Introduction to Research
This lesson plan was a part of the "EDUC 198 Directed Research in Education course" which I started teaching in Fall 2021. Course participants are Research Assistants (RAs) for the UCI Working Memory and Plasticity Lab (WMP Lab). This course is an introductory and supplementary class for undergraduate/new RAs who are doing research for course credit. In addition to their lab responsibilities, RAs are required to complete the assigned readings and a final project.
Starting with a Research Question
Assigned Reading: Bordage, G., & Dawson, B. (2003). Experimental study design and grant writing in eight steps and 28 questions. Medical education, 37(4), 376–385. https://doi.org/10.1046/j.1365-2923.2003.01468.x
This paper guides new researchers to formulate their research questions and write successful proposals. I selected this paper for my RAs because:
It’s easy to read - No jargon, no philosophical debates, just straight to the point, almost like a recipe when cooking!
It’s applicable to most scientific studies - Although the journal is for the medical field, the content is highly relevant and applicable to research in cognitive science, biology, psychology, and so forth.
It provides examples and key questions - So you can better follow the content of the paper and start brainstorming your question(s).
Note that I only ask you to read up to the Proposal Guideline section of the paper - This is because the rest of the paper is still helpful, although not critical to my expectation of your reading for the week.
It helps you to form your research question - Even if you are not planning on doing UROP, this paper should still help you with forming a research question for your upcoming week 4 assignment (research proposal template).
Additionally, here is a great resource offered by UC Merced’s library. It gives RAs examples of what different research questions for different fields of interest could look like.
Conducting Literature Review
Assigned Reading: Pautasso M. (2013). Ten simple rules for writing a literature review. PLoS computational biology, 9(7), e1003149. https://doi.org/10.1371/journal.pcbi.1003149
Optional Reading: Williams, J. K. (2018). A Comprehensive Review of Seven Steps to a Comprehensive Literature Review. The Qualitative Report, 23(2), 345-349. https://doi.org/10.46743/2160-3715/2018.3374
When doing literature reviews, try to keep these questions in mind:
What is the main point/finding/significance of this article?
Does it offer any method I can refer from?
How is this article relevant to my questions?
What is some surprising information I found?
What are some new and original ideas/questions prompted by this article?
In terms of organization of literature review, UNC-Chapel Hill has a great summary on different ways you can categorize your reviews into sections and themes: https://writingcenter.unc.edu/tips-and-tools/literature-reviews/
Knowing Your Research Method
Assigned Reading: Selections from "Understanding Research Methods: An Overview of the Essentials" 10th Edition (Patten & Newhart, 2018)
During this week of the quarter, one of the main learning goals was for RAs to understand different types of research methods. To facilitate this, I've selected chapters from a book entitled Understanding Research Methods: An Overview of the Essentials 10th Edition by Mildred L. Patten and Michelle Newhart.
Ch 3: The Role of Theory in Research
This chapter talks about what exactly is theory and why is it important. RAs might hear me say this a lot when giving feedback to their proposals - what is your theoretical framework and how is XYZ relate to your questions and theories - this is because the theory is what will differentiate our writing from scientific essays vs. opinions.
Ch 4: Experimental and Nonexperimental Studies
This chapter talks about different types of experiments RAs can set up to test their hypothesis. Most of what they propose are experimental studies. But I don't underestimate nonexperimental studies. A lot of non-STEM fields of studies utilize nonexperimental studies for their research goal. It also discusses "non-true experiments" where there might be too many confounding variables or a lack of control groups - sometimes we can't have the perfect experiment where everything is controlled due to ethical and practical concerns.
Ch 7 Quantitative and Qualitative Research: Key Differences
Even though we are a quant-heavy lab, I don't want RAs to underestimate how important qualitative research is. While the quantitative side can uncover important statistics (such as significant achievement gaps or high depression rate), the qualitative side can provide you with the context and narratives as to why this phenomenon exists (such as family struggles or lack of access to resources).
I also included a helpful blog post that covers different types of research methods and how suit different purposes: https://www.editage.com/insights/how-to-choose-the-research-methodology-best-suited-for-your-study
Introducing Statistical Analysis
For this week, the learning goal was for RAs to understand some common statistical analyses so that as they are carrying out their proposal idea, they are also considering how to analyze data after data collection.
All RAs are strongly encouraged to take stats classes in their undergrad: not only you will have time to go over the foundation of stats in these classes, you will also have the chance to do practice problems in these classes! Just like math, statistics is a practical skill that needs to be practiced. This means that if you don’t do a lot of stats, you will forget what’s going on and what does each thing mean. BUT at the same time, this also means that if you ever forget about a component of stats, you can always pick it up super quickly because it’s meant to be simple and applicable. Not to mention, it is always helpful to have these classes reflected on your transcript when applying to grad school or jobs as you can provide some evidence that you know the basics about statistics and research.
Assigned Reading: Ali, Z., & Bhaskar, S. B. (2016). Basic statistical tools in research and data analysis. Indian journal of anaesthesia, 60(9), 662–669. https://doi.org/10.4103/0019-5049.190623
I chose this reading because it's short and very informative (only 7 pages in content!). A lot of the other readings I've found are just too long or abstract in ways that they are describing statistics. Although it's written for a medical journal, the foundation of statistics is pretty much the same across disciplines with different emphasis or common practices.
Additionally, here are some helpful resources that I've been using or showing others on learning stats. You do not have to review them. These are here as resources:
Demystifying Statistical Analysis 1: A Handy Cheat Sheet
This blogpost is a cheat sheet on what type of tests to use based on your variables.
UCLA Institute for Digital Research & Education
This site provides information on how to conduct analysis and read output on different software.
YouTube videos - One of the personal criticisms I have about a lot of the tutorials or lectures on statistics is that that sometimes diving into the math formula is so confusing, not to mention having the big picture can also help you understand where you are going with learning all these math...and this is why I think a lot of the popular science YouTube video does a great job doing this.