Physical Models Support Active Learning As Effective Thinking Tools
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Chapter 3 Physical Models Support Active Learning as Efective Tinking Tools Cassidy R. Terrell,*,1 Margaret A. Franzen,2 Timothy Herman,2 Sunil Malapati,3 Dina L. Newman,4 and L. Kate Wright4 1Center for Learning Innovation, University of Minnesota, 111 S. Broadway, Rochester, Minnesota 55904, United States 2Center for BioMolecular Modeling, Milwaukee School of Engineering, 1025 N. Broadway, Milwaukee, Wisconsin 53202, United States 3Chemistry, Clarke University, 1550 Clarke Drive, Dubuque, Iowa 52001, United States 4Tomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, 85 Lomb Memorial Drive, Rochester, New York 14623, United States *E-mail: [email protected]. From the perspective of a novicestudent, the molecular biosciences are inherently invisible. A challenge facing bioscienceeducators isto helpstudents create detailed mental models of the biomolecules thatmake up a livingcelland how they all work togethertosupport life. With the advancement of rapid-prototyping, also knownas 3D (three dimensional)-printing, physical models of biomolecules are entering undergraduate classroomsastoolsto aid in constructing mental models of biological phenomenaat the molecular-level. Tisrelatively new pedagogical tool requires evidence-based practices for optimal use in aidingstudentconceptual and Downloaded via Cassidy Terrell on December 15, 2019 at 13:31:49 (UTC). visual development. Tis chapter presents currentevidence for the use of physical modelsas learningtools, while also introducingcasestudies on howphysical models of biomolecules are designedand assessed in undergraduate molecular See https://pubs.acs.org/sharingguidelines for options on how to legitimately share published articles. bioscience setings. Introduction In this chapter, we focus on development, useand assessment of biomolecularphysical models in undergraduate molecular bioscienceeducation. Here “molecular biosciences” encompasses any course utilizingconcepts featuring biomolecules, rangingfrom monomers tomacromolecules that support life on the molecular level (e.g. introductory biology; general, organic, and biochemistry (GOB); biochemistry, molecular biology, and cellular biologycourses). At the undergraduate level, VisionandChange identifes modelingand simulation ascorecompetencyand disciplinary practices © 2019 American Chemical Society Bussey et al.; Biochemistry Education: From Theory to Practice ACS Symposium Series; American Chemical Society: Washington, DC, 2019. (1). Te Next Generation ScienceStandards (NGSS) Framework defnition of models includes diagrams, physical replicas, mathematical representations, analogies, and computer simulations that aretools for the studenttoengage in “developing questions, making predictionsand explanations, analyzing and identifying faws in systems, and communicating ideas (2).” Moreover, models provide an opportunity for the studenttoengage in an iterative process of “comparing their predictionswith the real world and thenadjusting themtogain insights into the phenomenon being modeled (2).” Tisis the vein in which the potential power of models lies, as manyauthors suggest that learningbarriers, particularly thoserelatedtoabstract concepts, arisefrom unchallenged incorrect ideas, fawed mental modelsand the inabilitytorelate new concepts to other knowledge (3, 4). Here, we predict usingphysical modelswillfurther the student’s development of arobust mental model thatisable toovercome misconceptionsand further the student’s learning progression in the molecular biosciences. Since no modelis identical to the concept it represents (else it would cease being a model), students needto be trainedto be skeptical in analyzingany model (5–7). Students who can examine a modeland explain how the modelis both likeand unlike the real thing it represents demonstrate aconceptual understanding of what the modelrepresents. Furthermore, like the Hindu fable of the blind menand the elephant, each model only represents a part of the whole, and it is through transitioningamong multiple representations thatwegain a true sense of what modelsrepresent (8). Assuch, physical models oferanavenue to develop students’ visual literacy skills, arecognized compounding variable in the abstract nature of the molecular biosciences wherein students are inundatedwith a variety of representationscontaining difering levels of abstraction (1, 9–11). Several studies suggest that theserepresentationscan leadtostudent learning difculties and propagate misconceptions (4, 12–16). For example, spectacularanimations of molecular processes helptoconvey difcult concepts, yet they ofen provide a “wow” factor to the expert, while moving through the information too quickly for a noviceto process (17). Molecularvisualization sofware allowseducators and students aliketorotateand spin structures in virtual 3D space, but our assumption thatstudents areable to “see” the objects in 3D may be a false one, especially if they have never experienced similar, tangible structures in the real world (18). One possible explanation for these difculties is thatcurrent molecular biosciencecurricula include litle to no explicit instruction on interpreting, evaluatingand moving through levels of representations (4, 9, 19, 20). Physical models of abstract concepts can aid in developingvisual literacy skills that alsosupport the overall aim here – to develop robust learner mental models that enable students to think like scientists. Untilrecently, students’ primary exposuretophysical models was limitedto the use of small molecule modelingkits in a chemistrycourse. Advances in structural biology begantoreveal the 3D structure of macromolecules, but it was impossible for students toconstruct physical models of these complex structures. During thissame time, the development of molecularvisualization sofware made it possible for students to experiencevirtual representations of macromolecules in a computer environment. Today, advances in anadditivemanufacturing process knownasrapid prototyping –commonly referredtoas 3D-printing–havemade it possible toconstruct physical models of complex molecularstructures (Figure 1) (21). As 3D-printingtechnologycontinues toevolve, it is becoming possible to create modelswith complex color schemes in a variety of materialsfrom hard plastertofexible plastic and rubber. Te recent explosion of low-costflament-based 3D printers nowmakes it possible for molecular bioscienceeducators toacquire this modelingtechnology for as litle as several thousand dollars. 44 Bussey et al.; Biochemistry Education: From Theory to Practice ACS Symposium Series; American Chemical Society: Washington, DC, 2019. Figure 1. Physical models of molecular structures. A. An amino acid – constructed by students using a small molecule kit. Models B-E are “assemblies of atoms,” constructed by 3D printing. B. ATP with magnet- docked phosphate groups. C. A zinc fnger (PDB ID: 1ZAA) D. A four-subunit potassium channel (PDB ID: 1J95). E. Te 70S E. coli ribosome (PDB ID: 4V5D) with magnet-docked large and small subunits, three tRNAs and a short stretch of mRNA. Awide variety of modelshave been used in allscientifc disciplines torepresentcomplex, ofen abstract concepts. Moststudies on physical modelshave beenconducted in organic chemistry courses or K-12 education, with relatively few investigatingstudent learningand behavior with biomolecularphysical modelsat the undergraduate level. Among thesestudies, however, exists evidence for student learninggains in diferent molecular biosciencesetings. Intworelatedstudies, Oliver-Hoyoand authors report not only increasedstudentengagement but also integration of knowledgeacross biochemistryconcepts afer usingaseries of macromolecules with small molecules (22, 23). Another investigation demonstrated beter learninggains for students participating in a molecular dissection activity involving a 3D physical DNA modelcomparedto the comparative buildingactivity (24). In biology, higher learninggains for females arecitedafer usingaphysical protein model in one classsession (18), while anotherretroactivestudy usingseveral physical models relatedto the fow of genetic information demonstrates learninggains independent of gender (25). In fact, lowerachievingstudents demonstrated the highestabsolutegains (25). Tislaststudy is discussed in greater detaillater in this chapter. A few studies have examined the impact of combining physical modelswith virtual activities, and, although thereissome disagreement on the degree of impact, thesestudies do conclude with higher learninggainsassociatedwith the complementary use of thesevisual tools (26–28). Although theseresults are promising, moreresearch is needed on best practices with physical modelsand on howand whenstudents learn using thesetools. Much of this, however, will hinge on increased educator and student access to, and training with, physical models. Herein, we introduce threecasestudies involvingphysical models of biomolecules in anactive learning undergraduate classroom seting. Particularconsideration for the use of physical models for students requiringaccessibilityservices is presented in the fnal casestudy. Each casestudy stemsfrom and works closely with the MilwaukeeSchool of Engineering’s (MSOE) Center for BioMolecularModeling (CBM), and assuch we begin with an introductorycasestudy on the CBM’s history of engaging communities of students, educators and researchers in physical modeling. 45 Bussey et al.; Biochemistry Education: From Theory to Practice ACS Symposium Series; American Chemical Society: