Framing systems thinking from the perspective of self-regulated learning and metacognition – the process model of systems thinking
Systems thinking is central to understanding complex biological phenomena, yet existing frameworks primarily specify the skills learners should demonstrate and provide less detail on how they recognise, select, regulate, and transfer a systems perspective. We introduce the Process Model of Systems Thinking (PMST), which conceptualises systems thinking as a domain-specific learning strategy grounded in self-regulated learning and metacognition. The PMST distinguishes two recursively connected phases: Forethinking and Selecting Systems Thinking, and Applying and Adapting Systems Thinking as a Learning Strategy. Across both phases, conceptual systems knowledge, conceptual knowledge about the phenomenon, metaconceptual knowledge, and conditional and procedural metastrategic knowledge support task interpretation, strategy selection, application, monitoring, and adaptation. Theory-guided vignettes illustrate the model’s proposed processes, while selected studies on self-regulated learning, systems modelling, system language use, and metacognitive prompting provide empirical reference points for assessing its integrative potential. The PMST distinguishes supported systems-thinking performance from autonomous strategy selection and offers a framework for comparing instructional approaches according to the phases and knowledge resources they address. As a provisional and revisable model, it generates testable propositions for research on systems-thinking development, instruction, transfer, and increasingly autonomous use across biological contexts.
Authors
- Marie‐Christine P. J. Knippels (ORCID: https://orcid.org/0000-0003-4989-1863)
- Alexander Bergmann (ORCID: https://orcid.org/0000-0002-5492-8512)
Institutions
- Utrecht University (NL)
- University of Bamberg (DE)
Publication Details
- Journal
- Journal of Biological Education
- Published
- 2026-08-25
- DOI
- https://doi.org/10.1080/00219266.2026.2719536
- Primary Topic
- Complex Systems and Decision Making
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Technische Universität Kaiserslautern
- Universität Leipzig