Date
Publisher
arXiv
Computer science education is a dynamic field with many aspects that
influence the learner's path. While these aspects are usually studied in depth
separately, it is also important to carry out broader large-scale studies that
touch on many topics, because they allow us to put different results into each
other's perspective. Past large-scale surveys have provided valuable insights,
however, the emergence of new trends (e.g., AI), new learning formats (e.g.,
in-IDE learning), and the increasing learner diversity highlight the need for
an updated comprehensive study. To address this, we conducted a survey with
18,032 learners from 173 countries, ensuring diverse representation and
exploring a wide range of topics - formal education, learning formats, AI
usage, challenges, motivation, and more. This paper introduces the results of
this survey as an open dataset, describes our methodology and the survey
questions, and highlights, as a motivating example, three possible research
directions within this data: challenges in learning, emerging formats, and
insights into the in-IDE format. The dataset aims to support further research
and foster advancements in computer education.
What is the application?
Who is the user?
Who age?
Why use AI?
Study design
