From Problems to Solutions: How Self-Questions Drive Strong Scientific Reasoning

Metacognition, or awareness and control of thinking, is essential for problem solving because it helps solvers select strategies for learning and decide when to enact them (planning), check their understanding in the moment (monitoring), and assess effectiveness of solutions and learning strategies (evaluating). Most studies that examine metacognition do so retrospectively, leaving a critical gap in how metacognition is used in-the-moment for problem solving. In this study, we utilized a think-aloud interview approach to capture and characterize the metacognitive skills that senior undergraduate life science students at three institution types in the United States used spontaneously while solving challenging biology problems. We found that the students (n = 39) displayed a wide variety and quantity of monitoring, some evaluating, and nearly no planning skills while creating a solution backed with high-quality reasoning. Students frequently used self-questions to monitor and evaluate their thinking. We found that self-questioning is a critical skill for generating solutions, but it only moves problem solving forward if the student asks and correctly answers the self-question out loud. This study illustrates how self-questioning and other metacognitive regulation skills provide links to bridge the gap between a student's prior knowledge and specific features of a challenging problem. Based on our student data, we conceptualized a model of metacognitive phases during problem solving with high-quality reasoning. Finally, we present a self-question scaffold to facilitate the proposed phases (planning, monitoring, reasoning, and evaluating) so educators can equip students with metacognitive and scientific reasoning tools for effective problem solving.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-11-02
DOI
https://doi.org/10.64898/2026.10.30.762163
Primary Topic
Innovative Teaching and Learning Methods
Type
preprint
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preprint

From Problems to Solutions: How Self-Questions Drive Strong Scientific Reasoning

Noelle Clark, Julie Dangremond Stanton, Temilope Aina, Gheed Nafea et al.
bioRxiv (Cold Spring Harbor Laboratory)
Innovative Teaching and Learning Methods
preprint

From Problems to Solutions: How Self-Questions Drive Strong Scientific Reasoning

Noelle Clark, Julie Dangremond Stanton, Temilope Aina, Gheed Nafea, Todd Montgomery
preprint en

Abstract

Metacognition, or awareness and control of thinking, is essential for problem solving because it helps solvers select strategies for learning and decide when to enact them (planning), check their understanding in the moment (monitoring), and assess effectiveness of solutions and learning strategies (evaluating). Most studies that examine metacognition do so retrospectively, leaving a critical gap in how metacognition is used in-the-moment for problem solving. In this study, we utilized a think-aloud interview approach to capture and characterize the metacognitive skills that senior undergraduate life science students at three institution types in the United States used spontaneously while solving challenging biology problems. We found that the students (n = 39) displayed a wide variety and quantity of monitoring, some evaluating, and nearly no planning skills while creating a solution backed with high-quality reasoning. Students frequently used self-questions to monitor and evaluate their thinking. We found that self-questioning is a critical skill for generating solutions, but it only moves problem solving forward if the student asks and correctly answers the self-question out loud. This study illustrates how self-questioning and other metacognitive regulation skills provide links to bridge the gap between a student's prior knowledge and specific features of a challenging problem. Based on our student data, we conceptualized a model of metacognitive phases during problem solving with high-quality reasoning. Finally, we present a self-question scaffold to facilitate the proposed phases (planning, monitoring, reasoning, and evaluating) so educators can equip students with metacognitive and scientific reasoning tools for effective problem solving.

bioRxiv (Cold Spring Harbor Laboratory)
University of Georgia (US)
Quality education
Innovative Teaching and Learning Methods
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