  During the last ten years advances in open-source digital technology, used
especially by data science, led to very accessible ways how to obtain, store,
process, analyze or share data in almost every human activity. Data science
tools bring not only transparency, accessibility, and reproducibility in open
science, but also give benefits in open education as learning tools for
improving effectiveness of instruction.
  Together with our pedagogical introduction and review of Jupyter as an
interactive multimedia learning tool, we present our three-years long research
in the framework of a complex mixed-methods approach which examines physics
teachers' perception of Jupyter technology in three groups: Ph.D. candidates in
physics education research (PER) ($N = 9$), pre-service physics teachers ($N =
33$) and in-service physics teachers ($N = 40$).
  Despite the fact that open-source Jupyter notebooks are natural and easy as
email or web, the results suggest that in-service teachers are not prepared for
Jupyter technology and open analysis, but positively accept open education data
presented via another open-source data science tool, R Shiny interactive web
application, as an important form of immediate feedback and learning about the
quality of their instruction.
  Simultaneously our instruction results in the frame of the Flipped Learning
also indicate that young beginning PER researchers and pre-service physics
teachers can master key digital skills to work with Jupyter technology
appreciating its big impact on their learning, data and statistical literacy or
professional development.
  All results support the ongoing worldwide effort to implement Jupyter in
traditional education as a promising free open-source interactive learning tool
to foster learning process, especially for the upcoming young generation.
