  YouTube Kids (YTK) is one of the most popular kids' applications used by
millions of kids daily. However, various studies have highlighted concerns
about the videos on the platform, like the over-presence of entertaining and
commercial content. YouTube recently proposed high-quality guidelines that
include `promoting learning' and proposed to use it in ranking channels.
However, the concept of learning is multi-faceted, and it can be difficult to
define and measure in the context of online videos. This research focuses on
learning in terms of what's taught in schools and proposes a way to measure the
academic quality of children's videos. Using a new dataset of questions and
answers from children's videos, we first show that a Reading Comprehension (RC)
model can estimate academic learning. Then, using a large dataset of middle
school textbook questions on diverse topics, we quantify the academic quality
of top channels as the number of children's textbook questions that an RC model
can correctly answer. By analyzing over 80,000 videos posted on the top 100
channels, we present the first thorough analysis of the academic quality of
channels on YTK.
