The symposium aims to facilitate discussions on the current state of AI in education research and implementation in Germany, while also highlighting key issues, challenges, and directions for future developments. It is organized by the CAIS-Research Program Educational Technologies and Artificial Intelligence lead by Prof. Nikol Rummel.
Keynotes
Inge Molenaar (Radboud University, NL): Towards hybrid human-AI learning technologies
There are multiple scenarios in which artificial intelligence (AI) could improve teaching and learning. In this talk, the augmentation perspective and the concept of hybrid intelligence are introduced to frame our thinking about AI in education. The involvement of different stakeholders (i.e., researchers, education professionals, entrepreneurs, and policymakers) is necessary to understand the opportunities and challenges of AI in education. In order to facilitate a meaningful dialogue, a common language about AI in education is introduced. The six levels of automation model develop our thinking about the roles of AI, learners, and teachers. In this model, the transition of control between teacher and technology is articulated at different levels which are illustrated with different examples. Next the detect-diagnose-act framework is used to describe the core functions of AI in education and to discuss the future of AI in education with different inspiring innovative cases. This talk will elaborate on Hybrid Human-AI learning technologies that augment human intelligence with artificial intelligence to empower learners and teachers in their quest to make education more efficient, effective and responsive.
Vincent Aleven (Carnegie Mellon University, US): Harnessing human-AI synergy in the smart classroom: What works, new opportunities
What should the smart, AI-supported, classroom look like? We should of course continue to use AI in ways that have proven to be effective, such as in supporting deliberate practice with AI-based tutoring software. Yet even with the expanding use of AI-based tutoring systems, difficult and enduring challenges in the educational system remain, such as large opportunity gaps between different population segments. To create a smarter classroom, it will help to redesign the role of humans and AI in the educational system, enhancing both, in a way that is maximally synergistic. AI could support more humans in a wider range of roles as they facilitate learning: students, teachers, tutors, and parents could all, with the help of AI, assist students. Some of these forms of AI-based support have been shown to be successful in research studies and are beginning to transition into educational practice. Other forms are just beginning to be addressed by researchers. Human-centered design will be key to harnessing human-AI synergy. I will illustrate progress and opportunities with examples from my own, and others’ research.
Wayne Holmes (University College London, UK): The Ethics of Artificial Intelligence and Education. A critical studies approach.
Artificial Intelligence (AI) is frequently hailed as a ‘solution’ to many of education’s core problems (e.g., OECD, 2021) – problems such as student underachievement, assessment at scale, and better preparing learners for 21st century career paths. However, such claims tend to be aspirational rather than evidence-based (Miao & Holmes, 2021), and overly simplistic, forgetting issues such as agency, pedagogy, surveillance, efficacy, and ethics (Holmes et al., 2021; Holmes et al., 2022; Holmes & Porayska-Pomsta, 2022; Porayska-Pomsta, Holmes and Nemorin, 2023). In fact, current applications of AI in Higher Education tend to be solutions- rather than problems-oriented, and all too often undermine student agency and disempower educators; while the teaching of AI almost always focuses on the technological dimension of AI to the exclusion of the human dimension (its ethical, human, and social justice implications). Accordingly, this presentation will explore the application and teaching of Artificial Intelligence in education from a critical studies and human rights perspective. It will identify and address many of the key myths, it will argue for an ethics by design approach, and it will pose more questions about AI and the futures of learning than it answers.
Panels
Invited panel speakers will engage in a comprehensive discussion on the critical questions surrounding the research and design of AI systems for learning, while also delving into the broader contexts of preparing for and regulating the implementation of AI-based tools in education.
Challenges of using AI in education
When considering the integration of “intelligent” systems into educational settings, it is imperative to thoroughly address the ethical and regulatory challenges associated with their implementation. In this panel, we will discuss the following questions: What are the potential risks and implications that arise from utilizing these systems? Who are the various stakeholders involved in the implementation process? Besides incorporating their interests, how can we ensure a holistic and inclusive approach to integrating AI for learning? Finally, how can we examine and determine the potential societal implications that may emerge from the widespread adoption of AI in education?
Design and evaluation of AI systems for education
Understanding the current research practices in designing “intelligent” systems for educational settings is key to their effective implementation. In this panel discussion, we will explore the learning goals for which these systems can be employed and identify the variables that may be influenced by their implementation. Moreover, we will discuss various dimensions that are important when assessing the effectiveness of these systems ensuring a comprehensive evaluation.
Empowering Educators to harness the power of “intelligent tools”
In this panel discussion, our primary focus is to gain valuable insights into the perspectives of educators from diverse learning settings. We explore the essential requirements for equipping teachers and lecturers for successful AI integration while catering to their specific needs. We shed light on the crucial competencies that educators must possess to effectively utilize “intelligent” tools and address the critical issue of bridging the gap between evidence-centered design and the practical implementation of AI in education.