Explore the Logic of Experimental Design, Essay Example

What is the purpose of conducting an experiment? How does an experimental design accomplish its purpose?

The purpose of conducting an experiment is to collect data. Conducting experiments is a way to test hypotheses and draw conclusions, using abstract principles and theories from previous research. Researchers often conduct experiments to find out how something “ticks” or to attempt to explain a certain occurrence or phenomena in the world. Conducting experiments help research find answers to questions and develop theories and outcomes for further research on a subject. Additionally, conducting research allows for observation and discovery to prove, correct, or refine hypotheses(Easterby-Smith, Thorpe, & Jackson, 2012).

Conducting experiments is part of research, and according to ORI, research is a process for discovering new knowledge and investigating, gathering, and analyzing information in a systematic way. This is down through scientific methods that allow researchers to observe the world around them and create, test, and prove hypotheses about relationships in the world(ORI).

Experimental design is used to meet objectives in research to obtain data to answer research questions. Experimental design accomplishes its purpose by highlighting a clear definition of the experiment and its details, which is used for statistical analysis to get the results of the experiment. Experimental design typically uses controlled and uncontrolled experimental factors for a specific research model to meet specific objectives. Additionally, the most available resources are used in the most efficient ways possible for data collection and analysis(SAS, 2005).

What are the advantages and disadvantages of an experimental design in an educational study?

Advantages include the experimental design being a road map for how study methods are conducted, which assists in analyzing results and clarifies information(Knight, 2010). Additionally, experimental design in educational studies help develop theories, which gives a better understand of a learning ecology for understanding real work in the context of practical education(Cobb & Confrey, 2003). Other advantages include being simple to administer, small sampling may be used, and comparing experimental factors may be precise. Furthermore, experimental research in educational studies is a very appropriate method for drawing conclusions about educational institution interventions. Disadvantages include sample dropouts being a problem(Selwyn, 1996). Additionally, according toOdle and Mayer (2009), for the most part, it is not possible to perfectly control conditions in educational environments. This may result in a tradeoff experimental thoroughness and authenticity, because experiments that are highly controlled may be too far removed from the real-world classroom.

What is more important in an experimental study, designing the study in order to make strong internal validity claims or strong external validity claims? Why?

It is first important to understand the meanings of internal validity and external validity. According to Taylor and Asmundson (2008), internal validity refers to how much observed changes in the dependent variable of a study be a result of changes in the independent variable. Internal validity is a matter of low, medium, or high, instead of presence of absence. True design experiments have strong internal validity. In other words, “participantsare randomized to experimental conditions, andother means are used to ensure that changes inthe dependent variable can be attributed to theexperimental manipulation of the independent variable”(Taylor & Asmundson, 2008, p. 24). External validity refers to research findings being able to be generalized to and across populations or settings.

It appears that internal validity claims are a bit more important than external validity calims in an experimental study. Internal validity helps determine cause-and-effect relationships. Strong internal validity shows a good indication of strong evidence of causality. The strength of both are used to help researches evaluate the relevance of  study’s importance in overall research. However, if the study’s internal validity is very weak, “then it may be given little or no consideration in evaluating what the corpus of research suggests about an important research question” (Taylor & Asmundson, 2008, p. 33).

In an experiment, what is a control? What is the purpose of a control group? Of single or multiple comparison groups?

According to Helmenstine, a scientific experiment control group is an isolated group from the rest of a group in an experiment. The purpose of the control group is for the independent variable does not influence the results of the experiment. This renders the effects of the independent variable isolated in the experiment, which assists in ruling out alternate explanations in the results of the experiment(Helmenstine, 2014). A single and multiple comparison groups in research study experiments are units in the study that either do not receive any treatment or receive alternative treatments. The purpose of this is to determine counterfactual  (something that did not occur) casual inference in the research(Shadish & Clark, 2004).

What are confounds? Give an example of a design that has three confounds. Describe three ways to alter the design to address these confounds and explain the advantages and disadvantages of each.

According to Stat Trek (2014), confounds occur when experimental controls prevent a researcher from reasonably eliminating alternative explanations for a relationship between an independent variable and a dependent variable that has been observed.

The example is used that considers a drug manufacturer testing a new cold medicine. The study has 200 subjects of 50 percent men and 50 percent women. The drug is given to the men and not to the women, and the men report having fewer colds than the women, at the end of the testing period. The three confounds include 1) gender is confounded with using the drug, 2) not receiving a placebo is confounded with the men receiving the drug, and 3) not receiving the drug is confounded with the women not having the opportunity to benefit from the drug(Stat Trek, 2014).

Addressing these confounds could be done by implementing more controls in the experiment. Random assignments of being treated could be assigned to both men and women, or one group could be given a placebo in a blind experiment. This way, the control group reported more colds than the treatment group, then it could be assumed that the new cold medicine is effective(Stat Trek, 2014).

What does “cause” mean and why is it an important concept in research? How are correlation and causation related?

Cause in research means variable changes in an experiment results in directly causing changes in another variable. It is important in research because it allows for accurate measurements. Correlation means an association or relationship among two or more variables in an experiment. As far as being related, correlation and causation are not the same and it important to distinguish between the two.

You are a researcher interested in addressing the question: does smiling cause mood to rise (i.e., become more positive)? Sketch between-participants, within-participants, and matched-participants designs that address this question and discuss the advantages and disadvantages of each to yielding data that help you answer the question.

Between-Participants

Between-Participants design allows for participants to be either part of the treatment or control group, but not both. Also, a new group is required for each treatment tested. With Between-Participants, an advantage includes not as many chances for participants exactly working out the experiment aims. A disadvantage is that it requires a large sample, which leaves little room for confounding variables(Shuttleworth, 2009).

Within-Participants

With Within-Participants, all participants receive every treatment. This includes participants in the control group. The advantages include the option of using a smaller sample size and being able to control for confounding variables. A disadvantage fatigue and familiarity influencing performance(Shuttleworth, 2009).

Matched-Participants

With Matched-Participants, experimental groups are kept separated for each treatment. However, this type of experiment matches each subject in a group with an equal subject in another group. An advantage is the elimination of possible differences between individuals that influence the results. A disadvantage is the fact that variation will also be present(Shuttleworth, 2009).

References

Cobb, P., & Confrey, J. (2003, Jan/Feb). Design Experiments in Educational Research. Educational Researcher, 32(1), 9-13.

Easterby-Smith, M., Thorpe, R., & Jackson, P. (2012). Management Research (4th ed.). London: SAGE Publications Ltd.

Helmenstine, T. (2014). What Is a Control Group? Retrieved from About Education: http://chemistry.about.com/od/chemistryterminology/a/What-Is-A-Control-Group.htm

Knight, K. L. (2010, Jan-Feb). Study/Experimental/Research Design: Much More Than Statistics. J Athl Train, 98-100.

Odle, T., & Mayer, R. (2009, Dec. 23). Experimental Research. Retrieved from Education: http://www.education.com/reference/article/experimental-research/#B

ORI. (n.d.). What is Research. Retrieved from Office of Research Integrity : http://ori.hhs.gov/education/products/sdsu/research.htm

SAS. (2005). Concepts of Experimental Design. Cary, NC: SAS International.

Selwyn, M. R. (1996). Principles of Experimental Design for the Life Sciences (1st ed.). CRC Press.

Shadish, W. R., & Clark, M. H. (2004). Comparison Group. Retrieved from SAGE Research Methods: http://srmo.sagepub.com/view/the-sage-encyclopedia-of-social-science-research-methods/n142.xml

Shuttleworth, M. (2009, Feb 27). Matched Subjects Designs. Retrieved from Explorable: https://explorable.com/matched-subjects-design

Stat Trek. (2014). Confounding. Retrieved from Stat Trek: http://stattrek.com/statistics/dictionary.aspx?definition=confounding

Taylor, S., & Asmundson, G. J. (2008). Internal and External Validity in Clinical Research. In D. McKay, Handbook of Research Methods in Abnormal and Clinical Psychology. SAGE Publications, Inc.