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Use of Simultaneous-Synchronized Macroscopic, Microscopic, and Symbolic Representations To Enhance the Teaching and Learning of Chemical Concepts Joel W. Russell Department of Chemistry, Oakland University, Rochester, MI 48309 Robert B. Kozma SRI International, Menlo Park, CA 94025 Tricia Jones, Joann Wykoff, Nancy Marx, and Joan Davis University of Michigan, Ann Arbor, MI 48109 Introduction and Philosophy Lectures remain a key means for helping students understand chemistry. Lectures might help develop student understanding by providing (i) guidance and organization for study, (ii) motivation for study, (iii) explanations of concepts not easily mastered by self study, (iv) activities that help students recognize and correct misconceptions, and (v) opportunities for guided problem solving. In lectures, instructors can model how professional chemists observe and develop their understanding of chemical phenomena and how they solve problems. Chemists have extensive and selfconsistent mental models of chemical concepts and phenomena, which allow the recognition of general classifications of problems and applications of appropriate concepts, theories, and factual information to new situations (1, 2). Novice students have incomplete and inconsistent mental models and often represent scientific problems by their surface features in disconnected fragments not integrated by formal relationships (2–5). Many novices use a problem’s surface features to scroll through a “mental Rolodex” of equations and similar problems from text, lectures, and homework until a closest match is found to use for a quantitative solution to the problem (6). Lectures provide the opportunity for instructors to model expert problem-solving strategies and help students build up their own mental models with links between new and old concepts and with factual data. How can modern instructional technology assist instructors in helping students understand chemistry? Technology can expand the means for visualizing chemical phenomena and systems to the microscopic scale, to the world outside the classroom, and to phenomena with very fast or slow time frames. Using technology, particularly desirable classroom demonstrations and experiments need not be eliminated owing to high costs, safety concerns, or extensive preparation or cleanup times. Computer-based technologies can facilitate the achievement of the five means for enhancing student understanding listed above. Visualizations of chemical phenomena and concepts linked to microscopic-level animations and to examples from the students’ everyday life may aid the more visual learner and stimulate more students to achieve mastery-level understanding of chemical concepts. A prototype multimedia computer program discussed below, Multimedia and Mental Models in Chemistry (4M:CHEM), utilizes modern technology to make the classroom more interactive, stimulating, and able to assist students in building accurate mental models for chemical con-
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cepts and phenomena. The 4M:CHEM software allows students to participate in selecting experiments to test or illustrate ideas, in selecting parameters for variables in experiments, and in selecting viewing modes for observing outcomes of experiments. Both qualitative and quantitative experiments are included to assist the student in building chemical understanding and intuition as well as developing quantitative problem solving abilities. Design Rationale When this project began, most computer-based materials in chemistry were designed for use by students in computer labs for laboratory simulations, tutorial assistance, or drill and practice. This project focused on the opportunity to use the latest technology to provide lecture enhancement materials. An obvious advantage of computer-based materials is the ability to show molecular-level animations of chemical phenomena. Studies have shown that students who have the ability to visualize chemical phenomena at the molecular level develop good conceptual understanding (7–9). Turner (10) notes that many students who don’t succeed in chemistry courses “have never learned to visualize chemical systems or to make drawings to help solve problems”. Computer technology not only allows the modeling of how experts think microscopically but also allows the simultaneous representation of microscopic and macroscopic views of the same phenomena. Gabel (11) attributes the difficulties novices have in developing conceptual understanding in chemistry to one of three causes. First, chemistry teaching may simply stress “the symbolic level and problem solving at the expense of the phenomena and particle levels”. Second, if chemistry teaching occurs at the macroscopic, microscopic, and symbolic levels, “insufficient connections are made between the three levels and the information remains compartmentalized in long-term memories of students”. Third, students may fail to understand, even with instruction at all three levels that emphasizes the cross relationships, if the “phenomena considered were not related to the students’ everyday life”. This project provides explicit links between macroscopic, microscopic, and symbolic levels. An expanded version 2 now under development will provide additional links to phenomena in the students’ everyday life. 4M:CHEM utilizes a computer split-screen design with four windows that show simultaneously videos of real experiments, molecular-level animations of these experiments, symbolic representations, and graphs or diagrams of macroscopic properties or structures. These four windows can
Journal of Chemical Education • Vol. 74 No. 3 March 1997
Information • Textbooks • Media • Resources
Figure 1. Screen for heterogeneous equilibrium, LeChatelier’s principle, as ammonia is added. Upper left shows video of addition of ammonia solution to a saturated copper(II) iodate solution. Test tube in rack is saturated solution used for color comparison. Animation in upper right shows formation of Cu(NH3) 42+ and dissolving of solid at bottom as ammonia solution is added. Lines and bar graphs at lower left are color coded with symbols for species shown below graphs. Experiment to remove Cu2+ and viewing modes are selected with buttons in symbolic/control window at lower right.
Figure 2. Screen for quantitative pressure change experiment as gas is being added to cell. Upper left video shows close-up of sample cell in constant-temperature bath and oil manometer. Upper right is an animation of the dynamic equilibrium between NO2 and N2O 4 with shift toward a greater fraction of dimers as gas is added to the cell. Graphs on lower left show increases in partial pressures as cell is filled and shift in fractional composition. Experiments and viewing modes are selected with buttons in symbolic/control window at lower right.
be shown individually or in any combination. When multiple windows are activated, actions in each are synchronized. These synchronized views of chemical phenomena may be paused and restarted in order to aid discussions of connections between macroscopic, microscopic, and symbolic representations. Directly linking symbolic expressions, such as graphs and equations, to the corresponding real-world phenomena can facilitate students’ understanding (12). Multiple, coordinated representations can help students move progressively to more sophisticated mental models of scientific phenomena (13–15). These multiple representations can help students translate information expressed in one symbolic representation to understanding phenomena expressed in another representation. 4M:CHEM used in the classroom and for out-of-class explorations by small groups of students is designed to explicitly help students build mental links that strengthen their mental models or Bodner’s (16) chemical conceptual frameworks. A standardized screen layout was adopted to provide consistency between modules and have the screen structure itself promote links between representations of chemical phenomena. The screen is divided in quadrants as shown in Figure 1 with video, animation, graphical, and symbolic windows always appearing in the same quadrants. Choices of experiments, experimental parameters, and viewing modes are made with buttons in the lower right symbolic window. The square buttons labeled A, V, and G in the symbolic window are switches to turn on or off the displays in the animation, video, and graphical windows respectively. The “Go/Stop” button will start and stop the displays in the other windows. The “Pause” button will simultaneously pause all windows and restart them when again clicked with the mouse. Choices of experiments are made by activating one of the round buttons. If only the video window is opened, the window is shown at nearly full-screen size to enhance the visibility of finer details of experiments. For more complicated experiments tutorials are available with
this option noted by a “T” button appearing in the symbolic window. See Figure 2. Several design restrictions on the prototype modules were imposed by the availability of hardware and software when development began in 1991. The program shell was written for Macintosh computers in HyperCard. The initial release of Quicktime, used for movies of the animations and dynamic graphs, limited their display size to quarter-screen. Current compression/decompression hardware and software that can overcome window size limitations were unavailable. The animations and graphs were constructed using Macromedia Director. Video segments are from a videodisc and thus can be shown at high resolution without size restrictions. A VideoLogic LDV-4000 video board was used for overlay of computer displays and video. Other video boards, such as the Raster Ops 24STV, now allow similar performance at much lower costs. A new version of this software extended to other topics is under development by the principle authors and other colleagues. This version will use C++ and all digital components to enhance speed, provide cross platform capability, and eliminate the need for an expensive video card. Modules in Prototype Software After a survey of faculty teaching introductory chemistry at University of Michigan and Oakland University, the authors decided to focus the prototype modules on chemical equilibrium—a basic and central unifying concept of most introductory chemistry courses. This topic was also selected because earlier studies have shown equilibrium to be a topic for which many students maintain critical misconceptions after completing a year of college chemistry (Kozma, R.; Russell, J.; Johnston, J.; Dershimer, C., unpublished results; Hesse, J.; Anderson, C., unpublished results; 17, 18). The most common misconceptions identified in our earlier study were beliefs that equilibrium systems were static or contained equal amounts of reactants and prod-
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Information • Textbooks • Media • Resources preparation and cleanup. The pale blue color of the saturated copper(II) iodate soNo. of lution in the test tube in the rack in FigModule Topics Experiments ure 1 is compared with the dark blue soPHYSICAL Evaporation–Condensation 2 lution in the test tube to which ammonia H2O(l) ⇔ H2O(g) Vapor Pressure 7 data points solution was added. Rather than the soExamine Species 3 GAS PHASE lution getting lighter as copper(II) ions Chemical Reactions 2 N2O4(g) ⇔ 2 NO2(g) are removed (as most classes will predict), Pressure Change—Qualitative 2 the solution became much darker owing 8 data points Pressure Change—Quantitative, K p to formation of copper(II) tetraammonia Temperature Change—Qualitative 2 complex ions. Temperature Change—Quant., ∆H , ∆S 5 data points One method used in class by instrucSOLUTION Examine Species 2 tors to address the question of changes in Bromothymol blue Chemical Reactions 2 the iodate ion concentration is to discuss acid–base indicator LeChatelier’s Principle 2 the implications of removal of copper(II) HIn(aq) ⇔ H+(aq) + In{(aq) Equilibrium Constant, K c 6 data points ions upon the reaction quotient, Q, versus the solubility product, Ksp . Students HETEROGENEOUS Examine Species 3 should conclude that as the copper(II) Cu(IO3)2(s) ⇔ Chemical Reactions 2 Cu2+(aq) + 2IO{(aq) LeChatelier’s Principle 5 ions are removed from solution, Q beEquilibrium Constant, K sp 5 data points comes less than Ksp and solid dissolves to form additional ions. Alternatively and consistently, observation that no solid reucts (Kozma, R.; Russell, J.; Johnston, J.; Dershimer, C., unmains after addition of the ammonia solution implies that published results). Both of these misconceptions are directly the colorless iodate ions, originally in the solid, must all be addressed with the prototype software. in the solution. The graphical window shows the changes 4M:CHEM contains four completed modules on physiin concentrations of all ions with the line graph and the decal, gaseous, solution, and heterogeneous equilibrium and crease in mass of the solid with the bar graph. The display a nearly completed module for a system with three coupled has been paused in Figure 1 as the ammonia solution is beequilibria. In order to encourage use of 4M:CHEM as a lecing added. The lines and bar on the graphs are color coded ture enhancement supplement, experiments using exto the symbols of the species shown below the graphs. amples commonly discussed in textbooks were selected for The animation in Figure 1 showed initially a dynamic each module. Since quantitative experiments as well as equilibrium between solid copper(II) iodate at the bottom qualitative ones were desired for each module, choices were and copper(II) and iodate ions in solution. Averaged over further restricted to systems with measurable amounts of time the iodate ions have twice the concentration of the reactants and products at equilibrium. The chosen systems copper(II) ions. When the animation was paused to print Figure 1, ammonia solution was being added with formaand experiments are shown in Table 1. tion of the complex ions depicted. Upon restart, addition of ammonia solution continues until all solid dissolves. At this Example Qualitative Experiment point all iodate ions are in solution and all copper ions are For the heterogeneous equilibrium module, the bound with ammonia molecules in the complex ions. LeChatelier’s principle experiments allow five choices: add Some instructors, after showing first video only, will Cu(II) ions, remove Cu(II) ions, add iodate ions, remove ioshow video-animation, video-graph, and animation-graph to date ions, and add solid copper(II) iodate. If students and allow class discussion of the links between these representhe instructor elected the “remove copper(II) ion” experitations and finally all views together to discuss the advanment, an aqueous ammonia solution is added to a saturated tages and limitations of each representation. In this parcopper(II) iodate solution. Before showing the experiment, ticular example, owing to the speed of the complex ion forthe instructor might have the class discuss what changes mation reaction, time synchronization is maintained they would anticipate seeing in the video, animation, and throughout for the animation-graph but only with the time graphical windows. Would the color of the solution change? of addition of ammonia for the video-animation and videoWould the amount of solid change? If either or both of these graph. In the other three completed 4M:CHEM modules, changes are expected, how would they appear in the anitime synchronization is maintained throughout the experimation and the graph? Would the amount of iodate ion ments across all three viewing modes. change and in which visual representations could this be Figure 1 illustrates the advantages and limitations of observed? These questions are appropriate for class discuseach of these modes of representation. The symbolic winsion if a module of 4M:CHEM had been used earlier so that dow shows the chemical equation, now partially covered by students are familiar with the viewing modes (video, anithe graphical window. To chemists this equation shows by mation, graph). the double arrow symbol a chemical equilibrium between a For new experiments many instructors elect to show solid and dissolved ions. By implication chemists can invoke first only the video, to permit via class discussion an underall the properties of an equilibrium system from this form standing of what is actually observed. Using the nearly fullof the chemical equation. The video shows an initial lightscreen size video-only display, the absence of any solid in blue solution with rapid conversion to dark blue and disapthe final dark blue solution is more easily observed. In pearance of solid as the ammonia solution is added. The many lectures at University of Michigan and Oakland Unichange in concentration of iodate and a final equilibrium versity the video is preceded by a live demonstration of the state between the complex ion, copper(II) ion, and ammoexperiment. The 4M:CHEM video then allows the instrucnia must be inferred. The graph shows the changes in all tor the opportunity to pause the experiment to point out concentrations but appears static initially and at the end what has happened or is about to happen and to repeat the just as the video did. Only the animation clearly shows the experiment as many times as desired without additional dynamic nature of the initial equilibrium. Due to the magTable 1. Modules and Experiments for 4M:CHEM
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Information • Textbooks • Media • Resources nitude of the complex ion formation constant, the animation does not show any free copper(II) ions at the end. This is a limitation of using such a small number of species to make the animation viewable and programmable. A more significant limitation of the animation is the apparent fluctuation in numbers of ions during the initial equilibrium segment. This again results from the use of small numbers of ions. By the instructor discussing with the class each of these advantages and limitations, students can learn how each view contributes to the chemist’s mental model of a system at chemical equilibrium. Examples of other 4M:CHEM experiments were shown in a note in the NSF grant highlight column (19) and in a paper for the tested demonstration column of this Journal (Russell, J. Submitted for publication in J. Chem. Educ.). Example Quantitative Experiment
version from raw data to partial pressures in atmospheres for both species. The partial pressure of NO 2 is obtained from the absorbance data and that of N2O4 by subtraction of the NO2 partial pressure from the total pressure. If this experiment is used as the introduction to the equilibrium constant concept, various algebraic relationships between the partial pressures can be calculated before the usual equilibrium constant form is found. In Table 2 the original data, partial pressures, and equilibrium constant values are shown. Instructors may wish to use these results to discuss experimental uncertainties and the precision of the resultant equilibrium constant. Evaluation of Effectiveness of Software An initial examination of the effectiveness of the gaseous equilibrium module of 4M:CHEM was conducted using a pre-post test design with two lecturers in two sections of a general chemistry course at the University of Michigan. The pretests and posttests consisted of five constructed-response questions used in previous research (Kozma, R.; Russell, J.; Johnston, J.; Dershimer, C., unpublished results), for which students were asked to give brief answers, calculate answers, and draw diagrams. The pretest was given during the first 10 minutes of the first lecture and the posttest was given during the last 10 minutes of the second lecture. There were approximately 200 students enrolled in one section and 300 students in the second section. Of these 500 students, 295 attended both lectures and responded to both the brief pretest and the posttest given during the sessions. It should be noted that the tests did not count toward the students’ grade and quite likely provided little incentive for students to respond thoroughly (or at all) to the tests. Student responses were coded for content by a trained graduate assistant not involved in the design of the chemical content for this project. Students could have made any of 12 possible “correct” statements to the five open-ended questions. The mean pretest score was 3.18 (SD = 1.75) correct statements. The mean posttest score was significantly greater at 5.50 (SD = 2.49, t = 15.61, p < .0001). Of particular note were the responses on the first question, which asked students to “Define the term chemical equilibrium”. There were five correct codes for the answers to this question that were derived from the previous study (Kozma, R.; Russell, J.; Johnston, J.; Dershimer, C., unpublished results). Students could have accurately defined or described a chemical system at equilibrium by making one or more of the following statements: the system is dynamic, rates of the forward and reverse reactions are equal, con-
Figure 2 shows the screen for the gaseous equilibrium quantitative pressure change experiment. In this experiment a sample of NO2 -N2 O4 is added to a cell in a constanttemperature bath and the final total gas pressure is measured with an oil manometer. Since the experimental apparatus is new to most students, a tutorial is available that shows a schematic diagram along with a video view of the apparatus. When an item on the schematic diagram is pointed at and clicked with the mouse, the camera zooms in to the item on the video and the audio track of the videodisc describes the purpose of the item. Thus before running the experiment shown in Figure 2, students will know where to watch the cell developing a brown color as it is filled and where to observe changes in oil levels in the manometer. The tutorial uses the schematic diagram to step users through the procedure for filling the sample cell to a measured total pressure of gases. A final segment of the tutorial shows how the UV-vis spectrum of the sample is scanned and the absorbance found at a wavelength where only NO2 absorbs. A Beer’s law calibration graph is shown to illustrate how the NO2 partial pressure is found from the measured absorbance. The animation in Figure 2 shows gas entering from the top of the cell and, as pressure increases, the distribution of monomers and dimers shifting to more dimers. The graph not only shows the increase in partial pressures of both gases but the decrease in fraction of monomer in the pie graph. The pie graph was added after pilot classroom tests showed that few students could judge the change in distribution as both bar graphs increased. After the manometer level is constant, this display is stopped and the “take measurements” button in the symbolic window is activated. This action causes three new buttons to appear for Table 2. Quantitative Pressure Change Experiment To Determine Equilibrium reading the left and right sides of the Constant for N2O4(g) ⇔ 2 NO2(g) at 22 °C manometer and measuring the absorPressure C e l l M ano. Mano. Pressure Equil. bance of the sample at a wavelength in Run NO2 Length right side left side A 422.5 N2O4 Const.a the visible where only NO2 absorbs. ActiNo. ( c m ) ( m m o i l ) ( m m o i l ) ( a t m ) ( a t m ) (K ) vating the three data buttons sequen1 10.00 450 499 0.414 0.0067 0.0004 0.1 tially, the respective values for the manometer readings in millimeters of oil 2 10.00 423 526 0.824 0.0133 0.0015 0.12 and the absorbance at a particular wave3 10.00 398 552 1.189 0.0192 0.0030 0.12 length are recorded. When used in class, 4 10.00 378 571 1.408 0.0227 0.0050 0.10 generally only two sets of data points are recorded before all eight possible experi5 10.00 302 648 2.208 0.0356 0.0141 0.0899 ments are shown on a spreadsheet. The 6 3.00 202 750 1.010 0.0543 0.0246 0.120 spreadsheet is called by selecting “dis7 3.00 138 808 1.141 0.0613 0.0350 0.108 play” from a pull-down menu under “data” in the menu bar at the top of the 8 3.00 43 901 1.355 0.0728 0.0505 0.105 screen. The spreadsheet shows the conaMean, 0.111; SD, 0.010.
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Information • Textbooks • Media • Resources centrations are constant, all species are present, and a ratio of concentrations gives the equilibrium constant. Only 34% of the students made an accurate, error-free statement (a mean of 0.63 correct statements, SD = 0.87) in response to this question on the pretest. On the posttest, 56% (165 students) made one or more accurate statements. Of these, 154 or 52% of all students gave an accurate, error-free definition (mean of 0.84, SD = 0.87, t = 3.14, p < .0003). Particularly important was the decrease in “misconceptual” statements on this item. There were five codes for “misconceptual” statements that students could have made in response to this question. As a group, students made a mean of 0.50 (SD = 0.60) misconceptual statements on the pretest. As in our earlier research (Kozma, R.; Russell, J.; Johnston, J.; Dershimer, C., unpublished results), a large majority of these statements either asserted that at equilibrium, “concentrations of products and reactants are equal” or that “at equilibrium the reaction comes to a stop.” On the posttest, the mean was only 0.20 (SD = 0.43), a reduction of over 50% (t = {7.58, p < .0001). In summary, college students come into chemistry courses with an incomplete or inaccurate understanding about characteristics of chemical systems at equilibrium and about the influence of temperature and pressure on equilibrium. An initial assessment of 4M:CHEM in two lecture sections for two one-hour presentations showed an increase in students’ understanding of characteristics of systems at equilibrium and the effects of temperature on these systems. Our research on this software continues with evaluation studies of various sized lecture classes at several institutions and with laboratory experiments in which students are observed using the software individually and in pairs. The results of these studies will be reported in a follow-up article.
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Acknowledgment Major support for this project was provided by the National Science Foundation. Additional equipment support was provide by Apple Computer Corporation, University of Michigan, and Oakland University. Partial support for graduate students was provided by University of Michigan. Literature Cited 1. Chi, M.; Feltovich, P.; Glaser, R. Cognitive Sci. 1981, 5, 121–152. 2. Larkin, J. In Mental Models; Genter, D.; Stevens, A., Eds.; Erlbaum: Hillsdale, NJ, 1983; pp 75–98. 3. DiSessa, A. In Constructivism in the Computer Age, Forman, G.; Pufall, P., Eds.; Erlbaum: Hillsdale, NJ, 1988; pp 49–70. 4. Clement, X. In Mental Models; Genter, D.; Stevens, A., Eds.; Erlbaum: Hillsdale, NJ, 1983; pp 325–340. 5. McCoskey, J. In Mental Models; Genter, D.; Stevens, A., Eds.; Erlbaum: Hillsdale, NJ, 1983; pp 299–324. 6. Bunce, D.; Gabel, D.; Samuel, J. J. Res. Sci. Teach. 1991, 28, 505–521. 7. Nakhleh, M. J. Chem. Educ. 1993, 70, 52–55. 8. Nakhleh, M.; Mitchell, R. J. Chem. Educ. 1993, 70, 190–192. 9. Paselk, R. J. Chem. Educ. 1994, 71, 225. 10. Turner, K. J. Chem. Educ. 1990, 67, 954–957. 11. Gabel, D. J. Chem. Educ. 1993, 70, 193–194. 12. Brasell, J. J. Res. Sci. Teach. 1987, 24, 385–395. 13. White, B.; Frederiksen, J. Causal Model Progressions as a Foundation for Intelligent Learning Environments; Bolt, Beranek & Newman: Newton, MA, 1987. 14. White, B. Cognitive Inst. 1993, 10, 1–100. 15. Kozma, R.; Russell, J.; Jones, T,; Marx, N.; Davis, J. In International Perspective on the Psychological Foundations of Technologybased Learning Environments; Vosniadou. R.; DeCorte, E.; Mandel, H., Eds.; Erlbaum: Hillsdale, NJ, 1995; pp 41–60. 16. Bodner, G. J. Chem. Educ. 1986, 63, 873–878. 17. Bergquist, W.; Heikkinen, H. J. Chem. Educ. 1990, 67, 1000–1003. 18. Camacho, M.; Good, R. J. Res. Sci. Teach. 1989, 26, 251–272. 19. Russell, J.; Kozma, R. J. Chem. Educ. 1994, 71, 669–670.
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