GenAI-powered Agentic Platforms promise to foster productivity in Universities. Being used for academic (e.g. Tutors) or administrative (e.g. Chatbots) support, the potential is huge. Some Latin American universities have started the creation of these platforms using available platforms and models. In this panel, we will present the experience of three universities, members of the AI Global Education Network (AIGEN), in creating these agents.
Panelists:
Moderator: José Escamilla / Héctor G. Ceballos, Tecnológico de Monterrey, México
One of the key problems in Higher Education is Student Dropout. The reasons for dropout are complex and diverse, and it has resulted in the need of specific interventions for each situation. For these interventions to be successful, institutions have put in place academic support programs based on proper criteria of in-risk of dropout students. Although AI-based predictive models could help to identify those students at risk of dropout, the staff that will use these tools may face limitations. This panel showcases the strategies followed by three Latin American Universities to support in-risk students and how they plan to incorporate AI to this aim.
Panelists:
The purpose of this panel is to share strategies developed by higher education institutions to guide, regulate, and support the educational use of Generative AI (GenAI). Through policies, guidelines, training activities, and systematization processes, the panel seeks to promote a critical, ethical, and pedagogical appropriation of this emerging technology in the university setting. Institutional experiences that have specific criteria and recommendations for integrating GenAI in four key dimensions of academic practice will be analyzed: teaching, learning, assessment, and educational management.
Panelists:
Moderator: Héctor G. Ceballos, Tecnológico de Monterrey, México
This meta-analysis aims to synthesize the empirical evidence on the effectiveness of AI chatbots in educational settings, focusing on their impact on cognitive and affective outcomes. By systematically comparing findings across diverse learning environments and learner populations, this study seeks to identify key factors that moderate the effectiveness of AI-powered chatbots.
Panelists:
Moderator: Rob Moore
How genai is changing (could change, might change, will change) the tools we have for teaching and learning
Panelists:
Moderator: Chris Brooks
The use of Large Language Models (LLMs) has demonstrated clear performance gains for students. Yet performance is only part of the story. Scholars caution that polished outputs may come at the expense of genuine learning, as students risk offloading critical thinking and problem-solving to AI. This panel explores how we can move beyond productivity to design AI learning companions that prioritise learning gains over performance gains, nurturing curiosity, understanding, and deeper engagement.
Moderator: Hassan Khosravi
Feedback is one of the most powerful drivers of student learning, yet it is often delayed, inconsistent, or inaccessible at scale. While AI can generate instant responses, concerns remain about accuracy, trust, and the loss of the human dimension. This panel explores how human–AI teams can combine complementary expertise—AI’s scalability and speed with human empathy and contextual judgement—to reinvent the feedback loop and provide guidance that is timely, personalised, and transformative.
Moderator: Hassan Khosravi
The rise of generative AI is reshaping what, how, and why we assess. This panel will explore how educational assessment can evolve to support responsible learning while upholding academic integrity in AI-mediated environments. Panelists will examine how assessment systems can move beyond traditional formats to embrace more continuous, authentic, and future-ready approaches. Drawing on current research and practical examples, the discussion will consider how assessment can foster deeper learning, evaluate emerging competencies, and support both individual growth and institutional accountability. The panel brings together diverse perspectives to reimagine assessment that is both effective and ethically grounded in the age of AI.
Panelists:
Moderator: Jason Lodge, Professor of Educational Psychology, and Director of the Learning, Instruction, and Technology Lab, School of Education, The University of Queensland, Australia
What does it mean to be future-ready in an age of human–AI interactions? This panel brings together leading researchers in learning sciences, educational psychology, and AI in education to explore the skills and competencies learners need to navigate increasingly AI-mediated learning environments. The discussion will draw on current research on social and self-regulated learning (SSRL), hybrid human–AI regulation, and digital competence, and consider the implications for learning, teaching, technology design, and policy. With diverse disciplinary and geographic perspectives, the panel will offer critical insights for shaping equitable and effective futures for learners, educators, and developers alike.
Panelists:
Moderator: Dragan Gašević, Distinguished Professor and Director of the Centre for Learning Analytics, Faculty of Information Technology, Monash University, Australia
This panel will explore the new skill sets required in AI-infused workplaces. It will discuss how to balance traditional core skills (critical thinking, communication, collaboration) with AI-enabled competencies (prompt engineering, AI-assisted decision making, human-AI collaboration). The discussion will highlight how education and training can prepare learners to be competitive and adaptable in the future workforce.
Panelists:
Moderator: Mixue Li, Tsinghua University, China
This panel will address the pathways from measuring AI literacy to cultivating it in practice. The first part will focus on rigorous and systematic approaches to measuring AI literacy (tools, frameworks, assessment practices). The second part will examine how to translate measurement into effective cultivation, including curriculum design, interdisciplinary integration, and policy support, aiming to position AI literacy as a core competence for all learners.
Panelists:
Moderator: Lixiang Yan, Tsinghua University, China
Student–AI interaction extends beyond asking questions or receiving feedback; students can also become co-creators, collaborating with AI to explore ideas and shape their learning pathways. This panel will discuss how such interactions foster creativity, agency, and deeper engagement, and how they can be captured and modeled — from conversational traces to multimodal data — to better support meaningful educational experiences.
Panelists:
Moderator: Wanruo Shi, Tsinghua University, China
Intelligent augmentation is a concept that describes the synergistic relationship between humans and intelligent technologies, to empower individuals to work more efficiently and effectively by leveraging the capabilities of AI and other technologies. This symposium will explore the what, how, and why behind intelligent augmentation, providing insights into its potential applications, methods of implementation, and underlying motivations.
Panelists:
Moderator: Elizabeth Koh, Senior Educational Research Scientist, National Institute of Education, Nanyang Technological University, Singapore
Recent advances in AI have heightened attention to “human skills” such as communication, collaboration, and critical thinking. Despite their recognized importance in our everyday lives, education systems often lack valid and reliable approaches for assessing, strengthening, and maintaining these context-dependent competencies. This panel brings together perspectives from cognitive psychology, data science, and clinical science to consider how variability—across learners, settings, and interactions—should be considered as a valuable feature rather than treated as noise. Panelists will consider theoretical and methodological considerations for embracing such variability, layering personalization, and designing responsive infrastructures can transform how durable human skills are assessed and developed.
Panelists:
Moderator: Caitlin Mills, University of Minnesota
Coding agents are good at writing code; pedagogical agents are good at shaping learning. In this session, we bridge the two. Panelists will demonstrate, live, how to turn general‑purpose coding agents (Claude Code; Gemini Code Assist) into pedagogical micro‑apps grounded in learning science—worked examples, self‑explanation, and faded scaffolds—while instrumenting learning events (xAPI/Caliper) and applying safety/privacy guardrails (FERPA/GDPR; provider safety filters). Attendees will see two 15‑minute builds (web micro‑tutor; Socratic debugging coach), a concise evidence primer on pedagogical agents and intelligent tutoring systems, and a rubric to judge instructional quality. You will leave with prompts, code skeletons, and an evaluation checklist to adapt in your course or product. No prior ML background required; basic web/IDE familiarity helpful.
Moderator: Xiangen Hu
Recent findings indicate a growing trend among educators to harness generative AI for the creation of curriculum and instructional materials. However, there is a notable absence of empirical studies examining the accuracy and reliability of the content produced by generative AI. Moreover, the need for adaptive content that can cater to diverse learner profiles remains underexplored. This panel will discuss the implications of implementing a computed curriculum in the context of generative AI, discussing methodologies for content validation and exploring strategies for scaling a dynamic, responsive curriculum that meets individual learner needs effectively.
Panelists:
Moderator: Dr Abhinava Barthakur, University of South Australia
Panellists will explore how AI is transforming learning environments, and supporting engagement while also addressing the psychological dimensions of student wellbeing. The discussion extends beyond the classroom to consider the benefits of sport and physical activity for resilience and balance. Combining insights from education, psychology, and lifestyle, the panel highlights opportunities and challenges for universities seeking to integrate technology and wellbeing, offering pathways towards healthier, more sustainable student experiences in an AI-driven world.
Panelist:
Moderator: Rebecca Marrone
This session will walk attendees through the process of using AI tools to create apps, resources, and tools that have previously been inaccessible. Practical examples and vibe coding tools will be introduced and demoed.
Moderator: Aaron Cavano
This informative panel will explore how early-career researchers are leveraging artificial intelligence in their work. The discussion will centre on key challenges, including data privacy concerns, ethical considerations, and the necessity for interdisciplinary collaborations. Additionally, it will highlight the opportunities that arise for these researchers as they incorporate AI into their projects, providing insights into innovative practices and future directions.
Panelists:
Moderators: Abhinava Barthakur, University of South Australia, Rebecca Marrone, University of South Australia
We will talk about Regulatory, contextual, and technological perspectives on learner privacy
Keywords: Learner privacy, AI Act, context, informed consent, socio-technical solutions for privacy concerns
Panelists:
Moderator: Oleksandra Poquet, TUM, Munich