Running head: METHODOLOGY, DESIGN, DATA 1 3 METHODOLOGY, DESIGN, DATA Methodology, Design,

Running head: METHODOLOGY, DESIGN, DATA

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METHODOLOGY, DESIGN, DATA

Methodology, Design, Data

Research Method

The study answers the question, “What role does parental involvement play in high school students’ academic success?” The question “what?” suggests an explorative approach, although the emphasis is on the association between two variables; parental participation and academic success for high school students. The study will adopt a correlational research design from such a perspective, examining the relationships between the variables.

Strengths and Weaknesses

According to Curtis et al. (2016), the design does not include variable manipulation or control and focuses on establishing the correlations between such components. Moreover, the methodology has various benefits, including avoiding a manipulative process, using one or more data collection, and applicability to real-life situations. From an analytical perspective, Curtis et al. (2016) identify the ability to establish the direction and strength of the correlation, such as the association between parental inclusion and scholarly success in this study.

Data Collection Tools

Data collection will be through quantitative surveys. In this regard, standardized questionnaires will be employed to collect relevant data from the participants, adopted from Nokali et al. (2010), although customized to fit high school learners instead of elementary participants. Adopting an already existing questionnaire ensures reliability and validity. The questions will incorporate close-ended questions, as well as Likert scales, to measure the extent of parental involvement in their children’s academic functions and how such interventions improve their performance. The approach allows a quantitative approach to data collection. As highlighted, the questionnaires will be standardized to ensure uniformity. Jones et al. (2013) identify the benefits of using surveys, including collecting various types of data, including beliefs, opinions, behaviors, and attitudes. Moreover, ready and validated data collection tools, the capacity to gather large amounts of information, and a greater statistical power associated with generalizability are prominent.

Support for Method

Compatibility with a survey approach is another advantage of correlation research designs. In such a case, Curtis et al. (2016) state that the methodology is fast, easy, and affordable, especially when emphasizing the relationship between the variables. In such a case, the design will assess a common pool of participants, with a sample of (n=10). The hypothesis is that parental involvement significantly affects students’ academic success, whether positive or negative. As related to the two variables, prominent aspects encompass the level of parental contribution to their children’s educational activities, such as meeting with teachers, how they encourage or promote studying, and assisting them with home-based assignments. Other areas that will assist in data collection include social support, including psychosocial assistance, financial help, and coordination with teachers and academic staff in school settings to offer the support required for the learners.

Population and Sampling Procedures

The inclusion criteria for the participants encompass students currently at the high-school level, those preferably attending day school, and those interacting with parents at least three times a week in a school attending week. Additionally, the participants should be between 14 and 19, the standard age for high schoolers to standardize the responses and increase their viability. At the same time, the exclusion criteria will focus on students in other levels of education, those in boarding institutions, and those with reduced parental involvement due to various factors, such as independent living, studying far away from home, and parents who do not live with their children due to occupational demands. Moreover, students under 14 or above 19 will be excluded (Table 1).

Table 1: Inclusion and exclusion criteria.

Inclusion

Exclusion

Students at the high school level of education.

Learners not attending high school.

Learners living with parents and interacting with them at least 3 days in a school week.

Those living independently with minimal parental assistance, interaction, and support.

Students aged between 14 and 19.

Those aged below 14 and above 19.

Participants attending day school

Boarders and those not going home after school.

 

 

 

The selection will be randomized. Although nonexperimental with no control or manipulation, correlational studies can be randomized to improve the study’s quality and viability. In this regard, Lim and In (2019) identify various benefits, including eliminating accidental bias and the advantage of incorporating probability bias. Subsequently, the study will use simple randomization in the initial selection for students meeting the inclusion criteria, effectively narrowing down the sample to the 10 participants required for the study. A larger sample will be used, with 10 participants randomly selected from the pool.

Recruitment will involve poster use around the school after approval from the management. In this regard, the posters will have an email address that interested participants will use to contact the recruiters. Additionally, ethical consent will be obtained from the university’s ethical body after compliance with all the required aspects. All subjects will be educated on their participation rights and presented with informed consent forms after the researcher is satisfied that they have understood the content. Moreover, all data will be anonymized to eliminate any personal information that may lead to the identification of the respondents. At the same time, all data will be stored appropriately in an encrypted hard disk, with two researchers only given access to minimize access from unauthorized persons. Although involving human subjects, IRB approval will not be required, as the study is nonexperimental.

Data Collection

The data collected will be informed by the research question. As previously identified, the emphasis is on the correlation between parent involvement and academic performance for high school students. The surveys will incorporate Likert scales and close-ended questions to quantify the data and allow a quantitative analysis. Subsequently, the emphasis will be on parental support, such as the number of students who strongly agree or strongly disagree with the assumption that social and financial support significantly enhances their academic performance. Additionally, assessing the extent of parental involvement, including the number of hours, parental attendance at school functions, and collaboration with teachers at school using Likert scales. Other questions include psychosocial support, such as the absence of violence and emotional encouragement, contributing to a holistic approach to education, and its impacts on academic performance. Relating such outcomes with performance, including grade point averages, will allow correlation assessment.

 Data Analysis Process  

As highlighted, the research is quantitative and will utilize a quantitative analytical and statistical method. Guided by the study question, the focus is on assessing the relationship between parental participation and high school students’ academic performance. Owing to a correlational design, the analysis will use the Pearson Correlation Coefficient (r), which evaluates the strength of a linear relationship between two variables (Schober et al., 2018). Subsequently, the data will be quantified using the scales and the close-ended questions, including the number of students agreeing to the questions asked and their application extent, and how such data correlates with student grades, as assessed by their GPAs in a specific duration of time. The surveys will offer data, including parental support and psychosocial or emotional aspects hypothesized to positively influence academic outcomes, used to assess the impact on academic performance.

Justification of Statistical Analysis

R is multi-dimensional and assesses the direction and strength of the relationship between two variables. In such a case, Schober et al. (2018) illustrate the coefficient’s use, such as when r=1, which suggests a strong positive correlation, r=0 shows no correlation, while r=-1 shows a strong negative association. The strength ranges from 0 to 1 or 0 to -1, depending on the direction, with 0 as the lowest or none and 1 or -1 as the highest (Schober et al., 2018). To illustrate, if the r for the association between parental participation and student performance is 7, the outcome will suggest a strong correlation, indicating parental support significantly impacts students’ academic performance. Similarly, if the results yield -7, the conclusion is that parental involvement negatively and strongly correlates with students’ academic performance. A positive correlation will illustrate collinearity, where an increase in variable A leads to a similar rise in variable B.

Limitations and Assumptions

Despite using a validated survey tool or questionnaire, there is a significant risk for bias, particularly due to the customization of the tool to fit high-school students’ requirements. In such a case, the answers provided may be biased, owing to the emotional nature of the parental involvement variable, leading to exaggeration and overestimation. Additionally, a sample of 10 participants may not be adequate to allow generalization, adversely affecting the applicability of the outcomes in other settings. The study does not employ triangulation and relies on a single data collection tool, which may negatively impact validity. At the same time, the research focuses on relationships alone and does not establish a cause-and-effect relationship. Lastly, correlational studies are vulnerable to extraneous data and variables, which may adversely affect the results.

Dissemination of Findings

The research will be disseminated through publication in a relevant journal. The focus is on policymakers and other stakeholders that may influence parental involvement in their children’s education and success. At the same time, conference presentations, and stakeholder meetings to share updates will be pertinent.

References

Curtis, E. A., Comiskey, C., & Dempsey, O. (2016). Importance and use of correlational research. Nurse Researcher, 23(6), 20-25. https://doi.org/10.7748/nr.2016.e1382

El Nokali, N. E., Bachman, H. J., & Votruba-Drzal, E. (2010). Parent involvement and children’s academic and social development in elementary school. Child Development, 81(3), 988-1005. https://doi.org/10.1111/j.1467-8624.2010.01447.x

Jones, T., Baxter, M., & Khanduja, V. (2013). A quick guide to survey research. The Annals of The Royal College of Surgeons of England, 95(1), 5-7. https://doi.org/10.1308/003588413×13511609956372

Lim, C., & In, J. (2019). Randomization in clinical studies. Korean Journal of Anesthesiology, 72(3), 221-232. https://doi.org/10.4097/kja.19049

Schober, P., Boer, C., & Schwarte, L. A. (2018). Correlation coefficients. Anesthesia & Analgesia, 126(5), 1763-1768. https://doi.org/10.1213/ane.0000000000002864