Article pubs.acs.org/jchemeduc
Unraveling the Complexities: An Investigation of the Factors That Induce Load in Chemistry Students Constructing Lewis Structures Jessica M. Tiettmeyer,† Amelia F. Coleman,† Ryan S. Balok,† Tyler W. Gampp,† Patrick L. Duffy,† Kristina M. Mazzarone,‡ and Nathaniel P. Grove*,† †
Department of Chemistry and Biochemistry, University of North Carolina Wilmington, Wilmington, North Carolina 28403, United States ‡ Science Department, Cape Fear Community College, Wilmington, North Carolina 28401, United States ABSTRACT: Mastering the ability to construct and manipulate Lewis structures is an important first step along the journey to reaching representational competence. Lewis structures serve as a convenient organizational scheme that can help students to scaffold their chemical knowledge and help them to apply it to predict a variety of physical and chemical properties. Our previous research documented the many problems that students encountered in developing these skills and suggested that cognitive load may play an important role in the successful construction of Lewis structures. This study sought to better understand the structural characteristics and complexities that contributed significantly to the cognitive load of chemistry students drawing Lewis structures and to determine how those load-inducing characteristics changed as students gained additional chemical expertise. The results of the inquiry show that the inclusion of nearly any structural characteristic induced a significant increase in cognitive load for novice chemistry students, but these trends are mitigated as students gain additional chemical expertise. KEYWORDS: First-Year Undergraduate/General, Second-Year Undergraduate, Lewis Structures, Chemical Education Research FEATURE: Chemical Education Research
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INTRODUCTION In his seminal 1916 paper, The Atom and the Molecule, Gilbert Lewis, one of the most influential chemists of the late 19th and early 20th centuries, stated that it “is indeed the substances which are distinctly polar...which constitute...a class of liquids which are called abnormal with respect to numerous properties such as critical point, vapor pressure, heat of vaporization, viscosity, and surface tension.”1 This seemingly innocuous statement is a fundamental truth that underlies all of chemistry instruction: the form of matter, that is, its chemical composition, and its function are irrevocably intertwined. Almost 100 years later, the importance of this concept is evident in nearly every facet of primary, secondary, and tertiary science curricula. For example, the Next Generation Science Standards, which were developed and are used by 26 states to guide K−12 science education2 include “Structure and Function” among the main ideas necessary to help students not only develop a robust understanding of science, but to also create “informed citizens in a democracy and knowledgeable consumers.”3 A similar “Structure and Function” anchoring concept is included in the Undergraduate Chemistry Anchoring Concepts Content Map (ACCM) developed by the American Chemical Society Exams Institute for general chemistry.4 It is important to note that like all materials created by the Exams Institute, the ACCM was a community effort, a living document shaped with input from approximately 100 university chemistry instructors.5 As the central science, chemistry is at the forefront of teaching the interconnectivity of structure and function, and as such, it is imperative for chemistry students to develop as meaningful an understanding of these topics in their introductory courses as possible. © XXXX American Chemical Society and Division of Chemical Education, Inc.
For experienced chemists, the connection process described above happens almost without thought; they “see” a molecule and immediately begin to think of how it might behave chemically. For their students, however, this process is fraught with difficulty and according to Cooper et al. involves at least six distinct steps:6 (1) construct an appropriate structure that contains enough information to make further inferences (typically taught using a set of rules) showing where all the bonds and nonbonding electrons are located, (2) translate the twodimensional structure to a three-dimensional structure (using another set of rules), (3) use knowledge of relative electronegativities of atoms to predict bond polarities, (4) use the three-dimensional structure and bond polarity information to make inferences about the overall polarity of the molecule, (5) use this information to determine the types of IMFs that cause interactions between molecules, and (6) use all this information to predict how molecules will interact. What is abundantly clear from this description is the sheer amount of information that students must simultaneously juggle to successfully engage in one of the most important and central tasks to the discipline. Further, according to the first step in the sequence, students must “...construct an appropriate structure that contains enough information to make further inferences...”.6 In other words, students must be able to generate valid Lewis structures before they advance to the Received: May 18, 2016 Revised: January 7, 2017
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situations where that limit is reached or even exceeded, learning can be severely hampered.
subsequent, and arguably more meaningful, steps. As part of our initial work to better understand students’ construction and use of Lewis structures,7 we observed a statistically significant decline in success rate, from approximately 80% to around 30%, between formulas containing six atoms and seven. These results prompted us to question the role that cognitive load might play in this process, and this paper reports our initial findings in this area.
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TEACHING AND LEARNING OF LEWIS STRUCTURES
Although our understanding of structure and bonding has changed with the emergence of quantum mechanics in the 1930s, many of the ideas Lewis outlined in his aforementioned paper are still pertinent and applicable today. He suggested, for example, that each atom consisted of a “cube”, known today as an electron cloud, outside of a “kernel”, known today as a nucleus.1 This cube required eight electrons to be complete, and atoms made bonds with each other in an effort to fill its cube (Figure 2A).1 Using this “eight-electron rule,” Lewis was able to predict which elements were likely to bond with each other and noted trends in the physical properties among atoms with the same number of electrons in their cube.1 Over the years, representations that have included the cube and kernel have been replaced by the more familiar dots and dashes as shown in Figures 2B and C, but it is remarkable how little Lewis’ fundamental ideas about covalent bonding have changed. For well over 40 years, reports in this Journal have described alternative instructional strategies intended to help students better develop their abilities to draw and manipulate Lewis structures.15−34 The impact of these strategies, however, is questionable as our previous research has shown that even fairly simple structure-creation tasks can still be quite challenging for students.7 In trying to engage in these tasks, which often required skills, knowledge, and experiences that they had yet to develop, students frequently relied on a set of homegrown rules and heuristics.7 Symmetry, for example, became an incredibly important guide when trying to determine the placement of atoms in the structure, to the point where an incorrect, symmetrical atomic arrangement was preferred to a correct, asymmetrical one.7 Beyond the issues surrounding students’ construction of Lewis structures are the problems associated with their use. It is important to note that the construction of a valid Lewis structure is not necessarily an end goalLewis structures are merely the means by which students can begin to predict macroscopic phenomena. Unfortunately, many students do not explicitly think about using Lewis structures for this purpose.7,35 Our original work with Lewis structures revealed that in some cases, over half of the student participants, including graduate students, failed to recognize that Lewis structures could be used to help predict molecular shape, relative melting and boiling points, and the types of intermolecular attractions that could exist between molecules.7 A more extensive study conducted by Cooper, Underwood, and Hilley35 that resulted in the development of the Implicit Information from Lewis Structures Instrument (IILSI) documented a similar disconnect among both general chemistry and organic chemistry students at two different institutions. The authors concluded that this inability to make inferences about the information that can be provided by Lewis structures “is a major impediment to learning chemistry...” and one that could only be remedied by modifications in how the material is taught, and perhaps as importantly, assessed.35
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LIMITS ON SHORT-TERM (WORKING) MEMORY Psychologists have theorized for well over a century that there exists a distinction between a limited-capacity primary memory (now more commonly referred to as short-term or working memory) and an unlimited-capacity secondary memory.8 As early as the mid-1950s, George Miller, in an attempt to quantify the limits on working memory, suggested that the average adult learner could simultaneously process seven plus or minus two pieces of information.9 In more recent years, there has been vigorous debate among cognitive psychologists in regards to the limits proposed by Miller. Cowan, for example, has posited that the working memory’s capacity limit is actually much smaller, more likely an average of about four pieces of information.10 Others have suggested that the limited-number capacity model of working memory that has been the standard paradigm for decades does not adequately explain more recent behavioral and neural evidence.11−14 Instead, there is increasing support for a resource-limited model of working memory, that is, working memory is limited not by an absolute number of items, but by an absolute number of cognitive resources available for processing.11−14 As such, in instances where the pieces of information being processed are relatively simple, more can be managed simultaneously. In contrast, in cases where the material requires commitment of more substantial cognitive resources, any available reserves can be dynamically reassigned to meet the increased demand. This subsequently results in fewer, more cognitively complex pieces being managed in the working memory. The differences between the two proposed models are illustrated in Figure 1. Regardless of the true nature of working memory, there is little debate surrounding the fundamental assertion that it is limited in some manner, and in
Figure 1. Models of working memory. (A, B) Examples of numberlimited models: (A) an average of seven pieces of information can be processed simultaneously as classically suggested by Miller9 and (B) an average of four pieces of information as more recently suggested by Cowan.10 (C, D) A resource-limited model whereby cognitive resources can be dynamically assigned based on need. Because of this, the number of pieces of information that can be processed simultaneously varies.11−14 B
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Figure 2. Evolution of the Lewis structure. (A) A depiction of Lewis’ cube for the formation of a molecule of iodine; (B) a Lewis dot symbol for a molecule of iodine; and (C) a Lewis structure for a molecule of iodine that replaces the shared electron pair with a line.
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RESEARCH QUESTIONS Given the essential role that Lewis structures serve, especially in introductory chemistry courses, in helping students make connections between structure and function, it is more important than ever to understand the challenges they face in learning to construct and use them. Our previous research efforts,7 along with those of others,6,35 have served to deepen and broaden our understanding of these issues; however, none of this work has focused specifically on matters surrounding cognitive load. It was the goal of this study to do just that, and in so doing, answer the following research questions. (1) What structural characteristics of the Lewis structure induce a significant increase in cognitive load for chemistry students drawing Lewis structures? (2) How do the load-inducing characteristics change as students gain additional chemical expertise?
Given the goals of the research, each student was asked to construct Lewis structures while having their heart rates continuously monitored using a Scosche myTREK wireless heart rate monitor. The monitor was attached to the participant’s nonwriting arm using the included strap, and data were sent wirelessly via Bluetooth every second to either an Apple iPod touch or an iPad. Students were asked to construct ten Lewis structures during the course of their interview: H2O, NH3, N2F5+, P2S3, SI6, HSO4−, CBr4, SiF4, CO, and C2H3O2−. These ten structures were specifically selected so as to represent a range of difficulties, to include both single- and multiple-central atom molecules, atoms from beyond the second period of the periodic table (a structural characteristic that we noticed in our previous research seemed to induce a higher than expected amount of cognitive load), structures that require multiple bonds, expanded octets, and both charged and neutral species. Table 1 summarizes the specific structural characteristics assigned to each structure.
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METHODS To address the questions outlined above, a valid and reliable method of measuring cognitive load is required. The research literature is replete with many such approaches, but in general, they are typically grouped into one of three categories: performance techniques,36 subjective techniques,37−39 and physiological techniques.40−50 Our own work, which is described in detail in a previous publication,50 has focused on physiological techniques and has shown that monitoring changes in heart rate can be used to measure corresponding changes in cognitive load. In short, this technique relies on the fact that as working memory fills, stress is placed on the learner, and as a result, heart rate increases. Thus, chemistry problems that are of higher load will induce a larger change in heart rate than chemistry problems of lower cognitive load. Data were gathered during the 2014−2015 academic year from three groups of students at a public, comprehensive university in the southeastern United States: general chemistry 1 students (N = 36) toward the end of the semester and approximately a week after being tested on their understanding of Lewis structures; organic chemistry 1 students (N = 56) approximately half way through the semester; and senior chemistry majors (N = 19) enrolled in a senior seminar course. The general chemistry students were mainly freshmen (approximately 60% freshmen, 25% sophomores, and 15% juniors and seniors); organic chemistry students were primarily sophomores (65% sophomores and 35% juniors and seniors). Both groups included students majoring in chemistry, biology, marine biology, environmental science, exercise science, and nursing. The sex distribution of the participants generally reflected that of the university as a whole, approximately 60% female and 40% male.
Table 1. Structural Characteristics Assigned to Each of the Ten Lewis Structures Structures
a
NH3 N2F5+ P2S3 SI6 HSO4− CBr4 SiF4 CO C2H3O2−
Multiple Central Atoms
Atoms beyond 2nd Period
Multiple Bonds
Charged Species
Expanded Octets
b Present Present b Present b b b Present
b b Present Present Present Present Present b b
b b Present b Present b b Present Present
b Present b b Present b b b Present
b b b Present Present b b b b
a
H2O was excluded from analysis. bCharacteristic not present in this structure.
Each formula was placed at the top of a separate sheet of paper, something that was done to prevent participants from considering more than one structure simultaneously, and students were instructed to draw their Lewis structures in the space below the formula. As students completed their Lewis structures, which were given to them in the order written above, the start and end times were recorded for each problem so that we could subsequently match any heart rate fluctuations with the structure that was being constructed at that particular moment in time. Once finished with the structure, the researcher removed the sheet, and the participant was engaged in informal conversation for a short period of time. This brief cool down period, which lasted anywhere from 15 s to a minute, was built into the interview so that the participant’s C
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intimidated by the research, and therefore, the heart rate data gathered for the successive structures less influenced by any residual stress or discomfort. A multiple regression analysis was performed on the three sets of data to look for significant trends among the various structural characteristics present in the final structures and the changes in heart rate induced by creating each structure. Before these analyses were performed, however, the data sets were subjected to a number of additional tests to ensure that they did not violate the underlying assumptions inherent in using this particular approach.51 Specifically: • The data were analyzed for outliers using the Outlier Rule.52,53 In all, four points were removed from the general chemistry 1 sample, none was removed from the organic chemistry 1 sample, and two were removed from the data collected from the senior chemistry majors. • The homoscedasticity, that is, the uniformity of the variance associated with the dependent variable (change in heart rate) across the entire range of the independent variable, was confirmed. • The correlations among the independent variables were calculated, were shown to be quite small, and as such, we concluded the data did not exhibit multicollinearity. • Finally, the residuals were shown to be normally distributed.51 The results of the multiple regression analyses, both p-values and standardized β-values, are included in Table 2. The pvalues provide insight into whether the specific structural characteristic contributed significantly to the cognitive load, while the standardized β-values indicate how many standard deviation units more load inducing that characteristic is. For example, the inclusion of an atom from beyond the second period of the periodic table significantly increased the cognitive load for the organic chemistry 1 students by 0.231 standard deviation units. Note that in some cases, the standardized βvalues are negative. In these instances, the inclusion of that structural characteristic in the structure actually made the problem less load inducing.
heart rate could return to normal, resting levels. The resting levels were unique to each participant and were determined by the researcher through continuous, real-time monitoring of the participant’s heart rate during the interview. The institution’s Institutional Review Board approved all phases of this research, and informed consent was gathered from all participants before any research activities were initiated. Data Analysis
Figure 3 presents raw heart rate data collected from one of the organic chemistry student who participated in this research.
Figure 3. Raw heart rate data collected from an organic chemistry student.
The dashed, horizontal line indicates the resting heart rate for this participant, and the solid, vertical lines divide the data according to the time the student spent constructing each Lewis structure. Note that the order in which Lewis structures were provided to each participant was always the same: H2O, NH3, N2F5+, P2S3, SI6, HSO4−, CBr4, SiF4, CO, and C2H3O2−. For each Lewis structure constructed, the maximum heart rate change, known as the peak load, was determined by subtracting the largest recorded heart rate from the participant’s resting values. These peak loads were subsequently converted into percent changes by dividing the increase in heart rate by the resting heart rate that was established as a result of the cool down period. This was a necessary conversion given that all participants had a different resting heart rate and a unique response to each problem. As an example, for the construction of SI6 (Q5 in Figure 3), the peak load was determined to be 84 beats per minute; the resting heart rate was 61 beats per minute. This represented a 37.7% change (((84−61)/61) × 100). The regression analyses described in more detail in the Results and Discussion section were all performed using these percent changes.
Table 2. Results of the Multiple Regression Analyses Structural Complexity Multiple central atoms Atom beyond second period Multiple bonds Charged species
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Expanded octets
RESULTS AND DISCUSSION In all, over 1100 Lewis structures and their corresponding heart rate changes were gathered from the three groups of students that participated in this research: 360 from the general chemistry 1 students, 560 from the organic chemistry 1 students, and 190 from the senior chemistry majors. Note that for all analyses described below, the results collected for water were excluded. This particular structure was used merely as an introduction to the research activity and was specifically selected because of its ubiquitous nature in the chemistry curriculum. In this way, we hoped that students would be less
General Chemistry (N = 320) p < 0.001, β = 0.581a p = 0.047, β = 0.198a p < 0.001, β = 0.264a p = 0.023, β = 0.233a p = 0.080, β = 0.152
Organic Chemistry (N = 504)
Senior Chemistry (N = 169)
p = 0.005, β = 0.138a p < 0.001, β = 0.231a p = 0.558, β = 0.029 p = 0.367, β = 0.041 p = 0.081, β = −0.128
p = 0.665, β = 0.023 p = 0.770, β = −0.016 p = 0.689, β = 0.017 p = 0.471, β = 0.031 p = 0.144, β = −0.069
a
Indicates a statistically significant structural contributor to cognitive load.
In considering the results of the regression analyses, there are noticeable differences among the three groups of students in the structural characteristics that generated increased cognitive load. Not surprising given their limited representational experience, the addition of nearly any structural complexity caused significant increases in cognitive load for the general chemistry students who constructed Lewis structures for this D
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the work of Talanquer58−62 and others,63,64 the reliance on such heuristics can frequently lead students to focus on irrelevant features, for example, the symmetrical layout of the molecule, and may ultimately lead to cognitive biases and to incorrect answers. Additional research is required to better understand how these Lewis structure-specific heuristics develop and to test approaches that will assist students in understanding their limits.
research. In particular, Lewis structures that required students to string together multiple central atoms were especially problematic, inflating the average cognitive load of the activity by nearly 0.6 standard deviation units. The notable exception was the structures that included expanded octets. Despite the problems that this concept often causes for students in subsequent chemistry courses (how many organic chemistry instructors, for example, have borne witness to rampant and inappropriate expanded octets on carbon?),7 this structural characteristic did not greatly add to the load. As students continued their study of chemistry into a second year, the regression analyses revealed that they grew more proficient at manipulating certain structural characteristics in working memory while creating their Lewis structures. As such, features that had initially caused spikes in their general chemistry counterparts, specifically, molecules that contained multiple bonds and charged species, were no longer significant contributors to load. Molecules that contained more than one central atom and atoms from beyond the second period of the periodic table still triggered significant increases for our students, although the β-values demonstrate that the presence of multiple central atoms within the Lewis structure was not nearly as load inducing as it was previously. Finally, none of the structural characteristics investigated in this study caused significant increases in cognitive load for the senior chemistry students. The trends outlined above show that not all structural characteristics induce significant cognitive load for students, and for those that do, the length and magnitude of their impact varies. Some seemed to mitigate themselves within about a semester of Lewis structures being introduced toward the end of general chemistry 1. Others, however, persisted for much longer, albeit all had abated by the time students reached their senior year. These results are particularly problematic considering that for many students, general chemistry 1 may be the only chemistry course taken during their academic careers. In such instances, students may not be presented with additional opportunities to hone their structure creation skills, and as such, their abilities to simultaneously process the information necessary to construct valid Lewis structures may stagnate. This reality highlights even more clearly the importance of the educational experience students receive in their introductory chemistry courses and the absolute need to focus on the overarching and foundational skills and concepts that underlie our discipline.54 Our results suggest that chemical educators interested in helping students develop a more robust and meaningful understanding of how to compose and use Lewis structures would be well-served by directing more attention and time to strategies that students can employ to appropriately deal with larger molecules. In addition, sustained emphasis on periodicity may assist students in fashioning those Lewis structures that contain less familiar elements from beyond the second period. Left to their own devices, previous research has shown that students utilize a host of heuristics to address these issues.7 Some may view these heuristic “shortcuts” as evidence of a lack of effort or motivation by students; however, their development and use is a natural mental operation that we all employ, and at the core, can serve as an effective strategy to simplify highly complex operations.55−57 They often allow us to strip away extraneous information and focus more intently on what is most important about a problem, and do so relatively quickly.55−57 Unfortunately, as has been well documented in
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CONCLUSIONS The connection between structure and function is one of the most important unifying concepts in science, and Lewis structures serve as the starting point for this often long and arduous journey on the way to representational competence. They can function as convenient tools that when utilized to their full potential allow students to organize their chemical knowledge and help them apply it to predict a host of physical and chemical properties. Previous research7 has chronicled the many challenges students faced in constructing these essential representations and highlighted the myriad strategies they relied upon in the absence of a robust prior knowledge base to aid them in this process. The current study sought to understand the specific structural characteristics that contributed to cognitive load as students constructed Lewis structures and to document how those characteristics changed as students gained additional chemical experience. Initially, the addition of nearly any structural complexity introduced a significant increase in cognitive load, but as students deepened their understanding of fundamental chemistry concepts and progressed through more advanced coursework, the number of characteristics that induced load steadily diminished until eventually none contributed significantly by the students’ final year. On the basis of the results of this inquiry, we hypothesize that targeted instructional strategies that focus on assisting students develop approaches for better coping with molecules with more than one central atom and with central atoms from beyond the second period of the periodic table may be particularly effective in lowering the overall cognitive load of the Lewis structure construction process for many novice students. This in turn could liberate much needed space in working memory for students to attend to the other tasks necessary to make meaningful use of these essential representations. At the same time, it is important to better understand the full range of heuristics that students use as they create Lewis structures and to ensure that their limits are clearly understood. In the absence of such supports, students may never fully develop their skills, and as a result, never reach the ultimate goal: the ability to extract meaningful information from Lewis structures and to be able to use it to derive significant physical and chemical information.
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AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. ORCID
Nathaniel P. Grove: 0000-0003-4354-6655 Notes
The authors declare no competing financial interest. E
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ACKNOWLEDGMENTS The authors thank Dr. Michele Parker for her help with the statistical analyses and the student volunteers for their participation. This research is based upon work supported by the National Science Foundation under Grant Nos. DUETUES 1043129 and 1122661. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
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Journal of Chemical Education
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DOI: 10.1021/acs.jchemed.6b00363 J. Chem. Educ. XXXX, XXX, XXX−XXX
