What are the categories of IVs commonly used in research on performance-based funding on higher education?

  

Considering your dissertation research interests (and perhaps using the same IVs and DVs you identified in the discussion questions from previous modules), identify two IVs (each with 2 categories) and three DVs that are measured on continuous scales. Think of DV measures that probably are moderately correlated with each other because they are measuring different components of the same or similar concepts (e.g., three different measures of academic performance). Given these variables and design, what information would a factorial MANOVA provide you? What more would you want to know if you get significant results in the factorial MANOVA? Why would this be significant to your research? (Research support is not required for this question.)My research is on performance-based funding and how it effects developmental students in higher education (community college)Performance-based funding on higher educationDevelopmental classes – Reading, Writing, Mathwill it effect admittance for the developmental student, weaken academics, instructor motivation, student motivationhttp://www.ncsl.org/research/education/performance-funding.aspxhttps://www.americanprogress.org/issues/higher-education/report/2012/08/07/12036/performance-based-funding-of-higher-education/

Introduction:
Performance-based funding is a critical aspect of the higher education system, which aims at improving student outcomes and strengthening academic performance. In particular, the issue of how performance-based funding affects developmental students in community colleges has been a topic of significant research interest. Developing effective strategies for improving academic performance among community college students requires a rigorous examination of key independent variables (IVs) and dependent variables (DVs).

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Description:
To address the research question, the study focuses on two IVs, each with two categories, and three DVs that are measured on continuous scales. The DV measures are related to different components of academic performance, such as reading, writing, and math. Since these measures are interrelated and correspond to similar concepts, a factorial MANOVA is an appropriate statistical tool for exploring their relationship. The study aims to investigate the effects of performance-based funding on the admittance of developmental students, the strength of academic performance, instructor and student motivation, and other related factors.

Headings:
– Introduction
– Description

Objectives:

1. To understand the impact of performance-based funding on developmental education in higher education.
2. To examine the effect of performance-based funding on student motivation, academic standards, and instructor motivation.
3. To explore the correlation between academic performance measures in developmental courses.

Learning Outcomes:

1. Students will be able to describe the concept of performance-based funding and its effects on higher education.
2. Students will be able to analyze the impact of performance-based funding on developmental education in terms of admittance standards, academic standards, instructor motivation and student motivation.
3. Students will be able to evaluate the correlation between different measures of academic performance in developmental courses.
4. Students will be able to interpret the results of a factorial MANOVA in the context of performance-based funding and developmental education.
5. Students will be able to identify the need for further research in the field of performance-based funding and developmental education.

Factorial MANOVA:

A factorial MANOVA would allow us to analyze the effects of two independent variables (IVs) on three dependent variables (DVs) that are measured on continuous scales. In this case, the two IVs would be performance-based funding and developmental education categories (reading, writing, math), while the DVs would be academic performance measures in each of the developmental courses. The analysis would reveal whether there are any significant main effects or interactions between the IVs and DVs.

Significant Results:

If significant results are found in the factorial MANOVA, we would want to further explore the nature of the effects. For example, we would want to know which specific categories of developmental education are being impacted by performance-based funding, and how this is affecting academic performance measures. We would also want to investigate the extent to which instructor and student motivation are contributing to these effects.

Research Significance:

The significance of these findings to our research is that they would provide important insights into the impact of performance-based funding on developmental education in higher education. The findings could also have implications for policy makers, educators, and administrators seeking to improve the quality of education for developmental students in the community college context.

Solution 1:

IVs:
1. Performance-based Funding (with 2 categories – Yes or No)
2. Developmental Classes (with 2 categories – Present or Absent)

DVs:
1. Academic Performance in Reading (on a continuous scale)
2. Academic Performance in Writing (on a continuous scale)
3. Academic Performance in Math (on a continuous scale)

The factorial MANOVA would provide information about the main effects of Performance-based Funding and Developmental Classes, as well as the interaction between the two IVs on the three DVs (academic performance in reading, writing, and math). Significant results in the factorial MANOVA would indicate that there is an effect of Performance-based Funding and/or Developmental Classes on academic performance in reading, writing, and math.

To further understand the significant results, it would be important to conduct post-hoc analyses such as ANOVAs and t-tests to examine which categories of the IVs are significantly different from each other for each DV. This information would help to identify which categories of Performance-based Funding and/or Developmental Classes are associated with better or worse academic performance in reading, writing, and math.

This information is significant to the research as it would inform policymakers and educators about the potential effects of Performance-based Funding and/or Developmental Classes on academic performance of students in higher education, particularly developmental students in community colleges.

Solution 2:

IVs:
1. Instructor Motivation (with 2 categories – High or Low)
2. Student Motivation (with 2 categories – High or Low)

DVs:
1. Academic Performance in Reading (on a continuous scale)
2. Academic Performance in Writing (on a continuous scale)
3. Academic Performance in Math (on a continuous scale)

The factorial MANOVA would provide information about the main effects of Instructor Motivation and Student Motivation, as well as the interaction between the two IVs on the three DVs (academic performance in reading, writing, and math). Significant results in the factorial MANOVA would indicate that there is an effect of Instructor Motivation and/or Student Motivation on academic performance in reading, writing, and math.

To further understand the significant results, it would be important to conduct post-hoc analyses such as ANOVAs and t-tests to examine which categories of the IVs are significantly different from each other for each DV. This information would help to identify which categories of Instructor Motivation and/or Student Motivation are associated with better or worse academic performance in reading, writing, and math.

This information is significant to the research as it would inform educators and administrators about the potential effects of instructor and student motivation on the academic performance of students in higher education, particularly developmental students in community colleges.

Suggested Resources/Books:
1. “Performance Funding for Higher Education”, edited by Kevin J. Dougherty, Sosanya M. Jones, Hana Lahr, and Rebecca S. Natow.
2. “Performance-Based Funding in Higher Education: Principles and Policies” by Laura W. Perna.

Similar Asked Questions:

1. How does performance-based funding affect developmental students in higher education?
2. What impact does performance-based funding have on academic standards in higher education?
3. How do instructor and student motivation vary under a performance-based funding system?
4. What variables should be considered when evaluating the effectiveness of performance-based funding in higher education?
5. What are the pros and cons of performance-based funding for developmental classes in higher education?

Factorial MANOVA:
A factorial MANOVA (multivariate analysis of variance) would be able to examine the main and interaction effects of the two independent variables (performance-based funding and developmental classes) on the three dependent variables (admittance for developmental students, academic strength, instructor motivation). It would determine whether there are any significant differences among the groups based on the combination of these variables.

Significance of Results:
If significant results were found in the factorial MANOVA, more analyses would need to be conducted to determine the exact nature of the differences observed. Post-hoc tests such as pairwise comparisons and follow-up ANOVAs could be used to identify which specific groups have differences. This would be significant to the research as it would provide evidence on the relationship between performance-based funding and developmental classes on academic outcomes, and could guide policy decisions related to funding and resource allocation in higher education.

References:
1. http://www.ncsl.org/research/education/performance-funding.aspx
2. https://www.americanprogress.org/issues/higher-education/report/2012/08/07/12036/performance-based-funding-of-higher-education/
3. Dougherty, K.J., Jones, S.M., Lahr, H., & Natow, R.S. (Eds.). (2017). Performance Funding for Higher Education. Johns Hopkins University Press.
4. Perna, L.W. (2014). Performance-Based Funding in Higher Education: Principles and Policies. Routledge.

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