Keynote and plenary lectures

Abstract: Mathematical modelling education has a long tradition in many parts of the world. However, discussions about the primacy of real-world context or mathematics have shaped it since its very beginning, dating back to the 19th century.

Based on these central paradigmatic differences, Kaiser-Messmer (1986) distinguished two main perspectives in the discourse: A pragmatic perspective, which focuses on utilitarian or pragmatic goals, and a scientific-humanistic perspective, which is oriented towards humanistic ideals of education.

Kaiser and Sriraman (2006) synthesized international research to further differentiate this distinction into a typology of international perspectives on modelling in mathematics education, providing an overview of the convoluted debate. Based on a classification of the different aims of mathematical modelling education and their epistemological background, five perspectives and a meta-perspective were distinguished. The original distinction between the two opposing positions was taken up and further developed as realistic or applied modelling and epistemological or theoretical modelling. Further perspectives were introduced, including educational modelling, contextual modelling, socio-critical modelling and, as a meta-perspective, cognitive modelling.

Blum (2015) further developed these perspectives by conceptualizing them as a pair of aims and suitable examples, and by proposing six different perspectives.

The influence and usage of these two typologies have been evaluated in a systematic literature review by Krawitz et al. (2025), continuing the work of Preciado Babb et al. (2023).

Following such extensive developments, questions arise regarding the future directions of mathematical modelling education and related research. It seems to be timely to ask whether all the perspectives distinguished in these two typologies are still vivid or have been further developed, or whether new perspectives have emerged. Evaluating the current discourse in ICTMA proceedings and important journal papers reveals that new topics have been proposed or have gained more relevance, such as the metacognitive skills of students and teachers, and creativity and curiosity in mathematical modelling education. New perspectives have emerged, such as ethnomodelling, which emphasizes the important role of culture and cultural sensitivity. Meanwhile, the importance of other approaches, such as mathematical literacy and critical thinking, has increased.

Following a description of the discourse, the talk will tentatively describe further developments.

References

Blum, W. (2015). Quality teaching of mathematical modelling: What do we know, what can we do? In J. S. Cho (Ed.), Proceedings of the 12th international congress on mathematical education (pp. 73–96). Springer.

Kaiser, G., & Sriraman, B. (2006). A global survey of international perspectives on modelling in mathematics education. ZDM – Mathematics Education, 38(3), 302–310.

Kaiser-Messmer, G. (1986). Anwendungen im Mathematikunterricht. Vol. 1 Theoretische Konzeptionen. Franzbecker.

Krawitz, J., Schukajlow, S., Yang, X., & Geiger, V. (2025). A Systematic Review of International Perspectives on Mathematical Modelling: Modelling Goals and Task Characteristics. ZDM – Mathematics Education, 57(2/3), 193-212.

Preciado Babb, A. P., Acuña, F. P., Rocha, Y. A. O., & Rojas, A. S. (2023). Diversity of perspectives on mathematical modelling: A review of the international landscape. In G. Greefrath, S. Carreira, & G. A. Stillman (Eds.), Advancing and consolidating mathematical modelling (pp. 43–57). Springer.

Abstract: The use of mathematical models is ubiquitous in the natural sciences, and economists rely on them for diverse applications. However, compelling examples of mathematical models that successfully describe sociological and psychological phenomena remain less common. This lecture will explore one such example, stemming from our work at the Institute for Futures Studies, where my colleagues and I have developed a framework for understanding and predicting changes in public opinion on moral issues.
This model, refined and validated across numerous studies, is notable for its intentional simplicity. Its remarkable performance against empirical data underscores a key principle in modeling: complexity is not always a prerequisite for insight.

In this talk, I will first present the core modeling principles and the considerations that guided the development of our basic model of opinion change. I will illustrate how this foundational model can be extended for more nuanced predictions and discuss the methods we've employed to test its validity. I think this journey of model creation, application, and validation offers rich insights for the teaching of mathematical modeling. It provides a concrete case study on translating complex social dynamics into mathematical terms, the iterative process of model refinement, and the power of parsimonious approaches.

Abstract: In this talk, I share my thoughts in relation to culture and modelling.

My awareness gradually emerged over time beginning while growing up in an extremely diverse west coast of North America, later working in Guatemala, New Mexico, California, and Nepal, and where I live now in Brasil (seasoned with a few Fermi problems and some emic/etic dialogue). As a young and naïve master’s student in New Mexico, I participated in an NSF grant that allowed us to travel throughout the Southwestern USA, and then to Guatemala and México. Using LOGO, we observed first contacts with computers, this was where I began to observe interactions between humans, culture and mathematics. From this arose 4 caveats:, I have in my work:

• Caveat 1: Math is a language. Every known language, synthetic or natural, has its own grammar, prose and poetry. Mathematical prose can be expressed through modelling, which is incredibly diverse, and provides beautiful expressions of a modeler´s own creativity, values, culture and mathematics. 
• Caveat 2: Universality. All people on this planet “do” mathematics. Bishop said that we can think of mathematics as the numerous and diverse ways in which humans “count, locate, measure, design, play and explain.” Bassanezi and D’Ambrosio added modelling to the mix. 
• Caveat 3: Precision vs Imprecision. There are different and diverse ways to model – some are exact, precise and beautiful. At the same time, those emerging from informal contexts, often local and historically based, and can be somewhat imprecise. I study the imprecise found in common day-to-day contexts, yet I remain grateful for the precise. Ethomodellers begin by celebrating different types of modelling. Like D’Ambrosio and Bishop, this is culturally based, where each model pursues its own truth, and context. One type of modelling represents a necessary scientific-academic modelling, the other represents local-informal, or what I call, "mais ou menos." 
• Caveat 4: Humility. Looking at mathematics and the models that do not emerge in western capitalist contexts demands humility, flexibility, and an open mind. I learned this from my dear uncle on his ranch in Northern California, and Mayan merchants, and a rice farmer in Piaui who all asked the same question, “you studied at a university, why don’t you know this?”

These important elements form dialogical processes of ethnomodelling that researchers in Brasil, the USA, Ghana, México, Costa Rica, Nepal and Indonesia are “playing with”. My talk will conclude with some ethnomodels produced by researchers in many countries.

Abstract: Mathematical modelling is a powerful interdisciplinary tool that opens up rich learning opportunities for problem solvers of all ages, from students to teachers and teacher candidates. Research have shown that mathematical modelling plays a vital role in developing insights into real-world problems, which is more crucial than ever in today’s rapidly changing world. The global challenges of the COVID-19 pandemic, climate change, economic instability, and food insecurity during wartime have highlighted the urgent need for a modelling mindset – one that not only helps us understand and navigate current issues but also equips us to anticipate future crises. Mathematical modelling allows individuals to understand, explain, and interpret complex phenomena, predict potential outcomes, and develop proactive solutions, which makes it an essential mindset for the world citizens of the 21st century.

But how do we cultivate this mindset, especially in the next generation? How can we ensure that students develop the ability to think mathematically about the world? And, more critically, do teachers themselves possess this modelling mindset? Further, how can we support them in understanding mathematical modelling and overcoming the challenges of this task? Indeed, what does this modelling mindset entail?

These are the questions that have driven my research on mathematical modelling education throughout my academic career. This talk will share insights primarily from two longitudinal design-based research projects with prospective mathematics teachers – projects that highlight the rewarding opportunities in supporting teachers to develop their modelling knowledge as well as the behind-the-scenes challenges.

The core premise of these projects is that teachers are not simply curriculum implementers but active knowledge seekers. Therefore, investigating prospective teachers’ potential to identify, design, and organize meaningful modelling problems constituted a momentous research path. A shared goal of these studies is to empower future teachers to solve and pose modelling problems through cognitive, communal, reflective, and performance-based practices. The former design study incorporated all of these practices, while the latter concentrated on posing modelling problems and different types of reflection. In addition, the wide range of professional practices prompted deeper theorizing about the nature of teacher knowledge in mathematical modelling, highlighting its pedagogical, curricular, relational, and interdisciplinary dimensions.

Building upon these insights, this plenary will spotlight the meaningful opportunities that prospective teachers experienced through carefully crafted training sessions – opportunities that supported the development of a modelling mindset through practice, reflection, and collaboration. At the same time, it will offer a candid look behind the scenes of this work, shedding light on the complexities, uncertainties, and iterative challenges that shaped these efforts. Join me as we step backstage into the mathematical modelling research, where the process of cultivating a modelling mindset in teachers comes into focus – with all its accomplishments, tensions, and the layered nature of what this mindset entails.

Abstract: Artificial Intelligence (AI) is now an indispensable technology for our daily lives and society, from smartphone image recognition and online shopping recommendations to credit card fraud detection, self-driving cars, infectious disease and environmental predictions, and more. AI combines machine learning algorithms with large amounts of data to predict the likelihood of future events and generate new text, images, video and audio. Building on their broad applications, AI tools such as ChatGPT have been increasingly used in mathematics and statistics education. The topic of AI systems such as machine learning algorithms has also attracted attention as an important learning object in computer science and data science education.

It is an unavoidable challenge for us, the ICTMA community, to explore how AI tools and the topic of AI systems can be incorporated into mathematical modelling education, including AI’s impact on teaching pedagogy and student learning. We still know little about how teachers can leverage AI tools to teach modelling, and how students can use them to advance the modelling process. In addition, AI systems rely heavily on the use of mathematical models and modelling processes. These systems typically operate as “black boxes”, i.e. the relevant mathematical models and operating modelling processes are not obvious, nor are the underlying data and algorithms. This may imply a shift in modellers’ agency from building models themselves to focussing on critiquing, interpreting and validating models produced with the help of AI. However, students still need hands-on experience of creating and exploring models in order to critique, verify, understand and further develop models and AI systems. Teachers, lecturers and students also need to understand how they can utilise AI within the modelling process. An understanding of the modelling process will be key for these learning experiences, and the teaching and learning of mathematical modelling at all levels of education is expected to play a role.

In this dual plenary talk, we will each draw from our own areas of expertise and present an overview of the current state of AI and mathematical modelling education, explore potential uses of AI in the teaching and learning of mathematical modelling, and give some tips for considering AIs introduction into modelling education practice within primary, secondary and tertiary education. Finally, we aim to conclude with presenting practical tips to consider for incorporating AI into pedagogical practices and developing students understanding of AI systems. It is our hope that open questions for further research into utilising AI as an innovative tool within mathematical modelling education are generated from our plenary talk.

Professor Doctor Vince Geiger is the Research Director of the STEM in Education Program in the Institute of Learning Science and Teacher Education at Australian Catholic University. His work is situated in an interdisciplinary research space focused on the enabling and transformative role of mathematics within the STEM disciplines and other areas across the curriculum. This work, including over 150 peer reviewed publications, is driven by an understanding that the capacity to know and use mathematics confidently when addressing real-world problems is key to the empowerment of critically informed citizenship – the foundation for personal well-being and cohesive socially just societies. His contributions to research in STEM education are motivated by an awareness that capability in this space is vital for an individual's career prospects and the prosperity of nations.

Vince’s research interests include mathematical modelling education, critical mathematical thinking, numeracy, and the role of digital resources in supporting mathematical teaching and learning. His research has attracted over $7 million (AUD) in research funding both nationally and internationally and includes the projects: Enabling students’ critical mathematical thinking (Australian Research Council); Using mathematics to solve real world problems – The role of enablers (Australian Research Council), Principals as STEM Leaders (Department of Education and Training), Strengthening teachers’ instructional capabilities with Big Data (Australian Universities-German DAAD Joint Research Cooperation Scheme).

Most recently he is contributing to the DASME (Data Science in Mathematics Education) project, funded by the Novo Nordisk Foundation and led by Associate Professor Britta Jessen at the University of Copenhagen.

Vince’s research awards include the role of Giovani Prodi Professor at the University of Wurzburg and a Mathematics Education Research of Australasia (MERGA) Research Award. He is the current President of the International Community of Teachers of Mathematics and Applications, a Past President of the Australian Association of Mathematics Teachers, Editor-in-Chief of Mathematics Education Research Journal (Scopus med% 8); Editorial Board Member for the International Journal of Science and Mathematics Education, member of the Numeracy Expert Group for the 2nd Cycle of the Programme for International Assessment of Adult Competencies, and a member of the International Organising Committee for the International Commission for Mathematics Instruction Study-27 on mathematics education and the socio-ecological.

Gabriele Kaiser holds a master’s degree as a teacher for mathematics and humanities for lower and upper secondary level. She completed her doctorate in mathematics education in 1986 with a study on applications and modelling supervised by Werner Blum. The thesis war covering theoretical aspects such as an analysis of the historical and the recent discussion on applications and modelling as well as empirical aspects, namely the possibilities of this kind of examples in mathematics teaching. These research works were extended in new projects on modelling in mathematics teaching together, amongst others with colleagues from the mathematics department.

International comparison in mathematics teaching is one of the main fields of research of Gabriele Kaiser and therefore became the subject of her post-doctoral study, which comprised a comparative study on mathematics teaching in England and Germany.

Since 1998, she is full professor for mathematics education at the Faculty of Education of the University of Hamburg. Her areas of research are empirical studies on teacher education and teachers’ professionalism, modelling and applications in school, international comparative studies, gender and cultural aspects in mathematics education. She was convenor of the 13th International Congress on Mathematical Education, which took place in Hamburg in 2016 with more than 3500 participants. Forty books have come out in the frame of this congress edited by her.

Gabriele Kaiser’s most recent projects deal with teacher education, partly under an international perspective starting from the IEA Teacher Education Study in Mathematics (TEDS-M) on the efficiency of teacher education in various countries at primary and secondary level. Several follow-up studies – with Sigrid Blömeke and Johannes König – have been carried out in the frame of longitudinal studies and studies integrating knowledge and teacher noticing. A most recent study focuses on inclusive mathematics education and teacher professionalism

Gabriele Kaiser has been directing the large-scale project ProfaLe “Professional Teacher Action for Promoting Subject-based Learning under Changing Societal Conditions“ within the framework of the „Quality Campaign for Teacher Education“, which has focused amongst other the integration of subject teaching and teaching of mathematics education, the integration of the perspective of inclusion and language within teacher education. The project lasted from 2015 to 2023.

From 2005 to 2024 she has been the editor-in-chief of the high-ranking journal ZDM –Mathematics Education, which is since 2020 in SSCI. From 2025 onwards, she serves as associate editor. In addition, she is editing several book series at national and international level amongst others International Perspectives on Mathematical Modelling. From 2007 to 2011 and from 2019 to 2023 she has been president of the ICMI affiliate group “The International Community of Teachers of Mathematical Modelling and Applications” (ICTMA). From 2017 to 2021 she was a professorial fellow at the Institute for Leaning Sciences and Teacher Education at the Australian Catholic University in Brisbane (Australia), where she holds currently an honorary professorship. In addition, she holds an honorary professorship at the Educational University Hong Kong. Furthermore, since 2022 she serves as professor II at Nord University in Bodø (Norway).

Kimmo Eriksson is a professor of mathematics at Mälardalen University, Sweden, and a researcher at the Institute for Futures Studies. He is also the chairperson of the Global Social Norms research network (globalsocialnorms.org).

Kimmo received his PhD degree in mathematics from the Royal Institute of Technology in 1993, starting his academic career as an algebraic combinatorialist. He later branched out into game theory, mathematical statistics, cultural evolution, social psychology, sociology, and mathematics education, and in 2018 he obtained a second PhD degree in social psychology from University of Kent.

In his mathematics education research he has mainly analyzed data from TIMSS and PISA, often focusing on how within-country differences (e.g., by gender or socioeconomic status) vary between countries.

His main current research interest is to understand how and why moral opinions and social norms vary across space and time, using cross-national surveys and mathematical models of cultural evolution.

Daniel Clark Orey, Ph.D. is Professor Emeritus of Mathematics and Multicultural Education at California State University, Sacramento.

He has taught and lived in Oregon, Brazil, Guatemala, Mexico, Nepal and the United States.

He is a Fulbright Senior specialist with experiences at the Pontifical Catholic University of Campinas in Brazil (1998) and at Kathmandu University in Nepal (2007).

He is currently professor of mathematics education in the Department of Mathematics Education and serves in the Post-Doctoral Academic Masters and Doctoral Program in Mathematics Education at the Universidade Federal de Ouro Preto, Brazil.

Serife Sevinc (Şerife Sevinç; in her native language) is a mathematics education researcher and teacher educator who has worked at universities in Germany, Turkey, and the United States. She is currently an Associate Professor of Mathematics Education at Middle East Technical University, Türkiye, and a Postdoctoral Research Associate in the Department of Primary Education/Mathematics Education at Technische Universität Dresden (TU Dresden), Germany.

Dr. Sevinç earned her Ph.D. in Curriculum and Instruction with a specialization in Mathematics Education, as well as a minor Ph.D. in Inquiry Methodology, from Indiana University Bloomington, U.S.A. Her doctoral research, supervised by Prof. Richard Lesh, focused on the nature of pre-service teachers' knowledge in designing modeling problems and pre-service teachers' conceptions of problem characteristics that facilitate the modeling process. Through this work, she has made significant contributions to the field of mathematics education, publishing theoretical and empirical studies in prestigious international journals. Additionally, she has served as a reviewer for several leading mathematics education journals.

Her research interests center on students' and pre-service teachers' mathematical thinking in problem-solving and problem-posing processes, with a particular focus on mathematical modeling. She continues to investigate how the modeling process enhances students' and teachers' conceptual understanding of mathematics, as well as the knowledge required by pre-service teachers to design modeling problems. Her involvement in several international projects has enabled her to collaborate with esteemed colleagues in the U.S.A. and Europe. These projects range from exploring young students' experiences with mathematical modeling to examining cognitive and intercultural aspects of the modeling process among prospective mathematics teachers, contributing to cutting-edge advancements in the field.

In recent years, Dr. Sevinç has been an active member of the ICTMA (International Community of Teachers of Mathematical Modelling and Applications) community, regularly participating in its conferences and contributing to the ICTMA series books by publishing chapters, each highlighting significant aspects of mathematical modeling. She is also an active participant in the CERME (Congress of European Research in Mathematics Education) community, attending conferences, publishing in the CERME Proceedings, and serving as a co-leader of TWG6: Applications and Modelling at CERME14.

Beyond her research and academic contributions, Dr. Sevinç is deeply committed to advancing the field of mathematics education, particularly the modeling community. She achieves this through publishing research reports, practitioner articles, book chapters, and conference proceedings; organizing teacher training workshops; designing mathematical modeling courses for prospective teachers; and supervising master's theses and doctoral dissertations.

 

Takashi Kawakami is an Associate Professor of Mathematics Education at the Cooperative Faculty of Education, Utsunomiya University, Japan.

Born in 1983, the same year as ICTMA-1, he began his teaching career as a private primary school teacher after earning a master’s degree in Education from Chiba University (Japan) in 2008. In 2013, he transitioned to academic research as a full-time lecturer at Nishikyushu University (Japan), where he contributed to the training of kindergarten and primary school teachers and conducted research on mathematics and statistics education. Since 2017, he has imparted mathematics and statistics education to primary and secondary mathematics teachers at the Utsunomiya University. In 2023, he earned a Ph.D. in Education from Hyogo University of Teacher Education (Japan).

Takashi Kawakami’s research interests include mathematical modelling, statistics and data science education, STEM education, and mathematics teachers’ professional learning. His research began with mathematical modelling education in primary and secondary schools, which was the subject of his master’s thesis. His current primary focus is exploring the intersection of mathematical modelling and statistics/data science education using conceptual and empirical approaches.

In terms of the conceptual approach, he has been systematically reviewing the research literature on data-based modelling in statistics and mathematics education with Jonas Bergman Ärlebäck. In terms of the empirical approach, Takashi Kawakami’s doctoral thesis explored primary and secondary school students’ flexible use of mathematical/deterministic and statistical/stochastic reasoning to make informed predictions and decisions when modelling data-rich situations. More recently, in collaboration with Akihiko Saeki and other colleagues, Takashi Kawakami extended this work to initiatives that promote data-informed interdisciplinary modelling as a part of STEM education and data-informed sociocritical modelling as a component of citizen education.

Takashi Kawakami’s research was supported by grants from the Japan Society for the Promotion of Science and the CASIO Science Promotion Foundation. He has received several awards, both in Japan and overseas, including the Highly Commended Award for an Early Career Researcher at the 10th International Conference on Teaching Statistics (ICOTS-10) in 2018, the Excellent Paper Award from the Japan Society for Science Education, the Excellent Paper Award from the Mathematics Education Society of Japan, and the Utsunomiya University President’s Special Award.

Takashi Kawakami has contributed to international and national academic conferences. He has been actively involved in ICTMA conferences since 2013. He served on the Local Organising Committee for ICTMA-21 in Japan. He participated in the Survey Team “Statistics and Data Science Education as a Vehicle for Empowering Citizens” at ICME-15 in 2024. He reviewed the common discourse between research on mathematical modelling education and statistics/data science education. Since 2014, Takashi Kawakami has served as an organiser or co-organiser of thematic sessions on mathematical modelling education at the annual conference of the Japan Society for Science Education (JSSE). He is currently a board member of the JSSE and the guest editor-in-chief of a special issue of a JSSE journal focused on data science education.

Marcelo C. Borba is a Professor of the Graduate Program in Mathematics Education and of the Mathematics Department at UNESP (State University of São Paulo) in Brazil, where he chairs the research group GPIMEM (Research Group of Informatics, other Media and Mathematics Education).

Marcelo researches the use of digital technology in mathematics education, mathematical video produced by teachers and students, online distance education, modeling as a pedagogical approach, videos and ethnomatematics and qualitative research methodology.

He was an Associate Editor of ZDM, The International Journal of Mathematics Education between 2011 and 2023 and he was, from 2018 to 2022, the chair of the Teaching Committee of CAPES, a funding agency of the National Ministry of Education in Brazil. He is currently leading a project of CAPES-PrInt that promotes internationalization of research in technology in mathematics education in Brazil.

He was a Keynote speaker at PME-44 (Psychology of Mathematics Education Study Group), Thailand-Virtual (2020); at Plenary Panel of ICME 14 (International Congress of Mathematics Education), held in a hybrid format in China (2021); and at ICM-22 (International Congress of Mathematicians), which was originally scheduled to take place in Russia but was held virtually (2022).

He published around 20 books in English, Portuguese and Spanish, and more than a hundred papers in these three languages. Maybe more importantly, he is actively involved in planting trees within reforestation projects!

Britta Eyrich Jessen is an associate professor at University of Copenhagen. Her research concerns mathematical modelling, digital technologies in modelling education, interdisciplinarity and curriculum analyses linked to modelling application. Lately her research interests have moved towards statistical modelling and data science, and she plans to explore potential mergers between those domains. For this purpose, she has secured funding for the research project DASME – Data Science in Mathematics Education running July 2025 - December 2028.

Most often she works with tools and notions from the Anthropological Theory of the Didactics such as Study and Research Paths, as well as Herbartian schema. This allows her to focus on practices and reasoning linked to students’ engagement with modelling activities.

Her work mainly focuses on upper secondary education, and professional development of teachers at this level through lesson study and similar activities. She teaches and supervises pre-service and in-service teachers and is responsible for a course on “the mathematically modelling science” at the masters’ program on STEM education. She is a co-leader of the TWG06 on modelling and application at CERME.

Before her research carrier, she was an upper secondary teacher in mathematics and physics.

Pauline Vos, PhD (2002), is a Professor of Mathematics Education at the Western Norway University of Applied Sciences (HVL), in the city of Bergen.

She leads theoretical research into the why, when and how of using/learning what type of mathematics by which students/users, and practical research into the design of learning trajectories that deviate from deductive, teacher-centered approaches.

She builds on earlier experiences as mathematics teacher and teacher educator in The Netherlands, Zimbabwe and Moçambique. She has contributed to many past ICTMA conferences from ICTMA12 in London (2005) onwards.

To complementing her interest in mathematical modeling, she also has an interest in mathematical literacy and vocational mathematics.

Within the Congress of the European Society for Research in Mathematics Education, she leads the Thematic Working Group "Mathematics Education for Work, Society and Personal Development".

Dr. Kerri Spooner is a senior lecturer in the Department of Mathematical Sciences at Auckland University of Technology (AUT), New Zealand. Her academic journey is marked by her dedication to mathematics education. She holds a Doctoral degree in Tertiary Mathematical Modelling Education from AUT and a Master's degree in Secondary School Mathematical Modelling Education from the University of Auckland.

Kerri’s journey into mathematical modelling began in 2002 when she attended her first Mathematics in Industry Study Group (MISG) while working as a secondary school mathematics teacher. This experience sparked her interest in mathematical modelling and led her to participate in several MISGs and Mathematics in Industry New Zealand (MINZ) workshops. Kerri further developed her modelling skills by completing two tertiary modelling courses. These courses deepened her understanding of the mathematical modelling cycle and differential equations, equipping her with the skills to create mathematical models for various situations.

In 2011, Kerri worked as part of a professional mathematical modelling team. This experience, along with her participation in MISGs and MINZs, and her study in modelling, provided her with first-hand knowledge of professional modelling behaviours and their complexities. This awareness influences her teaching approach, aiming to create authentic and engaging modelling experiences for her students.

Kerri’s experiences with mathematical modelling, as well as her experiences as a secondary school teacher and tertiary lecturer, made her aware of the challenges students can face when modelling. She emphasizes the importance of being open to new contexts and ideas, learning new mathematics, and working collaboratively. She uses insights from her own experiences of modelling to inform her teaching and research, always striving to be open to new modelling behaviours presented by her students.

In 2012, encouraged by research showing that students as young as 13 could engage in modelling, Kerri developed and taught a holistic mathematical modelling unit for her secondary class. She aimed to provide students with an authentic experience of mathematical modelling, allowing them to engage fully with the process. She believes in the importance of students having an authentic experience of modelling that reflects professional practices. She emphasizes students’ active engagement in the modelling process, the benefits of group work, mimicking professional modelling teams, and using prompts to facilitate a successful holistic modelling experience. Kerri’s ideal way of teaching modelling involves taking genuine real-world problems and having students attempt to model them. However, she has also found students can also have valuable learning experiences modelling fictional situations.

As part of her dedication to providing students with experiences of modelling, since 2016 Kerri has overseen the New Zealand section of the International Mathematical Modelling Competition (IMMC). In 2019 and 2022 New Zealand teams have been outstanding award winners.

Throughout her career, Kerri has been recognized for her excellence in teaching, winning five teaching awards and being nominated for a national teaching excellence award. She is known for promoting active learning and student collaboration to engage students with course content and learning material. Her keen interest in successful ways to engage students in their learning drives her to attempt to create learning experiences that are authentic, engaging, and accessible.

Hans-Stefan Siller is a full professor at the Chair of Mathematics V – Didactics of Mathematics at the Julius Maximilian University of Würzburg. As a professor of didactics of mathematics, his remit encompasses the didactics of the subject of mathematics in all teaching positions, (vocational) grammar schools, secondary modern schools, middle schools, primary schools and schools with special educational needs. His research and work is focused at the interface of current research in mathematics didactics, conception and mathematical topics; in recent years increasingly at the interface of mathematics, MINT, education for sustainable development, digitalization and in research on giftedness.

Following his studies in mathematics and physics at the University of Graz (Austria), he acquired practical teaching experience at Austrian grammar schools in the city and province of Salzburg. He then successfully completed his doctoral studies at the Paris Lodron University of Salzburg (Austria). From 2011, he assumed responsibility for the Austrian school system at both the research and organizational level as project manager for the central written matriculation examination in Austria and the introduction of the central written matriculation examination for mathematics at Austrian grammar schools. In 2012, he habilitated at the University of Vienna and in April of the same year accepted his first professorship at the University of Koblenz-Landau, Koblenz campus. Since October 2017, he has been conducting research as a full professor of mathematics education at the Chair of Mathematics V - Mathematics Education. In the summer semester of 2021, he was a visiting professor at the University of Semarang (Indonesia).

Hans-Stefan Siller is conducting research on various questions in the domain of mathematics education, with a particular focus on interdisciplinary research settings. His research encompasses both the traditional subjects in the teaching of mathematics, in which teaching and learning processes are examined from cognitive and affective perspectives, and the digitalization of the teaching of mathematics, including the utilization of digital tools and media, the didactic preparation of content – taking into account fundamental concepts – interdisciplinary work, and the subject of mathematical modelling. In addition to these areas, he has demonstrated a commitment to addressing significant (and emerging) challenges faced by educators, including the integration of education for sustainable development (ESD) within mathematics lessons and the utilization of artificial intelligence (AI), with a particular focus on generative AI. Since 2021, for instance, he has led the mathematics working group on the integration of education for sustainable development on behalf of the German Standing Conference of the Ministers of Education and Cultural Affairs (KMK).

In all his research fields, Hans-Stefan Siller has demonstrated a commitment to both theoretical and evidence-based research findings, which have resulted in numerous high-ranking publications. Notably, his work is strongly oriented towards third-party funding, and seeks to integrate different perspectives, as is being implemented in one of his current projects, DIM²ENSION - DIgital Supported Mathematical Modelling for Sustainable Development Goals in EurOpean EducatioN, together with colleagues.
Since 2024, he has been contributing his expertise as an editor to the Mathematics Education Research Journal (MERJ).