Embodiment: A New Perspective for Evaluating Physicality in Learning
Article in Journal of Educational Computing Research · July 2013
DOI: 10.2190/EC.49.1.b
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EMBODIMENT: A NEW PERSPECTIVE FOR EVALUATING PHYSICALITY IN LEARNING*
INSOOK HAN Hanyang Cyber University
ABSTRACT
The purpose of this study is to provide a new perspective for evaluating physicality in learning with a preliminary experimental study based on embodied cognition. While there are studies showing no superiority of physical manipulation over virtual manipulation, there are also studies that seem to advocate adding more physicality in simulations for learning. Thus, this study addressed an alternative explanation for explaining the effects of physicality by focusing more on perceptual experiences and embodiment.
The experimental study with 48 graduate students supported pre-existing results, which did not discover any differences between physical and virtual manipulations in learning physics. More importantly, the results of this study showed that the perceptual experience of driving a manual transmission car was critical for comprehending how gears work. This implies that the physicality added to a learning experience should be evaluated in terms of its potential to create embodiment rather than the mode of interaction—
physical or virtual.
INTRODUCTION
Nowadays, new technologies are pervasive in K-12 and higher education settings and have become an appealing option for both presenting and supplementing
41 Ó2013, Baywood Publishing Co., Inc.
doi: http://dx.doi.org/10.2190/EC.49.1.b http://baywood.com
*This work was supported by the research fund of Hanyang Cyber University (HYCU- 2011-0028).
instructional materials. However, there is little theoretical evidence that supports the effectiveness of using computer simulations as instructional media. Based on Kulik (2003), who reviewed findings from controlled evalu- ations of technology applications in elementary and secondary schools, a number of studies conducted during the 1980s and 1990s found negative effects concerning simulations. According to those physical manipulation advocates who argue that physicality should be a prerequisite for science learning (e.g., National Science Teachers Association, 1999), computer simulations could restrict students’ learning since they do not provide physical or hands-on experiences (Zacharia, Loizou, & Papaevripidou, 2012). Unlike their assertion, however, when comparing physical with virtual manipulation, physically interacting with concrete materials did not show educational advantages over virtual manipulation (Klahr, Triona, & Williams, 2007; Triona & Klahr, 2003; Triona, Klahr, & Williams, 2005; Zacharia & Olympiou, 2011). Based on these study results, Zacharia and Olympiou (2011) concluded that the important factor influencing learning is not physicality but manipulation itself. On the other hand, some studies that incorporated haptic devices within simulations still report the benefit of adding more physicality in science learning (Brooks, Ouh-Young, Battert, & Kilpatrick, 1990; Han & Black, 2011; Reiner, 1999; Williams, Chen, & Seaton, 2003; Williams, He, Franklin,
& Wang, 2007).
These inconsistent results are due to the underlying contradictory per- spective on what “physicality” means. Zacharia, Loizou, and Papaevripidou (2012) define physicality as the actual and active touch of concrete material and apparatus. This physicality focuses on the mode of interacting with learning materials, virtual or physical, as a critical factor that might influence learning. However, recent theorizing on the embodied nature of cognition (Barsalou, 2008) provides a new way of understanding what physicality means. From this point of view, regardless of virtual or physical, it is important to provide perceptually grounded experiences sufficiently embodied for students to “feel” what the learning material repre- sents to have a full understanding of something (Barsalou, 2008; Black, 2010; Black, Segal, Vitale, & Fadjo, 2012). Based on this embodied cognition framework, a new guideline for evaluating physicality in learn- ing should be drawn to focus more on embodiment rather than the mode of interaction.
Thus, the purpose of this study is to provide experimental evidence to define physicality in terms of its embodiment. For this, in this study, we will first investigate the pre-existing evidence of advocating “manipulation effect”
of virtual and physical manipulation. Then, to further investigate the effect of embodiment in learning, learners’ prior bodily experiences will be examined as a factor to have influence on learning.
EMBODIED COGNITION AND PHYSICAL MANIPULATION IN LEARNING
Embodied cognition is a new way of discussing human cognition by empha- sizing the processes of perception and bodily experiences. Unlike traditional theories assuming that cognition is separated from our perception, bodily action, and mental states, a growing number of researchers (Barsalou, 2008; Gibbs, 2003; Smith & Gasser, 2005; Wilson, 2002) have recently claimed, under the name of “grounded or embodied cognition,” that our cognition is created based on the multimodal representation that we acquired from our bodily experiences through sensory modalities (such as eyes, ears, nose, hands, and mouth) while interacting with the environment. This point of view emphasizes having per- ceptual experiences for being able to learn abstract concepts by actually “feeling”
it (Black, 2007, 2010). From their perspective, people have the ability to construct their own mental representation with perceptual experiences, which can be essential grounding on which to build abstract concepts (Gibbs, 2006). In fact, there are previous studies implying that physically interacting with objects or environments could be the perceptual foundation for abstract learning.
Many studies demonstrate the positive influence of physical manipulation in learning and memory (Bara, Gentaz, Cole, & Sprenger-Charolles, 2004;
Glenberg, Gutierrez, Levin, Japuntich, & Kaschak, 2004; Lederman, & Klatzky, 1987; Ramini & Siegler, 2008; Siegler & Ramani, 2008). Glenberg and colleagues (2004) found that the experience of physical manipulation is grounding in regard to reading comprehension concerning young children. In this study, first and second graders were asked to manipulate physical toys to correspond to the sentences while they were reading a story. This physical manipulation helped children to index words and phrases in relation to real objects and resulted in a better understanding of the story. Similar results were also found in alphabetical learning with younger children demonstrating the benefit of actively tracing letters with their fingers (Bara et al., 2004).
Positive effects of physical manipulations were also observed in mathematics learning. Siegler and Ramani (2008) showed that playing the board games for four 15- to 20-minute sessions over a 2-week period produced substantial improve- ments in low-income children’s number line estimation, which seemed attribut- able to their increasing use of linear representations for numerical magnitudes.
The follow-up study with a larger sample of low-income children from Head Start programs replicated and extended this result (Ramini & Siegler, 2008). This study indicated that interactions with physical materials (board games) help children form more advanced mental representations of the linear number line, and the benefits of playing the board game remained apparent for 9 weeks following the experience. Using the embodied cognition framework, it is discussed that numerical board games help children to produce kinesthetic cues by physically moving
the tokens, which creates perceptual grounding to be linked to abstract symbols (numbers) and eventually help children to comprehend the linear number line.
PHYSICAL VERSUS VIRTUAL MANIPULATION
In contrast to the consistent results of the above studies showing the advantage of physical manipulation in learning, when compared to virtual manipulation, physical manipulation often failed to show its superiority (Klahr et al., 2007;
Triona & Klahr, 2003; Triona et al., 2005). Triona et al. (2005), as a follow-up study to the previous one conducted by Triona and Klahr (2003), investigated whether interacting either with physical instructional materials or virtual ones would create any differences in learning based on embodied cognition. Initially, Triona and Klahr (2003) tried to examine the effects of presentation media on elementary school students’ ability to design experiments by controlling an extraneous confounding variable either by working with virtual or physical instructional materials. After conducting the experiment with fourth- and fifth-graders, they concluded that students learned to design unconfounded experiments equally well when taught with both virtual and physical materials.
Later, they attempted to replicate the study with different populations and activity by incorporating the embodied cognitive aspect and hypothesized that perceptual experiences created while interacting with both virtual and physical materials would affect students’ knowledge acquisition differently (Triona et al., 2005).
Seventh- and eighth-graders designed mousetrap cars by assembling either physical components with their hands or virtual ones by clicking a mouse. After running the cars, they had to determine the most effective properties of mousetrap cars. Both groups learned equally well from physical and from virtual materials.
Zacharia and colleagues also conducted a series of studies in order to compare the effectiveness of physical and virtual materials in physics learning, focusing on heat and temperature in particular. In the study of Zacharia, Olympiou and Papaevripidou (2008), they indirectly found the benefit of virtual materials in college students’ conceptual understanding by comparing the combination of physical manipulation and virtual manipulation to physical manipulation alone. However, by comparing the result to the previous study (Zacharia &
Constantinou, 2008) that directly examined the influence of physical manipulation and virtual manipulation, which found that both were equally effective in students’
learning, they discussed that virtual manipulation in their study might benefit learning combining it with physical manipulation. Thus, as a follow up study, Zacharia and Olympiou (2011) conducted another study that compared all three experimental conditions (physical manipulation, virtual manipulation, and the combination of physical and virtual manipulation) to a control group. Unlike the study that found the indirect value of virtual manipulation (Zacharia et al., 2008), this study did not find any significant difference among the three experimental groups and all three outperformed the control group. In this study,
they concluded that the important factor influencing physics learning is not physicality but manipulation, which means that regardless of physical or virtual, manipulating materials itself affects learning.
EMBODIMENT RATHER THAN MANIPULATION
The series of studies that demonstrate no additional learning benefit of using physical manipulation over a virtual one seems to support the “manipu- lation itself” position in advocating the effectiveness of educational simulations.
However, another set of studies that used advanced technological devices incor- porated in simulation consistently reports the benefit of using force feedback devices in physics learning. The force feedback devices are devices such as game pads, joysticks, steering wheels, or mice that give us the feedback of force when interacting with computer simulations. For example, in Jones, Minogue, Tretter, Negishi, and Taylor’s study (2006), they compared three types of virtual manipulations which were two computer visualizations with haptic feedback and computer visualization without any haptic feedback, and examined their effects in secondary students’ science learning. Based on the reasoning that supports the results of the above mentioned studies, if manipulation itself matters more than physicality, then three groups should have not shown any differences in learning since they were equivalent in terms of the manipulative aspect. However, the study found potentials of adding haptic feedback in learning abstract science concept.
Also, other similar studies that incorporate haptic feedback in virtual manipulation report the consistent results for showing the benefit of haptic feedback in con- ceptual learning. Brooks et al. (1990) found that experienced biochemists from a university research center benefited from using haptic feedback. By using haptic feedback combined with a visual display regarding a six-dimensional docking task, they could improve their perception of valid docking positions for drugs and enhance their understanding of why a particular drug docks well or poorly.
Also, Reiner (1999) examined the role of tactile perception in the conceptual construction of forces and fields in graduate students who only had a general high school science background by employing a modified trackball that transferred a simulated force applied by a field to the learner’s hand. The results of the study indicate that providing tactile perception helped students with no background in physics construct a graphical representation of force lines, equal-force lines, and motion of a charged particle in a field of forces.
These results might be due to the physicality that was boosted by adding the feeling of forces that is a core aspect of comprehending physics concepts. This boosted physicality is what provides more abundant perceptual experiences than the regular virtual manipulation and creates embodied experiences (Han & Black, 2011). Therefore, the study results made us revisit the concept of physicality when discussing the effect of virtual and physical manipulations and reexamine whether the physicality provided in physical manipulation was perceptually different
with the one provided in virtual manipulation. In previous studies, designing uncompounded experiments (Triona & Klahr, 2003), assembling the components of cars to design an optimal car (Klahr et al., 2007; Triona et al., 2005), or measuring temperature using thermometers to examine the relationship between heat and temperature (Zacharia & Olympiou, 2011) with physical objects did not make a significant perceptual difference from virtually clicking components on computer screens, resulting in equal learning effect between physical and virtual manipulations. In other words, learning activities in the above mentioned studies did not include physical aspects that can be boosted with physical manipulation.
For example, whether students measured temperature using a real thermometer by holding it in hand or a virtual thermometer by clicking on a computer screen might not provide enormous perceptual differences.
These inconsistent results inform us that physicality may not be defined as the modes of interaction but rather, should be evaluated based on whether it can deliver more embodied experiences or not.
CURRENT STUDY
As discussed above, previous studies have investigated the effects of physical and virtual manipulations in learning, especially in science education, which found controversial causes for their learning effects. The studies that compared physical and virtual manipulation in learning and were unable to find any dif- ferences came to the conclusion of advocating the effects of manipulation itself rather than physicality. However, other studies that incorporated haptic feedback with advanced technological devices addressed the potential of adding more physicality in learning and discussed its effect in terms of perceptual embodiment.
Thus, this study will examine the effects of physical and virtual manipulation in learning and support pre-existing results, which did not discover any differences.
More importantly, the study will address an alternative explanation for explaining the effects of physicality by focusing more on perceptual experiences and embodi- ment from an embodied cognition perspective. Based on the theoretical back- grounds discussed above, here are the research questions and hypotheses that will be investigated.
Does Manipulation Matter in Learning and Reasoning?
H1: Both manipulations (physical and virtual) will benefit the learning of physics concepts more than reading text without any manipulation.
H2: Virtual and physical manipulations will not differ in students’ conceptual learning and reasoning.
Similar to previous studies that advocate the “manipulation itself matters” posi- tion, it is hypothesized that this study will also support that, regardless of the
physicality, manipulative experiences will enhance abstract concept learning.
Thus, learners who use manipulations for learning physics concepts will perform better than those who do not use any manipulation at all. However, physical and virtual manipulations will not make any difference in learning, since the physical manipulation in the study does not provide physicality that is not available in the virtual manipulation but is critical for understanding targeted concepts.
Does Embodiment Matter in Learning and Reasoning?
H1: Prior bodily experiences relevant to the target concept will benefit the learning of physics concepts.
Embodied cognition perspective suggests that learners’ perceptual experiences would enhance abstract concepts learning. Thus, in this study, it is hypothesized that prior bodily experiences that are relevant to the learning concept will benefit the learning of targeted concepts. Manual transmission car driving experiences, in particular, are physical interactions with a car that works based on the mechanism of gears’ torque. Physical experiences of feeling the force and hearing the sound of a manual transmission car is assumed to become an embodied cognitive grounding for comprehending how gears work. Thus, learners who have prior experiences with a manual transmission car will better com- prehend abstract concepts.
METHODS Participants
Forty-eight graduate students participated in the study. They were required to be neither Physics nor Engineering majors since the topic selected for this study was highly related to those two disciplines and mostly from the field of Psychology or Education. Participants were randomly assigned to one of three groups (control, simulation, and physical manipulation). All three groups were provided the same three test materials and only differentiated in learning activities.
The control group read an expository text without being provided any manipu- lative experience. The two intervention groups had opportunities to experience
“design a car” scenarios by manipulating gears and slopes with either a simulation or physical manipulation.
Physical Manipulation
The physical manipulation group was given a task to design a car that could climb a slope at a certain angle with concrete objects. Participants were given a wooden board, two boxes with different sizes for making three different angles (low, medium, and high with piling up both boxes), three pairs of gears (8-teeth,
16-teeth, and 24-teeth) and a car that had been already built with the LEGO Mindstorm package by the researcher. LEGO Mindstorm is a LEGO package with a programmable brick, motors, and various sensors that enable an individual to interact with the environment by programming it. The car was designed with one programmable brick, two motors, two wheels, and two pairs of gears, one of which was attached to motors on each side (driving gears) and the other which was attached next to the driving gears on each side (driven gears). Participants were asked to try out each pair of driven gears in three different sizes. After selecting a slope with one angle and a pair of driven gears, participants pressed an orange button on the programmable brick in order to execute the programming. The programming was already saved inside the brick by being downloaded from Mindstorm NXT software and made the car move forward while the driving gear revolved 10 times. The duration was set as a constant variable so that participants could observe a difference in the distance the car traveled with the various sized gears. The motor’s power was also intentionally set as 65 and a bucket of coins were put on the car as weight to differentiate each driving gear’s ability to go up each slope. For example, the 24-teeth gear was designed to be able to climb all three angles’ slopes with the given motor power and weight but the 16-teeth gear could not go up the highest one and the 8-teeth gear only could climb the lowest slope. While experiencing all nine possible combinations, participants were sup- posed to gain insights concerning the relation among gear sizes, rotating speed, and the car’s ability to go up slopes. However, they were not expected to understand explicit knowledge with regard to underlying physics laws.
The simulation group manipulated the angle of slopes (low, medium, or high) and three different sizes of driven gears within the interactive Flash-based simu- lation environment. In this environment (see Figure 1), participants selected an angle for a slope and then proceeded to a next page for selecting a driving gear.
In the gear selection page, whenever participants clicked one gear, it showed that the selected gear was attached next to the driving gear on the beam. Par- ticipants could go back to the slope selection page and change their slope or gear option before moving to the next page. When they clicked a “Next” button, they saw simultaneous video segments of the car climbing up their chosen slope with their chosen gears. This video segment contained three different shots, which were distance, close-up of the car, and close-up of the moving gear. After watching the video clip, participants could go back to the selection page and continue experimenting until they completed all nine combinations.
Instructional Text
Instructional text described the concept of torque, gear ratio and rotating speed, and the relations among them. The text was selected and modified from online material, “MINNESOTA FIRST LEGO LEAGUE: Building LEGO robots for FIRST LEGO League, version 1.0” (Hystad, 2002), and contained 568 words.
There were three paragraphs in this text. The first paragraph explained the concept of torque (241 words). With the visual images of gears, this paragraph explained what torque is and how much torque is generated depending on sizes of gears.
The second was for the concept of gear ratio as well as the relation between gear ratio and torque (153 words). This paragraph explained what gear ratio is and how torque is calculated using gear ratio. The last paragraph explained the relation among gear ratio, torque, and speed (174 words). By reading this
Figure 1. Virtual manipulation screen.
instructional text, participants were expected to understand that the bigger gears generate more torque, while they rotate more slowly.
Measures Pretest and Posttest
Pre- and posttests were to capture students’ prior and post knowledge con- cerning a gear’s moving direction, ratio and speed, toque, and work before and after the intervention. Pre- and posttests items were developed by the researcher based on the instructional text that was used for the intervention. For internal validity of the test instruments, test items were reviewed by two physics experts who majored in engineering. Two tests basically contained the same seven multiple-choice items, but only differed in their sequence of answer choices for participants to avoid answering them based on memory from the pretest.
Each correct answer received 1 point, which allowed for a maximum score of 7.
Examples of pre- and posttest items are as shown in Table 1.
Transfer Test
The transfer test items were developed to capture students’ abilities to reason about mechanical systems. Test items were developed by the researcher and reviewed by two physics experts who majored in engineering. This test included eight open-ended questions that were relevant to real world mechanical examples that either use gears or adapt the same logic to physics principles, which
Table 1. Examples of Pre- and Posttest Items
1. Which of the following statements is not true about the concept of “torque”?
A. Torque is a force that tends to rotate or turn things.
B. Newton-meters (Nm) is the unit of torque.
C. Torque increases, as a distance from a pivot point gets longer.
D. Torque decreases, as a distance from a pivot point gets longer.
2. Which of the following statements describing the relations between the size of gear and torque is true?
A. Given the torque of driving gear, you can increase the torque by attaching the driven gear that is bigger than the driving gear.
B. Given the torque of driving gear, you can increase the torque by attaching the driven gear that is smaller than the driving gear.
C. Given the torque of driving gear, the torque of driven gear is always constant regardless of its size.
D. The torque of driven gear is always the same with the torque of driving gear.
participants learned from the interventions. It was expected that learners who completely understood the mechanism of how gears work would also comprehend how other simple machines function and, thus, demonstrate better mechanical reasoning. The eight open-ended questions consisted of two or three small questions, each worth a point when correctly answered. The maximum score was 15. Examples for the transfer test are as shown in Table 2.
Procedures
All participants took the pretest first. Then participants were randomly allocated to one of three groups. The two intervention groups manipulated the LEGO car either in the virtual simulation or in the physical world for about 10 minutes before reading the instructional material for 10 minutes. The control group only read the instructional material without any manipulative experiences but for 20 minutes in order to control total time spent on learning. After learning from the material, all three groups took the posttest and also the transfer test. All procedures took approximately 60 minutes.
After all the experimental procedures were completed, a short interview was conducted to find out whether participants had manual transmission driving experiences. If so, they were asked additional questions concerning how they affected their learning and reasoning.
Table 2. Examples of Transfer Test Items
1. Spur gears are two gear wheels intermeshing in the same plane, regulating the speed or force of motion and reversing its direction. Followings are the real life examples that use spur gears.
a. Salad spinner b. Car window winder c. Mechanical clock Choose one example among three above, and explain how it works using two gears in different sizes.
1) draw two gears meshing together.
2) explain which one is a driving gear (which we apply our force to), and which one is a driven gear (which does the work).
3) describe how two gears work in your example in terms of the relations among gear ratio, torque, and speed.
2. Above is the diagram showing a lever of which the left end is twice as long (2X) as the right end (X).
1) If you apply force 5 pounds to the left end, how much force will be applied to the right end?
2) Explain your rationale to come up with the answer by analogy with the relation between gear ratio and torque.
RESULTS
Does Manipulation Matter in Learning and Reasoning?
Among 48 participants, 16 were in the control group, 17 were in the virtual group, and 15 were in the physical manipulation group. In terms of pretest scores, the ANOVA test revealed that there was no difference in learners’ prior knowledge level by groups (F(2, 45) =.051,p= .950). In order to examine how well each group performed after the interventions, we compared posttest and transfer test scores across the three groups. In the posttest, the control group performed the best (M = 4.69), followed by the physical (M= 3.93) and simu- lation (M= 3.82) groups. Since the variances among three groups were assumed equal based on Levene’s Test (F(2, 45) =.860,p=.430), we conducted ANCOVA with posttest scores. According to ANCOVA including a covariate of the pretest, however, these differences were not statistically significant (F(2, 45) = 1.761, p= .192,h2=.07).
As for the transfer test, since there was no pre-transfer test to directly compare with, the ANCOVA test with a covariate of the pretest was conducted in order to investigate whether there was any difference in transfer test scores among groups by controlling pretest effects. The variances among three groups were assumed equal based on Levene’s Test (F(2, 45) = .664,p= .520). Even though the physical manipulation group performed slightly better (M = 8.87) than the control (M = 8.13) and simulation (M = 8.00) groups (Table 3), the difference was not statistically significant (F(2, 45) = .531,p= .592,h2= .02).
As expected, virtual and physical manipulations did not make any differ- ences in learning, meaning that virtual and physical manipulations were equally effective in enhancing one’s ability to learn abstract physics concepts.
However, the study result indicated that learners with manipulative experiences did not learn better than those without any manipulations, which did not coincide with our expectation in that manipulative experiences regardless of physicality would enhance learning.
Table 3. Descriptive Statistics for Pretest, Posttest, and Transfer Test Scores by Groups
Pretest Posttest Transfer test
Group M SD M SD M SD N
Control Virtual Physical
3.00 3.06 2.87
1.75 1.78 1.64
4.68 3.80 3.97
0.36 0.35 0.37
8.10 7.90 9.00
0.79 0.77 0.82
16 17 15
Does Embodiment Matter in Learning and Reasoning?
Among 48 participants, 22 had prior experiences of driving a manual trans- mission car and 26 had no experiences. Driving a manual transmission car is a physical experience that can embody the naïve concept of torque without the conscious effort of learning explicit physics concepts. In order to investigate whether embodied physical experiences regarding driving a manual transmission car affects learning, we compared the posttest and transfer test scores between those with and without experiences. First of all, the ANOVA test for the pretest revealed that there was no difference between experience and non-experience groups.
When comparing posttest scores between groups, the experience group per- formed better (M= 4.59) than the non-experience group (M= 3.77) (Table 4).
To control the prior knowledge effect, the ANCOVA including a covariate of the pretest was conducted. The Levene’s Test showed the variances among three groups were assumed equal (F(1, 46) = .262, p = .611). The ANCOVA result revealed that this difference was statistically significant having a significance level of .05 (F(1, 46) = 4.479,p= .040,h2= .09).
In addition, we conducted another ANCOVA test with a covariate of the pretest to investigate whether there was any difference in transfer test scores through prior experiences. The variances among three groups were assumed equal based on Levene’s Test (F(1, 46) = 2.184,p= .146). Participants with the experience of driving a manual transmission car performed better (M = 9.14) than those without experience (M= 7.61), which was proven to be marginally significant (F(1, 46) = 3.590, p = .065, h2 = .07). These results support our hypothesis that physical experiences would benefit learning and reasoning.
Additional Findings
Since this is an exploratory study with a small number of participants, it is inappropriate to conduct an inferential statistical test in order to examine an interaction effect between manipulation types and prior experiences. However, we did find an interesting tendency in descriptive statistics that is worth observing (see Figure 2).
Table 4. Descriptive Statistics for Pretest, Posttest, and Transfer Test Scores by Experiences
Pretest Posttest Transfer test
Group M SD M SD M SD N
Experience Non-experience
2.91 3.04
1.51 1.87
4.61 3.75
0.30 0.28
9.22 7.54
0.65 0.60
22 26
Figure 2. The interaction tendency between groups and experiences in the posttest (a) and the transfer test (b).
(a)
(b)
As for the posttest scores, the non-experience learners’ score showed a tendency of decreasing when they respectively used no manipulation (control group), as well as virtual and physical manipulations. However, the experienced learners’
score was boosted when they used the physical manipulation. Also, the non- experienced learners demonstrated little difference in their transfer test scores regardless of manipulation and physicality, while the experienced learners demon- strated greater understanding when provided the physical manipulation as in the posttest. These trends of increased test scores with the physical manipulation in the experienced group was further supported by the interview that asked how their prior experiences affected their learning of gear mechanisms and reasoning about mechanical systems. Those who had manual transmission driving experience and were provided the physical manipulation said that they could immediately link their driving experiences with the activity provided with which they should have changed gears with different sizes and made a car go up a slope with a certain angle. This activity also reminded them of the sound and feeling of driving a car when the car struggled to go up a steep mountain pass.
These additional findings from descriptive statistics and interviews, in addition to the previous results from statistical tests, may inform us of a critical implication about the importance of perceptual embodied experiences in abstract concept learning. With this in mind, a discussion on this follows in the next section.
DISCUSSION
The main purpose of this study was to provide a new perspective for examining the effectiveness of physical and virtual manipulation based on embodied cog- nition. For this, an exploratory experiment was conducted and the results were analyzed to investigate the effects of physicality and manipulation in learning.
The first finding explained how both the virtual and the physical manipulations did not make any difference in learning and reasoning. This result is consistent with previous research in that the virtual and the physical manipulations were equally effective in learning physics concepts (Triona & Klahr, 2003; Triona et al., 2005; Zacharia & Constantinou, 2008; Zacharia et al., 2008; Zacharia &
Olympiou, 2011). As in previous studies, for physical manipulation, participants changed the gears with their own fingers and observed the real LEGO car’s movement but did not have a chance to experience force and speed, which did not make an immense perceptual difference from clicking to select the gears and observing the videotaped movement. However, the current study did not support the hypothesis that the manipulation itself would be beneficial for learning by failing to prove that the manipulation groups performed better than the group reading an instructional text without any manipulation. This may be due to the posttest items that were selected from the instructional text provided to participants. The control group was provided 20 minutes for studying the materials, while the manipulation groups only had 10 minutes after experiencing
manipulation activities for 10 minutes. Participants were asked to answer the posttest questions right after the interventions so that the characteristic of the test was to become a recall test of which performance is commonly proportional to the time spent on studying. Even though the total intervention time across three groups were designed to be equal, study on the instructional material that was directly related to the immediate posttest was longer in the control group, which potentially created an equivalent learning effect with the manipulation groups. Also, in the transfer test, the three groups performed equally well. Even though the physical manipulation group had the highest scores, it was not statis- tically significant to conclude that physical manipulation was the most effective intervention in reasoning with mechanical systems.
The second was to investigate how perceptual/embodied experiences would affect abstract concept learning. The manual transmission car driving is a casual perceptual experience that is not intended for explicit learning. Thus, even though participants had a perceptual experience for manual transmission, they did not necessarily know the underlined mechanism regarding how the system works and its related concepts. This was also supported with the pretest results that showed no differences between the experienced and the non-experienced group.
However, when it comes to learning, prior experience seemed to play a role for perceptual grounding in order to build related concepts onto it. In both the pretest and the transfer test, participants who had prior physical experiences performed better than those without experiences. This result supports previous findings that learners’ prior perceptual experiences are physically embodied and prepared learners for later explicit learning (Hammer & Black, 2009; Han & Black, 2011).
Thus, the result implies that when a physical manipulation does not include
“real” physicality that cannot be offered in virtual space, physicality is not what matters in learning. However, when the physicality contains bodily experiences with which learners can feel the force and embody the physical interactions, physicality matters, and this “physicality” is a perceptual experience which creates “embodiment” from an embodied cognition perspective.
Besides, the additional findings seem to further inform us that there may be an interaction effect between manipulation types and experiences. Only the learners who already had perceptual experiences and embodied “feeling” of manual transmission driving seemed to perform the best when provided with the physical manipulation activity. This may be due to the perceptual simulation that becomes activated when a situation similar to prior embodied experiences is presented (Barsalou, 2008). In other words, the physical manipulation of changing gears and watching a car going up a slope was the best stimulus for activating learners’ prior perceptual experiences of driving a manual transmis- sion car. This was also supported by the interview demonstrating their volun- tary activation of their memory. The result seems to suggest that even though people did not have explicit knowledge concerning the manual transmission system, once provided with the closely related physical manipulation activity,
their perceptual experiences become stimulated to mentally simulate how the sound and the feelings of the engine would be when producing more or less forces and how the speed would change when they geared down or up. Certainly, this is an exploratory result with a small number of participants and cannot be interpreted as a statistically significant conclusion. However, it offers insight for a way of interpreting physicality based on embodiment.
CONCLUSION AND LIMITATIONS
This study addresses the issues of evaluating the effectiveness of physical and virtual manipulations and suggests a new way of considering physicality in learning when compared with virtual manipulation in simulation. This study implies that physicality should be determined not by the mode of interaction—
whether it is physical or virtual, but by the essence of experiences delivered by that interaction. In other words, even if it is delivered through virtual simulation, when the experience contains additional physicality, such as force feedback, which is a key component for learning physics and provides more embodied experiences, then it should be beneficial to learning. On the contrary, even though it is a physical manipulation, when the experience does not contain any funda- mental perceptual differences other than virtual manipulation, it would not make any difference in learning. In conclusion, physicality should be evaluated in terms of its potential to create embodiment.
This study has limitations in terms of a small number of participants, and the design of posttest measurements, which means that results should be interpreted cautiously to avoid over-generalization. Further research using a better design involving a larger number of participants to better control variables is needed to examine findings in more depth.
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