score.
Instrumentation. If the measurement device(s) used in your study changes during the course of the study, changes in scores may be related to the instrument rather than the independent variable. For instance, if your pretest and posttest are different, the change in scores may be a result of the second test being easier than the first rather than the teaching method employed. For this reason, it is recommended that pre- and posttests be identical or at least highly correlated.
Selection. Selection refers to the manner in which subjects are selected to participate in a study and the manner in which they are assigned to groups. If there are differences between the groups prior to the study taking place, these differences will continue throughout the study and may appear as a change in a statistical analysis. Addressing these differences through subject matching or randomization is highly recommended.
Experimenter Bias. We engage in research in order to learn something new or to support a belief or theory. Therefore, we as researchers may be biased toward the results we want. This bias can effect our observations and possibly even result in blatant research errors that skew the study in the direction we want. Using an experimenter who is unaware of the anticipated results (usually called a double blind study because the tester is blind to the results) works best to control for this bias.
Mortality. Mortality, or subject dropout, is always a concern to researchers. They can drastically affect the results when the mortality rate or mortality quality is different between groups. Imagine in the work experience study if many motivated students dropped out of one group due to illness and many low motivated students dropped out of the other group due to personal factors. The result would be a difference in motivation between the two groups at the end and could therefore invalidate the results.
Table 1: Controlling for Threats to Internal Validity
Threat to Internal Validity Controlling Threat
History Random selection, random assignment
Maturation Subject matching, randomization
Testing Control group
Statistical Regression Omit extreme scores, randomization
Instrumentation Instrumental consistency, assure alternative form reliability
Selection Random selection, random assignment
Experimenter Bias Double blind study
Mortality Subject matching and omission
External Validity. External validity refers to the generalizability of a study. In other words, can we be reasonable sure that the results of our study consisting of a sample of the population truly represents the entire population? Threats to external validity can result in significant results within a sample group but an inability for this to be generalized to the population at large. Four of these threats are discussed below and summarized in Table.2.
Demand Characteristics. Subjects are often provided with cues to the anticipated results of a study. When asked a series of questions about depression, for instance, subjects may become wise to the hypothesis that certain treatments work better in treating mental illness. When subjects become wise to anticipated results (often called a placebo effect), they can begin to exhibit performance that they believe is expected of them. Making sure that subjects are not aware of anticipated outcomes (referred to as a blind study) reduces the possibility of this threat.
Hawthorne Effects. Similar to a placebo, research has found that the mere presence of others watching your performance causes a change in your performance. If this change is significant, can we be reasonably sure that it will also occur when no one is watching? Addressing this issue can be tricky but employing a control group to measure the Hawthorne effect of those not receiving any treatment can be very helpful. In this sense, the control groups is also being observed and will exhibit similar changes in their behavior as the experimental group therefore negating the Hawthorne effect.
Order Effects (or Carryover Effects). Order effects refer to the order in which treatment is administered and can be a major threat to external validity if multiple treatments are used. If subjects are given medication for two months, therapy for another two months, and no treatment for another two months, it would be possible, and even likely, that the level of depression would be least after the final no treatment phase. Does this mean that no treatment is better than the other two treatments? It likely means that the benefits of the first two treatments have carried over to the last phase, artificially elevating the no treatment success rates.