Developing a Quantitative Research Plan: Choosing a Research Design

welcome to the tutorial on quantitative research design this is dr. Zapp Q and we're going to spend the next twenty to thirty minutes talking about quantitative research designs just like any great builder starts out with a blueprint to guide and direct the construction of a building a researcher needs to start out with a research design to really guide decisions that need to be made about conducting the research about making plans a research design does three things it says when and how often data is collected what data needs to be gathered and from whom and how to analyze the data in this tutorial we're going to talk about several different quantitative research designs we're going to discuss when they're used and why they should be chosen and ultimately the purpose of this tutorial is to help you identify the most appropriate research design for your research study and to help you justify why it's the best choice now before we move on and start talking about research designs I want to make a note some of you for your research plans will actually choose multiple research designs and this is called a mixed design study as for example you may choose a causal comparative in a correlational design this is different than a mixed method approach a mixed method approach is a full quantitative and full qualitative design it really requires that you conduct a full-blown quantitative study and a full-blown qualitative study in essence you're committing to conduct two separate studies but here we're only going to talk about quantitative research design with the assumption that you've chosen a quantitative design for your study now there are numerous quantitative research designs too numerous to really cover here so we're going to focus our attention primarily on the major designs proposed by Campbell and Stanley in 1963 and crawl in 1993 they say that there are three primary categories of studies there's descriptive studies and descriptive studies are done when a researcher wants to know what is let's take Charlie for example charlie is a graduate student and he's interested in college students who have anxiety disorders because let's say that his cousin has an anxiety disorder if he simply wants to know how many students who enter college in let's say 2012 have an anxiety disorder a clinically diagnosed anxiety disorder he may do a descriptive study he simply wants to know what is what exists the next category are correlational studies and these can be relationship focused studies or predictive focused studies in a correlational study you really want to know is there a relationship between two different variables or does a group of variables or one variable predict another variable in our example of Charlie Charlie may want to know is there a relationship between achievement in a freshman English class and the presence of an anxiety disorder he wants to know simply is there a relationship not as one's causing the other but is there a relationship between the two he may also ask does the presence of an anxiety disorder predict achievement in a college freshman English class the final category is group comparison and this usually involves manipulation or treatment of some type and there are three types there's a pre experimental quasi-experimental and true experimental and we'll define those in a few minutes but really here let's go back to Charlie if he wants to do a group comparison study he's interested in is there a difference in two different groups or does a specific treatment affect something else so for example let's say he finds out that there is a relationship between the presence of an anxiety disorder and academic achievement in a college English class and he finds that the presence of a disorder actually decreases academic achievement so he wants to do an intervention maybe he asked for volunteers who have generalized anxiety disorder he provides one group with a special treatment that helps them lower their anxiety during the English class and he doesn't provide the other group with the treatment and then he compares the two at the end to determine does the treatment ultimately affect academic achievement in the college English class he's doing a group comparison we're going to take a more in-depth look at each of these specific research designs but before we do I want to identify or talk about a few additional designs that some of you may choose to do in addition to the designs that I just over viewed as some of you may choose to do an instrument development a Content or document analysis a meta analysis or a single subject design let me talk a little bit about three of those first of all some of you may choose to do an instrument development oftentimes when you go to conduct quantitative research you find that the instrument that you were hoping to find doesn't exist and an instrument needs to be developed and so you decide to develop an instrument and conduct statistical analysis to determine its validity and reliability this is a very very rigorous and intense type of design some of you may choose to do some type of document or content analysis and that is analyzing some type of communication and so for something that I see often or this is that students will analyze a discussion forum to determine the presence of let's say community in a discussion forum in an online class another example this may be looking at lesson plans analyzing lesson plans for a specific variable the last is a single subject design for those of you that are really interested in a specific counseling group or a special education group and you have a small sample size you may want to consider this design it's a really valid research design and it's similar to a time series design which we'll talk about in which each participant really serves as their own control and they're observed repeated repeatedly usually what happens is let's say for example were looking at children with autism and we want to teach them a basic skill such as hand washing what we would do is you would baseline them so you would establish a baseline for each participant how many steps of the hand-washing procedure can they do you would then at different times implement a treatment that maybe teaches them hand-washing and then you would observe the behavior after the treatment and this is called a single subject design if you're really interested in doing this design Wasson 2003 has a great book that I highly highly recommend but for the purpose of this tutorial we're going to go back and focus on the main designs that Campbell and Stanley talked about so let's go ahead and focus on those the first type of study we're going to look at is a descriptive study and descriptive studies focus on what is they really aim to understand what is happening what is in a specific situation with an identified population and they're usually used to gain knowledge to identify a problem or identify what is so that further research can be conducted it's important to note here that oftentimes descriptive studies are not very rigorous in nature so a lot of universities don't allow basic descriptive studies for things such as theses and dissertations and that's the case of Liberty we really don't allow them and without special permission but they but it is important that you know and you understand what a descriptive study is if I was a researcher and I wanted to do a descriptive study let's say I response to intervention is fairly a new term it's a new type of intervention in the school systems and I simply want to know what is the attitude of school counselors about the use of response to intervention I would do a descriptive study another descriptive study maybe what is the responsibilities to school counselors even have an RTI as its implemented in their school so just in general I want to know what our school counselors doing to help to help implement RTI in the school I would do a descriptive study now most research texts identify two different types of descriptive studies a survey study and an observational study a survey study uses some type of written document or online questionnaire or interview on to gather information about what is and there's usually two basic types of survey studies and that's longitudinal designs and cross-sectional designs longitudinal design study a population over a period of time they oftentimes are referred to as trend studies or cohort studies or panel studies so maybe going back to our example of Charlie maybe he wants to study the academic achievement of students identified with anxiety disorder in their freshman year of college their junior year college and their senior year of college he's studying them over a period of time a cross-sectional study then just looks at individuals at one point in time so again going back to our example of Charlie Charlie simply wants to know what is the academic achievement of freshmen college students with an anxiety disorder so he just was looking at one specific point in time about what is oftentimes surveys I'll collect data on attitudes and beliefs then like I said the other type of design is the observational design and this is the process of observing something that's happening and making a conclusion about it so for example I may go into a school system and observe teachers or observe school counselors again just as a reminder descriptive studies oftentimes are not rigorous enough for dissertations and theses and that's the case at Liberty we oftentimes don't allow descriptive designs for dissertation purposes however our descriptive studies can be very important as you build a case for a thesis or a dissertation because they are describing what the problem is now let's look at another type of study the next design we're going to talk about is one that I didn't mention above but it's similar to a group comparison and that's a causal comparative study the aim of a causal comparative study is really to examine the possible cause and effect relationship between variables that exist it really you're studying a phenomenon after the fact that is it's already occurred either naturally or it's been manipulated let's consider some examples if you want to examine gender or ethnicity as an independent variable you have a causal comparative study it's something that you as the researcher have not manipulated it gender occurs naturally ethnicity occurs naturally if you as a researcher wanted to examine individuals that smoked versus individuals that didn't smoke that has already happened they've already chosen that behavior another example would be an intervention that it's naturally occurring within a school system and is not occurring in another school system you want to study something that's already been implemented oftentimes causal comparative studies are used in educational research because it's too difficult to an ethical or impossible to manipulate the independent variable so for example it's unethical for me to tell one group of individuals let's say one group of students to smoke and another group not to smoke maybe there's a specific intervention a school-wide intervention happening at a school and you can't ask the whole school to implement this new intervention just for your research study that would be too difficult and since it's naturally occurring you can go ahead and study it now it's important to note that a causal comparative study is almost identical to a pre experimental design and we'll talk about in a little bit that that's not a credible design but the difference is is that oftentimes a causal comparative study has a control group actually it always has a control group so what you're looking at with a causal comparative design as you're looking at a phenomenon or something that's happen and and you're comparing it with something else so for example a school has this dynamic program that they're implementing and you're going to compare that school's students achievement level to another school that's not using on that specific that specific on treatment when we talk about threats to validity we'll talk about all the controls that need to be in place because again there's lots of threats to validity but this is a valid type of study I like to give you an example of a question that might be used for with a causal comparative study for example I may say is there a difference in male and female university students social presence while participating in an 8-week online class I simply want to know is there a difference in their social presence between males and females and again I can't manipulate it it's unethical and impossible for me to manipulate gender and so I would choose a causal comparative study as we're talking about causal comparative studies there's a few additional notes that I want to make about this specific design and especially take note of this if you're planning to use this type of design note that like a descriptive study a causal comparative design does not require the researcher to exert control or manipulate the phenomenon however unlike a descriptive study you are looking at the possible cause and effect relationship between variables and therefore you do you have an independent variable with a least two levels at least two groups that you're comparing and you have a dependent variable you're looking at the possible effect that that independent variable has on the dependent variable and note that I said possible cause and effect this is really really important language if you choose a causal comparative design you cannot prove you cannot state that you have a cause and effect relationship if you have a causal comparative design because there are too many threats to validity so make sure if you choose a causal comparative design you're using correct terminology and just as a reminder and you choose a causal comparative design you do so because it's too difficult too unethical or impossible for you as the researcher to manipulate the independent variable also note that often times causal comparative designs are chosen because you want to explore a phenomenon that's happening if a lot of causal comparative research has been done in a specific area and you're finding a lot of causal comparative literature or research in that specific area you're studying it probably means that we need to start moving more toward more rigorous research such as an experimental design which we're going to talk about next so um that's the causal comparative design actually before we talk about experimental research designs we're going to talk about the correlational research designs a correlational design like a causal comparative study is used for exploratory or beginning research to determine if there is truly more rigorous research that's warranted the purpose of a correlational study is simply to examine if a relationship exists between variables is there a relationship between like we said in the case of charlie is there a relationship between the presence of an anxiety disorders whether or not somebody has an anxiety disorder and their academic achievement or their grade in a freshman college class other examples of correlational studies may be is there a relationship between high school GPA and college board SAT scores we know in the research that some research says there is and some Research says there isn't if you choose to do a correlational design it's important that you recognize that you cannot speak in terms of cause and effect you simply have two variables of interest one does not cause the other because you don't know the direction of the cause and effect you can't guarantee that one variable caused another all you know is that they are varying together either let's say we're looking at two scores such as GPA and SAT we just want to know do they increase and do they decrease together um also you may be looking at predictive I remember I said at the beginning there are two basic types of correlational designs there's ones that look at relationship and thus far everything I've described is been in terms of relationship there's also predictive studies if you want to know do SAT scores predict on the call predict on college SAT scores um that you can look at what does one variable predict another variable now it's important to note and especially in talking about prediction that you have a solid theoretical or conceptual framework in which you're basing that study oftentimes with with predictive studies there's been multiple studies that have shown that there's relationship between certain variables or multiple variables and you want to add to that conceptual where that that model or that theoretical model let me give you an example of what I mean by that um we know that there's been a lot of research on high school GPA and SAT scores performance in college and we've seen that not only do does high school GPA predict SAT scores but also gender and ethnicity and sometimes there's an interaction between gender and ethnicity and socioeconomic status and high school GPA and the results of an SAT score so let's say in the literature I find a strong conceptual base or a model that says gender and ethnicity and socioeconomic status and GPA predict SAT scores let's say that it that that model predicts SAT school predicts let's say sixty percent of the SAT score that means there's still forty percent of the model that's unexplained and maybe I have another framework or another theory that says parents parental or parental attendance at college is another important piece of the pie so then I'm going to test that so it's important in correlational designs that you really have a strong theoretical core conceptional rationale for every variable that you plan to study not just ones that you think but there needs to be research in theory that backs it up again I want to reiterate if you choose a correlational study if you want to look at the relationship between two variables or multiple variables notes that you're you can only make statements about relationship and you use this design because there's a very little research in the area and it's exploratory you're only beginning research in the area or the models that have been presented specifically predictive models that have been presented are not complete they're still parts of it that are unexplained now we're going to focus our attention on experimental designs Campbell and Stanley in 1963 purported that there are three primary experimental designs and that's the pre experimental design the true experimental design in the quasi experimental design in the distinguishing factor or a distinguishing characteristic of all experimental designs is that the researcher manipulates the independent variable that is the researcher actually conducts the treatment does something to the participant so let's look at these three types of designs as we discuss these three types of designs there are commonly used symbols in research text and actually Campbell and Stanley in 1963 are the ones that proposed these symbols but anyway they're these symbols and research texts that help us visually see the designs that we're talking about and so we're going to use those two symbols as we talk about these different designs and over the next few slides and the X simply means that exposure to treatment there that means there's been a treatment done o represents observation or the measurement the dependent variable really what you're measuring multiple rolls reflect multiple groups and our reflects randomization and I'll define these more in a little bit we're going to start by discussing pre experimental designs and the primary characteristic of a pre experimental design is that the researcher manipulated the independent variable oftentimes pre experimental designs are used as preliminary research pilot studies to determine the effectiveness of a treatment to see if there's more research that's warranted Kimmel and Stanley really say that pre experimental designs are weak and have little to no value it's important to note that pre experimental designs are distinguished as separate from quasi experimental designs in texts such as Campbell and Stanley but not so much in borg borg and gaul so some some research techs don't even acknowledge or pre experimental designs or they wrap them into Tom quasi experimental designs or the quasi experimental design discussion I bring up pre experimental designs here because I want you to be able to recognize them and I want you to recognize that they are not rigorous studies they like Campbell and Stanley said they have no value so for a dissertation or thesis they really shouldn't be done they are however often used in program evaluation and for school systems and can be very effective for that purpose an example of a question that might be asked for is pre experimental design is simply does parent scores on a parent skill assessment increase after participation in a successful parenting program let's look at what a design that would be probably a one-shot case study let's look at what that looks like in the next slide here are commonly used pre experimental designs as I just mentioned the question I just proposed you know do parents increase in their skills or do parents have better parenting skills after a parenting intervention that's an example of a one-shot case study parents are given a parenting skill intervention and then their parenting skills are measured now you probably already see the weakness in this study give you a moment to think about it do you have it the problem with this is I can't say it was the intervention that caused this parenting skills perhaps parents already have the skills perhaps they were watching a parenting program and that caused the score they got in the parent on the parenting skill let's say survey or measurement that I used so I really can't say it was the intervention that caused caused the effect on the pair or cause the parenting skills additional pre experimental designs are the one group pretest post-test again here I give pair I would going back to our parenting example I would give parents a pretest to measure their parenting skills I do the intervention and then I'd give them the post-test now this may be a stronger design because I can see if there was an indie increase or decrease in parenting skills but it might have been the pretest that caused the increase on the post-test so again I can't say it was the parenting skill class that caused the it actually caused the intervention or caused the increase or decrease in the parenting skills I'm saying again similar weakness in the post-test only nonequivalent group design if I have two groups and I give one parenting skills and don't give it to the other and then measure them at the end it may be simple group differences that um that that were the cause the differences in the parenting skills and not actually the intervention so these are pre experimental designs let me give you one more example and see if you can identify the design let's go back to our case of Charlie let's say Charlie has a group of students freshman college students who have an anxiety disorder and he gives them in anxiety intervention and it helps them reduce their anxiety about about their academics or in their classes and then he post tests to see if there is a decrease in their anxiety again the problem is if he has one group he does the intervention he measures them it may not be the treatment that that actually caused the effect the lowering let's say of the skills so again pre experimental designs it's important to know what they are they can be very effective in program evaluation sort of exploring is it even worth going on and examining a treatment further however for a dissertation they are not acceptable designs as you can see there's major threats to validity and you can't talk about cause and effect relationship so let's look at two experimental designs that are often used and are some of the strongest designs that can be used for a dissertation let's first talk about quasi experimental designs now the quasi experimental design is often use in educational research because it's more convenient and less disruptive than the stronger true experimental design the purpose of a quasi experimental design is to test the effectiveness of an intervention or treatment with a target population it really allows the researcher to control the treatments and and look to see if the intervention had an effect on the identified dependent variable again this is the most rigorous design aside from the true experimental design and often chosen in educational research because it's more convenient and less disruptive let's say for let's look at an example of that let's say that you wanted to look at problem-based pedagogy for teaching math and so you ask the question what effect does participation in a math lesson developed using a problem-based pedagogy have on second grade students math achievement scores when compared to participation in a math lesson that was developed using traditional pedagogy and you have mrs. Smith's class and this is jones's class and mrs. Smith's class or mrs. Smith you trained to use the problem-based pedagogy approach and this is Joan she continues using the traditional approach and you your your specific target population is second-grade students now it would be really nice we're going to talk about random and assignment in a moment it'd be really nice to randomly nine students to either mrs. Smith's class or mrs. mrs. Jones's class however that's probably not possible in an educational situation you can't just go randomly assigning students to class their classes therefore you use mrs. Smith's class that's already been put together and mrs. Jones class one gets the treatment one doesn't and you compare their math achievement scores at the end they you use already composed classes and so that's a quasi-experimental design let's look at more specifically let's look at specific types of quasi experimental designs if you choose to conduct a quasi experimental design you maybe use one of these specific designs probably most prominent is the one that I just explained and that's the non equivalent pretest post-test control group design and that's the middle one here represented in our with our little X's and O's what you do is you pretest students so you give both let's say you gave mrs. Smith's class and this is Jones's class a pretest on a you want to find out what their math achievement was prior to the intervention you then give miss Smith's class the intervention you don't give it to mrs. Jones's class and then you post-test them this way you can actually see if the groups were equivalent in their math achievement prior to the intervention so you know if it was the intervention or not that caused the post-test scores and interrupted time series design is very similar to that where you you create a baseline so you would actually give let's say multiple math achievement tests prior to the intervention you give one group the intervention then you do multiple post tests another group another design is the counter balance design and this one can be very effective at looking at when you want to do multiple treatments and you give each group a different regimen of the treatment and then compare them so you can see what the effect is now this is a great design one the weaknesses as you can see would be you you're adding multiple or you're adding more as more groups and again sometimes in educational research it can be difficult when you have multiple groups because each group needs to be fairly large when we talk about different when we talk about statistical convention and power when we talk about an analysis you'll see that you probably need anywhere between 30 and 60 individuals per group again just to recap a quasi-experimental design is often used in educational research and it includes both it has two primary characteristics and that's manipulation you as the researcher actually cause the treatment you manipulate you manipulate the independent variable and there's always a control group a comparison group now talking about control comparison group let me stop here for a moment and talk about that there are different types of control groups and you need to decide what type of control group you are going to use Kasdan 2003 book has a great discussion on different types of control groups you you have most of the time in um in educational research you're going to use a no treatment control group of some sort or a nonspecific treatment group in which one group gets an intervention and the other group is the same in every single aspect in every single way except for that intervention come and the Oh ants let me also say this when you're thinking about that control group it's important that the element that you're studying is the only thing different so for example I can't compare mrs. Jones's math class to mrs. Smith tsa's English class the cot or compare sixth grade a sixth grade math class to a fifth grade math class everything about the intervention needs to be the same so the content of the material everything needs to be very very similar except for the intervention but anyway when you're talking when we're talking about control groups or a group that's there as a comparison group it's important to identify that there are different types of groups and again I highly highly recommend Kasdan as you talk about this and he talks about factors that you really need to consider when can when choosing your control and that's the intent of your research previous research that's been done as well as ethical and practical considerations let me go back and just remind you quasi experimental design has two characteristics and manipulation and control it is often used in educational research because it's too impossible or are not ethical to do a the more rigorous to experimental design which we're going to talk about next and really the aim of a quasi experimental design is to determine the effectiveness of some type of intervention um if you're thinking about a causal comparative study and you have the opportunity to do a quasi experimental to study I highly highly recommend you consider a quasi experimental study is a much more rigorous it's a better research design there's less threats to internal validity the last design we're going to talk about is the true experimental design and this design is truly the most rigorous design and and ultimately the design that you want to choose if you have the opportunity to do so the purpose of this design is to examine the cause-and-effect relationship between variables how you really investigate the possible cause and effect relationship by exposing one or more experimental groups to some type of treatment that you as the root researcher do and you compare those results to one or more control groups not receiving the treatment again this is considered the most rigorous design examples of questions that you may ask if you're doing a true experimental design is there a difference in students sense of community based on the type of technology they're using in a class so for example let's say I have two classes one class does their all of their discussion via blackboard discussion another class does all of their discussion via Skype and I want to compare this community differ among the students so everything in the classes are exactly the same except the technology that's used for the discussion and and obviously there's theoretical and conceptual reasons for why you would compare those two things put that on and let's say for there are three characteristics of a true experimental design so I have I've already talked about manipulation so I is the researcher and manipulating the independent variable and I just talked about that I'm giving one group a discussion using discussion board and I'm giving another group a discussion I'm going to I'm going to do it via Skype or via some type of online conferencing system there's a control group so there's a comparison group and the last thing that I the characterizes or makes a true experimental design unique is the ability to randomize so in this specific scenario I would ask for a group of volunteers and then I would randomly assign them to either the treatment group or the control group now the the important thing to recognize about randomization is this random is campbell and stanley in 1963 say that if you randomize you can assume group equivalents you can assume a group equivalent and so your so you can assume the groups are starting out the same and so it's actually the treatment that caused the effect as we've done with the other categories or other types of designs let's look at specific types of true experimental designs one of the most rigorous designs is the post-test only design in in this case you randomized your groups you do random assignment notice and random assignment not random selection random assignment so I have my group of volunteers in the example I gave I used college students let's say I have a group of them and then I randomly assign one to treatment one to non treatment I do the treatment and then I post-test both of them there's also a pretest post-test equivalent group design in which is exactly what I just explained however you randomized them you do a pretest you give one group the experiment or the treatment and then you not the other group and then you pulse test them now Campbell and Stanley say that this design introduces a threat to validity and that's the testing threat to validity so it's preferable to do the post-test only design there are other textbooks and researchers that disagree with that an alternative is to combine those two and do have a come to a design called a Solomon for design and here you can see two groups get the treatment two groups get the pretest and then you compare and so you can see if the pretest caused any effect or introduced such testing threats of validity a Solomon four design is probably the strongest true experimental design the problem with that the problem with the Solomon for design is sample size you need a very very large sample size to do a Solomon four design again remember 30 to 60 individuals per group probably so oftentimes it's just not feasible it's too costly you don't have enough individuals to do a Solomon 4 design now we've just discussed the primary designs and we discussed types of designs and specific then specific designs within each of those types so true experimental design you post tests only design pretest post-test equivalent group design Solomon for when you are identifying your specific research design you can identify the type but then be as specific as possible we've talked about the different types of designs and identify the different types of designs we've also talked about reasons that you would I choose the designs and so you also need to talk about why you would why you chose that specific design here with the true experimental design it's the most rigorous research design when I want to look at a cause-and-effect relationship between variables and therefore that's why I would use a true experimental design let's talk a little bit more about choosing your design here's a list of questions that can be helpful in identifying which design you're using for your research and remember I said you can use mixed design so let's say for example one of my independent variables is gender which I'm not going to manipulate but one of my independent variables is a treatment that I as a researcher am going to manipulate obviously since I'm not manipulating gender I have a causal comparative design but if I am manipulating some type of treatment depending on whether or not I use randomization I have a quasi experimental or true experimental design so just recognize that you may have multiple designs so for every variable specifically independent variables or variables of interest you need to go through and ask these questions so let's go through and ask these questions and I want you to think about your research and I want you to think about answer yes or no to these first of all or answer the question first of all are you concerned with relationship or difference between variable if you're concerned with the relationship between variables then you have a correlational design if you're just looking at the relationship between two variables which most research is more complex than that if you're looking at the relationship just between two variables you we may need to talk your design may not be rigorous enough but if you're just looking the relationship between two variables you have a basic correlational design if you're looking at multiple variables a relationship of multiple variables to one or examining a model you have some type of predictive design so we've already determined your design if you're looking at relationship now if you're looking at the difference between variables or are two groups different you then have some type of group Harrison so the next question you're going to ask is will I manipulate the independent variable if your answer is no it's already occurring within the environment then you have a causal comparative design which is a type of ex post facto design so you have causal comparative if your answer to that question is yes I am going to manipulate the independent variable then you need to keep asking yourself these questions the next question you need to ask yourself is will I use a control group if your answer to that is no then you have a pre experimental design and you need to rethink your design if your answer to that is yes that means you have some type of quasi or - experimental design so the next question you're going to ask yourself is will you randomly assign your participant so will you gather volunteer participants and randomly assign them if you are randomly assigning them then you have a true some probably some type of true experimental design if you're not randomly assigning them then you're going to have to have a pretest and you have some type of quasi experimental design so I want you to walk through for each of your questions or each of your ideas and I want you to identify what design you are choosing you then need to ask yourself is your design feasible and is it the best design the strongest design that you can do and does it have enough controls for internal validity I also want you to ask yourself what other research has been done in this area and is the design that I'm choosing warranted based on what's already been done now there's two ways to think about this maybe a lot of the research in the area that you're looking at has been correlation correlational and causal comparative and so you're going to do an experimental design that's a rat that's a great rationale is everything - this date has been exploratory when I did my dissertation that was the case everything's been exploratory and now we need more rigorous research another way to justify it is most of the research in the area that you're doing has been quasi experimental because - impossible and too difficult to do a true experimental in an educational setting and so you justify seeing other research has similar research has used this design and this design is thus warranted so go again go through these questions and ask yourself what design help them guide and identify what design you're doing once you have identified the design you need to ask yourself a few other questions and begin justifying that design so using the information that we've just gone over using the information in your research text as well as the handout I've provided identify your design and justify that design justify that design using the literature in research text as well as empirical literature as I just explained the handout that I provided has some examples of identifying and justifying your research design here are a few additional examples that you may want to look at again identify what you're examining what you're doing identify the design that you're using how you're implementing that design and then justify why why you're using that design why is it the most appropriate design based both again on research text as well as other research that has been done in the field so take some time work through like I said work through the handout there are some great questions at the end of the handout and write up a section that you could include in a dissertation thesis or your research plan

Channel: The Doctoral Journey

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Keywords: Quantitative Research, design, Quantitative Research Process

Id: UywO2XuFuBA

Length: 46min 12sec (2772 seconds)

Published: Thu Jun 06 2013