Andrew Petersen

University of Toronto

The emerging capabilities of Large Language Models (LLMs) have forced computing and data systems educators to reexamine fundamental aspects of our pedagogy to address the challenges raised by these technologies. However, LLMs also provide opportunities to improve already evidenced pedagogical techniques and approaches. In particular, they allow us to address the challenge of providing rapid feedback and other personalized interactions at scale.

This talk presents current research projects being undertaken at the University of Toronto’s Computer Science Education Research Group. Each of these projects focuses on utilizing LLMs to help with adoption and scaling of existing, effective pedagogical approaches. They support students as they prepare for class meetings (using voice explanations), solve exercises (using hints), and prepare for assignments and tests (using conversational agents and discussion board platforms). In all these projects, the student voice – their experiences and challenges – are at the foreground and drive a focus on inclusion and sustainability.

These projects contribute to a broader vision of education that emphasizes meeting each learner where they are. Our focus is on rapidly closing feedback loops, efficiently offering tailored feedback and support, and respecting the distinct needs and concerns of our students. This approach is not just about enhancing the learning experience through technology, but also about integrating responsible AI use and sustainable educational practices to create a more effective and inclusive learning environment.

Stephanie Scherzinger

University of Passau

Inspired by the familiar visualization of dental plaque during a dental checkup, this article introduces an innovative approach to visualize redundancies in relational data. Grounded in a robust information-theoretic framework that has remained underutilized in practical applications, we present fresh ideas for integrating these visualizations into the teaching and learning of database schema normalization. Through practical demonstrations using common textbook examples, we illustrate the potential of our visualization technique and invite the audience to engage in a collaborative discussion. Our aim is to empower both educators and students with a fresh perspective on schema normalization.

Esther Ventura-Medina

Eindhoven University of Technology

Current and future global societal challenges place a great demand on the education of the future engineers. Engineering graduates are not only required to have a good command of technical disciplinary knowledge but also be able to work with people from a wide range of backgrounds and integrate knowledge from different domains in fit-for-purpose socio-technical solutions. In addition, given the fast pace of technological development future engineers need to be able to deal with uncertainty, be resilient and adaptable.

Developing a wide set of skills in future engineers places a significant challenge in educational systems and demands the use of innovative approaches to education that while grounded on our understanding of how people learn allows to develop further educational practice. A great deal in the process of developing educational innovation relies on data gathered within educational ecosystems through educational research.

Drawing from previous research and classroom experiences in using student-centred pedagogies such as Problem-, Project- and Online Scenario-based learning we will discuss some of the key challenges about understanding learning from a data driven perspective. In particular, we will focus on aspects of collaboration, cooperation, decision-making and regulation of learning that support group processes. We will consider how we could leverage learning analytics and data-driven models and systems, such as machine learning and artificial intelligence, to support student-centred approaches. Finally, we will discuss the importance and challenges around data that supports the development of innovative educational practices that allow us to create an agile, adaptable and sustainable educational ecosystem.

Sourav Bhowmick

Nanyang Technological University

Looking to the past is often a good way to see the future. Leonardo Da Vinci (1452-1519) integrated art with science, engineering with human values. If he was alive today, how he would have designed and taught a database systems course? Would his integrative spirit empowered learners to a more satisfying learning experience? In this talk, we take a hypothetical journey by taking Leonardo as an inspirational muse to envision a richer, integrative, and potentially more satisfying learning environment for database systems.