Think Again Of That Study On The Predictive Relations 169108

Think Again of That Study On The Predictive Relationships

Topic 2 Dq 1aug 18 20 2022think Again Of That Study On The Predictive

Topic 2 Dq 1aug 18 20 2022think Again Of That Study On The Predictive

Topic 2 DQ 1 Aug 18-20, 2022 Think again of that study on the predictive relationships of high school principals’ leadership styles and academic achievement in their schools in your state. The instrumentation must be aligned with the research questions and study design and must be feasible for administration of the study. How do you identify instruments appropriate for use with GCU core quantitative research designs? How might you address concerns about the influence of instrumentation on study feasibility? Do you have any ethical concerns about recruitment and data collection? Explain.

Paper For Above instruction

The selection of appropriate instruments is critical in quantitative research, as they serve as the primary tools for data collection and directly impact the validity and reliability of study findings (Waldschmidt & Casteel, 2021). To identify suitable instruments aligned with GCU core quantitative research designs, researchers must ensure that these tools accurately measure the variables of interest, adhere to established validity and reliability standards, and are appropriate for the study population. Common methods involve reviewing existing, validated instruments from prior research, adapting them as necessary, and conducting pilot testing to confirm their applicability within the specific context (Frey, 2018). When instruments are well-aligned with research questions and designed with the study's methodology in mind, the resulting data become more trustworthy, enhancing the overall quality of research outcomes.

Addressing feasibility concerns involves several strategies. First, researchers should evaluate the complexity and time requirements of administering instruments to ensure they are manageable within the study timeline and resources. Utilizing existing data sources, such as secondary data, can also improve feasibility by reducing data collection burdens (Tripathy, 2013). For instance, in a study examining the relationship between high school principals’ leadership styles and academic achievement, utilizing already available state-level academic data can streamline the process and mitigate logistical hurdles. Additionally, pilot testing instruments to assess administration time and clarity can preempt issues, allowing adjustments before full deployment. Ensuring that data collection methods are cost-effective and minimally intrusive further enhances feasibility (Hagan, 2014).

Ethically, recruitment and data collection raise concerns that must be carefully managed. Protecting participant confidentiality and privacy is paramount. This entails obtaining informed consent, anonymizing data, and ensuring that no personal identifiers are collected without explicit permission, especially when secondary data are involved (Tripathy, 2013). Researchers must also consider potential power imbalances and ensure voluntary participation without coercion. Addressing these ethical principles—justice, beneficence, and respect for persons—helps safeguard participant rights throughout the research process (Taquette & Borges da Matta Souza, 2022). For secondary data, securing data access agreements and adhering to data-sharing policies are necessary to uphold ethical standards.

In summary, aligning instruments with research questions and design is crucial for validity and feasibility. Using validated, straightforward instruments, leveraging secondary data, and maintaining strict ethical standards in recruitment and data handling are essential strategies. These approaches not only facilitate successful data collection but also uphold ethical integrity throughout the research, ensuring meaningful and trustworthy findings (Godbey, 2018).

References

• Frey, B. (2018). The SAGE encyclopedia of educational research, measurement, and evaluation (Vols. 1–4). SAGE.
• Godbey, S. (2018). Testing future teachers: A quantitative exploration of factors impacting the information literacy of teacher education students. College & Research Libraries, 79(5), 600–612.
• Hagan, T. L. (2014). Measurements in quantitative research: How to select and report on research instruments. Oncology Nursing Forum, 41(4), 469–470.
• Taquette, S. R., & Borges da Matta Souza, L. M. (2022). Ethical dilemmas in qualitative research: A critical literature review. International Journal of Qualitative Methods, 21, 1–16.
• Tripathy, J. (2013). Secondary Data Analysis: Ethical issues and challenges. Iranian Journal of Public Health, 42(12), 1478–1479.
• Waldschmidt, J., & Casteel, A. (2021). Quantitative instrumentation and data collections. In GCU Doctoral Research: Introduction to Sampling, Data Collection, and Data Analysis (1st ed.). Grand Canyon University.