The World is Flat: A Brief History of the Twenty-First Century

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Understanding By Design

Artificial intelligence (AI) is becoming increasingly integrated in user-facing technology, but public understanding of these technologies is often limited. There is a need for additional HCI research investigating a) what competencies users need in order to effectively interact with and critically evaluate AI and b) how to design learner-centered AI technologies that foster increased user understanding of AI. This paper takes a step towards realizing both of these goals by providing a concrete definition of AI literacy based on existing research. We synthesize a variety of interdisciplinary literature into a set of core competencies of AI literacy and suggest several design considerations to support AI developers and educators in creating learner-centered AI. These competencies and design considerations are organized in a conceptual framework thematically derived from the literature. This paper's contributions can be used to start a conversation about and guide future research on AI literacy within the HCI community.

What is AI Literacy? Competencies and Design Considerations

In this paper we have examined the position and roles of Computer Science in curricula in the light of recent calls for curriculum change and we have proposed principles and issues to consider in curriculum design as well as identifying priority areas for further research. The paper is based on discussions within and beyond the International Federation of Information Processing (IFIP) Education Community since 2012 as well as an analysis of curriculum developments in five different countries. Emerging themes have been discussed with reference to important perspectives from curriculum theory including "powerful knowledge" as a key element of entitlement and management of the growth of expertise. Based on this analysis we have identified areas of consensus as well as constraints, risks and issues that are still subject to controversy. There is an emerging consensus of the importance of Computer Science and the nature of its "powerful knowledge". Furthermore current understanding of the opportunities and benefits for starting to learn Computer Science early in primary schools has identified this early start as an entitlement and equity issue. There is a strong consensus that teacher professional development in Computer Science Education is critical for supporting curriculum change and is currently a major challenge in many countries. Other key issues include understanding how the growth of expertise affects potential structure and sequencing in the curriculum and the balance of content. Further considerations include how new technological opportunities interact with pedagogical approaches and can provide new potential for the growth of expertise.

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Computer science in K-12 school curricula of the 2lst century: Why, what and when?

In two special issues of the ACM journal "Transactions on Computing Education" (TOCE), 14 extensive case studies about the various situations of Computer Science Education (CSE) in K-12 schools in 12 countries (respectively states) were collected. During the work at the ITiCSE 2015, we have performed a deductive qualitative text analysis on these case studies in order to extract the most useful information. As a category system, we applied some selected categories of the Darmstadt Model that was developed by the working group "Computer Science/Informatics in Secondary Schools" at the ITiCSE 2011. Based on the coding results, we summarized information about the different fields of Computing Education at schools, the intended goals and competencies, the taught content, the applied programming languages and tools and the different forms of assessment and teacher education. Despite the limitations of the analyzed articles, representing just snapshots of complex situations from the specific viewpoint of the respective authors, we were able to collect some interesting results.

https://www.ddi.edu.tum.de/fileadmin/tueds10/www/Publikationen/2015/2015-Hubwieser-et-al-ITiCSEWG3-Report.pdf

A Global Snapshot of Computer Science Education in K-12 Schools

The ubiquity of AI in society means the time is ripe to consider what educated 21st century digital citizens should know about this subject. In May 2018, the Association for the Advancement of Artificial Intelligence (AAAI) and the Computer Science Teachers Association (CSTA) formed a joint working group to develop national guidelines for teaching AI to K-12 students. Inspired by CSTA's national standards for K-12 computing education, the AI for K-12 guidelines will define what students in each grade band should know about artificial intelligence, machine learning, and robotics. The AI for K-12 working group is also creating an online resource directory where teachers can find AI- related videos, demos, software, and activity descriptions they can incorporate into their lesson plans. This blue sky talk invites the AI research community to reflect on the big ideas in AI that every K-12 student should know, and how we should communicate with the public about advances in AI and their future impact on society. It is a call to action for more AI researchers to become AI educators, creating resources that help teachers and students understand our work.

/pdf/envisioning-ai-for-k-12-what-should-every-child-know-about-1wpcgp0ze2.pdf

Envisioning AI for K-12: What Should Every Child Know about AI?

ion Understand the notion of hierarchy and abstraction in computing including highlevel languages, translation, instruction sets, and logic circuits. Discuss the value of abstraction to manage problem complexity. Describe the concept of synchronization as an algorithm to divide and conquer large problems. Connections to other fields Examine connections between elements of mathematics and computer science including binary numbers, logic, sets, and functions. Describe how mathematical and statistical functions, sets, and logic are used in computation. Use abstraction to decompose a problem into sub-problems. Decompose a problem by defining new functions and classes. Demonstrate concurrency by separating processes into threads and dividing data into parallel streams. Provide examples of interdisciplinary applications of computational thinking. Describe how computation shares features with art and music by translating human intention into an artifact. Understand the connections between other fields and computer science. Participate in a simulation to act out the solution to a local issue. Make a list of issues to consider while addressing a larger problem. Level 1A Level 1B Level 2 Level 3A Level 3B Computational Thinking

CSTA K--12 Computer Science Standards: Revised 2011

The time is ripe to consider what 21st-century digital citizens should know about artificial intelligence (AI). Efforts are under way in the USA, China, and many other countries to promote AI education in kindergarten through high school (K–12). The past year has seen the release of new curricula and online resources for the K–12 audience, and new professional development opportunities for K–12 teachers to learn the basics of AI. This column surveys the current state of K–12 AI education and introduces the work of the AI4K12 Initiative, which is developing national guidelines for AI education in the USA.
 
A Note to the Reader
This is the inaugural column on AI education. It aims to inform the AAAI community of current and future developments in AI education. We hope that the reader finds the columns to be informative and that they stimulate debate. It is our fond hope that this and subsequent columns inspire the reader to get involved in the broad field of AI education, by volunteering their expertise in their local school district, by providing level-headed input when discussing AI with family and friends or by lending their considerable expertise to various decision makers. We welcome your feedback, whether in the form of a response to an article or a suggestion for a future article. 
– Michael Wollowski, AI in Education Column Editor

A Year in K-12 AI Education

In May 2018, the Association for the Advancement of Artificial Intelligence (AAAI) and the Computer Science Teachers Association (CSTA) formed a joint working group to develop national guidelines for teaching K-12 students about artificial intelligence. Inspired by CSTA's national standards for K-12 computing education, the - AI for K-12 guidelines (ai4k12.org) will define what students in each grade band should know about artificial intelligence, machine learning, and robotics. The working group is also creating an online resource directory where teachers can find AI-related videos, demo software, and activity descriptions they can incorporate into their lesson plans. The goal of this session is to raise the SIGCSE community's awareness of the initiative, its deliverables, and outcomes, and to foster a community-wide conversation about AI education in K-12. This initiative parallels other recent initiatives in K-12 AI education and community-wide initiatives and discussions around CS For All and CS in K-12. This Special Session is aimed toward K-12 CS educators, researchers, and curriculum and tool designers.

Special Session: AI for K-12 Guidelines Initiative

As CS expands into more K-12 classrooms and children become familiar with computational thinking, advances in AI pose new challenges for CS educators. Children now enjoy conversing with AI-powered agents such as Alexa and Siri, while their parents worry about the imminent arrival of autonomous robots and self-driving cars. As AI technologies become more prominent in our lives, we need to consider what every child should know about AI. This BOF provides a timely opportunity to introduce CS educators and researchers to several AI for K-12 efforts, including available curricula, tools, and resources. Attendees will discuss how AI can best be incorporated into the K-12 CS curriculum, the tools/resources that will be needed to support students and teachers learning about AI, and how AI education might impact their own work. This BOF is complementary to the SIGCSE 2019 Special Session: AI for K-12 Guidelines Initiative that introduces the current draft of our 'Big Ideas in AI." Further information about the initiative and resources is available at http://ai4k12.org.

Deborah Seehorn

Papers

Envisioning AI for K-12: What Should Every Child Know about AI?

CSTA K--12 Computer Science Standards: Revised 2011

A Year in K-12 AI Education

Special Session: AI for K-12 Guidelines Initiative

AI for K-12: Making Room for AI in K-12 CS Curricula