Article pubs.acs.org/jchemeduc
The Effect of Viewing Order of Macroscopic and Particulate Visualizations on Students’ Particulate Explanations Vickie M. Williamson,*,† Sarah M. Lane,† Travis Gilbreath,† Roy Tasker,‡ Guy Ashkenazi,§ Kenneth C. Williamson,∥ and Ronald D. Macfarlane† †
Department of Chemistry, Texas A & M University, College Station, Texas 77823-3255, United States School of Natural Sciences, University of Western SydneyHawkesbury Campus, Penrith South DC, 1797 New South Wales, Australia § The Israel Center for Excellence through Education, Jerusalem 96408, Israel ∥ Department of Construction Science, Texas A & M University, College Station, Texas 77843, United States ‡
ABSTRACT: A prior study showed that students best make predictions about the outcome of opening a valve between two flasks containing a fluid or vacuum when they view both a demonstration video and a particulate animation, but the study showed no influence from the order in which these visualizations were used. The purpose of this current research was to study the effect of the order of visualization on students’ particulate-level explanations. For this study, first-year general chemistry students in a south-central university in the United States were asked to choose, or type in their own explanations, for three experiments involving diffusion− effusion. Student ability to focus on particulate explanations was investigated after viewing either a macroscopic demonstration or an animated particle view. Students were directed to a Web site where they received one of two randomly assigned treatments. One group of students was shown the particulate animation first, followed by the macroscopic demonstration. For the other group, the order was reversed. Student explanations were assessed after each view. Finally, both groups were shown a side-by-side view of the animation and demonstration and their explanation was assessed one final time. Results showed that the order of visualizations did make a difference, with the macroscopic view followed by the particle view yielding significantly more particulate explanations. KEYWORDS: Chemical Education Research, First-Year Undergraduate/General, Learning Theories FEATURE: Chemical Education Research • Using physical models to represent atoms such as model kits, magnets, modeling compound, and so on • Using computer modeling programs to view and rotate molecules • Using animations to show particles in a chemical process • Requiring students to draw or animate particle behavior • Using interactive computer models that allow students to control particle behavior Animations were of interest in this study and are one of the most frequently used techniques for particle behavior in the chemistry classroom. For example, a number of studies have found the use of particulate animations to result in better conceptual understanding of chemistry (e.g., refs 4−6). In his review of the literature on animations, Sanger concluded that animations should be used in the classroom when its attributes are in line with the learning goals.7 As some positive results have been reported with the use of demonstrations and with particulate animations, a natural progression is to investigate the use of both techniques. Burke, Greenbowe, and Windschitl8 in their article on the development and use of animations noted that the use of animations of short duration and the use of demonstrations with animations could be effective. A few previous studies have shown that complementary use of video (demonstration) and animation (particulate) can increase students’ understanding of chemical and physical phenomena (e.g., refs 9−11).
T
his study examines the effect of the order of visualization on students’ particulate-level explanations for three experiments involving diffusion−effusion. Specifically, we investigated the ability of first-year general chemistry students to focus on particulate explanations after viewing either a macroscopic demonstration or an animated particle view. The literature review that follows informed the research and provided a framework for this study.
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LITERATURE BACKGROUND In their review of the literature, Williamson and Jose1 discussed a number of techniques reported to help students form mental images of chemical phenomena at the macroscopic level (images similar to the visual observations that students could perceive). The techniques that an instructor might use could include: wet laboratories, demonstrations of chemical phenomena, and simulations of laboratory experiments. Increases in student understanding of chemistry were reported in the literature for all of these methods. Of course, questions of how these techniques were used and with what populations often moderated the results. In some studies, demonstrations have been shown to help with attention (e.g., ref 2), and understanding (e.g., ref 3). Demonstrations were of interest in this study. Williamson and Jose1 also discussed a number of visualization techniques found in the literature that were reported to help students better visualize particle behavior. These techniques included: • Asking students to role-play as particles in a chemical process © 2012 American Chemical Society and Division of Chemical Education, Inc.
Published: June 21, 2012 979
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In one study by Velazquez-Marcano et al.,12 students were asked to predict the outcome of several experiments based on video demonstrations and particulate animations. The study found that seeing a second visualization (video or animation) increased the students’ probability of correctly predicting the outcome of an experiment, but that the order of the visualizations did not matter. The study investigated students’ ability to correctly predict the outcome of diffusion−effusion phenomena. Researchers have found that students hold misconceptions about the behavior of gases and liquids. In her review of the misconception literature, Nakhleh13 noted that in some of the earliest research, gases were investigated and that misconceptions concerning gases existed at all grade levels. Nakhleh also discussed other misconceptions, many of which centered on the particulate nature of the phases of matter.13 Another study was done by Simpson using the same visuals as Velazquez-Marcano et al. to gauge student understanding of chemical phenomena by testing students’ explanations after viewing either a video or an animation.14 Simpson’s study found that student particulate explanations were more detailed after viewing the video before the animation rather than in the opposite order. Unfortunately, this study had a major flaw. In the animations used for the study, the word, “molecule” was used as a part of the animation legend, and the correct particulate explanation for the phenomena also contained the word “molecule”. It is believed that some students may have simply chosen the explanation with the matching word rather than choosing their own explanation. Students have difficulties giving correct particulate-level explanations. For example: Williamson, Huffman, and Peck15 tested over 1000 first-year general chemistry students using six concepts dealing with dissolution, diffusion, and effusion with six versions of an instrument, which progressed from everyday to scientific content and randomly covered all six concepts. No strong correlations were found between the students’ logical reasoning ability and their use of particulate terminology in their written explanations. This study found that increased amount of scientific terminology in the question did not really affect student responses; instead, students were cued to use particulate terminology in their responses as soon as any particulate terminology was used. None of the concepts in this study showed a high percentage of completely correct responses using the particulate terminology. When cued by the question, only 50−60% of the students used particulate terminology, but less than 3.5% gave scientifically correct explanations with particulate terms.15 The study in this paper used the same visualizations and experiments that were used in the Simpson study, except that the word “molecule” was deleted. The purpose was to investigate the particulate explanations that students give after various visualizations and to investigate any effect of order. Few studies have been done to investigate the effects of the order in which visualizations are used. The current study investigated the effect of order with these two techniques (video demonstration and particulate animation). Russell et al.16 used a computer program that simultaneously displayed both a video and a particle animation, along with graphical displays. In this study, the authors reported that students’ conceptual understanding and ability to create dynamic mental models improved. In their computer program, students could either play the visualizations independently or simultaneously. There was no control for how the visualizations
were used by students. The current study also investigated the use of simultaneous visualizations.
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THEORETICAL FRAMEWORK We used a constructivist theoretical framework for this study. Originally, many educators believed that knowledge could be transferred intact from the mind of the teacher to the mind of the learner.17 Jean Piaget questioned this idea. Although not an educator, Piaget was a cognitive psychologist researching the ways in which people think and acquire new ideas. Piaget believed that instead of intact transfers, learners build new knowledge through a process of assimilation and accommodation.18 This process involves the creation of schema or mental frameworks. A learner has a set of schema that he or she brings to any given learning environment; a person is not a blank slate. When learners are presented with new information or ideas, they first assimilate the ideas, and then attempt to accommodate the new ideas with their preexisting schema. Learning occurs when schema are modified or created to accommodate the new ideas. Through this process, new knowledge is constructed in the mind of the learner, hence, the name constructivism. Since Piaget’s original work in the area, a great number of psychologists and educators have adapted and evolved the idea. Today, constructivism (in its many forms) has been applied to many different fields. In contrast to Piaget’s learner-centered theories, Vygotsky emphasized the role of the teacher rather than the learner.19 Vygotsky’s key contribution is called the zone of proximal development, which is the idea that learners have several different levels or zones in their process of acquiring new knowledge. At the lowest level is the preexisting knowledge or schemas; learners use these schemas to relate prior knowledge to new knowledge that is at the edge of their understanding. While this is similar to Piaget, Vygotsky acknowledges the role of the teacher in facilitating learning at the edge of students’ understanding. If learners are not guided in this, they will either fall back into their previous schema or fail to advance in their understanding, or they will step into an area that they cannot connect to any prior knowledge and be lost. The basic premise of constructivism is that students build from prior knowledge in order to learn new concepts and ideas.20 The ideas of constructivism have been applied to chemistry and used as a tool both for teaching and for exploring the way in which learners understand complex chemical concepts. A number of studies have investigated the application of constructivism to chemistry.4,5,21,22 Of particular interest are the different levels of representations in chemistry. Johnstone first suggested that there are three “thinking levels” in chemistry.23 The most concrete operational level is the macroscopic observation of structure and processes with the senses. The macroscopic level is often predicted to be the easiest for learners to understand; however, it also is an area of misconceptions.23 The next level of chemical representation is the molecular or particulate level. Learners construct and apply their mental models of what is happening at the molecular level of a particular phenomenon. The most abstract level of representation in chemistry is the symbolic level, where concepts and phenomena are communicated through chemical symbols and mathematics. Historically, students have had a great deal of trouble shifting their understanding at one level of chemical representation to the other levels.24 When attempting to teach learners, strong evidence shows students have difficulty 980
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The AV group observed the visualizations in the opposite order with the animation first and the video second. Finally, both groups observed a combination of the animation and video in a side-by-side view.
making the connections between the representational levels (e.g., ref 25). In the quest to increase connections between representational levels, Kozma and Russell26 suggest that use of visualization techniques helps students develop representational competence. The authors believe that the development of representational competence is progressive, but not automatic or uniform, and is content-dependent. Further, the development of representational competence is similar to Vygotsky’s theories on cognitive development, for example, the person’s development is influenced by interactions with material and social resources in a given situation, leading to the idea that a person has a zone of proximal development rather than a rigid stage from which he or she can operate. This leads the authors to conclude (ref 26, p 141): “We recommend the widespread use of these visualization resources in chemical education”. The current study probed the effect of macroscopic-level visualizations (video) and particulate-level visualizations (animation) on students’ particulate-level explanations. It was also of interest to determine whether the order in which the visualizations are shown has an effect on students’ particulate explanation. Additionally, the researchers were curious about the effects of simultaneously showing both visualizations. The topics of diffusion−effusion were chosen, as this study is an extension of the Velazquez-Marcano et al.,12 and Simpson studies.14
Instruments
The Test of Logical Thinking (TOLT) was administered earlier in the semester as an optional quiz, and was used to check that treatment groups were at a similar level of logical thinking ability. The TOLT scores range from 0 to 10. The test contains two items for each of five areas. These areas are included in the TOLT: proportions, control of variables, probability, correlations, and combinations.27 Significant relationships between TOLT scores and other measures were originally reported, which included integrated science process skills, the Scholastic Aptitude Test, and visualization tests, such as the paper folding test and the surface development test.27 Logical thinking has been used to establish group equivalency in other studies (e.g., refs 6 and 12). The primary instrument for this study was delivered online. The online instrument consisted of three main sections: an introduction, a biographical section, and the testing section. The introduction served to inform students of the study and remind them that it was an optional quiz credit; all internal review board confidentiality and permission requirements were met. Students were allowed as much time as they wished to complete each section; however, they were not allowed to return to previous sections or pages within a section. This was done through scripting, which did not allow right-mouse clicks or the menu to appear at the top of the browser. The data collected were inserted into a database but could not be updated, ensuring that students could not change their responses after moving forward in the instrument.
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RESEARCH QUESTIONS The research questions were: 1. To what extent will students give particulate explanations for phenomena concerning diffusion−effusion after viewing a macro-level visualization (video demonstration) and a particulate-level visualization (animation)? 2. What effect will the order in which students view the video and animation have on their particulate explanations of phenomena concerning diffusion−effusion? 3. What effect will seeing the animation and video sideby-side have on student particulate explanations of phenomena concerning diffusion−effusion?
Research Design
Early in the semester students were assigned the TOLT as a quiz opportunity. Subsequently, the online instrument was also assigned as a quiz opportunity. The students who participated in the study individually accessed the online instrument via a computer. When students initially logged on, they first read an introduction with a consent form, and then filled out a biographical section (gender and university classification). Next, in the testing section, the students were given a brief introduction to the Web site, and information about a vacuum. Students were randomly assigned to one of the two treatment groups, VA or AV. The instrument did this assignment automatically, and students were not aware that they were assigned to different groups. These treatment groups were constant through all three experiments. Each of the three experiments began with a static drawing of two flasks that are connected via a closed stopcock. In the first experiment, students saw a flask indicating NO2 was present in the bottom, and a vacuum in the top flask (Figure 1). The static drawing also had an arrow that pointed to the two flasks attached together, where the stopcock was open. For the prediction, students were asked to select the outcome from a set of five possible results that would occur when the stopcock was opened (Figure 2). After answering the prediction question, students were then shown the first visualization. For the VA group, this was a video demonstration, and for the AV group, it was a particulate animation. In the video demonstration for experiment 1, students saw a real-life image that was similar to the static drawing in Figure 1. As the video played, they saw a hand open
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METHODOLOGY We used three diffusion−effusion experiments to test particulate-level understanding of general chemistry students. An online instrument administered the test to the students that participated in this study. The test began by randomly dividing the students into two groups that differed only in the order that they viewed the visualizations: video, then animation (VA), or animation, then video (AV). The test had three experiments (referred to as experiments 1, 2, and 3), and each experiment was broken down into four parts, which are further discussed in the Research Design section. Subjects
A total of 456 students in second-semester general chemistry courses at a large south-central university in the United States participated in the study. Minimal quiz credit was used as an incentive to participate. All of the instructors had numerous quizzes, and they dropped several of the lowest quiz grades; therefore, students who did not participate in the study had no adverse consequences. Participating subjects were randomly assigned to one of two treatment groups: the VA treatment group or the AV treatment group. The VA group viewed a video demonstration followed by an animated particulate view. 981
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students. The first four choices were the most frequent explanations given by students. In this study, only the particulate-level explanation of the phenomenon (choice “c” for experiment 1) was accepted as the correct answer. A panel of chemistry experts (each holding a doctorate degree in the area) validated the answers for experiments 1, 2, and 3. The “a” answer focuses on the outcome and the “b” answer attributes the outcome to a mechanistic view of nature, while the “d” answer attributes the phenomena to an attribute of the gas. This panel indicated that the particulate-level explanation was the most accurate. After the students chose their explanation for step 1, the second visualization was shown to them (step 2), and they were asked to explain the movement of the NO2 gas again using the same question, “Why does the gas go up?” (See Table 1 for Figure 1. Static picture for experiment 1.
Table 1. Online Instrument Sequence
Figure 2. Prediction choices for experiment 1.
the stopcock and the brown NO2 gas distribute evenly between the two bulbs. In the case of the animation, students were told they were viewing a particulate-level window into the experiment. They saw a key, identifying green balls as NO2 and gray balls as the stopcock. The word “molecule” was not used in the key to avoid the problem of students associating the word with the correct answer (as mentioned above). Students saw the green NO2 balls randomly moving. When they clicked the “open stopcock” button, the stopcock disappeared and the NO2 filled up the entire space. After seeing the first visualization (either the video or the animation, depending on the treatment group), students then chose an explanation from a list, or they had the option to fill in a text box with their own explanation. Students were shown the flasks in the prediction set (Figure 2) with the correct answer labeled at the same time that they were presented with the explanation choices. The question text and explanation choices for experiment 1 are shown in Box 1.
more on the sequence of activities in the steps.) Finally, after viewing both visualizations, students were shown the animation and the video side-by-side and asked to explain a third time. In this third visualization, the animation appeared on the left and the video appeared on the right. They were synchronized so that when a student clicked the “open stopcock” button, the stopcock was also opened in the video. After completing the three visualizations for the first experiment, students viewed the second and third experiments in the same order beginning with the static visual and with the same methods. Each experiment, however, was different in content. The second experiment had a static picture, as seen in Figure 3, in which the bottom flask was filled with water, while the top flask was a vacuum. The prediction choices for experiments 2 and 3 were similar to that of experiment 1, which is shown in Figure 2. For each experiment, the most popular five of the seven choices used by Velazquez-Marcano et al.12 were presented. The video demonstration for experiment 2 showed liquid water in the bottom flask (colored green for visibility) and an empty, evacuated flask on top. Once the stopcock was open, no visible difference could be seen. For the animation, on the other hand, students could clearly see a few water particles moving above the liquid water. Once the stopcock was opened, a few of these particles could be seen moving into the previously empty space while most of the particles in the liquid water stayed in
Box 1. Question and Explanation Choices for Experiment 1 1. Why a. b. c. d. e.
does the gas go up? It expands to fill the empty space on top. The vacuum pulls the gas upward. Gas molecules move randomly in all directions. Gases are light and tend to flow upward. Explanation not given. Type your own explanation in the text box.
The explanation choices were derived from open-ended questions that were given to a pilot group of general chemistry 982
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Box 3. Question and Explanation Choices for Experiment 3 3. Why top? a. b. c.
does the gas go up so slowly when there is air on
There is no empty space it needs to fill. There is no force that pulls it up. There are frequent collisions between air and gas molecules. d. The heavier gas tends to stay at the bottom. e. Explanation not given. Type your own explanation in the text box.
Therefore, experiment 1 dealt with the combination of NO2 gas and a vacuum, experiment 2 dealt with water and a vacuum, and experiment 3 dealt with NO2 gas and air. Table 1 shows the complete sequence of the online instrument.
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Figure 3. Static picture for experiment 2.
RESULTS AND DISCUSSION Of the 557 initial participants invited, 456 completed both the TOLT and online instrument, so only the data from these students were analyzed. These participants were split between the two protocols, with 207 in the VA treatment and 249 in the AV treatment. Biographical, TOLT, prediction, and visualization data were analyzed for differences between the two treatment groups using a MANOVA (multivariate analysis of variance) to obtain more accurate p values than would be found repeating a simple t test. These values were evaluated at a 95% confidence interval, with values below p = 0.05 indicating a significant difference between treatment groups. The biographical, TOLT, and prediction data were used to establish equivalent treatment groups. The explanations from experiments 1−3 were used to look for differences in treatment.
place in the animation. The question text and explanation choices for experiment 2 are shown in Box 2. Box 2. Question and Explanation Choices for Experiment 2 2. Why does the water stay down, while the gas goes up? a. The water cannot fill the empty space on top without creating an equal empty space at the bottom. b. The vacuum does not have enough force to lift the water, which is heavier than gas. c. The attraction between water molecules is greater than between gas molecules. d. Liquids are heavier and tend to flow downward. e. Explanation not given. Type your own explanation in the text box.
Biographical Data
Analysis of the two treatment groups in terms of gender and university classification showed that the two groups had almost equal percentages for each category (Table 2). While the
The third experiment features the static picture seen in Figure 4. The bottom flask is filled with NO2 and the top flask
Table 2. Distribution of Demographical Data by Treatment VA Treatment
AV Treatment
Variables
N
%
N
%
Totals Male Female First-year Second-year Junior Senior
207 70 138 148 45 14 0
45.39 33.82 66.67 71.50 21.74 6.76 0.00
249 89 160 174 61 10 4
54.61 35.74 64.26 69.88 24.50 4.02 1.61
number of students that participated the AV treatment (n = 249) was significantly larger than the number that participated in the VA treatment (n = 207), the relative demographic ratios were equivalent for each group. Both treatment groups had a majority of female subjects with over 60% in each, which is common for a general chemistry class at this university. The distribution of student classification in these groups was also skewed toward a first-year population, as expected in a first-year course.
Figure 4. Static picture for experiment 3.
is filled with air. The visualizations for experiment 3 are similar to the first experiment; the main difference is the time it takes for the NO2 gas to distribute to the upper flask. In the video, a clock is included and clearly shows the process takes about an hour to complete. The clock is not shown for the animation, which shows air and NO2 molecules mixing once the stopcock is open. The question text and explanation choices for experiment 3 are shown in Box 3.
TOLT Test Data
The difference in logical thinking skill between treatment groups was not statistically significant (p = 0.50). Both treatment 983
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order dependent on their assigned treatment group. Both groups were shown a side-by-side view of the video and animation last. After each of the visualizations, the students were asked to explain what they saw; the correct response was the particulate explanation for the experiment. The correct response percentages are summarized in Table 4. The p values
groups had relatively high TOLT scores out of the possible 10 points. The mean score for the VA group was 7.50 (SD = 2.14), while 7.36 (SD = 2.27) was the mean for the AV group. Thus, both treatment groups had similar logical reasoning abilities. Prediction Data
To gain further information about the similarities or differences between the two treatment groups, the prediction given in each of the experiments was evaluated. The prediction choices of the outcome of each experiment can be seen in the Methodology section. The number of correct predictions at the beginning of each experiment was compared; the percentage correct for each experiment can be seen in Table 3. The comparisons showed
Table 4. Comparison of Correct Explanations Correct Responses, % Treatment Experiment 1 Video Animation Combination Experiment 2 Video Animation Combination Experiment 3 Video Animation Combination
Table 3. Comparison of Correct Predictions Correct Responses, % Iteration
VA Treatment (N = 207)
AV Treatment (N = 249)
p Values
Experiment 1 Experiment 2 Experiment 3
21.74 23.19 60.87
19.28 24.90 56.22
0.5170 0.6715 0.3176
a
a Evaluated at the 95% confidence interval; values below p = 0.05 indicate a significant difference between treatment groups.
VA Treatment (N = 207)
AV Treatment (N = 249)
14 53 38
15 33 32
21 59 50
33 31 37
33 76 68
43 58 51
arranged by treatment group for each section of the experiments can be seen in Table 5.
that both groups had similar percentages of correct answers, indicating that the groups were equivalent at this point. More importantly, the p values for all of the predictions revealed no significant difference between the two treatment groups. This indicates that at this point, on average, before viewing any visualization, the students in the two treatment groups were equivalent in their prediction making for the concepts being tested. The occurrence of correct predictions increased between the first two experiments and the third. When giving the prediction for experiment 3, students had seen the visualizations for the prior experiments. Is this an indication of learning transfer from the first two experiments, or the fact that experiment 3 did not involve a vacuum? This study did not investigate these questions, but sought to establish that the groups were equal. It should be stressed that while the predictions were a part of the testing section of this study, they were not used for anything more than measuring the similarity of the two treatment groups.
VA Group
For the VA treatment group, all changes between visualizations were either a significant increase or decrease. The VA group had significant increases from the video to the animation and from the first to the last visualization (video to the combination) for all three experiments. Although it needs to be confirmed by further study, the video first seemed to serve as a visualization that students could more easily relate to and to be used to make connections to prior knowledge and other real-life examples of gases expanding. This further reinforces the idea that students need a basis from which to connect to prior knowledge and construct new understandings. Students in this VA group, however, had a significant decrease in correct responses from the animation to the combination visualization for all three experiments. Although it needs to be confirmed by further study, this suggests that some students had an incomplete understanding of the particulate nature of the experiment. In the side-by-side view, students were given both the particulate and the macroscopic view. Even though they had already seen both views of the experiment before and knew they were seeing the same experiment again, a significant number of students still reverted to incorrect macroscopic explanations. Although there is no data to explain why students did this, our previous studies suggest that students tend to hold their misconceptions tightly, even when faced with evidence that their predictions are incorrect,12 or fall back on explanations at the macroscopic level.14 These suggestions need to be confirmed through additional study. Figure 5 shows a graphical depiction of the VA data.
Visualization Data
To address the research questions, the percentages of correct explanations were analyzed. From all three experiments, the correct explanation was accepted to be the molecular-level explanation, as indicated by our expert panel. Other explanations exhibited several misconceptions or limited understanding, such as viewing the expansion of NO2 gas only at the macroscopic level. Also, written answers from the fifth choice in each experiment were read and reviewed for correctness. However, it was found that the number of written answers was not sufficient to make any statistical difference. The only exception was found in experiment 3. For the VA group, 5.3% provided written answers after viewing the video. Only two of these written answers mentioned molecules and could be considered correct. As this was much less than 1% of the subjects, these two explanations were not included in the total correct responses. As described in the Instruments section above, students viewed two visualizations, a video and an animation, with the
AV Group
Figure 6 gives a graphical display of the AV group data. The AV treatment does not show the same trend of significant changes in Table 5 as the VA group. Results are especially different in experiment 2, in which the data show no significant changes between the three visualizations. This could be due to the fact 984
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Table 5. Comparison of MANOVA Results within Each Treatmenta p Values, VA Treatment Experiment 1 2 3
V to A b
