ZDM Special Issue Call for Papers: Capturing Mathematical Thinking and Learning Processes in Real Time (Issue 6 in 2027)

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Rationale

Understanding how individuals think about and learn mathematics is a central concern in mathematics education research. Yet, assessing the processes of individuals’ mathematical thinking and learning remains a significant methodological challenge. This is especially the case for studying such processes in real time, as they occur. Still, doing so is essential for several reasons. First, mathematical problems can often be approached in multiple ways (e.g., Heinze et al., 2009; Obersteiner et al., 2022). Learners may follow different reasoning paths or learning trajectories, even when arriving at the same solution. Examining these diverse pathways can reveal important differences in individuals’ understanding, strategy use, and development that are not captured by outcomes alone. Research participants are not always able to report on the pathways they have followed (Inglis & Alcock, 2018). Various real-time assessment techniques can specify when exactly and in what ways individual reasoning processes differ (e.g., Schindler & Lilienthal, 2019; Vamvakoussi et al., 2012). Second, process measures allow for identifying processing stages within a certain task (Dotan et al., 2019), contributing to our understanding of what is involved in mathematical problem solving and what the specific challenges for learners are. For example, challenges could occur while reading a task, processing the provided information (e.g., text, pictures) or finding a suitable solution. Studies with eye tracking or mouse tracking are able to discriminate between various possibilities (Dewolf et al., 2015; MacKay et al., 2020). Third, real-time tracking of thinking and learning processes opens possibilities for adaptive learning environments that provide immediate, individualized support (Plass & Pawar, 2020). Advances in technology—such as log data analysis or eye tracking—enable researchers to explore these processes with greater precision and at larger scale than ever before (e.g., Schons et al., 2024). Finally, it is well documented that affective variables (e.g., anxiety) are related to mathematical problem solving (e.g., Schukajlow et al., 2023). Process measures can detect a learner’s affective state at any moment, which can be useful for providing instructional support, and which can enhance our understanding of reasons for specific performance patterns (e.g., Pizzie & Kraemer, 2021).

The papers in this Special Issue should reflect on one or more of the following questions:

Why is it important to assess mathematical thinking and learning in real time in a particular context?
What are the implications, given the specific timescales considered?
What theoretical frameworks are suitable to describe mathematical thinking and learning processes, considering cognitive and/or affective dimensions of such learning processes?
How are these processes affected by various variables (e.g., individual or contextual factors)?Is it possible to influence learning processes (e.g., by instruction) and to what extent can such changes be reliably assessed?
What are the potentials and limitations of the specific assessment method(s) used?
What are the implications of understanding mathematical thinking and learning processes for instruction?

Open Call Procedure

Prospective authors should submit by e-mail an extended abstract of no more than 500 words (including references) of their manuscript to the guest editors: Andreas Obersteiner (andreas.o...@tum.de), Martha Alibali (martha....@wisc.edu), and Wim Van Dooren (wim.va...@kuleuven.be) by December 31, 2025.
The extended abstract should include the rationale, research goals and questions/hypotheses, methodology (including sample size and participants), and (preliminary) results. If authors have questions regarding the appropriateness of manuscripts for acceptance in the special issue, they should contact the guest editors beforehand. The guest editors will select the abstracts for the special issue based on their scientific quality and inform the authors about their decision. There is no guarantee that all submitted abstracts will be accepted.

Successful authors need to submit full manuscripts through the Editorial Manager of ZDM between September 1 and September 30, 2026. Manuscript submissions need to be in line with the ZDM’s Author Guidelines . All manuscripts will be reviewed by the special issue guest editors and special issue authors. Final editorial decisions on all manuscripts will be made by the handling editor assigned by the ZDM editor-in-chief.