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Course‐based undergraduate research experiences (CUREs) are an instructional strategy to help students learn the content and process of science by engaging students in authentic science research. The ESA‐endorsed 4‐Dimensional Ecology Education framework emphasizes engaging students in authentic ecology scientific practices, and uniquely foregrounds human dimensions as a core tenant of ecological literacy. Model‐based CURE instruction may help ecology instructors by giving students a scaffold to better orient their line of inquiry and develop more accurate conceptions of the broader socio‐ecological system through the integration of the CURE experimental data to known concepts within the system. We explored how student model accuracy changes throughout the course, what modeling practices students engaged in during collaborative modeling, and how students used CURE data along with social and ecological sciences in their models. We found that students created more accurate models as the course progressed, and all student groups exhibited expert‐like modeling practices during the summative collaborative modeling process. Importantly, we also found that students were able to integrate experimental data they generated through the CURE within their broader understanding of the study system. A major benefit of model‐based CUREs is to cultivate scientific thinking by helping students connect how individual pieces of research inform larger phenomenon. [ABSTRACT FROM AUTHOR]

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Abstract Course‐based undergraduate research experiences (CUREs) are an instructional strategy to help students learn the content and process of science by engaging students in authentic science research. The ESA‐endorsed 4‐Dimensional Ecology Education framework emphasizes engaging students in authentic ecology scientific practices, and uniquely foregrounds human dimensions as a core tenant of ecological literacy. Model‐based CURE instruction may help ecology instructors by giving students a scaffold to better orient their line of inquiry and develop more accurate conceptions of the broader socio‐ecological system through the integration of the CURE experimental data to known concepts within the system. We explored how student model accuracy changes throughout the course, what modeling practices students engaged in during collaborative modeling, and how students used CURE data along with social and ecological sciences in their models. We found that students created more accurate models as the course progressed, and all student groups exhibited expert‐like modeling practices during the summative collaborative modeling process. Importantly, we also found that students were able to integrate experimental data they generated through the CURE within their broader understanding of the study system. A major benefit of model‐based CUREs is to cultivate scientific thinking by helping students connect how individual pieces of research inform larger phenomenon.