Abstract: Attrition rates in introductory computing courses can be as high as 30% and by year two attrition rates can be upwards towards 60%. Over the past several years I have been working on understanding why these rates are so high and how we can improve our introductory courses to help combat these attrition rates. While I have successfully been able to keep my introductory courses attrition rates below 10% it is difficult to get quantifiable data to justify why. The reason to that is because of participation bias. Students that do not participate in studies are five times more likely to fail or drop the course than those who participate. Since they do not participate in studies, we do not have any data to see why they might have dropped the course. Which is a major issue to studying student attrition rates. When computing education researchers are preparing the design of their next studies, I beseech them to consider the following question: What’s your placebo?

Short Bio: Ryan Bockmon is a PhD candidate from University of Nebraska – Lincoln. He started teaching computing courses at his local high school as an undergraduate while he attended school at Montana State University. The course he created has now replaced the introductory computing course at Montana State University. After obtaining his undergraduate degree he then went abroad to teach a computing course at the Technical University of Vienna. He now spends his time in graduate school teaching the introductory data science course at University of Nebraska – Lincoln while researching the connection between students’ spatial skills and their ability to program. He also spends his time doing outreach by building materials for Click2CS. A website that helps train 4-H programs to develop their own computing program. The site was launched in early 2022 and has reached 2,500 active members.