Research seminars

6 October (7–8:30 pm BST): Eleni Petraki and Damith Herath (University of Canberra)

Advancing robotics education: directions for school and tertiary contexts

Robotics has long fascinated researchers and learners alike, and its significance has grown exponentially with the rise of artificial intelligence and automation in everyday life. This webinar explores the evolution of robotics education within STEAM disciplines, highlighting historical developments and current innovations that address the field’s multidisciplinary nature. While historically fields such as Artificial Intelligence, computer science and robotics were distinct disciplines, research is pointing to pedagogical approaches for integrated STEAM pedagogies. Drawing on the research within the first truly interdisciplinary textbooks (Herath and St-Onge, 2022), we illustrate the redesign of an engineering and robotics curriculum from an Australian tertiary course aimed at equipping future engineers with the diverse skills demanded by a growing workforce. The session concludes with evidence-based recommendations for best practices in robotics pedagogy, emphasising theory-driven methods and interdisciplinary learning approaches.

Eleni Petraki is an Associate Professor in Curriculum Design and Human–AI Education in the Faculty of Education at the University of Canberra. She has over 26 years of experience in language teaching and teacher education, spanning curriculum design, educational research, and applied linguistics. Eleni was a Chief Investigator and recipient of an ARC Discovery National Competitive Grant (2020–2025) in the field of machine education and artificial intelligence. Her research focuses on curriculum design, education for human–AI collaboration, artificial intelligence in education, and interaction analysis and communication.

Damith Herath is a Professor of Robotics and Art at the University of Canberra and leads the Collaborative Robotics Lab, a multidisciplinary research team with strong industry partnerships. An award-winning entrepreneur and a roboticist, Professor Herath has over two decades of experience leading complex robotic integration projects. In 2011, he founded Australia's first collaborative robotics startup, which was recognised as one of Australia's most innovative young tech companies in 2014. Professor Herath has also chaired several international workshops on Robots and Art and is the lead editor of the seminal book "Robots and Art: Exploring an Unlikely Symbiosis," a significant contribution to the field featuring leading roboticists and artists.

8 December: Fred Martin, Deepti Tagare, Lucretia M. Fraga, Lijun Ni, Lin Zhu, Ismaila Temitayo Sanusi, Hailey Muñiz, Varsha Yerram, and Diane Schilder

From tool users to model builders: Integrating student learning of AI into interdisciplinary middle school inquiry

We present the design and study of a researcher-practitioner partnership (RPP) with two school districts — one in Texas and one in New York — where we work directly with middle school teachers to build foundational artificial intelligence (AI) fluency. We introduced 18 educators in science, maths, English language arts, and social studies to foundational concepts in AI and invited them to invent ways of bringing AI concepts to their students while deepening their required content-area teaching.

In a series of four Zoom online workshops, we introduced teachers to hands-on platforms, including Machine Learning for Kids and Google Teachable Machine. Teachers did mini-projects with these tools and then developed an AI-infused lesson that they brought to their students.

We’ll share findings from the project, including teachers’ innovative activities and our larger insights. Examples of teacher projects include a language-arts ‘Genre DNA’ project where students discovered that AI was easily fooled by typical terms used in literary genres; an image-based classification project in science that revealed model bias; and an AI ethics-focused Model UN simulation exploring the civic implications of algorithmic governance.

Finally, implications for scalable, equitable, and interdisciplinary approaches to AI education will be highlighted, emphasising the move from treating AI as a ‘magic box’ to an object of student critique.

Fred Martin is Professor and Chair of Computer Science at the University of Texas at San Antonio. Over his 30+ year career he has developed constructionist materials for children and teachers on topics such as robotics, data science, computing, and now AI education. 

Deepti Tagare is Assistant Professor in Learning Design and Technology at the University of Texas at San Antonio. She has a joint appointment in the Department of Computer Science. Her research focuses on preparing educators in K–12 and higher education for teaching computational thinking skills, and for providing AI literacy education and AI-integrated education.

Lucretia M. Fraga is a Professor of Instructional Technology at the University of the Incarnate Word, specialising in educator preparation, instructional design, and AI integration. With more than 30 years across K–12 and higher education, her scholarship and leadership focus on professional development, educator AI fluency, ethical implementation, and research-practice partnerships.

Lijun Ni is an Associate Professor of Computing Education at the University at Albany, State University of New York. Her research focuses on K–12 computer science education, teacher preparation and professional learning communities, AI and computational thinking, and broadening participation in STEM.

Lin Zhu is a PhD student at the University at Albany, SUNY, specialising in learning sciences and technology. Her research focuses on human interaction with emerging technologies, with her interests including digital game-based learning, AI education, and teacher preparation and professional learning.

Ismaila Temitayo Sanusi is with the University of Texas at San Antonio and specialises in computer science education research, including democratising AI and machine learning (ML) for young learners and novices.

Hailey Muñiz is a computer science undergraduate researcher at the University of Texas at San Antonio. Her research focuses on gamified and code-based AI education.

Varsha Yerram is a computer science undergraduate research assistant at the University at Albany, SUNY, minoring in cybersecurity. Her research focuses on K–12 AI education, AI tool design, and teacher preparation.

Diane Schilder is an evaluation consultant who has served as principal investigator and principal evaluator for computer science initiatives for nearly three decades. She leads formative and summative evaluations of STEM interventions, including AI education for the National Science Foundation and the US Department of Education, as well as for state agencies, universities, and school districts.