Hanˇc et al. RESEARCH Teachers' perception of Jupyter and R Shiny as digital tools for open education and science Jozef Hanˇc1* , Peter Strauchˇ 1, Eva Paˇnkov´a1 and Martina Hanˇcov´a2 *Correspondence: [email protected] Abstract 1Institute of Physics, Faculty of Science, Pavol Jozef Saf´arikˇ During the last ten years advances in open-source digital technology, used University, Koˇsice,Slovakia especially by data science, led to very accessible ways how to obtain, store, Full list of author information is process, analyze or share data in almost every human activity. Data science tools available at the end of the article yEqual contributor 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. Keywords: data science tools; learning tools; interactive multimedia; data visualization; data analysis; user experience questionnaire; flipped learning Introduction arXiv:2007.11262v2 [physics.ed-ph] 23 Jul 2020 During the last decade, new digital technologies such as mobile devices, cloud in- frastructure, open data, artificial intelligence, decentralized and social networks (Downes, 2019) caused that we live in the digital and data-intensive age. Ninety percent of all data has been created in the last two years (Boaler, 2020; Marr, 2018). Data touches all aspects of our lives. The world economy, our jobs, our health, our environment and our roles as citizens increasingly depend on the knowledge, skills and technology required to work with, understand, and effectively use data (Boisvert et al, 2016). In April 2020 GitHub (GitHub, Inc., 2020; Warner, 2018), the world largest web cloud platform for storing, social coding and collaborating on any open code or Hanˇc et al. Page 2 of 32 digital content, reached a further milestone, 50 million developers working on over 100 million repositories | 3,000 times more than after its starting year 2008. Simultaneously, during last years open-source software and data science tools, namely programming languages Python and R together with environments for work- ing with them | especially Jupyter and RStudio, have conquered the data science world (kaggle, 2020) providing everybody free, open, revolutionary and very acces- sible ways how to gather, store, process, analyze, present or share data in almost every human activity. Speaking about science, in the near future, the European Open Science Cloud (EOSC, eosc-portal.eu), officially launched at the end of 2018, will offer to mil- lions of European researchers, professionals, but also university students, in science, technology, the humanities and social sciences a virtual environment with open and seamless services for storage, management, analysis and re-use of open research data, interoperable among all scientific domains or EU member states. By federat- ing, the EOSC will connect existing and being built scientific data infrastructures, currently dispersed and isolated across disciplines and borders of EU states. One of the key and easily accessible open digital research environments in EOSC (see e.g. the infrastructure EOSC project OpenDreamKit, 2015-2019, opendreamkit.org) should become the mentioned technology of Jupyter Notebooks. The highest ambi- tion of the EOSC is to change the way we do science, to open it. As for education, in 2015 from US a worldwide Call for Action to promote data literacy swept the world (Boisvert et al, 2016; EDC Oceans of Data Institute, 2015). Its signatories call for \a revolution in education, placing data literacy at its core, in- tegrated throughout K-16 education nationwide and around the world. By enabling learners to use data more effectively, we prepare them to make better decisions and to lead more secure, better-informed and productive lives." On February 2020, Jo Boaler, a professor of mathematics education at Stanford, invited a group of fifty mathematicians, data scientists, teachers and education policy leaders to start a movement, a YouCubed initiative, which will modernize the K-12 math curriculum and will prepare high school students to the data age (Boaler, 2020; Spector, 2020). Jupyter in science and education One of the current main data science tools for open science is Jupyter technology of interactive multimedia notebooks | shortly and officially called Jupyter Notebooks. From the viewpoint of users, the technology is natural and easy as email or web. It was released in 2014 in the frame of Project Jupyter (jupyter.org, Kluyver et al, 2016; Project Jupyter et al, 2018) as a free, open alternative to the well-known Mathe- matica Notebooks from commercial software Wolfram Mathematica (wolfram.com). As for the technology platform, Project Jupyter evolved from IPython, a personal side project of a Jupyter-project co-founder and former nuclear physicist, Fernando Per´ez. Jupyter is an open source, free interactive web computing environment, accessi- ble through any modern web browser, that enables users to use, modify or create interactive multimedia web documents which mix live code (over 100 computer lan- guages with a focus on Python, called kernels), interactive computations, equations, simulations, plots, images, narrative texts, annotations, audios or videos. Hanˇc et al. Page 3 of 32 Over the last 5 years, Jupyter Notebooks have become the most widely used as an environment for performing scientific calculations, open analysis, data processing and scientific reporting (Frederickson, 2019). Data and analysis of the recent Nobel prize-winning detections of gravitational waves (2015), predicted by Einstein in 1915, were released as a Jupyter Notebook. At the same time we are witnesses of an explosion of scientific and technical articles dealing with Jupyter's application in science, technology and education (Fig.1). Figure 1 Annual numbers of scientific publications dealing with Jupyter in four scholar databeses during 2015-2019. Our review as bar plots was effectively created using Scientific Python in a Jupyter notebook (data analysis library pandas). As we can see in hundreds of scholarly papers connected to education (Fig.1), e.g. Weiss(2017) { chemistry, Koehler and Kim(2018) { mathematics, Odden et al (2019) { physics, Wright et al(2020) { biology, Cardoso et al(2019) { engineer- ing, Jupyter is widely applied in open STEM and STEAM education (Khine and Areepattamannil, 2019), supporting data literacy and including also programming, statistics, data science, cognitive science, computer science, machine learning, digi- tal humanities, scientific computation or robotics (Barba et al, 2019). Today, Jupyter notebooks, as living interactive \storytelling" documents, is the technology behind many innovative educational programs and also became Hanˇc et al. Page 4 of 32 platform-of-choice for tutorials, workshops, online lessons, and even books. One of the best elaborated book examples is an open GitHub handbook Teaching and Learning with Jupyter (Barba et al, 2019) covering topics like why and how to use Jupyter in education, pedagogical instruction designs and case studies elicited from authors' real experience or technical details of Jupyter implementation in practice. Another example is Coursera (coursera.org), a world-wide MOOC platform, offering many free courses and guided projects using Jupyter as a key learning tool. The revolutionary significance of Jupyter for open science and education also became the subject of philosophical reflections, e.g. from a writer and programmer J. Sommers (Somers, 2018) or a Nobel prize laureate P. Romer (Romer, 2018) or a Canadian philosopher and open education visionary S. Downes (Downes, 2019). Jupyter as a tool of interactive teaching methods Finally in this introductory section, we would like to point out three important, but less known, Jupyter features in connection with three modern interactive instruc- tion approaches which are \designed to promote conceptual understanding through interactive engagement of students in heads-on (always) and hands-on (usually) activities which yield immediate feedback through discussion with peers and/or instructors" (Fraser