Investigations in Mathematics Learning

Special Issue 2028 Call for Manuscripts

Humanizing Mathematical Modeling: Culture, Identity, and Civic Transformation

Mathematical modeling is often framed as a neutral, technical activity centered on representing real-world situations, making assumptions, generating solutions, and validating results. Yet scholarship in socio-critical modeling, ethnomodeling, and humanizing mathematics shows that modeling is also shaped by culture, identity, participation, values, and power. Decisions about what counts as evidence, which assumptions are foregrounded, whose knowledge is recognized, and how results are communicated all shape what modeling becomes in classrooms, communities, and public life.

We welcome manuscripts addressing topics such as:

●      socio-critical, decolonial, or humanizing perspectives on mathematical modeling

●      ethnomodeling and cultural or community-based mathematical knowledge

●      belonging, recognition, identity, participation, and positioning in the mathematical modeling activity

●      data, representation, visualization, omission, bias, and power in modeling

●      modeling for civic engagement, public reasoning, social justice, or community action

●      teacher education and professional learning for equitable and culturally grounded modeling

●      modeling in multilingual, transnational, cross-cultural, or community-based contexts

●      methodological approaches for studying relational, cultural, ethical, or civic dimensions of modeling

●      connections among modeling, data science education, critical statistical literacy, and community-engaged mathematics.

All IML manuscripts will be reviewed by a double-blind peer-review process. The submission deadline for extended abstracts is October 1, 2026. We anticipate sharing feedback with authors by November 1, 2026. Full manuscripts will be due January 2, 2027. Manuscripts will be published in Volume 20(1) in 2028. The editorial team for this special issue of Investigations in Mathematics Learning consists of Eva Thanheiser (Portland State University) and Daniel C. Orey (Universidade Federal de Ouro Preto). Send all inquiries and abstracts to the guest editors at [email protected]. The Editorial Team of Investigations in Mathematics Learning, will support the guest editors and oversee the publishing process of this special issue. The full Call for Manuscripts contains additional information regarding guidelines for abstracts, the review process, and timeline.