Research Design Questions Suppose You Were Going To Create

Research Design Questionssuppose You Were Going To Create Your Own Stu

Research Design Questionssuppose You Were Going To Create Your Own Stu

Suppose you were going to create your own study to examine what course-delivery format (online, blended, or face-to-face) leads to the best performance in a psychological statistics class. In a paper, identify the following for your study: What is your research question? What is your hypothesis (both null and alternate)? Is this a qualitative or quantitative design (based on type of variable collected) and why? Is this a descriptive, correlational or experimental design and why? What would be an example of a variable for this study that could be measured on a nominal scale? An ordinal scale? Interval scale? Ratio scale? Once you have collected your data, would you use inferential or descriptive statistics and why? Create a sample frequency distribution for one of the variables. Choose either a simple or grouped frequency distribution and explain your choice.

Paper For Above instruction

Introduction

In educational research, understanding the impact of course-delivery formats on student performance is vital for improving teaching strategies and student outcomes. This study aims to investigate which of the three common delivery methods—online, blended, or face-to-face—yields the highest academic performance in a psychological statistics course. By examining the differences in student performance across these formats, educators can tailor instructional approaches to optimize learning efficacy.

Research Question

The primary research question guiding this study is: "Does the course-delivery format (online, blended, or face-to-face) influence student performance in a psychological statistics class?" This question seeks to determine whether the mode of instruction significantly impacts academic achievement.

Hypotheses

Based on the research question, the null hypothesis (H0) states that there is no difference in student performance across the three course-delivery formats: "Course-delivery format has no effect on student performance in a psychological statistics class." The alternative hypothesis (H1) posits that at least one format leads to different performance outcomes: "Course-delivery format affects student performance in a psychological statistics class."

Research Design Type

This study employs a quantitative research design because it involves the collection of numerical data—such as test scores or grades—allowing for statistical analysis. Quantitative methods are appropriate here as they facilitate measurement and comparison of student performance metrics across different formats, providing objective insights into the effects of delivery modes.

Design Classification: Descriptive, Correlational, or Experimental

This research qualifies as an experimental design because it involves manipulating the independent variable—the course-delivery format—and observing its effects on the dependent variable—student performance. Random assignment of students to different formats and control over extraneous variables strengthen the experimental approach, enabling causal inferences about the effect of the delivery mode on performance.

Variables and Measurement Scales

  • Nominal scale: Course-delivery format (online, blended, face-to-face). This variable categorizes students without implying any order or magnitude.
  • Ordinal scale: Student satisfaction ratings (e.g., very dissatisfied to very satisfied). This represents order but not necessarily equal intervals between categories.
  • Interval scale: Scores on a standardized test measuring statistical knowledge, where intervals between scores are equal but there is no true zero point.
  • Ratio scale: Number of completed assignments or attendance hours—these have a true zero point and allow for ratio comparisons.

Statistical Approach: Inferential or Descriptive

After data collection, inferential statistics would be employed to determine whether differences in performance across formats are statistically significant. Inferential methods, such as ANOVA, allow generalization of findings from the sample to the population, enabling conclusions about causal effects of instructional mode.

Sample Frequency Distribution

For the categorical variable of course-delivery format, a grouped frequency distribution is appropriate due to the discrete categories (online, blended, face-to-face). Suppose a sample of 90 students is evenly distributed: 30 online, 30 blended, and 30 face-to-face. The grouped frequency distribution would display the number of students in each category, facilitating clear comparisons.

Choosing grouped over simple frequency distribution simplifies visualization when dealing with multiple categories. It allows for an easier overview of how many students are in each format, supporting interpretation of the data pattern in relation to student performance outcomes.

Conclusion

This study's design comprehensively addresses the influence of course-delivery formats on student performance in a psychological statistics class. Utilizing quantitative, experimental methods and appropriate measurement scales ensures reliability and validity. The importance of statistical analysis in deriving meaningful conclusions underscores the value of this research for educational practices.

References

  • Campbell, D. T., & Stanley, J. C. (1963). Experimental and Quasi-Experimental Designs for Research. Houghton Mifflin.
  • Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. Sage Publications.
  • Gall, M. D., Gall, J. P., & Borg, W. R. (2007). Educational Research: An Introduction. Pearson Education.
  • Johnson, R. B., & Christensen, L. (2019). Educational Research: Quantitative, Qualitative, and Mixed Approaches. Sage.
  • Neuman, W. L. (2014). Social Research Methods: Qualitative and Quantitative Approaches. Pearson.
  • Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics. Sage.
  • Polit, D. F., & Beck, C. T. (2017). Nursing Research: Generating and Assessing Evidence for Nursing Practice. Wolters Kluwer.
  • Vockell, E. L., & Asher, J. W. (2014). Elementary School Practice Research. Prentice Hall.
  • Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and Quasi-Experimental Designs. Houghton Mifflin.
  • Tabachnick, B. G., & Fidell, L. S. (2013). Using Multivariate Statistics. Pearson.

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