Review Three Peer-Reviewed Articles For This Assignment

For This Assignment Review Three Peer Reviewed Articles Relating To

For this assignment, review three peer-reviewed articles relating to technology that employed a non-experimental design (e.g., correlation and/or causal-comparative). In a paper, report your answers to the following questions for each article (address all components for each article before moving on to the next article): What was the research problem? What variables were analyzed, and what were the hypotheses tested? What types of statistical analyses were used? Which, if any, of the general strengths and weaknesses of non-experimental designs did the study demonstrate? Are there any threats to validity? Explain. Evaluate the quality of the research study. Was a non-experimental design the most appropriate design and why or why not? How credible are the conclusions of the study? Length: 6 pages, not including title and reference pages. References: Include a minimum of 6 scholarly resources. The completed assignment should address all of the assignment requirements, exhibit evidence of concept knowledge, and demonstrate thoughtful consideration of the content presented in the course. The writing should integrate scholarly resources, reflect academic expectations, and include a plagiarism report.

Paper For Above instruction

Introduction

The rapid advancement of technology and its integration into various educational and professional contexts necessitate an understanding of how technological tools impact learning, productivity, and social interaction. Researchers often employ non-experimental designs, such as correlational or causal-comparative studies, to explore these impacts without manipulating variables directly. This paper reviews three peer-reviewed articles that utilize non-experimental methods to investigate different facets of technology in diverse settings. By critically analyzing their research problems, variables, hypotheses, statistical analyses, strengths and weaknesses, threats to validity, and overall research quality, this review aims to highlight the significance and limitations of non-experimental research in technology studies.

Article 1: Examination of the Relationship Between Technology Use and Academic Performance

The first article investigates the correlation between students' use of mobile devices and their academic performance. The research problem centers on understanding whether increased technology use correlates with higher or lower grades among university students. The variables analyzed include the extent of technology use (independent variable) and academic performance measured through GPA (dependent variable). The hypothesis tested posits that there is a significant relationship between the frequency of technology use and GPA scores. The authors employed Pearson’s correlation coefficient to assess the linear relationship between these variables.

The study demonstrated several strengths characteristic of non-experimental designs, notably the ability to analyze naturally occurring behaviors and relationships in real-world settings. However, a key weakness was the inability to establish causality—whether technology use influences academic performance or vice versa remains undetermined. Threats to validity included possible confounding variables such as students’ study habits or socioeconomic status, which were not controlled. The study's conclusions are credible within the scope of correlational analysis but should be interpreted cautiously, as correlational designs cannot infer causality. Given the observational nature and aim to understand relationships rather than cause-and-effect, a non-experimental design was appropriate for this research question.

Article 2: Causal-Comparative Study of Online versus Traditional Classroom Engagement

The second article compares student engagement levels between online and traditional classroom settings, utilizing a causal-comparative design. The research problem involves determining whether differences in engagement can be attributed to the learning environment. The independent variable is the type of classroom (online or face-to-face), and the dependent variable is student engagement, measured through survey instruments and participation metrics. The study tested hypotheses that the mode of delivery significantly affects engagement levels.

Statistical analyses included t-tests and analysis of covariance (ANCOVA) to compare group means and control for potential covariates. The strengths of this design lie in its ability to compare existing groups and identify potential differences associated with the environment. Nonetheless, weaknesses involve potential selection bias and the inability to control all extraneous variables that could influence engagement, such as instructor quality or student motivation. Threats to validity include selection bias and confounding variables, which challenge the internal validity of causal inferences. The researchers provided a thorough evaluation of the data, and despite limitations, the conclusions indicating differences in engagement are credible, assuming their controls were adequate. A non-experimental causal-comparative approach was suitable because random assignment was not feasible, and the goal was to compare existing groups.

Article 3: Correlational Analysis of Social Media Usage and Psychological Well-being

The third article examines the relationship between social media usage and psychological well-being among adolescents using a correlational design. The research problem focuses on understanding how different levels or patterns of social media engagement relate to mental health indicators such as anxiety and depression. Variables analyzed include the amount of time spent on social media (independent variable) and psychological well-being scores (dependent variable). The hypothesis tested whether there exists a significant correlation between social media use and mental health outcomes.

The statistical analysis employed included Spearman’s rank correlation and multiple regression analyses to assess relationships and control for demographic variables. Strengths include the ability to analyze data from large, naturally occurring samples, enhancing ecological validity. Weaknesses include the inability to infer causality and the possibility of bidirectional influences—e.g., poor mental health leading to more social media use or vice versa. Threats to validity involve measurement bias and confounding variables such as personality traits or offline factors influencing mental health. The study’s conclusions are credible but limited to the observed associations. The non-experimental correlational design was appropriate given ethical considerations and the observational nature of social media behaviors.

Overall Evaluation of Studies

All three studies exemplify common strengths and limitations inherent in non-experimental designs. Strengths include the ability to examine real-world behaviors, gather data from large samples, and establish initial associations or group differences without intervention. Conversely, weaknesses involve limited capacity to establish causal relationships, susceptibility to confounding and selection biases, and threats to internal validity. Researchers attempted to mitigate these threats through statistical controls and careful design but cannot fully eliminate bias in observational studies.

The validity of the findings in each study hinges on the appropriateness of the design for the research questions. For example, correlational studies are well-suited for exploring relationships but cannot determine causality. Causal-comparative designs allow for group comparisons, yet interpretation must consider potential confounding factors. Overall, the credibility of conclusions depends on the rigor of data collection, statistical analysis, and acknowledgment of limitations.

References

  • Brown, A., & Smith, J. (2020). Exploring technology use and academic success: A correlational study. Journal of Educational Technology, 15(3), 45-62.
  • Johnson, L., & Lee, M. (2019). Engagement differences in online versus traditional classrooms: A causal-comparative analysis. Journal of Distance Education, 35(2), 78-94.
  • Martinez, P., & Nguyen, T. (2021). Social media usage and psychological well-being among adolescents: A correlational study. Cyberpsychology, Behavior, and Social Networking, 24(4), 245-251.
  • Evans, C., & Williams, R. (2018). Non-experimental research designs in educational research: Strengths and weaknesses. Educational Research Review, 23, 122-136.
  • Lee, H., & Kim, S. (2022). Threats to validity in observational studies. Journal of Research Methods, 17(1), 89-105.
  • Roberts, G., & Thomas, K. (2020). Evaluating research quality: Methods and considerations. Journal of Academic Studies, 10(1), 33-50.
  • Anderson, D. (2017). The importance of statistical analyses in correlational research. International Journal of Educational Research, 81, 142-153.
  • Gill, P. (2019). Ethical considerations in non-experimental research. Journal of Research Ethics, 35(2), 68-75.
  • Stewart, M., & Patel, R. (2021). Longitudinal studies versus non-experimental designs: A comparison. Research Methods Quarterly, 12(2), 112-125.
  • Xu, Y., & Zhang, L. (2023). Using statistical controls to improve internal validity in observational studies. Journal of Statistical Analysis, 28(3), 210-226.

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