PSYC FPX 4600 Assessment 2 Research Proposal
Capella University
PSYC-FPX4600: Research Methods in Psychology
Instructor’s Name
June 2024
PSYC FPX 4600 Assessment 2 A research proposal stipulates the framework of the study, detailing its objectives, hypothesis, methodology, and plan for data analysis (Malakar, 2022). In this study, an archival data set from the grades.sav dataset will be utilized to answer a specific research question, operationalize the variables, and test the hypothesis. The proposal, therefore, entails a literature review, a sampling strategy appropriate to archival data, and explanations of inferential statistical methods applicable to the study. Second, such designs offer an ethical standard, dependability, and validity such that a clear roadmap provides research conducting.
Methods
Sampling
During my study, I will use stratified random sampling to get the sample from the grades.sav dataset. Stratified random sampling is a technique that uses probability sampling where every subgroup in the population has adequate representation (Ahmed, 2024). The population here comprises students whose performance in school and other demographics are different. I will first stratify the dataset by dividing it into strata on academic performance, such as top performers, average performers, and low performers, and demographic factors, including age, gender, and socioeconomic status. Once the strata are ascertained, I would randomly select students from all the subgroups proportionate to the size of that subgroup within the overall population. This method assures that students from all performance levels and backgrounds are represented, which minimizes potential biases and improves the generalizability of the results of the study. By using this stratified sampling technique, I can have an accurate assessment of how academic factors such as study habits and attendance affect final grades, adjusting for differences in academic ability and demographics.
Measures
The first three measures for my study would be academic performance grades academic factors: attendance and study habits. Final grades will be the dependent variable and in this research, an indicator of the outcome. My measure for academic performance has already been operationalized and is available in the data set as a continuous measure that can be analyzed fairly easily for correlation with other factors. The independent variables in the study attendance and study habits would be measured based on pre-existing data within the grades.sav dataset, which contains records of attendance and self-reported study habits. These variables will be taken to be continuous measures and thereby allow an analysis of direct effects on final grades. Clear operational definitions for these variables have to be provided for a reliable and valid study (Jeffries et al., 2021). For example, class attendance will be operationalized by the percentage of classes attended, and study habits by self-reported data, which can be on a Likert scale that assesses frequency and consistency of study sessions. These are valid because they reflect concrete academic behaviors that can directly affect performance. Also, since this uses archival data, there is a lesser chance of measurement error because the variables already exist in the dataset.
Procedure
The procedure of my paper will start with the stage of data collection, including downloading and studying the dataset grades (Vijayan et al., 2021). and with detailed data on students’ academic results, attendance, and time spent on learning. As a basis for the study, this dataset is used at the stage of stratification and sampling; I put students into strata along with their level of success in studies and demographic characteristics of age gender, and socioeconomic status. I will group them into high achievers, average performers, and low achievers. Then, from these subgroups, I will apply stratified random sampling to ensure that proportional representation is achieved across all the strata. This ensures that the sample is diversified and representative of the students.
After sampling, I will analyze the data using SPSS (Sen & Yildirim, 2022). I will carry out multiple regression analysis to find out how independent variables like attendance and study habits predict academic performance, which is the dependent variable, final grades. This will enable me to determine the strength and significance of the relationships between the variables. This includes ethical guidelines such as strict adherence to maintaining confidentiality-anonymized data and the use of the dataset for research-only purposes only. Since the data are archival, informed consent is already obtained, and new data will not be gathered. Lastly, I will interpret the results taking into account confounding factors like differences in demographics to find whether the effects of attendance and study habits vary across subgroups. The procedure is transparent, ethical, and methodologically sound to guarantee valid and reliable results.
References
Ahmed, S. K. (2024). Research methodology simplified: how to choose the right sampling technique and determine the appropriate sample size for research. Oral Oncology Reports, 12(100662), 100662–100662. https://doi.org/10.1016/j.oor.2024.100662
Jeffries, A. C., Marcora, S. M., Coutts, A. J., Wallace, L., McCall, A., & Impellizzeri, F. M. (2021). Development of a revised conceptual framework of physical training for use in research and practice. Sports Medicine, 52. https://doi.org/10.1007/s40279-021-01551-5
