A-B Testing: Difference between revisions

'''A/B Testing''', also known as split testing, is a method used in controlled experiments to compare two versions of a variable, typically denoted as A and B. It is commonly employed in fields such as marketing, web design, and user experience research. By randomly assigning participants to either version A or B, researchers can assess which variant performs better based on predefined metrics such as click-through rates, conversion rates, or user engagement. A/B testing allows for data-driven decision-making by providing insights into the effectiveness of changes made to a product or service.

Eric mentions '''A/B Testing''' in the context of adding “differential diagnosis” to our educational toolkit:

 

'''Eric:''' "One of the things I believe is that we're not taught subjects in a way that maximally benefits the largest number of learners. We're taught subjects due to the political economy of making these subjects take a very long time, and rewarding the specialty that might have been the career choice of the person teaching it."

 

'''Tom:''' "So what teaching method would optimize for the greatest number of learners?"

 

 

 

'''Eric:''' "Right, and, you know, you start to understand—you present several different styles, you know let's do some A/B Testing—like, you go to your optometrist: Is this better like this? Or like this? Right, and so you start to understand somebody's learning style and learning profile."