Call for papers: Users' mental models regarding large language models

• Silvia Knobloch-Westerwick (TU Berlin)
• Nicole Krämer (U Duisburg)
• Vera Schmitt (U Mainz) 
• Sonja Utz (U Tübingen)

Large Language Models (LLMs) are transforming how individuals seek and process information, how they construct both their environment and themselves, as well as how they evaluate truth and engage in public discourse. This special issue focuses on users’ mental models of LLMs, with emphasis on their notions regarding epistemology (truth, trust, knowledge), design (algorithms, interfaces, AI systems), and effects (cognition, emotion, behavior).

The aim is to advance theory-driven, interdisciplinary basic research in the disciplines of communication science, psychology, computer science/HCI, and philosophy about LLMs as epistemic agents and interaction partners, shaping users’ mental models of knowledge, reality, and even themselves.

Scholarly work on mental models traces back to Kelly (1955), Johnson-Laird (1983), Norman (1983), and Byrne (2005), each contributing to a constructivist perspective describing cognition in terms of internally constructed representations that support prediction and understanding. This line of thinking subsequently exerted a profound influence across disciplines: in interface and industrial design, it informed the alignment of system behavior with users’ expectations; in computer science and communication, it shaped approaches to modeling, interaction, and information exchange; and across psychology, philosophy, and epistemology, it contributed to constructivist views of knowledge as actively built rather than passively received.

With the rise of mediated communication, mental models increasingly formed and evolved through interaction with digital environments. More recently, large language models have further transformed this landscape by generating coherent, context-sensitive representations on demand, thereby actively participating in the construction, reinforcement, and revision of users’ mental models. The present special issue will zoom in on these developments.

We invite submissions from diverse disciplines (e.g., psychology, education, human factors, and computer science) to advance understanding of mental models regarding LLMs among users and designers. Papers may address basic or applied perspectives that explore mental models (MMs) of LLMs. We view MMs broadly, as they include cognitive, motivational, and socioemotional outcomes.

Example topics may include the following (but are not limited to these):

• human-AI interaction and mental models of LLMs
• epistemic trust and credibility in AI systems
• disinformation, narratives, and bias in LLM-mediated communication
• algorithmic design and explainability as they relate to users’ mental models
• domain-specific communication (health and nutrition, politics, sustainability) and LLM mental models
• emotional and behavioral effects resulting from users’ mental models of LLMs

It is anticipated that the special issue will feature 10-20 contributions. Ideal papers for this special issue will take an interdisciplinary or transdisciplinary perspective.

We welcome the following Technology, Mind, and Behavior article categories:

• Feature Articles (basic research, use-inspired basic research, systematic review or  meta-analysis, translative or integrative reviews)
• Brief Reports (conceptual replications, position papers)
• Methodological Innovations

Please note that all submission types except position papers and integrative/translative reviews must present original analysis of empirical data. Systematic reviews and meta-analyses must comply and report according to PRISMA guidelines. Position papers and integrative/translative reviews cannot contain new theory. TMB does not accept review papers. All submissions to TMB must be grounded in rigorous psychological science.

Due to time constraints, Registered Reports and Rapid Communications will not be accepted for this special issue.

This special issue encourages adherence to Technology, Mind, and Behavior’s open science policies. Authors are encouraged to make their data, analysis code, and study materials openly available (Open Data and Open Materials badges) to enhance transparency and reproducibility. Preregistration of hypotheses, study designs, and analytic plans is recommended where appropriate (Preregistered badge), and replication studies are welcomed. Given the interdisciplinary and applied nature of this topic, we also welcome innovative forms of openness (e.g., sharing AI conversational agent prompts, model specifications) when feasible and appropriate.

Authors should prepare their manuscripts in accordance with the TMB Submission Guidelines, and especially the submission checklist, to ensure compliance with journal formatting and ethical standards, and to avoid editorial delays during initial screening. When ready to submit, please do so through the TMB Online Submission Portal. Select the appropriate article type and indicate that your submission is part of the special collection on “Users’ Mental Models Regarding Large Language Models” during the submission process.

The manuscript submission deadline will be October 29, 2026 (by midnight U.S. EST) with the intent of publishing the special issue in 2027.

Please direct any questions you have about the special issue to the editors’ assistant Esra Eresopens in new window, who will navigate incoming inquiries to the editors. Prospective authors are encouraged to contact the editors in advance to discuss the alignment of their manuscripts with the theme of the issue or to enlist as potential reviewersopens in new window.