Take the course, adapt for your classroom, or incorporate into your next lab meeting. See the full curriculum at c4r.io/units

C4R, the Community for Rigor, creates free, practical learning resources for researchers and educators. We help people put scientific rigor into practice through lessons, activities, and ready-to-use online teaching materials.

Careful design and thoughtful reporting are cornerstones of rigorous research. Careful experimental design incorporates several principles like: selecting appropriate controls, choosing the right randomization method, avoiding bias, and choosing the best sample size for the experiment. Writing readable code, creating visualizations to tell your data story, and sharing data effectively are all pieces of thoughtful reporting. C4R has created free online modules for each of these topics for you to teach or learn from. What other topics are cornerstones of rigorous research? #ScientificRigor #OpenScience

C4R uses many established frameworks in developing our curriculum. However, for controls, the existing frameworks didn't fully capture the ways researchers address variables. Karen Word, Senior Curriculum Developer at C4R, gives us an inside look at why this framework was created. To understand what this framework means and how it fits into your own research check out the full interview on our YouTube channel: buff.ly/7l4QHmN #ResearchMethods #ScientificRigor

If you'd like to learn more or adopt these materials for you classroom or lab explore our full curriculum: c4r.io/units

Avoiding these 3 common control issues produces more rigorous research: 1. Insufficient negative controls Solution: add targeted negative controls 2. Human bias hindering controls Solution: apply a masking design 3. Uneven variable distribution Solution: use randomization What control issues do you most often see?

C4R creates free, online, educational units to help you better understand (or teach) the principles and practices of scientific rigor.

What would change if your lab or classroom fully adopted C4R's free scientific rigor materials? We asked researchers this question. They shared hopes of better, more rigorous, and higher quality science. To them, adoption would mean improved collaboration, increase awareness, and promotion of higher quality experimental designs like randomization. What would change if your lab or classroom adopted C4R's materials? #ResearchCulture #TeamScience

To learn more explore C4R's free controls unit. c4r.io/units

Controlling for variables is a cornerstone of rigorous research. How do researchers control for them? The framework we use is has three categories, constrain, distribute, and test. Constrain Limiting the range of the variable Distribute Distributing the range of the variable as equally as possible across groups Test Making a comparison group or adjusting for effect of the variable during analysis All three are ways to address a variable's potential influence on an experiment. How are you controlling for variables in your research? #ExperimentalDesign #ResearchDesign

This week we're diving deeper into our free online unit, Controls: Clarity, not coincidence.

You're testing Compound X, which you dissolve in DMSO. After treatment, you observe a difference. What comparison best separates the effect of Compound X and the solvent (DMSO)? A. Compare to untreated cells B. Compare with cells treated with the same concentration of DMSO alone C. Compare different concentrations of Compound X D. Compare the effect across several independent experimental replicates

To learn more about Controls explore our Free Controls unit: c4r.io/units

What are controls doing in a research design? C4R Senior Curriculum Developer, Karen Word, breaks down Constrain, Distribute, Test, the framework used in our Controls unit. Next week we'll share why we developed it. #ScientificRigor #ResearchMethods

Want to learn more about repeated measures design? Explore C4R's Controls Unit: c4r.io/units

Repeated measures design is a method where measurements are taken from the same subject under different conditions or over time. Does this replace the need for control groups in a study design? Additional controls can help us address the disadvantages of repeated measures design. "Recovery" time points, negative control groups, and targeted negative control groups are a few examples of how we can strengthen a repeated measures study. #ResearchMethods #ScientificRIgor

What scientific rigor topic do you wish more researchers talked about? At C4R26, our annual conference dedicated to scientific rigor, we asked attendees to answer this question on The Rigor Wall. What would you add to The Rigor Wall? #C4R26 #ScientificRigor