EDUCATIONAL RESEARCH

EDUCATIONAL RESEARCH DEFINE RESEARCH WHAT ARE THE DIFFERENT TYPES OF RESEARCH, TYPES OF RESEARCH DESIGN, BENEFITS / IMPORTANCE OF RESEARCH TYPES OF RESEARCH The different characteristics of research: Research May be Applied or Basic The purpose of applied research is to solve an immediate, practical problem. Basic Research (Pure) adds to the existing body of knowledge; doesn't necessarily provide results of immediate, practical use. Research May be Obtrusive or Non-Obtrusive Obtrusive research - where the researcher introduces conditions that influence participants. Where the researcher manipulates the environment. Non-obtrusive research - where researcher avoids influencing subjects in any way and tries to be as inconspicuous as possible. 2 Four Main Types of Research Historical research - describes what was-mostly nonobtrusive Descriptive research - describes what is-mostly nonobtrusive Correlation research - makes comparisons, looking for trends or tendencies Experimental research - describes what will be - mostly obtrusive RESEARCH DESIGNS Experimental Research Designs Pretest-Posttest Design Pretest ÆtreatmentÆposttest Posttest Only Control Group Design-weak due to lack of control sampling through a pretest (1) TreatmentÆposttest (2) Æposttest (control group) Pretest-Posttest-Control Group Design (1) Pretest ÆtreatmentÆposttest (2) Pretest Æ Æposttest (control group) Quasi-Experimental Design (1) Pretest Æ groupÆtreatmentÆposttest (2) Pretest Æ groupÆ Æposttest(control group) *Grouping is performed based on pretest* Solomon 4-Group Design-used to check effects of posttest (1) Pretest ÆtreatmentÆposttest (2) Pretest Æ Æposttest (control group) (3) treatmentÆposttest (4) Æposttest (control group) 3 Historical Research A systematic process of searching for information and fact to describe analyze or interpret the past Value-can provide prospective for decision making about current problems -issues are often better understood if we understand the historical perspective Sources-must have good backed sources to protect from criticism -most common sources are past records Descriptive Research Describes, interprets, and clarifies what in the present -often done with surveys -may be done by observation or an observational instrument Developmental Research is one common type of descriptive research which involves the study of changes in behavior over a period of time 4 Correlation Research The purpose is to find relationships between two or more variable so to: - Better understand the conditions and events that we encounter (what goes with what) - To predict future conditions and events. - Correlations do not show cause and effect Coefficients of Correlation -range from –1 to 1 -the farther the number is away from 0 the higher the correlation -a negative correlation suggest an inverse effect -a 1 or -1 shows a perfect correlation -a correlation of 0 indicates no relationship Experimental Research An experiment is a research situation where at least one independent variable, called the experimental variable, is deliberately manipulated or varied by the researcher. Variable –element or characteristic being studied Parameter-element that remains unchanged (age, number of subjects IMPORTANCE OF RESEARCH The importance of research is to be able the deepen new knowledge and careful study about something or the subject. With diligent search and studious inquiry aimed at discovery and interpretation of facts, revision of accepted theories or laws or practical application of such new or revised theories or laws. OUTLINE AND DISCUSS THE DIFFERENT PARTS OF RESEARCH Basic Structure The vast majority of scientific reports can be broken down into the following constituent parts. Title - Author(s) Abstract Table of Contents Introduction Equipment and Methodology Results AND Discussion Conclusions References and Citations Appendices Title and Authors Although the title is the shortest page of your report, it is often the most difficult to write. It is important to make clear to a researcher everything that needs saying but without the title being overlong and unwieldy. It does not have to be the first section written because, in many cases, the final title will not occur to you until you have finished writing the report. Nowadays, most research establishments have a database to search titles by keyword so try to make sure that your title contains these. This is doubly important if your research is likely to be published on the internet. The authors section should include your name, as the main writer of the report, alongside the name of your supervisor. In the case of working as part of a team, you should usually include the other members of your group here. Abstract The abstract is the most crucial part of the report because anybody searching for your research on a database or in a journal will usually read only the abstract. Therefore, it must summarize your research, results and conclusions in less than 200 words. Sometimes it is good to think of it as a sample of your research rather than a review; it should inform the researcher that your article contains the information they need. There are a few ideas on how to write your abstract but the best advice is that you look at some journals relevant to your research and try to format your abstract in a similar way. Contents This section and is merely a breakdown of sections and subsections by page number. For a short and straightforward paper it may not be necessary to include a contents page. This is not mandatory for a research paper. Introduction This section of your report is where you will document all the painstaking research into the background of your experiment. The main thing to bear in mind, when writing the introduction, is that a scientist who is unfamiliar with your exact subject matter may be reading the article. It is important, therefore, to try and give a quick and condensed history of the research leading to your experiment, with correct citations. You should also give a little background on why you chose to do this particular experiment and what you expect to find. It is a little ‘old-fashioned' to hypothesis statement at the beginning of the report but the reader should be aware of exactly what you are trying to prove. Method For this portion of your report you must describe the methods used when performing the experiment. This should include, if relevant, the location and times of sample collection, what equipment was utilized, and the techniques used. The idea behind the methodology section is that another researcher can exactly replicate your experiments without having to guess what equipment and what techniques should be used. Scientific articles are peer reviewed and this includes the possibility that other researchers may try to replicate your results.There have been many high profile scientific breakthroughs over the years whose results were unable to be repeated; these experiments were disregarded. For field studies you should give an exact map reference and time as well as including a map in the appendix. If you used complex machinery or computer programs in the course of your experiment, to avoid breaking the flow of your report, you should give only the main information and refer to the exact technical specifications in the appendix. Results These should be a quick synopsis of the facts, figures and statistical tests used to arrive at your final results. You should try to avoid cluttering up your report and insert most of your raw data into the appendix. It is far better to stick with including only tables and graphs that show clearly the results. Do not be tempted to insert large numbers of graphs and figures just for the sake of it; each figure and graph should be mentioned, referred to and discussed in the text. Try to avoid putting in tables and graphs showing the same information; select the type that shows your results most clearly. It is usually preferable to use graphs and relegate the tables to the appendix because it is easier to show trends in graphical format. Figures and graphs should be clear and occupy at least half a page; you are not a magazine editor trying to fit a small graph into an article. All such information must be numbered, as diagrams for graphs and illustrations, and figures for tables; they should be referred to by this number in the body of the report. You do not need to put the full breakdown of the calculations used for your statistical tests; most scientists hate statistics and are only interested in whether your results were significant or not. Relegate the calculations to the appendix. The results section of your report should be neutral and you should avoid discussing your results or how they differed from or compared with what was expected. This information belongs in the next section. Discussion This is the pivotal section of your hard work in obtaining and analyzing your results. In your discussion you should seek to discuss your findings, and describe how they compared and differed from the results you expected. In a nutshell, you are trying to show whether your hypothesis was proved, not proved or inconclusive. You must be extremely critical of yourself in this section; you will not get marked down for mistakes in experiment design or for poor results, only for not recognizing them. Everybody who has written a dissertation or thesis has had to give a presentation to a room full of fellow students, scientists and professors and give a quick synopsis. These people will tear your report apart if you do not recognize its shortcomings and flaws. Very few experiments are 100 per cent correct in their design and conception so it is not really important what your results were, only that you understand their significance. Usually you will have had some promising results and some that did not fit with what you expected. Discuss why things may have gone wrong and what could be done to refine the results in future. Suggest what changes in experimental design might improve the results; there is no right or wrong in science, only progress. Finally, you can discuss at the end ideas for further research, either refining the experiment or suggesting new areas. Even if your paper was a one off, somebody may come along and decide that they find your research interesting and that they would like to continue from where you left off. Summary and Conclusion This is really just a more elaborate version of the abstract. In a few paragraphs you should summarize your findings. Your abstract will do most of this for you but, as long as you do not get carried away, especially for longer reports, it can help the reader absorb your findings a little more. References Include all of your direct references here, even if you only found a couple of sentences. In the case where somebody referred to an original source, reference that too, but if you did not manage to get hold of it, try to rewrite so that you will not have to reference (or use "referred in"-citation). Acknowledgements Here it is polite to acknowledge anybody who helped you with this report, although do not go overboard; it is not an Oscar speech. Your supervisor is a good start, as well as others who helped. If a landowner gave you permission to take samples then it is good practice to acknowledge them and give them a summary of your results, if permitted. Appendices Appendices are very useful because they give you a place to dump raw data and calculations. They must still be laid out correctly; the data must be relevant and referred to in the main report. If you have a lot of relevant photographs of sample sites and methods then they belong here. It is also useful to insert a Google map plan to show from where you took samples. Final Thoughts Hopefully this will have given you a good oversight into writing that perfect report. It is not as daunting as it seems and if you do your research and listen to your supervisor then all should be well and you can get a good grade. FORMULATE AT LEAST 3 PROBLEMS THAT ARE RELATED TO YOUR MAJOR. COMPARE AND CONTRAST QUALITATIVE RESEARCH AND QUANTITATIVE RESEARCH ? Many times those that undertake a research project often find they are not aware of the differences between Qualitative Research and Quantitative Research methods.  Many mistakenly think the two terms can be used interchangeably. So what is the difference between Qualitative Research and Quantitative Research? Qualitative Research is primarily exploratory research. It is used to gain an understanding of underlying reasons, opinions, and motivations. It provides insights into the problem or helps to develop ideas or hypotheses for potential quantitative research. Qualitative Research is also used to uncover trends in thought and opinions, and dive deeper into the problem. Qualitative data collection methods vary using unstructured or semi-structured techniques. Some common methods include focus groups (group discussions), individual interviews, and participation/observations. The sample size is typically small, and respondents are selected to fulfill a given quota. Quantitative Research is used to quantify the problem by way of generating numerical data or data that can be transformed into useable statistics. It is used to quantify attitudes, opinions, behaviors, and other defined variables – and generalize results from a larger sample population. Quantitative Research uses measurable data to formulate facts and uncover patterns in research. Quantitative data collection methods are much more structured than Qualitative data collection methods. Quantitative data collection methods include various forms of surveys – online surveys, paper surveys, mobile surveys and kiosk surveys, face-to-face interviews, telephone interviews, longitudinal studies, website interceptors, online polls, and systematic observations. Snap Survey Software is the ideal survey platform and online research software where structured techniques such as large numbers of respondents and descriptive findings are required. Snap Survey Software has many robust features that will help your organization effectively gather and analyze quantitative data. WHAT ARE VARIABLES? Research Variables: Dependent, Independent, Control, Extraneous & Moderator Research As a researcher, you're going to perform an experiment. I'm kind of hungry right now, so let's say your experiment will examine four people's ability to throw a ball when they haven't eaten for a specific period of time - 6, 12, 18 and 24 hours. We can say that in your experiment, you are going to do something and then see what happens to other things. But, that sentence isn't very scientific. So, we're going to learn some new words to replace the unscientific ones, so we can provide a scientific explanation for what you're going to do in your experiment. The starting point here is to identify what a variable is. A variable is defined as anything that has a quantity or quality that varies. Your experiment's variables are not eating and throwing a ball. Now, let's science up that earlier statement. 'You are going to manipulate a variable to see what happens to another variable.' It still isn't quite right because we're using the blandest term for variable, and we didn't differentiate between the variables. Let's take a look at some other terms that will help us make this statement more scientific and specific. Dependent and Independent Variables A moment ago, we discussed the two variables in our experiment - hunger and throwing a ball. But, they are both better defined by the terms 'dependent' or 'independent' variable. The dependent variable is the variable a researcher is interested in. The changes to the dependent variable are what the researcher is trying to measure with all their fancy techniques. In our example, your dependent variable is the person's ability to throw a ball. We're trying to measure the change in ball throwing as influenced by hunger. An independent variable is a variable believed to affect the dependent variable. This is the variable that you, the researcher, will manipulate to see if it makes the dependent variable change. In our example of hungry people throwing a ball, our independent variable is how long it's been since they've eaten. To reiterate, the independent variable is the thing over which the researcher has control and is manipulating. In this experiment, the researcher is controlling the food intake of the participant. The dependent variable is believed to be dependent on the independent variable. Your experiment's dependent variable is the ball throwing, which will hopefully change due to the independent variable. So now, our scientific sentence is, 'You are going to manipulate an independent variable to see what happens to the dependent variable.' Unwanted Influence Sometimes, when you're studying a dependent variable, your results don't make any sense. For instance, what if people in one group are doing amazingly well while the other groups are doing about the same. This could be caused by a confounding variable, defined as an interference caused by another variable. In our unusually competent group example, the confounding variable could be that this group is made up of players from the baseball team. In our original example of hungry people throwing the ball, there are several confounding variables we need to make sure we account for. Some examples would be: Metabolism and weight of the individuals (for example, a 90 lb woman not eating for 24 hours compared to a 350 lb man not eating for 6 hours) Ball size (people with smaller hands may have a difficult time handling a large ball) Age (a 90-year-old person will perform differently than a 19-year-old person) Confounding variables are a specific type of extraneous variable. Extraneous variables are defined as any variable other than the independent and dependent variable. So, a confounding variable is a variable that could strongly influence your study, while extraneous variables are weaker and typically influence your experiment in a lesser way. Some examples from our ball throwing study include: Time of year Location of the experiment The person providing instructions Our scientific sentence is now, 'You're going to manipulate the independent variable to see what happens to the dependent variable, controlling for confounding or extraneous variables.' Reducing or Increasing Changes In an experiment, if you have multiple trials, you want to reduce the number of changes between each trial. If you tell the ball throwers on the first day to toss a ping-pong ball into a little red cup, and on the second day you tell ball throwers to hurl a bowling ball into a barrel, your results are going to be different. DISCUSS THE FOLLOWING WAYS OF DEFINING THE DIFFERENT VARIABLES IN THE STUDY? Types of Variables Binary variable Obsevations (i.e., dependent variables) that occur in one of two possible states, often labelled zero and one. E.g., “improved/not improved” and “completed task/failed to complete task.” Categorical Variable Usually an independent or predictor variable that contains values indicating membership in one of several possible categories. E.g., gender (male or female), marital status (married, single, divorced, widowed). The categories are often assigned numerical values used as lables, e.g., 0 = male; 1 = female. Synonym for nominal variable. Confounding variable A variable that obscures the effects of another variable. If one elementary reading teacher used used a phonics textbook in her class and another instructor used a whole language textbook in his class, and students in the two classes were given achievement tests to see how well they read, the independent variables (teacher effectiveness and textbooks) would be confounded. There is no way to determine if differences in reading between the two classes were caused by either or both of the independent variables. Continuous variable A variable that is not restricted to particular values (other than limited by the accuracy of the measuring instrument). E.g., reaction time, neuroticism, IQ. Equal size intervals on different parts of the scale are assumed, if not demonstrated. Synonym for interval variable. Control variable An extraneous variable that an investigator does not wish to examine in a study. Thus the investigator controls this variable. Also called a covariate. Criterion variable The presumed effect in a nonexperimental study. Dependent variable The presumed effect in an experimental study. The values of the dependent variable depend upon another variable, the independent variable. Strictly speaking, “dependent variable” should not be used when writing about nonexperimental designs. Dichotomous variable Synonym for binary variable Discrete variable Variable having only integer values. For example, number of trials need by a student to learn a memorization task. C:\rsm\y520\sec5982_fall02\week_2\variable_types.fm 2 Dummy Variables Created by recoding categorial variables that have more than two categories into a series of binary variables. E.g., Marital status, if originally labelled 1=married, 2=single, and 3=divorced, widowed, or separated, could be redefined in terms of two variables as follows: var_1: 1=single, 0=otherwise. Var_2: 1=divorced, widowed, or separated, 0=otherwise. For a married person, both var_1 and var_2 would be zero. In general, a categorical variable with k categories would be recoded in terms of k - 1 dummy variables. Dummy variables are used in regression analysis to avoid the unreasonable assumption that the original numerical codes for the categories, i.e., the values 1, 2, ..., k, correspond to an interval scale. Use: to place cases in specific groups. Endogenous variable A variable that is an inherent part of the system being studied and that is determined from within the system. A variable that is caused by other variables in a causal system. Exogenous variable A variable entering from and determined from outside of the system being studied. A causal system says nothing about its exogenous variables. Independent variable The presumed cause in an experimental study. All other variables that may impact the dependent variable are controlled. The values of the independent variable are under experimenter control. Strictly speaking, “independent variable” should not be used when writing about nonexperimental designs. Interval variable Synonym for continuous variable Intervening variable A variable that explains a relation or provides a causal link between other variables. Also called by some authors “mediating variable” or “intermediary variable.” Example: The statistical association between income and longevity needs to be explained because just having money does not make one live longer. Other variables intervene between money and long life. People with high incomes tend to have better medical care than those with low incomes. Medical care is an intervening variable. It mediates the relation between income and longevity. Latent variable An underlying variable that cannot be observed. It is hypothesized to exist in order to explain other variables, such as specific behaviors, that can be observed. Example: if we observe the voting records of members of the House of Representatives on spending bills for the military, foodstamps, law enforcement, and promoting business investment, we might find underlying patterns that could be explained by postulating latent variables such as conservatism and liberalism. C:\rsm\y520\sec5982_fall02\week_2\variable_types.fm 3 Manifest variable An observed variable assumed to indicate the presence of a latent variable. Also known as an indicator variable. We cannot observe intelligence directly, for it is a latent variable. We can look at indicators such as vocabulary size, success in one’s occupation, IQ test score, ability to play complicated games (e.g., bridge) well, writing ability, and so on. Manipulated variable Synonym for independent variable. Mediating variable Synonym for intervening variable. Example: Parents transmit their social status to their children directly, but they also do so indirectly, through education: viz. Parent’s status ➛ child’s education ➛ child’s status Moderating variable A variable that influences, or moderates, the relation between two other variables and thus produces an interaction effect. Nominal variable Synonym for categorical variable. Ordinal variable A variable used to rank a sample of individuals with respect to some characteristics, but differences (i.e., intervals) and different points of the scale are not necessarily equivalent. Examples: anxiety might be rated on a scale “none,” “mild,” “moderate,” and “severe,” with numerical values of 0, 1, 2, 3. A patient with an anxiety score of 1 is ranked as less anxious than a patient with a score of 3, but patients with scores 0 and 2 do not necessarily have the same differences in anxiety as patients with scores of 1 and 3. Outcome variable The presumed effect in a nonexperimental study. Synonym for criterion variable. Polychotomous variables Variables that can have more than two possible values. Strictly speaking, this includes all but binary variables. The usual reference is to categorical variables with more than two categories. Predictor variable The presumed “cause” on a nonexperimental study. Often used in correlational studies. For example, SAT scores predict first semester GPA. The SAT score is the predictor variable. Treatment variable Synonym for independent variable HOW ARE YOU GOING TO PRESENT THE DIFFERENTVARIABLES IN THE STUDY? ndependent Variables = Grouping Variables Dependent Variable = Outcome Measures What is a Variable - and What's Not? Independent Variables Dependent Variables Extraneous or Confounding Variables Variables from a Title Summary Back to Basics of Research Outline Objectives: Be able to identify the independent and dependent variables of a study from its title or abstract. Be able to define the term "extraneous variable." Be able to identify the features of independent and dependent variables What is a variable - and what's not? A variable is a characteristic or feature that varies, or changes within a study. The opposite of variable is constant: something that doesn't change. In math, the symbols "x" , "y" or "b" represent variables in an equation, while "pi" is a constant. In an experimental example, if a study is investigating the differences between males and females, gender would be a variable (some subjects in the study would be men, and others would be women). If a study has only female subjects, gender would not be a variable, since there would be only women. If a study includes both males and females as subjects, but is not interested in differences between men and women - and does not compare them, gender would not be a variable in that study. If a study compares three different diets, but keeps all 3 diets the same in the amount of sodium, then sodium isn't a variable in that study - it's a constant. Other features of the diets would be variables of interest - maybe the calories or carbohydrates or fat content. In this course, we will study independent variables, dependent variables, and confounding or intervening variables. In this section, we will focus on how to identify and distinguish Independent from Dependent variables, and the roles these variables play in a research study. Independent Variables In experimental research, an investigator manipulates one variable and measures the effect of that manipulation on another variable. The variable that the researcher manipulates is called the independent, or grouping variable. The independent variable is the variable that is different between the groups compared: all the members of one group will have the same level of the independent variable, a second group will have a different level of that same variable, and the same for a 3rd or 4th group, if present. For example, let's take a study in which the investigators want to determine how often an exercise must be done to increase strength. Stop for a minute and think about how they might organize a study so they could figure this out. There are usually several possible studies that could be done to address a question. These investigators decided to compare 3 groups, one group participate in a set of specific exercises 4 times per week; a second group would do the same exercises, but only twice per week, and a control group would participate in stretching exercises that would have no impact on strength. The variable that differs between these 3 groups that are compared is an Independent Variable. This particular independent variable has 3 LEVELS of the SINGLE independent variable - in this example: type of exercise. Some non-experimental studies also have independent variables, but they may not be determined or manipulated by the investigators. For example, a study may compare test performance between men and women; so gender would be the independent variable. However, since investigators didn't determine or specify which individuals would be men and which would be women (!), it is not considered to be an active independent variable. Because gender does define the variable used for comparison, it is still an independent variable, even though it has lost some of its power. We'll look at this in more detail in the next chapter. (back to top) Dependent Variables The outcome variable measured in each subject, which may be influenced by manipulation of the independent variable is termed the dependent variable. In experimental studies, where the independent variables are imposed and manipulated, the dependent variable is the variable thought to be changed or influenced by the independent variable. Example: study title: Effects of a new tooth paste (YummyTooth) on incidence of caries in 1st grade children. The intervention group was given YummyTooth toothpaste, while the control group was given an identical toothpaste that did not contain the secret ingredient in YummyTooth. Subjects were observed brushing their teeth 3x per day with the assigned toothpaste (by teacher or parent). 6 months later, dental appointments were scheduled, and the number of dental caries present in each child was reported. In this study, the toothpaste was the independent variable; it was different between the two groups: one level was the YummyTooth toothpaste itself, and the second level (a control group) was the identical non-YummyTooth toothpaste (a placebo). The outcome measure (dependent variable) - that "depended" upon the type of toothpaste, was the number of dental caries. Frequently a single research study may have many dependent variables. However, since most analyses only consider one dependent variable at a time (called univariate analyses), each dependent variable analysis is considered a separate study for the purposes of statistical analysis. Independent Variables in Observational Studies and Some Quasi-Experimental Studies: When Independent Variables are not Manipulated Observational and some quasi-experimental studies lack active interventions - their independent variables are not specifically imposed by the investigators. They may study variables that cannot physically impose the intervention (e.g., gender, country of birth, family history of heart disease) or cannot manipulate it ethically (smoking, exposure to risk factors). While these studies cannot tell us whether one variable causes changes, they can tell us how strong a relationship exists between variables. Identifying the Independent variables in these studies is a bit trickier than in true experiments, where the investigators control them. Observational studies may collect all of the data from a single questionnaire or set of medical records, so all information comes from a single assessment. Since they don't impose a change, they cannot tell us what would happen if we changed something. They tell us about relationships among variables in populations. In many cases, a single set of data can be analyzed in several ways, so it is important to determine exactly how the particular study probed the data: what questions did they ask? In these studies, independent variables are still the grouping variables, so key in on statements that indicate comparisons. In a tooth-brushing study, the investigators might ask the parents how frequently the children brushed their teeth (check 0, 1, 2, 3), and collect the caries data from dental records from the schools. In this case, the investigators are not imposing a tooth-brushing regime, but are simply inquiring about existing habits, and then comparing those groups to determine the strength of the relationship. Here, as before, the independent variable is tooth-brushing, but now it is the comparison of groups of children in each category (#times brushed per day). The dependent (outcome measure) variable, is still the number of caries. Another example from a study title:  Impact of smoking status on long-term mortality in patients with acute myocardial infarction The independent variable is smoking status (undoubtedly not imposed, not active)- could be reporting just smoking/non-smoking/quit categories. The dependent variable would be long-term mortality. Confounding or Extraneous Variables In the best circumstances, the only consistent feature that differs between the intervention and control groups is the intervention level itself. The groups that are compared should be similar in every other way, and only differ in the independent variable level. In the YummyTooth toothpaste example above, this would mean that the groups receiving the two types of toothpaste should be similar. If children with a history of many more caries were systematically put into the control group, this would introduce bias. When the two groups start out the same (have the same incidence of prior caries), then introduce a single intervention difference, any difference in later number of caries reflects only the influence of the intervention. If there are other differences between the two groups of children, such as a bias that put children with more caries in the control group, then we can no longer have that confidence. In this situation, even if the YummyTooth group of children have significantly fewer caries, we won't be able to tell whether it was the toothpaste, or the history of caries, or some combination, that caused the different number of caries between the groups. These biasing variables are called confounding or extraneous variables. The confounding variables are differences between groups other than the independent variables. That means that most members of a group are alike on a variable, but different from the other group, e.g., if the control group was mostly smokers and the experimental group mostly non-smokers. These variables interfere with assessment of the effects of the independent variable because they, in addition to the independent variable, potentially affect the dependent variable. Since they cannot be separated from the independent variable, they are said to be confounding variables. These variables produce differences between groups that cannot be attributed to the independent variable. In these situations,the independent variable is not the only difference that exists between the groups. Therefore, there may be many other variables contributing to the differences observed between the groups compared. Thus, we cannot conclude that the independent variable is the cause of the difference or change seen. These other factors that may influence the dependent variable are termed "extraneous", "intervening" or "confounding" variables. Usually this type of confounding variable is avoided by randomly assigning subjects to groups, so not all of one kind of subject goes into one group. Identifying Independent & Dependent Variables Let's say that a study reports "The effects of kicking on the position of the ball." Just from this title of the study, we can tell that the outcome measure (the dependent variable) will be the position of the ball (or the distance traveled). The variable thought to influence the distance, the independent variable, would be the kicking. We would assume that in the study, some balls were kicked (intervention or experimental group), and others were not kicked; or had something else done to them; so there were at least 2 levels of the independent variable. You can use this typical form to determine the independent and dependent variables from the title of the study. If the study title is in the form "The effects of X on Y in Z". X is the independent variable and Y is the dependent variable - the outcome, and Z is the type of subjects represented. A simple example would be: The effects of tomatoes on risk of prostate cancer in Scandinavian men. The "tomatoes" is in the X position, so it is the independent variable - it is the variable being compared between groups (and the variable possibly manipulated - it also implies that there's another level - a comparison group of some sort). The Y position is "risk of prostate cancer" - that's the dependent variable, which is measured as the outcome. The target population: Scandinavian men is the sample in which the study was done - however, the results may be more generalizable. (back to top) Here's another example: A randomized trial of breast cancer risk counseling: the impact on self-reported mammography use. From this title, you can tell that the independent variable is type of counseling (with 2 or more levels, risk counseling and no counseling or standard care). The dependent variable is self-reported mammography use. Variable Summary:   Independent Variable Dependent Variable manipulated/measured "manipulated" or "imposed" by researchers in an experiment measured as outcome variable groups different/groups the same grouping variable: different levels for different groups in observational studies all subjects in all groups are measured the same way   each study may have several independent variables each study likely has several to many dependent variables WHAT ARE THESE VARIABLES TO BE DEFINED? Defining Variables Variables can be defined as any aspect of a theory that can vary or change as part of the interaction within the theory.  In other words, variables are anything can effect or change the results of a study.  Every study has variables as these are needed in order to understand differences. In our theory, we have proposed that students exposed to the workforce take a more active role in their education than those who have no exposure.  Looking at this theory, you might see that several obvious variables are at play, including ‘prior work experience’ and ‘age of student.’  However, other variables may also play a role in or influence what we observed.  It is possible that older students have better social skills causing them to interact more in the classroom.  They may have learned better studying skills, resulting in higher examination grades.  They may feel awkward in a classroom of younger students or doubt their ability more and therefore try harder to succeed.  All of these potential explanations or variables need to be addressed for the results of research to be valid. Let’s start with the variables that are directly related to the theory.  First, the prior work experience is what we are saying has the effect on the classroom performance.  We could say that work history is therefore the cause and classroom grades are the effect.  In this example, our independent variable (IV), the variable we start with (the input variable) is work experience.  Our dependent variable (DV), or the variable we end up with (the outcome variable) is grades. We could add additional variables to our list to create more complex research.  If we also looked at the affect of study skills on grades, study skills would become a second independent variable.  If we wanted to measure the length of time to graduation along with grades, this would become a second dependent variable.  There is no limit to the number of variables that can be measured, although the more variables, the more complex the study and the more complex the statistical analysis. The most powerful benefit of increasing our variables, however, is control.  If we suspect something might impact our outcome, we need to either include it as a variable or hold it constant between all groups.  If we find a variable that we did not include or hold constant to have an impact on our outcome, the study is said to be confounded.  Variables that can confound our results, called confounding variables, are categorized into two groups: extraneous and intervening. Extraneous Variables .  Extraneous variables can be defined as any variable other than the independent variable that could cause a change in the dependent variable.  In our study we might realize that age could play a role in our outcome, as could family history, education of parents or partner, interest in the class topic, or even time of day, preference for the instructor’s teaching style or personality.  The list, unfortunately, could be quite long and must be dealt with in order to increase the probability of reaching valid and reliable results. Intervening Variables .  Intervening variables, like extraneous variables, can alter the results of our research.  These variables, however, are much more difficult to control for.  Intervening variables include motivation, tiredness, boredom, and any other factor that arises during the course of research.   For example, if one group becomes bored with their role in the research more so than the other group, the results may have less to do with our independent variable, and more to do with the boredom of our subjects. WHAT IS A STATEMENTOF THE PROBLEM? A problem statement is a clear description of the issue(s), it includes a vision, issue statement, and method used to solve the problem. The 5 'W's can be used to spark the discussion about the problem. A problem statement expresses the words that will be used to keep the effort focused and it should represent a solveable problem. How to Write a Problem Statement A problem statement is a clear concise description of the issue(s) that need(s) to be addressed by a problem solving team. It is used to center and focus the team at the beginning, keep the team on track during the effort, and is used to validate that the effort delivered an outcome that solves the problem statement. It has a specific form: Vision - what does the world look like if we solve the problem? Issue Statement - one or two sentences that describe the problem using specific issues. It is not a "lack of a solution" statement. For example, our problem is that we don't have an ERP system. Method - the process that will get followed to solve the problem. For example, DMAIC or Kaizen. How to get started The 5 'W's - Who, What, Where, When and Why - is a great tool that helps get pertinent information out for discussion. From the [poem] from Rudyard Kipling's "The Elephant's Child" which opens with: I keep six honest serving-men  (They taught me all I knew);  Their names are What and Why and When  And How and Where and Who. Who - Who does the problem affect? Specific groups, organizations, customers, etc. What - What are the boundaries of the problem, e.g. organizational, work flow, geographic, customer, segments, etc. - What is the issue? - What is the impact of the issue? - What impact is the issue causing? - What will happen when it is fixed? - What would happen if we didn’t solve the problem? When - When does the issue occur? - When does it need to be fixed? Where - Where is the issue occurring? Only in certain locations, processes, products, etc. Why - Why is it important that we fix the problem? - What impact does it have on the business or customer? - What impact does it have on all stakeholders, e.g. employees, suppliers, customers, shareholders, etc. Each of the answers will help to zero in on the specific issue(s) and frame the Issue Statement. Your problem statement should be solveable. That is, it should take a reasonable amount of time to formulate, try and deploy a potential solution. Example Consider a software development and hosted data services company that supplies products and services to wireless carriers. They had issues deploying new software releases into the production environment. Deployment in this case is the work necessary for taking a production ready binary and installing, testing and releasing it into the production environment. The company failed to deploy the releases on-schedule over 50% of the time. Problem Statement: We want all of our software releases to go to production seamlessly, without defects, where everyone is aware and informed of the outcomes and status. (Vision) Today we have too many release failures that result in too many rollback failures. If we ignore this problem; resources will need to increase to handle the cascading problems, and we may miss critical customer deadlines which could result in lost revenue, SLA penalties, lost business, and further damage to our quality reputation. (Issue Statement) We will use our Kaizen Blitz methodology in evaluating the last release to help us improve our processes. (Method) Conclusion A problem well stated is half solved, Wally Davis taught me that one.  And he's right, the better the clarity around what the team is attempting to fix, the more efficient they'll be in solving the problem, the solution will better 'fix' the issues, and the team can get back to executing the business versus fixing it. DIFFERENTIATE ASSUMPTION FROM THE HYPOTHESIS? In science hypothesis and assumption are concepts that are similar in nature and are used commonly in research and experiments. So what is Hypothesis? Something that has yet not been proved to classify as a theory but believed to be true by the researcher is labeled as a hypothesis. A hypothesis is merely a proposition that is presented or put forward by a scientist to explain a natural phenomenon. It does not become a theory until it is proved and tested under different conditions and circumstances. At best, it is an assumption that has been made working. What is Assumption? An assumption is any statement that is believed to be true. Many times, people pay dearly when they jump to conclusions based upon their assumptions. Thinking about the feelings of others is merely assumption as there is no way to tell what a person is thinking or feeling. What is the difference between a Hypothesis and Assumption? • Hypothesis is an argument put forward to explain a phenomenon or sets of phenomena • Hypothesis is not a theory until it has been proved and verified under different circumstances • Anything taken for granted is an assumption, and a hypothesis is at best a working assumption • Hypothesis is a theory in waiting as it can be called theory only after verification Source: http://www.differencebetween.com/difference-between-hypothesis-and-vs-assumption/#ixzz36nojxXoh Webster's Dictionary presents the following definitions for these terms: Fact - the assertion or statement of a thing done or existing; Assumption - the act of taking for granted, or supposing a thing without proof; Observation - the act or the faculty of observing or taking notice; the act of seeing, or of fixing the mind upon, anything. Hypothesis - something not proved, but assumed for the purpose of argument, or to account for a fact or an occurrence So what interpretation the Lean Start-up practice is suggesting? In his article “Difference Between a Hypothesis and an Assumption“, Sean Murphy argues that hypothesis is what is being tested explicitly by an experiment. An assumption is tested implicitly. By making your assumptions as well as your hypotheses explicit you increase the clarity of your approach and the chance for learning. The two things that can trip you up most often is an unconscious assumption that masks a problem with your hypothesis or an unconscious bias in who you are testing the value hypothesis on. Source: http://tiny.cc/w1zmix The two most important assumptions entrepreneurs make are what I call the value hypothesis and the growth hypothesis. The value hypothesis tests whether a product or service really delivers value to customers once they are using it. The growth hypothesis tests how new customers will discover a product or service. As soon as we formulate a hypothesis that we want to test, the product development team should be engineered to design and run this experiment as quickly as possible, using the smallest batch size that will get the job done. Here is the process suggested by Steve Blank: Personally my interpretation on the difference between assumption and hypothesis is the following: Assumption is a general feeling about a business problem. In order to test if it’s true or not one should develop a sound hypothesis (one or many) relevant to the assumption and the business problem. For example: Let’s say that you like to develop ice-cream business. One of the assumptions may be that most kids like to eat ice-cream. However, you like to develop this business in your city X. So in this case, you might like to test the following hypothesis: More than 50% of the children in city X eat ice-cream. Next step is to come-up with a good test to validate this assumption. WHAT ARE HYPOTHESIS AND WHAT ARE THE DIFFERENT TYPES OF HYPOTHESIS? HYPOTHESIS   As mentioned previously, a hypothesis is a tool of quantitative studies. It is a tentative and formal prediction about the relationship between two or more variables in the population being studied, and the hypothesis translates the research question into a prediction of expected outcomes. So…a hypothesis is a statement about the relationship between two or more variables that we set out to prove or disprove in our research. study. To be complete the hypothesis must include three components:    The variables.  The population.  The relationship between the variables.   A hypothesis should be:  stated clearly using appropriate terminology;  testable;  a statement of relationships between variables;  limited in scope (focused).   Examples of a hypothesis are: Health Education programmes influence the number of people who smoke. Newspapers affect people's voting pattern. Attendance at lectures influences exam marks. Diet influences intelligence.   Types of hypotheses There are different types of hypotheses: Simple hypothesis - this predicts the relationship between a single independent variable (IV) and a single dependent variable (DV)    For example:    Lower levels of exercise postpartum (IV) will be associated with greater weight retention (DV).   NB. IV = independent variable D V = dependent variable   Complex hypothesis - this predicts the relationship between two or more independent variables and two or more dependent variables.     1. Example of  a complex multiple independent variable hypothesis: Low risk pregnant women (IV) who:          value health highly;                                                           believe that engaging in health promoting behaviours will result in positive outcomes;        perceive fewer barriers to health promoting activities;        are more likely than other women to attend pregnancy-related education programmes (DV).     2. Example of a complex multiple dependent variable hypothesis: The implementation of an evidence based protocol for urinary incontinence (IV) will result in (DV):             decreased frequency of urinary incontinence episodes;        decreased urine loss per episode;        decreased avoidance of activities among women in ambulatory care settings.                    Hypotheses can be stated in various ways as long as the researcher specifies or implies the relationship that will be tested.   For example: Lower levels of exercise postpartum are associated with greater weight retention. There is a relationship between level of exercise postpartum and weight retention. The greater the level of exercise postpartum, the lower the weight retention. Women with different levels of exercise postpartum differ with regard to weight retention. Weight retention postpartum decreases as the woman's level of exercise increases. Women who exercise vigorously postpartum have lower weight retention than women who do not.    Directional hypotheses   These are usually derived from theory. They may imply that the researcher is intellectually committed to a particular outcome. They specify the expected direction of the relationship between variables i.e. the researcher predicts not only the existence of a relationship but also its nature.    Non-directional hypotheses Used when there is little or no theory, or when findings of previous studies are contradictory. They may imply impartiality. Do not stipulate the direction of the relationship.   Associative and causal hypotheses  Associative hypotheses Propose relationships between variables - when one variable changes, the other changes. Do not indicate cause and effect.  Causal hypothesese Propose a cause and effect interaction between two or more variables. The independent variable is manipulated to cause effect on the dependent variable.      The dependent variable is measured to examine the effect created by the independent variable.   A format for stating causal hypotheses is: The subjects in the experimental group who are exposed to the independent variable demonstrate greater change, as measured by the dependent variable, than do the subjects in the control group who are not exposed to the independent variable.     Null hypotheses These are used when the researcher believes there is no relationship between two variables or when there is inadequate theoretical or empirical information to state a research hypothesis   Null hypotheses can be:   simple or complex;   associative or causal.    Testable hypotheses Contain variables that are measurable or able to be manipulated. They need to predict a relationship that can be 'supported' or 'not supported' based on data collection and analysis.   WHAT IS THE PURPOSE OF THE RELATED LITERATURE? The purpose of a literature review is to: establish a theoretical framework for your topic / subject area define key terms, definitions and terminology identify studies, models, case studies etc supporting your topic define / establish your area of study, ie your research topic. The purpose of the literature review is to provide a critical written account of the current state of research on a selected topic: Identifies areas of prior scholarship Places each source in the context of its contribution to the understanding of the specific issue, area of research, or theory under review. Describes the relationship of each source to the others that you have selected Identifies new ways to interpret, and shed light on any gaps in, previous research Points the way forward for further research. HOW ARE YOU GOING TO CLARIFY THEM? A literature review is an evaluative report of information found in the literature related to your selected area of study. The review should describe, summarise, evaluate and clarify this literature. It should give a theoretical base for the research and help you (the author) determine the nature of your research. Works which are irrelevant should be discarded and those which are peripheral should be looked at critically. A literature review is more than the search for information, and goes beyond being a descriptive annotated bibliography. All works included in the review must be read, evaluated and analysed (which you would do for an annotated bibliography), but relationships between the literature must also be identified and articulated, in relation to your field of research. "In writing the literature review, the purpose is to convey to the reader what knowledge and ideas have been established on a topic, and what their strengths and weaknesses are. The literature review must be defined by a guiding concept (e.g. your research objective, the problem or issue you are discussing, or your argumentative thesis). It is not just a descriptive list of the material available, or a set of summaries. http://www.writing.utoronto.ca/advice/specific-types-of-writing/literature-review WHAT ARE THE DIFFERENT TYPES OF RESEARCH INSTRUMENT? DISCUSS INSTRUMENT BRIEFLY. nstrument is the generic term that researchers use for a measurement device (survey, test, questionnaire, etc.). To help distinguish between instrument and instrumentation, consider that the instrument is the device and instrumentation is the course of action (the process of developing, testing, and using the device). Instruments fall into two broad categories, researcher-completed and subject-completed, distinguished by those instruments that researchers administer versus those that are completed by participants. Researchers chose which type of instrument, or instruments, to use based on the research question. Examples are listed below: Researcher-completed Instruments Subject-completed Instruments Rating scales Questionnaires Interview schedules/guides Self-checklists Tally sheets Attitude scales Flowcharts Personality inventories Performance checklists Achievement/aptitude tests Time-and-motion logs Projective devices Observation forms Sociometric devices Usability Usability refers to the ease with which an instrument can be administered, interpreted by the participant, and scored/interpreted by the researcher. Example usability problems include: Students are asked to rate a lesson immediately after class, but there are only a few minutes before the next class begins (problem with administration). Students are asked to keep self-checklists of their after school activities, but the directions are complicated and the item descriptions confusing (problem with interpretation). Teachers are asked about their attitudes regarding school policy, but some questions are worded poorly which results in low completion rates (problem with scoring/interpretation). Validity and reliability concerns (discussed below) will help alleviate usability issues. For now, we can identify five usability considerations: How long will it take to administer? Are the directions clear? How easy is it to score? Do equivalent forms exist? Have any problems been reported by others who used it? It is best to use an existing instrument, one that has been developed and tested numerous times, such as can be found in the Mental Measurements Yearbook. We will turn to why next. DIFFERENTIATE THEORY FROM CONCEPT – THEORY AND CONCEPT IN A STUDY? Concept vs Theory   Concept and theory are two terms that one encounters quite often in the scientific jargon. As similar as they may sound, it must be understood that the two terms, concept and theory, are used in different contexts to signify different aspects which indeed aids in recognizing the true definitions of concept and theory. What is a Concept? A concept is a term that is often used in metaphysics, especially in ontology that can be defined as a fundamental category of existence. It is a group of abstract ideas put together in order to describe a phenomenon. However, in philosophy, there exists three ways of defining a concept. • Mental representations – concepts as a subset of mental representations made from the physical material of the brain that allows the human beings to draw inferences about things that they encounter in day to day life. According to the physicalist theory of mind, the brain uses concepts for processes such as decision making, categorization, learning, inference and memory. • Abilities – concepts as abilities that are peculiar to cognitive agents. • Abstract objects – this debate concerning the ontological status of concepts is based upon a Platonist theory of mind recognizes concepts as aspects that mediate between language, referents and thought. There are also several prominent theories on the structure of concepts such as classical theory, prototype theory and theory-theory. What is Theory? Theory can be defined as a collection of ideas, facts, phenomena or events that can be used to explain a certain topic. When developing a theory, it is necessary to use the rational and contemplative forms of generalized and abstract thinking while a theory is based upon general factors that are independent of the phenomenon being explained. A theory provides an explanation for observations and based upon the various assumptions of this explanation, several possible hypotheses can be derived in order to test the theory. A person who develops theories is known as a theorist. In the modern sense of the word, theory refers to scientific theories which stand for a comprehensive explanation of a nature that fulfils modern scientific criteria while being consistent with the scientific method. What is the difference between Concept and Theory? Concept and theory are two terms that seem quite similar in nature and because of this apparent similarity, it is sometimes quite difficult to discern one from the other. In a precise study such as science, one cannot afford to make mistakes such as this. • A concept is an abstract notion. A theory is a collection of explanations about a particular subject. • A concept needs not be tested. The main component of a theory is that it must be able to be tested and proved or disapproved. • Concepts are prone to morph and change. Theories although not considered as facts, can be named as the best possible educated guess surrounding a certain phenomenon. • A concept is a general idea. A theory is an explanation that is supported by significant evidence. A concept does not have such evidence backing it. • A concept can be unorganized. A theory must be organized. WHO ARE RESPONDENTS AND HOW ARE YOU GOING TO CHOOSE THEM? Respondents: answer (respond/reply to) questionnaires - usually quantitative research. Respondents generally answer (respond/reply to) the questions asked by the researcher - no more, no less. DISCUSS THE PRESENTATION OF YOUR FINDINGS BASED ON THE FOLLOWING SEQUENCE: STATISTICAL Statistically significant results are those that are interpreted not likely to have occurred purely by chance and thereby have other underlying causes for their occurrence. Whenever a statistical analysis is performed and results interpreted, there is always a finite chance that the results are purely by chance. This is an inherent limitation of any statistical analysis and cannot be done away with. Also, mistakes such as measurement errors may cause the experimenter to misinterpret the results. However, the probability that the process was simply a chance encounter can be calculated, and a minimum threshold of statistical significance can be set. If the results are obtained such that the probability that they are simply a chance process is less than this threshold of significance, then we can say the results are not due to chance. Common statistically significant levels are 5%, 1% and 0.1% depending on the analysis In terms of null hypothesis, the concept of statistical significance can be understood to be the minimum level at which the null hypothesis can be rejected. This means if the experimenter sets his statistical significance level at 5% and the probability that the results are a chance process is 3%, then the experimenter can claim that the null hypothesis can be rejected. In this case, the experimenter will call his results to be statistically significant. Lower the significance level, higher the confidence. Statistically significant results are required for many practical cases of experimentation in various branches of research. The choice of the statistical significance level is influenced by a number of parameters and changes with different experiments. In most cases of practical consideration, however, the distribution of parameters or qualities follows a normal distribution, which is also the simplest case under consideration. However, care should always be taken to account for other distributions within the given population. While determining significant results statistically, it is important to note that it is impossible to use statistics to prove that the difference in levels of two parameters is zero. This means that the results of a significant analysis should not be interpreted as meaning there was no difference. The only thing that the statistical analysis can state is that the experiment failed to find any difference. Although 5%, 1% and 0.1% are common significance levels, it is not clear cut which level to use in an actual study - it depends on the norms of the field, previous studies, and the amount of evidence needed. However, it is not recommended to have a higher significance level than 5% because it too often leads to type 1-errors. LAYMANS a person who is not trained in or does not have a detailed knowledgeof a particular subject: The book is supposed to be the layman’s guide to home repair. REV. OF RELATED LITERATURE CHAPTER 2REVIEW OF RELATED LITERATURE AND STUDIES This chapter presents the related literature and studies after the thorough and in-depthsearch done by the researchers. This will also present the synthesis of the art, theoretical andconceptual framework to fully understand the research to be done and lastly the definition of terms for better comprehension of the study. Related Literature Tracer study is an approach which widely being used in most organization especially inthe educational institutions to track and to keep record of their students once they havegraduated from the institution. Through tracer study, an institution able to evaluate the quality of education given to their graduates by knowing the graduates placements and positions in thesociety which later can be used as a benchmark in producing more qualified and competitivegraduates. There are books that we can use as a tool for studying different aspects of educationand for studying the pres ent topic which is “ A Tracer Study on The Employment Status of ABJournalism Graduates Batches 2009-2012.In the book Employment and Career Opportunities after Graduation by Arcelo andSanyal, the existence of a huge number of educated unemployed can lead to a certain amountof political instability in a country, for they being among the educated class and knowledgeableabout the privileges society can offer, feel doubly deprived. In this matter, the analysis of theunemployment situation in the Philippines shown that the young graduates is still in the job-hunting stage. 1 This book is concerned to the graduates of AB Journalism that will be hunting 10 jobs after they graduated. Also, if the trainings and learning‟s in the journalism program will beused on the jobs suited for them.The book The Philippine Labor Code, An employer has a right to select his employeesand to decide when to engage them. He has a right under the law to full freedom in employingany person free to accept employment from him, and this, except as restricted by valid statuteor valid contract, at a wage and under conditions agreeable to them. 2 This author want to giveinsights about the rights between the employee and employer with regards to the employmentthat should be given to any person to be employed. This will distinguish the importance of beingemployed and the choice in choosing a job that are desired to apply in.The Philippines may go beyond the standing of employment in the country, rights andimportance should be understood. As specified in the book of Labor Economics by Cristobal M.Pagoso, it state that in view of low literacy rates in rising unemployment in developing countriesit has become imperative that greater educational opportunities should be provided for the greatproportion of adult population as well as the large number of youth outside the formal schoolsystem to help them acquire further knowledge and skill thereby improve their livelihood andstrengthen the country. 3 As a student of AB Journalism, one thing we must be considered is the notion that there‟s no age matter when it comes to job offerings because in the field of working, to be fair to any person who are capable of jobs is a factor to be employed.From the book Contemporary Social Problems and Issues, stated that the educationallevels and literacy rates of workers in the Philippines are among the highest in Asia, buttechnical, manual and managerial are poorly developed and in short supply.There is an over-abundance of college graduates that most especially in Manila area were in the field of education, law and other professionals exceed in demand to find employment appropriate to hiseducational training. 4 The authors wants to show on how did the graduates of journalism willused 11 their skills and trainings to gained and developed the technical, manual and managerial skillsthat Filipino workers are lack of. This is the realization that even college graduates may find itdifficult to be employed if they are not well-equipped of trainings and programs that their collegehad.In the book the Philippine Labor Code by CesAzucena, whenever the public interestrequires, the Secretary of Labor may direct all persons or entities within the coverage of thisTitle to submit a report on the status of employment, including job vacancies, details of jobrequisitions, separation from job wages, other terms and conditions, and other employmentdata. 5 This will make job seekers to be aware of job vacancies as well as the job suitable for them. This will also give awareness to the public to know the standing of the employment in our country ACCEPTANCE OR REJECTION OF HYPOTHESIS In order to undertake hypothesis testing you need to express your research hypothesis as a null and alternative hypothesis. The null hypothesis and alternative hypothesis are statements regarding the differences or effects that occur in the population. You will use your sample to test which statement (i.e., the null hypothesis or alternative hypothesis) is most likely (although technically, you test the evidence against the null hypothesis). So, with respect to our teaching example, the null and alternative hypothesis will reflect statements about all statistics students on graduate management courses. The null hypothesis is essentially the "devil's advocate" position. That is, it assumes that whatever you are trying to prove did not happen (hint: it usually states that something equals zero). For example, the two different teaching methods did not result in different exam performances (i.e., zero difference). Another example might be that there is no relationship between anxiety and athletic performance (i.e., the slope is zero). The alternative hypothesis states the opposite and is usually the hypothesis you are trying to prove (e.g., the two different teaching methods did result in different exam performances). Initially, you can state these hypotheses in more general terms (e.g., using terms like "effect", "relationship", etc.), as shown below for the teaching methods example: Null Hypotheses (H0): Undertaking seminar classes has no effect on students' performance. Alternative Hypothesis (HA): Undertaking seminar class has a positive effect on students' performance. Depending on how you want to "summarize" the exam performances will determine how you might want to write a more specific null and alternative hypothesis. For example, you could compare the mean exam performance of each group (i.e., the "seminar" group and the "lectures-only" group). This is what we will demonstrate here, but other options include comparing the distributions, medians, amongst other things. As such, we can state: Null Hypotheses (H0): The mean exam mark for the "seminar" and "lecture-only" teaching methods is the same in the population. Alternative Hypothesis (HA): The mean exam mark for the "seminar" and "lecture-only" teaching methods is not the same in the population. Now that you have identified the null and alternative hypotheses, you need to find evidence and develop a strategy for declaring your "support" for either the null or alternative hypothesis. We can do this using some statistical theory and some arbitrary cut-off points. Both these issues are dealt with next. Hypothesis Testingtop ^ Significance levels The level of statistical significance is often expressed as the so-called p-value. Depending on the statistical test you have chosen, you will calculate a probability (i.e., the p-value) of observing your sample results (or more extreme) given that the null hypothesis is true. Another way of phrasing this is to consider the probability that a difference in a mean score (or other statistic) could have arisen based on the assumption that there really is no difference. Let us consider this statement with respect to our example where we are interested in the difference in mean exam performance between two different teaching methods. If there really is no difference between the two teaching methods in the population (i.e., given that the null hypothesis is true), how likely would it be to see a difference in the mean exam performance between the two teaching methods as large as (or larger than) that which has been observed in your sample? So, you might get a p-value such as 0.03 (i.e., p = .03). This means that there is a 3% chance of finding a difference as large as (or larger than) the one in your study given that the null hypothesis is true. However, you want to know whether this is "statistically significant". Typically, if there was a 5% or less chance (5 times in 100 or less) that the difference in the mean exam performance between the two teaching methods (or whatever statistic you are using) is as different as observed given the null hypothesis is true, you would reject the null hypothesis and accept the alternative hypothesis. Alternately, if the chance was greater than 5% (5 times in 100 or more), you would fail to reject the null hypothesis and would not accept the alternative hypothesis. As such, in this example where p = .03, we would reject the null hypothesis and accept the alternative hypothesis. We reject it because at a significance level of 0.03 (i.e., less than a 5% chance), the result we obtained could happen too frequently for us to be confident that it was the two teaching methods that had an effect on exam performance. Whilst there is relatively little justification why a significance level of 0.05 is used rather than 0.01 or 0.10, for example, it is widely used in academic research. However, if you want to be particularly confident in your results, you can set a more stringent level of 0.01 (a 1% chance or less; 1 in 100 chance or less). WHAT ARE THE COMPONENTS OF THE SUMMARY OF THE STUDY? The conclusion of a research study begins with a narrative summary of the entire study. The key here is that this is a summary; it is not overly detailed. The conclusion reiterates or paraphrases the research questions and hypotheses, reminds the reader of the methodology used, and restates the findings concentrating in the highlights of the study findings. The section then presents conclusions. These are interpretations of the findings of the study and their potential significance. This section allows the researcher to interject opinion where appropriate so long as they are clearly separated from facts. The concluding remarks allow the researcher to discuss implications of the work and to form a logical argument surrounding the research questions and hypotheses. This is also a final opportunity to address any issues or questions resulting from conducting the study. These comments include noting negative results or failures produced by the study. The conclusion section progresses to suggestions for further research. While completing the study, the researcher should identify questions that arise but are beyond the scope of the current study; these may become future research topics. The researcher should also identify limitations of the study and express that overcoming these limitations is a topic for further research. Additional gaps or tensions discovered while preparing the literature review may also be noted as possible topics for future research so long as they are at least loosely related to the topic at hand. The researcher may also suggest replying the study in a different context to potentially increase generalizability of the results. Finally, a references section must be included. Regardless of which publication format is followed, every source directly identified in the study must be adequately referenced. This is an ethical responsibility of the researcher. A good rule of thumb is that if there is an in-text citation or footnote, there must be a reference, and vice versa. Also remember to include citation and reference information for charts and graphs that are based on data outside the study data. It is also important for the researcher to have the references and citations copy edited by a third party editor. The copy editor will check for correct and consistent formatting based on the publication format that is appropriate to the field of study. A well-crafted conclusion of an empirical study will provide the reader with a good argument for the implications and applications of the research findings. Adequate references and citations will help the researcher avoid ethical controversy including accusations of plagiarism and will provide other researchers with initial resources to conduct further studies on related topics. WHAT IS THE BASIS OF RECOMMENDATION? The conclusion of a research study begins with a narrative summary of the entire study. The key here is that this is a summary; it is not overly detailed. The conclusion reiterates or paraphrases the research questions and hypotheses, reminds the reader of the methodology used, and restates the findings concentrating in the highlights of the study findings. The section then presents conclusions. These are interpretations of the findings of the study and their potential significance. This section allows the researcher to interject opinion where appropriate so long as they are clearly separated from facts. The concluding remarks allow the researcher to discuss implications of the work and to form a logical argument surrounding the research questions and hypotheses. This is also a final opportunity to address any issues or questions resulting from conducting the study. These comments include noting negative results or failures produced by the study. The conclusion section progresses to suggestions for further research. While completing the study, the researcher should identify questions that arise but are beyond the scope of the current study; these may become future research topics. The researcher should also identify limitations of the study and express that overcoming these limitations is a topic for further research. Additional gaps or tensions discovered while preparing the literature review may also be noted as possible topics for future research so long as they are at least loosely related to the topic at hand. The researcher may also suggest replying the study in a different context to potentially increase generalizability of the results. Finally, a references section must be included. Regardless of which publication format is followed, every source directly identified in the study must be adequately referenced. This is an ethical responsibility of the researcher. A good rule of thumb is that if there is an in-text citation or footnote, there must be a reference, and vice versa. Also remember to include citation and reference information for charts and graphs that are based on data outside the study data. It is also important for the researcher to have the references and citations copy edited by a third party editor. The copy editor will check for correct and consistent formatting based on the publication format that is appropriate to the field of study. A well-crafted conclusion of an empirical study will provide the reader with a good argument for the implications and applications of the research findings. Adequate references and citations will help the researcher avoid ethical controversy including accusations of plagiarism and will provide other researchers with initial resources to conduct further studies on related topics. DEFINE APPENDICES Appendix, supplement both mean material added at the end of a book. An appendix gives useful additional information, but even without it the rest of the book is complete: In the appendix are forty detailed charts. A supplement, bound in the book or published separately, is given for comparison, as an enhancement, to provide corrections, to present later information, and the like: A yearly supplement is issued. Appendices, a plural borrowed directly from Latin, is sometimes used, especially in scholarly writing, to refer to supplementary material at the end of a book. DEFINE PRELIMINARIES Preliminary research In the preliminary research stage, the writer begins the process of finalizing the topic (and thus, eventually, the thesis or hypothesis) and documenting the sources to be used for guidance and support. Techniques and strategies Reading a book’s table of contents can help a writer reach a better understanding of a topic. Image source. using an online search engine or print resources at the local media center or library to gain familiarity with a topic reading a text’s table of contents, index, and chapter headings in order to determine one’s primary interest for the assignment examining sources to determine the availability of authentic, credible, current resources for documenting one’s topic selecting a final topic for a thesis or hypothesis that permits focused research and writing Finding the scope The preliminary research stage serves as an important connection between pre-writing and formulating a thesis. This stage is characterized by many of the components of the pre-writing stage, such as gathering information from a variety of sources. But rather than thinking broadly, as in pre-writing, the goal in the preliminary research stage is to narrow things down and hone in on a reasonable scope for the topic. This stage enables the writer to understand which of his or her ideas can be documented by sources other than the writer’s own personal opinion or the unsupported opinions of others. Even an opinion piece needs to be substantiated by a reasoned argument that can be verified by the audience through documented research. Preliminary research also permits the writer to change his or her mind about the intended topic before too much time and effort are committed to the process. Focus upon a specific topic that is sustained throughout the research and writing process is the goal of the preliminary research stage. For example, the student who is interested in filmmaking might discover that the topic is too broad for the assignment at hand. Through preliminary research, the student gains more familiarity with the topic and discovers that she is fascinated by sound design, a more focused topic than the broad field of filmmaking. By narrowing the topic to sound design, the topic becomes more manageable and the student can conduct effective research within the assignment’s specified completion time. Preliminary research can also lead a writer to a topic outside the scope of what he or she had originally intended. The student who chose to write about sound design may stumble upon an article about sound design in the film Jaws, and decide she’s particularly interested in the way subtle sounds — like the low base thud signaling the arrival of the deadly shark — can be used to manipulate the audience of a horror film. She may even steer away from filmmaking completely and choose to write about sound and human psychology, or about physics and human anatomy in considering how sound is handled by the human ear. While the seemingly free association of ideas in the preliminary research stage may resemble the brainstorming processes used in pre-writing, the difference is that preliminary research limits the writer to ideas that are supported by sources. Thus, it prepares the writer to formulate a thesis or hypothesis that can be backed by research. DEFINE BIBLIOGRAPHY. WHAT ARE THE CONTENTS OF BIBILIOGRAPHY? A list of the written sources of information on a subject. Bibliographies generally appear as a list at the end of a book or article. They may show what works the author used in writing the article or book, or they may list works that a reader might find useful. a complete or selective list of works compiled upon some common principle, as authorship, subject, place of publication, or printer. a list of source materials that are used or consulted in the preparation of a work or that are referred to in the text. a branch of library science dealing with the history, physical description, comparison, and classification of books and other works. An annotated bibliography is a list of citations related to a particular topic or theme that include a brief descriptive and/or evaluative summary. The annotated bibliography can be arranged chronologically by date of publication or alphabetically by author, with citations to print and/or digital materials, such as, books, newspaper articles, journal articles, dissertations, government documents, pamphlets, web sites, etc., and multimedia sources like films and audio recordings. Harner, James L. On Compiling an Annotated Bibliography. 2nd edition. New York: Modern Language Association, 2000. Importance of a Good Annotated Bibliography In lieu of writing a formal research paper, your professor may ask you to develop an annotated bibliography. You may be assigned to write an annotated bibliography for a number of reasons, including: 1) to show that you understand the literature underpinning a research problem; 2) to demonstrate that you can conduct an effective and thorough review of pertinent literature; or, 3) to share sources among your classmates so that, collectively, everyone in the class obtains a comprehensive understanding of key research about a particular topic. Think of an annotated bibliography as a more deliberate, in-depth review of the literature than what is normally conducted for a research paper. On a broader level, writing an annotated bibliography can be excellent preparation for conducting a larger research project by allowing you to evaluate what research has already been conducted and where your proposed study may fit within it. By reading and critically analyzing a variety of sources associated with a research problem, you can begin to evaluate what the issues are and to gain a better perspective on what scholars are saying about your topic. As a result, you are better prepared to develop your own point of view and con tributions to the literature. In summary, a good annotated bibliography... Encourages you to think critically about the content of the works you are using, their place within the broader field of study, and their relation to your own research, assumptions, and ideas; Provides evidence that you have read and understood your sources; Establishes validity for the research you have done and of you as a researcher; Gives you an opportunity to consider and include key digital, multimedia, or archival materials among your review of the literature; Situates your study and underlying research problem in a continuing professional conversation; Provides an opportunity for others to determine whether a source will be helpful for their research; and, Could help researchers determine whether they are interested in a topic by providing background information and an idea of the kind of scholarly investigations that have been conducted in a particular area of study. In addition, writing an annotated bibliography helps you develop skills related to critically reading and identifying the key points of a research study and to effectively synthesize the content in a way that helps the reader determine its validity and usefulness in relation to the research problem or topic of investigation. Annotated Bibliographies. The Writing Center. University of North Carolina; Annotated Bibliographies. The Writing Lab and The OWL. Purdue University; Annotated Bibliography. The Waldin Writing Center. Waldin University; Hartley, James. Academic Writing and Publishing: A Practical Guide. (New York: Routledge, 2008), p. 127-128. Structure and Writing Style I. Types Descriptive: This annotation describes the source without summarizing the actual argument, hypothesis, or message in the content. Like an abstract, it describes what the source addresses, what issues are being investigated, and any special features, such as appendices or bibliographies, that are used to supplement the main text. What it does not include is any evaluation or criticism of the content. This type of annotation seeks to answer the question: Does this source cover or address the topic I am researching? Informative/Summative: This type of annotation summarizes what the content, message, or argument of the source is. It generally contains the hypothesis, methodology, and conclusion or findings, but like the descriptive type, you are not offering your own evaluative comments about such content. This type of annotation seeks to answer these types of questions: What are the author's main arguments? What conclusions did the author draw? Evaluative/Critical/Analytical: This annotation includes your evaluative statements about the content of a source. It is the most common type of annotation your professor will ask you to write. Your critique may focus on describing a study's strengths and weaknesses or it may describe the applicability of the conclusions to the research problem you are studying. This type of annotation seeks to answer these types of questions: Is the reasoning sound? Is the methodology sound? Does this source address all the relevant issues? How does this source compare to other sources on this topic? NOTE: Strategies about how to critically evaluate a source can be found here. II. Choosing Sources for Your Bibliography There are two good strategies you should use to begin identifying possible sources for your bibliography--one that looks back into the literature and one that looks forward. The first strategy is to identify several recent scholarly books or journal articles on the topic of your annotated bibliography and review the sources cited by the author(s). Often, the items cited by an author will effectively lead you to related sources about the topic. The second strategy is to identify one or more important books, book chapters, journal articles, or other documents on your topic and paste the title of the item in Google Scholar [e.g., from Negotiation Journal, entering the article, "Civic Fusion: Moving from Certainty through Not Knowing to Curiosity"], placing quotation marks around the title so Google Scholar searches as a phrase rather than a combination of individual words. Below the citation may be a "Cited by" reference followed by a linked number. This link will direct you to a list of other study's that have cited that particular item after it was published. Your method for selecting which sources to annotate depends on the purpose of the assignment and the research problem you are investigating. For example, if the research problem is to compare the social factors that led to protests in Egypt with the social factors that led to protests against the government of the Phillippines in the 1980's, you will have to consider including non-U.S., historical, and, if possible, foreign language sources in your bibliography. NOTE: Appropriate sources to include can be anything that has value in understanding the research problem. Be creative in thinking about possible sources, including non-textual items, such as, films, maps, photographs, and audio recordings, or archival documents and primary source materials, such as, diaries, government documents, collections of personal correspondence, meeting minutes, and official memorandums. Consult with a librarian if you're not sure how to locate these types of materials for your bibliography. III. Strategies to Define the Scope of your Bibliography It is important that the sources cited and described in your bibliography are well-defined and sufficiently narrow in coverage to ensure that you're not overwhelmed by the number of potential items to consider including. Many of the general strategies used to narrow a topic for a research paper are the same that you can use to define the scope of your bibliography. These are: Aspect -- choose one lens through which to view the research problem, or look at just one facet of your topic [e.g., rather than a bibliography of sources about the role of food in religious rituals, create a bibliography on the role of food in Hindu ceremonies]. Time -- the shorter the time period to be covered, the more narrow the focus [e.g., rather than political scandals of the 20th century, cite literature on political scandals during the 1930s and the 1990s]. Geography -- the smaller the region of analysis, the fewer items there are to consider including in your bibliography [e.g., rather than cite sources about trade relations in West Africa, include only sources that examine trade relations between Niger and Cameroon]. Type -- focus your bibliography on a specific type or class of people, places, or things [e.g., rather than health care provision in Japan, cite research on health care provided to elderly men in Japan]. Source -- your bibliography includes specific types of materials [e.g., only books, only scholarly journal articles, only films, etc.]. However, be sure to describe why only one type of source is appropriate. Combination -- use two or more of the above strategies to focus your bibliography very narrowly or to broaden coverage of a very specific research problem [e.g., cite literature only about political scandals during the 1930s and the 1990s and that have only taken place in Great Britain]. IV. Assessing the Relevance and Value of Sources All the items you include in your bibliography should reflect the source's contribution to understanding the research problem or the overall issue being addressed. In order to determine how you will use the source or define its contribution, you will need to assess the quality of the central argument within the source. Specific elements to assess include an item’s overall value in relation to other sources on the topic, its limitations, its effectiveness in defining the research problem, the methodology used, the quality of the evidence, and the author’s conclusions and/or recommendations. With this in mind, determining whether a source should be included in your bibliography depends on how you think about and answer the following questions related to its content: Are you interested in the way the author frames the research questions or in the way the author goes about answering it [the method]? Does the research findings make new connections or promote new ways of understanding a problem? Are you interested in the way the author uses a theoretical framework or a key concept? Does the source refer to and analyze a particular body of evidence that you want to cite? How are the author's conclusions relevant to your overall investigation of the topic? V. Format and Content The format of an annotated bibliography can differ depending on its purpose and the nature of the assignment. Contents may be listed alphabetically by author or arranged chronologically by publication date. If the bibliography includes a lot of sources, items may also be subdivided thematically or by type. If you are unsure, ask your professor for specific guidelines in terms of length, focus, and the type of annotation you are to write. Introduction Your bibliography should include a brief introductory paragraph that explains the method used to identify possible sources [including what sources, such as databases, you searched], the rationale for selecting the sources, and a statement, if appropriate, regarding what sources were deliberately excluded and the reasons why. Citation This first part of your entry contains the bibliographic information written in a standard documentation style, such as, MLA, Chicago, or APA. Ask your professor what style is most appropriate and be consistent! Annotation The second part should summarize, in paragraph form, the content of the source. What you say about the source is dictated by the type of annotation you are asked to write. In most cases, however, your annotation should provide critical commentary that examines the source and its relationship to the topic. Things to think critically about when writing the annotation include: Does the source offer a good introduction on the issue? Does the source effectively address the issue? Would novices find the work accessible or is it intended for an audience already familiar with the topic? What limitations does the source have [reading level, timeliness, reliability, etc.]? Are any special features, such as, appendices or non-textual elements effectively presented? What is your overall reaction to the source? If it's a website or online resource, is it up-to-date, well-organized, and easy to read, use, and navigate? Length Annotations can vary significantly in length, from a couple of sentences to a couple of pages. However, they are normally about 300 words. The length will depend on the purpose. If you're just writing summaries of your sources, the annotations may not be very long. However, if you are writing an extensive analysis of each source, you'll need to devote more space. Pinky Marie M. 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