Interactive Visualizations to Introduce Data Science for High School Students

Abstract

Artificial intelligence integrates with our daily life in more ways each day with the invention of new tools and applications. For example, businesses utilize machine learning, which is a subfield of artificial intelligence, to identify the ideal customer for targeted advertisement. Machine learning and data science scale previous manual problems to a wider customer base. With all the various applications for artificial intelligence, there is still a noticeable gap in the number of qualified job applicants who can solve some of the machine learning problems of the day. There is a movement to introduce computer science education earlier to K-12 students. One motivation behind an earlier introduction is to better prepare students to study computer science at universities and fulfill these coveted technology positions in the future. Given this motivation, there needs to be more computer science instructional activities and lesson plans to support K-12 teachers. Currently there are several new tools and curricula available for computer science. However, there is a need for beginner and K-12 accessible data science and machine learning instructional methods. These topics are advanced computer science electives but an earlier introduction can still benefit students. Interactive visual activities support high school students to learn challenging topics. In this paper, we consider how a visual analytic process can present difficult data science concepts. We present an interactive visual educational tool to teach data science to high school students. The first activity introduces the visual analytic pipeline. The next interactive activities present machine learning classification and regression topics. We select datasets and applications which are relatable to our main audience. This paper describes the design and implementation of the data science educational tool for high school students. CCS CONCEPTS • Applied computing → Interactive learning environments.

AI literacy in K-12: a systematic literature review

“…It is therefore an approach focused on learning by using AI-oriented tools. In this vein, different experiences have focused on learning programming tools for applications based on Machine Learning (Reyes et al, 2020;Toivonen et al, 2020;von Wangenheim et al, 2021;Wan et al, 2020), robotics (Chen et al, 2017;Eguchi, 2021;Eguchi & Okada, 2020;Holowka, 2020;Narahara & Kobayashi, 2018;Nurbekova et al, 2018;Verner et al, 2021), programming and the creation of applications (Chittora & Baynes, 2020;Giannakos et al, 2020;Kahn et al, 2018;Kelly et al, 2008;Park et al, 2021). Some of these tools use Scratch-based coding platforms to make AI-based programming attractive to children.…”

“…Hence, it is crucial to incorporate AI teaching from the earliest stages of education (Heintz, 2021). However, although some countries are making significant efforts to promote AI teaching in K-12 (Touretzky et al, 2019a), this is being implemented through highly varied AI training experiences, such as data-driven design (Vartiainen et al, 2021), interactive data visualizations (Chittora & Baynes, 2020;von Wangenheim et al, 2021), virtual reality and robotics (Narahara & Kobayashi, 2018), games (Giannakos et al, 2020), or even based on combined workshop series (Lee et al, 2021). To date, there are very few methodological proposals on how to introduce the AI curriculum in K-12 education (Lee et al, 2020).…”

A New Chapter is Being Written About Writing Instruction: Instructional Leadership at K-12 Levels in The Age of Artificial Intelligence (AI)

“…These endeavor of integration appear in different forms at the K-12 level. For example, while it is used in the process of data-driven design in some countries (Chittora & Baynes, 2020;Vartiainen et al, 2020), in some others it is deployed in areas such as virtual reality, robotic coding and engineering processes (Narahara & Kobayashi, 2018). Nevertheless, steps of concrete sort have not yet been taken regarding the inclusion of artificial intelligence applications in the curricula (Lee et al, 2020).…”