Proposal for Future Research

In short:  A proposal for future research involves everything about designing a quantitative study without actually collecting data. It’s an opportunity to explore complex designs, like randomized controlled trials or longitudinal studies, that would be too big to conduct on your own. 

Please note that we generally only accept quantitative studies as proposals. We are likely to reject proposals for qualitative or simple survey research, as students can, at the very least, run a pilot with small samples.

Your proposal must have all the parts of any quantitative paper, including a detailed literature review as well as sections on participants, procedures, measures, data analysis plan, etc. You do not need to present expected results or propose a budget for the research. IRB approval is also not required.

Key Components

• Intro & literature review
• Research question
• Research design
• Participant or sampling strategy
• Procedures
• Valid instruments & measures
• Data analysis plan
• Ethical issues
• Limitations

The whole story:  A proposal for future research begins with a comprehensive literature review that culminates in the identification of knowledge gaps or limitations of past work. Ideally, you will go beyond describing or summarizing studies to identifying patterns and trends (and where applicable, contradictions). Your goal is to clarify what is known, what remains unclear, and what should be studied next. 

This leads directly to the rationale for your proposed project. Your argument should be strong enough to persuade someone to fund your idea. The simple fact that something hasn’t previously been studied is not enough; the utility of your project must be persuasively described.  If you were a funder, would you fund this project?

Following this, you must pose a specific, testable set of research questions or hypotheses. A high-quality quantitative research question investigates whether a meaningful relationship exists between a narrow set of clearly defined variables that can be operationally measured using standardized methods such as Likert-type questionnaires, behavioral observations, or experimental tasks.

Next you’ll describe the research design best equipped to test your hypotheses, whether experimental or quasi-experimental. You should articulate plans for recruiting participants or sampling from a population. Power analysis should be used to aid in identifying a minimally-viable sample size (e.g., using G*Power or a similar software tool).

Next, identify research instruments (e.g., scales, tests, experimental tasks, etc.) that are documented as having adequate reliability and validity and are capable of measuring the concepts required to answer the research questions and hypotheses. Where necessary, a limited number of modified scales and novel research instruments designed by the student may be part of the set of research instruments used. Copies of all instruments should be included in an appendix.

Next, you must describe a data analysis plan. Statistical techniques proposed must suit the data and question. You should explain which quantitative statistical software, such as SPSS or R software, would be used to conduct inferential statistical analyses in a rigorous manner, and how you might check assumptions (e.g., normally distributed or skewed data) and explain all statistical choices made and steps taken.

Limitations should be acknowledged and possible future directions for follow-up research should be described. The final integrative project should follow a clear structure (e.g., abstract, introduction, methods, results, discussion, references) and provide well-organized tables or figures as applicable. All references should be properly listed and all writing should be in APA style.

To learn more: 

• APA’s Journal Article Standards for Quantitative Research (https://apastyle.apa.org/jars/quantitative), including a detailed and useful outline (https://apastyle.apa.org/jars/quant-table-1.pdf)
• APA also provides this handy brief outline of a research proposal.

Relevant Courses at TC:   

• Research Methods in Clinical Psychology (CCPX)
• Advanced Research Methods in Clinical Psych (CCPX)
• Programing for Psych Research (CCPX)
• Any of the many Statistics courses offered by HUDK 

Please see our Research Methods Concentration for a full list of courses