Keynote 1, Monday, October 23, 20023
09:15, room B21-308
Computing Across the Curriculum: CS Knowledge and Skills that Everyone Values
This talk will explore how computing can be used to support teaching and learning across the curriculum, especially in non-computer-science classes. It will focus on identifying computing concepts that are most relevant in non-computer-science domains and, thus, most useful across the curriculum and important for general computational literacy. To identify relevant concepts and provide examples of computing across the curriculum, the talk will first explore five years of work at Georgia State University to co-design integrated computing activities with non-computer-science teacher education faculty and prepare future teachers to use the activities.
To complement this qualitative, design-based approach, the talk will also present quantitative, summative analyses of computing concepts that are taught in integrated computing activities. Activities and curricula were collected from around the globe to examine how programming and other computing concepts and practices are used for activities in non-computer-science classrooms. The talk will focus on the emergent paradigms for integrated computing activities, common computing concepts already used, opportunities for expanding computing tools, and how well these activities prepare students for later, standalone computing and programming courses.
Based on these analyses, recommendations for teacher preparation and integrated computing activities in primary and secondary schools will be made. In addition, lessons learned about strategies for increasing teacher buy-in and coherence with current education practices will be discussed. The goal of the talk is both to improve current practice based on emerging data about integrated computing activities and to identify areas of opportunities for growth related to teachers’ and students’ computer science knowledge and skills to better support teaching, learning, and computational literacy.
Lauren Margulieux is an associate professor at Georgia State University in the Department of Learning Sciences. She am passionate about helping others to develop skills and pursue opportunities. In particular, she focuses on spreading computational literacy and the use of computing to achieve personal and professional goals.
Keynote 2, Tuesday, October 24, 2023
09:00, room B21-308
Teaching AI in K-12: Examples, Issues & Guidance from K-12 CS Education Research
There is growing recognition of the need to teach about artificial intelligence and machine learning (AI/ML) at the school level in light of the meteoric growth in the range and diversity of application of machine learning (ML) in all industries and everyday consumer products, with Large Language Models (LLMs) being only the latest and most compelling example yet! Efforts to bring AI, especially ML education to school learners are being propelled by substantial industry interest and efforts such as AI4K12, as well as technological developments that make AI tools readily available to learners of all ages. These efforts span a variety of learning goals as well as pedagogies ranging from exploratory, playful interactions with pre-trained AI models, the extension of K-12 introductory CS activities to include AI tools such as classifiers, integration of AI into other subjects, activities that lift the hood on how AI works, critical examination of ethical and societal issues that are exacerbated by bias in algorithms, and unplugged activities that make complex AI/ML ideas accessible to younger learners. What are the emerging lessons from early AI education research efforts? What challenges and issues do K-12 curriculum designers need to address in designing for teaching AI in K-12? How should teachers be prepared to teach this novel subject? What are key lessons from K-12 CS research and practice efforts that can provide guidance on how to purposefully address the pertinent, topical question of how to teach AI in school and tackle what to many feels like “the next new thing”.
In this keynote address, Shuchi Grover will share examples from the field as well as her own research into designing for AI learning in high schools—designing AI/ML curricular modules that focus on socially relevant applications, and integrating AI learning into high school cybersecurity curricula. She will also draw on her deep expertise developed over 15 years in K-12 CS education research to highlight key learnings from two decades of CS education research and practice that can help build on successes while mitigating missteps in K-12 AI Education.
Shuchi Grover is a computer scientist and learning scientist by training. She has been committed to PK-12 computer science education in formal and informal settings for over two decades. Formerly a senior researcher at SRI International’s Center for Technology in Learning and Visiting Scholar at Stanford University, she is currently senior research scientist at Looking Glass Ventures where she leads several NSF-funded projects involving research \& design of curriculum, assessments, tools, and environments that help develop 21st century competencies in topics such a computing, STEM+CS integration, data science, AI, and cybersecurity as well as issues of neuro-diversity, gender equity, and teacher preparation. She created, co-authored and edited Computer Science in K-12: A-to-Z Handbook on Teaching Programming.
Shuchi has a Ph.D. in Learning Sciences \& Technology Design with a focus on K-12 CS Education (Stanford University), master’s degrees in education (Harvard University) and computer science (CWRU, Cleveland), and bachelor’s degrees in computer science and physics (BITS Pilani, India).
Keynote 3, Wednesday, October 25, 2023
09:00, room B21-308
Informatics in Schools and Everyday Life
Because of the short-term usability of product specific skills, we have to focus on conceptual knowledge to guarantee useful long-lasting educational benefits for pupils and teachers as well. Examples for long-term concepts include topics like “notions and notations”, “information, codes and redundancy”, “significance and plausibility”, “modelling and abstraction”, “formalized systems”, “determinism versus chaos”, “orders of magnitude”, and “algorithmic complexity”.
These concepts are illustrated by everyday life situations like “optimizing” the loading of a dish-washer or the order of cookies on a baking tray, “stacks and queues” in supermarkets, “strategies” to solve a puzzle, advantages of “simulating” weightings with a beam balance or the “digitalization” of human characteristics. The use of computers obviously constructs realities with all the benefits and drawbacks. Let the wisdom gathered from the fruits of the “tree of knowledge” lead us to ensure a desirable living for us and our successors.
Helmut Schauer was a full professor at the Department of Informatics of the University of Zurich. He was the head of the Educational Engineering Research Group. His research interests include web-based and game-based learning, assessments beyond multiple choice, collaborative learning environments, object-oriented programming in Java and visualization of algorithms and data structures.
He has contributed to numerous discussions on curriculum issues at various levels of education. His special interest focuses on curriculum and didactic of informatics in secondary school levels. He is a past president of the Swiss Informatics Society SI and a board member of ECDL-SI, which oversees the operations of the ECDL Program in Switzerland.