Children's Mechanistic Reasoning

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.

Glycemic control in adolescents with type 1 diabetes: Are computerized simulations effective learning tools?

OBJECTIVE

Type 1 diabetes mellitus (T1DM) in adolescent patients is often characterized by poor glycemic control. This study aimed at exploring the contribution of learning with computerized simulations to support: (a) mechanistic understanding of the biochemical processes related to diabetes; (b) diabetes self-management knowledge; and (c) glycemic control. We hypothesized that learning with such simulations might support adolescents in gaining a better understanding of the biochemical processes related to glucose regulation, and consequently improve their glycemic control.

METHODS

A prospective case-control study was conducted in 12- to 18-year-old adolescents with T1DM (n = 85) who were routinely treated at an outpatient diabetes clinic. While the control group (n = 45) received the routine face-to-face follow-up, the intervention group (n = 40) learned in addition with computerized simulations that were embedded in pedagogically supportive activities. Participants in both groups completed a set of questionnaires regarding sociodemographic characteristics, diabetes mechanistic reasoning and diabetes self-management. Clinical data and serum glycated hemoglobin (HbA1c) levels were gathered from medical records. All the data was collected at recruitment and 3 months later.

RESULTS

Analysis revealed improvement HbA1c levels in the intervention group (8.7% ± 1.7%) vs the controls (9.6% ± 1.6%) after 3 months (P < .05). Regression analysis showed that levels of diabetes mechanistic understanding and diabetes self-management knowledge, in addition to sociodemographic parameters, accounted for 31% of the HbA1c variance (P < .001).

CONCLUSION

These results suggest that learning with computerized simulations about biochemical processes can improve adolescents' adherence to medical recommendations and result in improved glycemic control. Implementing scientific learning into the hospital educational setting is discussed.

Characterizing Students' Ideas about the Effects of a Mutation in a Noncoding Region of DNA

Understanding student ideas in large-enrollment biology courses can be challenging, because easy-to-administer multiple-choice questions frequently do not fully capture the diversity of student ideas. As part of the Automated Analysis of Constructed Responses (AACR) project, we designed a question prompting students to describe the possible effects of a mutation in a noncoding region of DNA. We characterized answers from 1127 students enrolled in eight different large-enrollment introductory biology courses at three different institutions over five semesters and generated an analytic scoring system containing three categories of correct ideas and five categories of incorrect ideas. We iteratively developed a computer model for scoring student answers and tested the model before and after implementing an instructional activity designed to help a new set of students explore this concept. After completing a targeted activity and re-answering the question, students showed improvement from preassessment, with 64% of students in incorrect and 67% of students in partially incorrect (mixed) categories shifting to correct ideas only. This question, computer-scoring model, and instructional activity can now be reliably used by other instructors to better understand and characterize student ideas on the effects of mutations outside a gene-coding region.

Exploring Secondary Students’ Alternative Conceptions about Engineering Design Technology

This paper presents the assessment items that were developed by science and technology teachers in Québec to explore their students’ alternative ideas about engineering design technology and technological systems. These assessment items were administered to Secondary Cycle One students in Francophone and Anglophone schools in Québec to elicit their ideas about the foundational technology concepts included in the science and technology curriculum. Students’ responses are presented to share their alternative and scientific explanations. In addition, various approaches to facilitate a deeper understanding of scientific models and mechanistic reasoning in students are also discussed.

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.