Conversations as a Source for Teaching Scientific Concepts at Different
  Education Levels
Donya Rooein Dirk Hovy
Open conversations are one of the most engaging forms of teaching. However,
creating those conversations in educational software is a complex endeavor,
especially if we want to address the needs of different audiences. While
language models hold great promise for educational applications, there are
substantial challenges in training them to engage in meaningful and effective
conversational teaching, especially when considering the diverse needs of
various audiences. No official data sets exist for this task to facilitate the
training of language models for conversational teaching, considering the
diverse needs of various audiences. This paper presents a novel source for
facilitating conversational teaching of scientific concepts at various
difficulty levels (from preschooler to expert), namely dialogues taken from
video transcripts. We analyse this data source in various ways to show that it
offers a diverse array of examples that can be used to generate contextually
appropriate and natural responses to scientific topics for specific target
audiences. It is a freely available valuable resource for training and
evaluating conversation models, encompassing organically occurring dialogues.
While the raw data is available online, we provide additional metadata for
conversational analysis of dialogues at each level in all available videos.