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- Discussion Card for Creswell's Ch. 1
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August
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Question: How would you determine if your research question would be a good fit for correlational research design? I'm interested in this approach, but the amount and types of statistical data involved in this form of research are intimidating!
ReplyDeleteQuote: (p.370) "Correlational research does not "prove" a relationship; rather it indicates an association between two or more vaiables."
Fact: Prediction studies are useful because they help anticipate or forecast future behavior. (p. 359) I can see how this type of research would be especially useful in education and many other fields of study.
Question: Page 356- Oh My Goodness! I don't get it at all! So, my question is huh? "Investigators use the correlation statistical test to describe and measure the degree of association (relationships) between two or more variables or sets of scores." "No attempt to control/manipulate the variables as in an experiment." Am I just having a s-l-o-w moment?
ReplyDeleteInteresting Fact: Page 357 - "Explanatory Correlational Design - researchers are interested in where changed in one variable are reflected in changes in another."
Quote: page 375 "In some educational situations, neither the treatment nor the ability to manipulate the conditions are conducive to an experiment." Correlational Reasearch = Prescriptive Educational Practices?
Barbara - I am in the same boat you are! I believe correlational research would fit right in to what I am already doing. The task to complete this research does seem daunting!
ReplyDeleteBarbara-
ReplyDeleteI love the prediction type studies. That way after conducting the research I can see if I was correct or not. Kind of fun!
Barbara - Very powerful quote! However, is what we do in our classroom when assessing student correlational when we compare a pretest and a posttest? And wouldn't an increase in score prove what our preset goal might have been and if we met it or not?
ReplyDeleteQuote: p355 "In educational research, your objective may be to relate variables rather than manipulate the independent variable, as in an experiment. If so, your design is correlational research."
ReplyDeleteFact: A statistically significant relationship does not mean that there is a cause/effect relationship, but just an association between the variables.
Question: The correlation statistics are a bit challenging to understand. Because this course is an overview of research, how much of the statistics are we expected to master in this course as opposed to the courses in the next couple of semesters?
Ditto, Barb and Ann. I like the idea of correlational design, as well. I'm just a bit intimidated by the numbers!
ReplyDeleteInteresting Fact: I thought it was interesting that in a correlational research design the researchers do not attempt to control or manipulate the variables as in an experiment; instead they relate, using the correlation statistic, two or more scores for each individual. page 356
ReplyDeleteQuote: Correlation design allows you to predict an outcome, such as the prediction that ability, quality of schooling, student motivation, and academic coursework influence student achievement.
Question: When using a correlation study have do you identify individuals to use in your study?
Question: When is it best to use scatterplots versus correlation matrix?
ReplyDeleteQuote: (pg. 363) "After correlation researchers graph scores and produce a correlation matrix, they can then interpret the meaning of the association between scores. This calls for understanding the direction of the association, the form of the distribution, the degree of association, and its strength."
Fact: Correlational research is used when a researcher wants to see if two or more variables influence each other.
Corey Nickell
ReplyDeleteQuestion: (Pg 356) How accurate is co-varying? I have heard people say there are computer programs that can predict what students will score on the Map test is this a similar prediction? How exactly is this a huge difference from prediction research design (variables)?
Quote: (Page 375) “In some educational situations, neither the treatment nor the ability to manipulate the conditions are conducive to an experiment. In this case, educators turn to a correlational design.”
Interesting fact: I have to admit all the scatterplots, matrixes, correlations, and other numerous tables really scared me!
LaDawndra
ReplyDeleteQuestion:
Quote:
"This design allows you to predict an outcome, such as the prediction that ability, quality of schooling student motivation, and academic coursework influence student acheivement(Anderson & Keith) You also use this design when you know and can apply statistical knowledge based on cladulating the correlation satistical test" p325.
Fact:
A correlation is a statistical test to determine the tendency or pattern for two or more variables or sets. In plain terms a correlation identifies how two sets of data compare with one another on a line plot or graph.
Ladawndra
ReplyDeleteQuestion:
How do you know for sure after conducting the correlation if indeed the sets of data show relationship?
Ann,
ReplyDeleteBeing able to predict is fun! I think you are on the right track here. GRE scores and ACT scores are supposed to be predictors of success in college. We use these a lot for educational assessment.
Good job,
Dr. Hendrix
LaDawndra,
ReplyDeleteYou will analyze them with a program like SPSS and see if your significance level is significant or not and you will look at some of the correlational tests that SPSS can do. SPSS is a computer software that runs statistics.
Good job,
Dr. Hendrix
Question: If correlational research involves using one variable to predict another, what type of data needs to be collected in the interim? Would this research be easier to do with one classroom without feeling as if one was "depriving" students in part of the class from what might be an instructional advantage?
ReplyDeleteQuote: "Correlational research does not 'prove' a relationship; rather, it indicates an association between two or more variables."
Fact: The two primary correlation designs are explanation and prediction.
Fact: Fisher (1935) pioneered significance testing and ANOVA, important statistical ideas for studying the difference between observed and predicted scores in correlational analysis. I find this interesting since, I will be studying ANOVA soon.
ReplyDeleteQuestion: With the use of computer programs and correlational designs, it seems as if just about anything could be explained or predicted. Are we really that anal to worry about it all?
Quote:" Ideally, you should randomly select the indviduals to generalize results to the population, and seek permissions to collect the data from responsible authorities and from the institutional review board." It all seems so difficult just to ask a question....