A-B Testing: Difference between revisions
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A/B | '''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. | ||
==On Youtube== | |||
''' | Eric mentions '''A/B Testing''' in an appearance on [https://youtu.be/XbKXeVOUQYY?t=1532 Impact Theory] in the context of adding âdifferential diagnosisâ to our educational toolkit: | ||
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<blockquote> | |||
'''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." | |||
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'''Tom:''' "So what teaching method would optimize for the greatest number of learners?" | |||
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'''Eric:''' "Well, first of all, differential diagnosis, like, are you a visual learner or are you an auditory learner?" | |||
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'''Tom:''' "And we now segment them out." | |||
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'''Eric:''' "Right, and, you know, you start to understandâyou present several different styles, you know let's do some A/B Testingâlike, 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." | |||
</blockquote> | |||
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{{#widget:YouTube|id=XbKXeVOUQYY|start=1532}} | |||
[[Category:Concepts]] | [[Category:Concepts]] | ||
[[Category:Psychology]] | [[Category:Psychology]] |
Latest revision as of 05:17, 31 March 2024
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.
On Youtube[edit]
Eric mentions A/B Testing in an appearance on Impact Theory in the context of adding âdifferential diagnosisâ 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: "Well, first of all, differential diagnosis, like, are you a visual learner or are you an auditory learner?"
Tom: "And we now segment them out."
Eric: "Right, and, you know, you start to understandâyou present several different styles, you know let's do some A/B Testingâlike, 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."