Research Design in Psychology Coursework

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To understand the effectiveness of the definite course-delivery formats (online, blended, or face-to-face) for the best performance in a psychological statistics class, it is necessary to work out a study that can support a certain hypothesis. Thus, the research question of the study is the examination of the dependence of the effectiveness of the students’ work in a psychological statistics class on a definite course-delivery format. The goal of the research is to determine the factors which can influence the level of the effectiveness of students’ study when they are enrolled in the same class but are taught according to different course-delivery formats. To develop this study, it is important to focus on online and face-to-face course-delivery formats.

The peculiarities of the study require the development of the support or the refutation for the following hypothesis: there are not any strict differences between the levels of effectiveness of students’ work in a psychological statistics class when they follow online or face-to-face course-delivery formats. This factor cannot be considered as decisive for analyzing the students’ effectiveness.

To analyze the correlation between the level of effectiveness and students’ grades and the used course-delivery format, it is necessary to use the information given by students in the form of their notes which provide the answers (definite marks in the course for a certain period) to the questions from the questionnaires. The information can be considered truthful and should be given anonymously with the help of an online service. The type of information determines the design as quantitative.

The research can be considered as correlational because it requires analyzing the dependence between definite factors or variables which are the course-delivery formats (online and face-to-face) and the effectiveness of students’ work measured with the help of their grades (marks). Thus, the results of the study can be distinguished as positive, negative, or nonexistent. The correlation generally does not mean that one variable can result in changes in the other variable. However, these variables are connected (Keppel & Zedeck, 2000). To measure the definite variable (students’ grades or marks received during a certain period when they were enrolled into online or face-to-face courses), it is helpful to use the ordinal scale to differentiate rank orders for effective measurement.

The peculiarities of the research do not allow using descriptive statistics. That is why it is necessary to use inferential statistics to utilize the limited information and data for making generalizations about the whole picture.

The participants for the study will be divided into two groups. The first group consists of those students who follow online courses, and the second group includes those students who attend courses with the face-to-face course-delivery format. To analyze the features of the dependence of the students’ effectiveness at classes on a definite course-delivery format, it is required to use a simple frequency distribution in which the score category is a grade or mark. If the groups (a sample) consist of 40 participants (20/20), the possible results can be as follows (including the grades for all the types of works for a definite period):

Grade
(the score category)
Students’ results (frequencies)
Online formatFace-to-face format
A37 (possible results)Y (possible results)
B69Y
C45Y
D9Y
E/FY

A simple frequency distribution can be useful for analyzing the level of students’ grades or marks which they receive attending their courses and completing definite tasks during a certain period which can be varied from one week to one month, or a semester because the grouped frequency distribution is more effective when the range of scores is too large.

Moreover, to follow the principles of objectivity in the study, it is important to analyze the anonymous data received from the participants of the research with the help of definite online resources.

Reference

Keppel, G., & Zedeck, S. (2000). Data analysis for research designs. USA: Worth Publishers.

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