Supporting Scientific Practice through Model-Based Inquiry: A Students'-Eye View of Grappling with Data, Uncertainty, and Community in a Laboratory Experience.

Modeling is a scientific practice that supports creative reasoning, motivates inquiry, and facilitates community sense-making. This paper explores students' perspectives on modeling in an undergraduate laboratory course, Authentic Inquiry through Modeling (AIM-Bio), in which they proposed, tested, and revised their own models. We conducted comparative case studies of eight students over a semester. Students described using models to support multiple forms of scientific reasoning and hypothesis generation. They recounted the challenges of dealing with uncertainty and integrating diverse ideas. They also described how these challenges pushed their thinking. Overall, students reported feeling a sense of scientific authenticity and agency through their modeling experience. We additionally provide an in-depth look at two students whose unique experiences in AIM-Bio emphasize the variable ways modeling can support inquiry learning. We claim that modeling emerged as a legitimate practice among students, because the AIM-Bio curriculum encouraged diversity in students' models, provided opportunities for students to grapple with uncertainty, and fostered collaboration between students. We suggest that biology educators consider how model-based inquiry can allow students to participate in science, as a way to support interest in, identification with, and ultimately persistence in science, technology, engineering, and mathematics fields.

Authentic Inquiry through Modeling in Biology (AIM-Bio): An Introductory Laboratory Curriculum That Increases Undergraduates' Scientific Agency and Skills.

Providing opportunities for science, technology, engineering, and mathematics undergraduates to engage in authentic scientific practices is likely to influence their view of science and may impact their decision to persist through graduation. Laboratory courses provide a natural place to introduce students to scientific practices, but existing curricula often miss this opportunity by focusing on confirming science content rather than exploring authentic questions. Integrating authentic science within laboratory courses is particularly challenging at high-enrollment institutions and community colleges, where access to research-active faculty may be limiting. The Authentic Inquiry through Modeling in Biology (AIM-Bio) curriculum presented here engages students in authentic scientific practices through iterative cycles of model generation, testing, and revision. AIM-Bio university and community college students demonstrated their ability to propose diverse models for biological phenomena, formulate and address hypotheses by designing and conducting experiments, and collaborate with classmates to revise models based on experimental data. Assessments demonstrated that AIM-Bio students had an enhanced sense of project ownership and greater identification as scientists compared with students in existing laboratory courses. AIM-Bio students also experienced measurable gains in their nature of science understanding and skills for doing science. Our results suggest AIM-Bio as a potential alternative to more resource-intensive curricula with similar outcomes.

Teaching Real Data Interpretation with Models (TRIM): Analysis of Student Dialogue in a Large-Enrollment Cell and Developmental Biology Course.

We present our design for a cell biology course to integrate content with scientific practices, specifically data interpretation and model-based reasoning. A 2-yr research project within this course allowed us to understand how students interpret authentic biological data in this setting. Through analysis of written work, we measured the extent to which students' data interpretations were valid and/or generative. By analyzing small-group audio recordings during in-class activities, we demonstrated how students used instructor-provided models to build and refine data interpretations. Often, students used models to broaden the scope of data interpretations, tying conclusions to a biological significance. Coding analysis revealed several strategies and challenges that were common among students in this collaborative setting. Spontaneous argumentation was present in 82% of transcripts, suggesting that data interpretation using models may be a way to elicit this important disciplinary practice. Argumentation dialogue included frequent co-construction of claims backed by evidence from data. Other common strategies included collaborative decoding of data representations and noticing data patterns before making interpretive claims. Focusing on irrelevant data patterns was the most common challenge. Our findings provide evidence to support the feasibility of supporting students' data-interpretation skills within a large lecture course.

Features of Knowledge Building in Biology: Understanding Undergraduate Students' Ideas about Molecular Mechanisms.

Research has suggested that teaching and learning in molecular and cellular biology (MCB) is difficult. We used a new lens to understand undergraduate reasoning about molecular mechanisms: the knowledge-integration approach to conceptual change. Knowledge integration is the dynamic process by which learners acquire new ideas, develop connections between ideas, and reorganize and restructure prior knowledge. Semistructured, clinical think-aloud interviews were conducted with introductory and upper-division MCB students. Interviews included a written conceptual assessment, a concept-mapping activity, and an opportunity to explain the biomechanisms of DNA replication, transcription, and translation. Student reasoning patterns were explored through mixed-method analyses. Results suggested that students must sort mechanistic entities into appropriate mental categories that reflect the nature of MCB mechanisms and that conflation between these categories is common. We also showed how connections between molecular mechanisms and their biological roles are part of building an integrated knowledge network as students develop expertise. We observed differences in the nature of connections between ideas related to different forms of reasoning. Finally, we provide a tentative model for MCB knowledge integration and suggest its implications for undergraduate learning.

Complement levels and activity in the normal and LPS-injured lung.

Complement, a complex protein system, plays an essential role in host defense through bacterial lysis, stimulation of phagocytosis, recruitment of immune cells to infected tissue, and promotion of the inflammatory response. Although complement is most well-characterized in serum, complement activity is also present in the lung. Here we further characterize the complement system in the normal and inflamed lung. By Western blot, C5, C6, and factor I were detected in bronchoalveolar lavage (BAL) at lower levels than in serum, whereas C2 was detected at similar levels in BAL and serum. C4 binding protein (C4BP) was not detectable in BAL. Exposure to lipopolysaccharide (LPS) elevated levels of C1q, factor B, C2, C4, C5, C6, and C3 in human BAL and C3, C5, and factor B in mouse and rat BAL. Message for C1q-B, C1r, C1s, C2, C4, C3, C5, C6, factor B, and factor H, but not C9 or C4BP, was readily detectable by RT-PCR in normal mouse lung. Exposure to LPS enhanced factor B expression, decreased C5 expression, and did not affect C1q-B expression in mouse and rat lung. BAL from rats exposed to LPS had a greater ability to deposit C3b onto bacteria through complement activation than did BAL from control rats. In summary, these data demonstrate that complement levels, expression, and function are altered in acute lung injury and suggest that complement within the lung is regulated to promote opsonization of pathogens and limit potentially harmful inflammation.