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You must submit a study plan for one of the research issues (posted on the KEATS site following the final session) for which a factorial Analysis of Variance model would be an appropriate technique.
Answer the following questions to describe your study strategy (each point should be answered concisely; a few well-written sentences should be sufficient).
A study to determine which of two study skills programs is more effective, as well as whether students who attend study skills seminars in their first year of their degree program achieve more (or less) academic success in their final year than those who receive the same training in their second year. How will you operationalise your research question (what will be your dependent measure, and how will you measure it)?
The dependent variables for the above research question will be the academic success. The student average score at the final year of the degree program, which can be obtained from the final year degree transcripts, will be used to measure the academic success. Note the average score is a continuous variable hence it is an appropriate response variable for the factorial ANOVA test.
Explain and justify the minimum effect size you would wish to have power to detect, or the widest confidence interval you would plan for.
Every course is totalled out of 100 marks; therefore, the absolute minimum effect size that the study wishes to have power to detect will be difference between the groups. In this case, the desired minimum effect size will be achieved if one of the intervention group results to an improvement of the degree scores by an average of 10 points out of 100 or 10% difference in the grade level.
Explain and justify the sampling strategy you will use to recruit subjects, and determine any experimental group assignment.
Student taking a similar degree program will be randomly selected to constitute the sample for the study. Note selecting student taking the same degree program will improve homogeneity of the subjects. The sample will then be divided into equal groups where the experimental group receive either of the two skills. Further, half of the experimental group will receive the skills during the first year of study and other half during the second year of study. Note only those who will complete study are included in the final analysis.
Design an ANOVA model suitable for analysing the results of your study. What independent variables will be factors in your analysis? Identify whether each factor would vary within-subject or between subjects. What covariates would you consider measuring or including?
The programme (study skills programmes) and the academic year the student started the programme are the independent variables which will be included as the factors of study. Both the study skills programmes and the academic year are would vary between subjects. The gender of the student would be considered as the covariate in the study.
Describe how a pattern of results in the ANOVA model might (a) provide direct support for or (b) challenge, your experimental hypothesis. You may include a figure to represent these patterns in your answer if you wish. Explain which main effects or interactions in your analysis would provide the most direct evidence regarding your research hypothesis.
A significant main effect of ‘study skills programme’ will support that hypothesis that two study skills programmes have varying effect on the academic success of the student in the final year of study.
A significant main effect of ‘academic year’ will support that hypothesis that those student who started the programmes in the first year of study differ in academic success from those who started in the second year of study.
A significant interaction effect of ‘study skills programme’ and ‘academic year’ will support that hypothesis that interaction between two study skills programmes and year the student started the programme have varying effect on the academic success of the student in the final year of study.
Critically evaluate the design you have proposed, identifying at least one strength and one weakness of the design.
The factorial ANOVA design main strength is that it helps determine the effect of more than two factors two levels groups while reducing the experimental error and any confounding variables.
The main weakness of this design is that it becomes very difficult to experiment with so many factors, or with many levels. If an error occurs in one of the group, it will jeopardize the entire work of analysis.
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