virtual reality in education: rooting learning in experience · 2015-07-29 · virtual reality in...

Invited talk. In Proceedings of the International Symposium on Virtual Education 2001, Busan, South Korea,pp. 43–54. Symposium Organizing Committee, Dongseo University.

Virtual Reality in Education: Rooting Learning in Experience

Yam San CheeSchool of Computing, National University of Singapore

[email protected]

AbstractThere has been a general tendency for learning to get further removed fromexperience as students progress from primary education, through secondaryeducation, and to tertiary education. Learning becomes more language-based,conceptual, and abstract. There are important side effects. In the domain of physics,for example, it is well known that many students can readily solve physics problemsdrawn from textbooks. However, they have little "feel" and understanding of thequalitative dimensions of the phenomena they study. In this talk, I shall argue forthe need to root learning in experience. I shall discuss how the technology of virtualreality can be used to achieve this goal, thereby providing a foundation for students'conceptual and higher-order learning. I shall illustrate the ideas using C–VISions, anetworked collaborative virtual learning environment developed for this purpose.

Keywords: virtual reality, education, experiential learning, collaborative learning, qualitative understanding

1 Introduction

Childhood education is best characterized by engagement in mimicking, play, and experimentation. As languageskills develop and as formal schooling kicks in, language-based learning begins to acquire increasingsignificance until the time comes when it dominates students’ learning experience. In secondary and tertiaryeducation, we find that learning has become predominantly conceptual and abstract. The focus of education isupon the acquisition and possession of knowledge or facts.

Thus, many secondary school students will readily tell you that Newton’s Third Law states: “Every force has anequal and opposite reaction.” They consider the canonical situation of an object resting on a surface, think of theobject’s gravitational force exerted on the surface and the equal and opposite reaction force of the surface on theobject, and feel that they understand Newton’s Third Law.

The brittleness of students’ understanding becomes evident when we ask them to consider the situation wherean object, say a book, is falling from off a table toward the ground and to explain how Newton’s Third Lawapplies in this situation (cf. Laurillard, 1993). Almost invariably, students are stumped. Some students resort toasserting that Newton’s Third Law is inapplicable in such a situation in order to find a way out of the dilemma.This illustration demonstrates that while students may “know” Newton’s Third Law, they surely fail tounderstand it. (As it turns out, Newton’s Third Law is best understood in terms of the force that two bodiesmutually exert on one another.)

A careful study of the literature reveals that brittle knowledge coupled with a lack of understanding iswidespread in science education. For example, McCloskey (1983) describes a range of pervasive scientificmisconceptions that arise from students relying on their intuition of physics phenomena, while diSessa (2000)explains the difficulty and challenge related to conceptual change in science learning.

So why is educating for deep understanding so difficult? The answer, I believe, is to be found in the values andmethods of traditional education. It is instructive, perhaps, to consider what Charles Dickens wrote in his bookHard Times:


Now, what I want is, Facts. Teach these boys and girls nothing but Facts. Facts alone arewanted in life. Plant nothing else, and root out everything else. You can only form the mindsof reasoning animals upon Facts: nothing else will ever be of any service to them.

Facts were considered the “one thing needful” in the days of Dickens. Perhaps this philosophy of education wasadequate in the 19th century, but it hardly serves us well in the 21st.

The conventional mode of teaching in schools today still follows the instructional framework depicted in Figure1. As shown, teachers and students operate entirely at the conceptual level using language as a tool for dialog. Aprocess of dialog between teacher and student can sometimes invoke powerful processes of learning. However,student response is often lacking (the lower arrow is missing) leading to teaching becoming a one-waymonologue from the teacher to the student.

Figure 1. The Instructional Framework

2 Rooting learning in experience

In order for students to learn with deep understanding, the content of the learning must be rendered meaningfulto the learner. Successful meaning making, for any individual, requires the personal construction of knowledge,which, in turn, gives rise to ownership of knowledge. Personal knowledge construction entails investment ofconsiderable time and intellectual effort. Edelman (1992) presents an account of how semantic bootstrappingoccurs. How does a young child learn the meaning of words? From a dictionary? No. Edelman shows that ayoung child learns word meanings by associating the pronunciation of the words (eg. when spoken by thechild’s mother) with the visual and tactile experience of the objects being named. In this manner, phonology iscoupled to perception, giving rise to the encoding of semantic associations in the brain. The learning andacquisition of syntax arises later, after the young child begins to speak and starts to regularize patterns ofspeech.

From the above, we begin to get a sense of what is needed for learning with understanding. For words andconcepts at the language level to be meaningful, they must ultimately be rooted in experience becauseexperience is the foundation of meaning and meaning making. Consistent with this line of thinking, Laurillard(1993) proposes adopting the conversational framework in lieu of the instructional framework. Theconversational framework is shown in Figure 2.

Figure 2 reveals what is lacking in Figure 1. The differences between the figures account for the weakness ofthe instructional approach. In the conversational framework, teachers and students do not operate purely at themental, conceptual, language-based level. Their engagement in learning discourse is rooted in the real (orphysical) world of action that provides grounding for the things they say. The interaction process betweenteacher and student operates not only on the conceptual level. Significantly, it operates also on the physicalworld level where the execution of actions and tasks provide the basis for a dialogic process of action andconsequent reflection on actions taken. Within each participant (ie. the teacher and the student), a whole processof internal adaptation and neuronal encodings takes place as both participants in the interaction modify theirown thinking. We believe that the interaction scenario presented here offers the best prospects of deep learningand conceptual change.


Figure 2. The Conversational Framework

3 The Experiential Learning Cycle

The earlier discussion leads naturally to the framework that we find appropriate to adopt when considering howwe ought to design technology applications to support student learning. Kolb’s (1984) Experiential LearningCycle (see Figure 3) appears, to us, to most effectively capture the essence of effective human learning. Forhuman learning to be grounded in deep understanding, a concrete, experiential basis is necessary. Hence,students need to be given the opportunity to ground their learning in active, first-person experimentation whichprovides the basis for concrete experience. Concrete experience, in turn, provides a basis for reflectiveobservation. Multiple observations, in turn, provide the basis for generalization and abstract conceptualizationwhich, in turn needs to be validated or refined through further experimentation and contact with the world.Thus, we see that learning in general, and conceptual learning in particular, can be viewed as taking place in anongoing, iterative cycle of stages until, at some point in time, a stable ideational state is reached.Notwithstanding this stable state, ideas and conceptual understandings are always subject to furtherperturbations that may lead to further revisions and refinements of a student’s understanding.

Figure 3: Kolb’s Experiential Learning Cycle


4 Networked virtual environments for learning

Given the preceding discussion, we now turn to the issue of designing technology to support student learning. Along time ago, diSessa (1986) illustrated how the construction of artificial, computer-based worlds couldprovide real experience for supporting learning. Today, 3D synthetic virtual environments offer a richer form ofexperiential learning not available previously.

The most unique and possibly also the most powerful characteristic of 3D virtual environments for learning isthat they afford a first-person form of immersive or semi-immersive experiential learning. Too much ofschooling today is based upon third-person knowledge, where students learn that or learn about something,without the opportunity to directly experience for themselves the thing that they seek to learn. The qualitativeoutcomes of third-person versus first-person learning are very different. A preponderance of third-personlearning has meant that student learning outcomes are usually shallow and retention rates are low.

A first-person learning experience in virtual worlds has the advantage of giving users autonomy or control overtheir learning experience. Because of the way in which the virtual environments are modeled and constructed,user actions always entail appropriate and immediate world feedback. This feedback provides a naturalmechanism by which users can judge whether they have taken appropriate or correct actions in the virtualworld. User-directed action and problem solving also foster a strong sense of ownership of the problem and itssubsequent solution.

Because virtual environments lend themselves naturally to first-person learning, the learning environmentsconstructed are usually based on the use of simulation. Simulation-based learning supports both active as well asinteractive learning. Users are given control over critical elements of the environment. They are able tomanipulate variables, change parameters, and test hypotheses. They can freely “play” with experiments thatmight be dangerous to conduct in the real world, and they can run the simulations as many times as they wish,taking time to focus on different salient parameters of the simulation each time it is run.

Simulation-based learning environments, in turn, present objects with natural affordances for supportinginteraction. Thus, users are able to act directly upon virtual handles, levers, or controls in the environment, andthe ability to do so creates a sense of presence—of “being there”—in the virtual environment.

Because virtual environments instantiate a synthetic replica of the objects and phenomena of interest, they servean important representational function by helping to concretize and reify ideas. Indeed, clever use ofrepresentations may go so far as to make the otherwise unimaginable imaginable (as well as experienceable).For learners, this is a vital form of support for learning that can facilitate the formation of initial (possiblyincomplete and not wholly accurate) mental models.

Ultimately, however, students need to be able to generalize from their learning experiences to form appropriateabstractions and rules related to knowledge of the domain they are learning about. To this end, virtualenvironments can incorporate the use of other forms of visual information, such as graphs, as well as symbolicinformation to facilitate building a “bridge” between the contextual world of the experience and thedecontextualized world of more abstract representations of knowledge.

So far, we have focused on aspects related to virtual reality and experience. However, networked virtualenvironments possess one other important dimension: that of the network, which supports communication,coordination of actions, and collaboration in learning activities between many different people at the same time.As argued earlier, experiential grounding for learning is essential. With experiential grounding in place, anatural context is created for meaning making through discourse-based learning to take place.

In a collaborative virtual environment, people are a very useful learning resource for one another. The ability tocommunicate through the technology, either by means of a text or audio chat system, allows users to engage inmeaning making discourse. The fact that multiple users are engaged in a mutually shared context of experiencemakes discourse-based sense making a natural human learning activity. Thus, if users are puzzled by anobservation or fail to understand the meaning of a mutually shared video stream that they have been watchingtogether, they will find it very natural to ask questions of others who share the same virtual world at that time. Inaddition, the ability to re-enact simulations and to compare common learning experiences over time is alsolikely to facilitate discourse that is of a more reflective nature.


5 The C–VISions learning environment

Networked virtual environments have a history going back to the 1980s. The history of networked virtualenvironments has shown that such systems are inherently difficult to develop as they are, at the same time,distributed systems, 3D graphical applications, and real-time interactive software (Singhal & Zyda, 1999).

At the National University of Singapore, we have developed C–VISions (Collaborative Virtual InteractiveSimulations), a networked virtual environment for collaborative learning. It supports student learning byallowing them to engage in collaborative virtual interactive simulations, coupled with a communication channelusing either text chat or voice chat.

Figure 4 shows a screen snapshot of one of our simulation environments, the Battleships World. In thisenvironment, we allow students to explore and learn about the physics of projectiles in motion. Each battleshiphas two canons on board. The canons can be fired and the ensuing trajectories of the cannon balls can bestudied. The C–VISions environment provides for learning simulations in the domains of chemistry and biologyas well, but we have chosen to begin with several physics simulations because we are acutely aware of thedifficulties that many students have with understanding qualitative physics (see Gardner, 1991; McCloskey,1983).

Figure 4: The Battleships Simulation World

The C–VISions system interface contains two arrows pointing in opposite directions in the top-right corner.These arrows are used to slide out and slide away an HTML pane that contains a description of the simulationworld, the tasks that users can engage in, and specific problems that users are asked to solve in a collaborativemanner. The problems posed are non-trivial.

The C–VISions learning environment has been designed to allow users to directly act upon objects of interest inthe simulation environment. As users move the mouse cursor over the 3D virtual world, “hot icons” are used toindicate objects that can be directly acted upon. The shape of the icon changes according to the kind of actionthat can be executed upon the object over which the mouse is positioned. With reference to Figure 4, the mousecursor changes to a bomb with a lighted fuse when the cursor is positioned over the canon, indicating that it canbe fired. Other hot icons provide feedback that the angle of elevation of the canons can be adjusted, the shipsails can be raised, the ships unanchored, etc.


In order for users to wrestle with the given problems, they must be able to manipulate the properties of objects.Figure 5 is a screen snapshot of the Vacuum Chamber World which allows students to explore and learn aboutthe physics of falling objects in a vacuum and in the same environment with air. In this world, students maywish to change an object’s mass. To do this, they select the Inspector tool (the button showing a magnifyingglass on the task bar) and click on the object whose property or properties they wish to modify. Doing so willthrow up the Inspector window which allows users to examine the properties and property values of the objectselected. By clicking on the Editor tab, users can modify pertinent property values of the selected object.

Figure 5: Vacuum Chamber showing the Flower Pot Inspector

Consistent with Kolb’s experiential learning framework, C–VISions allows students to acquire concrete learningexperiences through active experimentation. As students together “play” with the simulation, they engage inmutual problem solving activity as part of a search for a consensual solution.

A shared text chat or audio chat tool allows students to communicate with one another and to discuss their ideasand thinking in the context of collaborative problem solving. Importantly, the communication tool also serves asa channel through which users talk to coordinate their individual actions in the common problem solving space.Hence, discourse can be of two main types: learning discourse, oriented toward making sense of observationsand directed to solving the problems given, and coordination discourse, directed toward coordinating jointactivity in the virtual world.

Through conversation, students (typically) gradually evolve a consensual answer to the problems given andnegotiate a shared understanding of the phenomena being studied. In order to arrive at this end state, theyengage in extensive mutual as well as self explanation, building up a coherent account of their understanding.Over multiple runs of the simulation, students acquire multiple observations of the phenomena under study, andthese multiple observations provide the basis for generalization and abstraction and the derivation of scientificconcepts.

In practice, this “happy” state does not occur so readily as the road from experience to conception is a rocky oneat best and fraught with multiple opportunities for misinterpretations of data and for misconceptions to arise. Toaid the transition from experience to conception, C–VISions provides users with a visualization tool to assistthem in viewing, reviewing, and focusing on salient simulation behavior to aid understanding and conceptformation. Thus, in the Vacuum Chamber simulation world, the visualization tool allows users to plot graphs ofheight, velocity, and acceleration over time. These graphs can be played and replayed by all users for the mostrecently executed event in the simulation world. As the event is replayed in the mini-browser on the left (see


Figure 6), the corresponding graph is plotted, in a synchronized fashion, on the right. The re-enactment of theseevents in the mini-browser can, in turn, be mutually discussed and reflected upon by students.

Figure 6: Vacuum Chamber showing the Visualization Tool

One of the hardest challenges that students face when attempting to learn Newtonian physics is that the world ofsensory experience is not Newtonian (diSessa, 1986). By providing a visualization tool, we intend not only toprovide students with a path from the concrete to the more abstract but also to make use of the visualization toolto shape and constrain students’ understandings by having them relate the more difficult and more abstractrepresentations (such as the graphs of velocity against time and acceleration against time; not shown here) backto the phenomena observed so that experience can become “colored” or seen through the lens of scientifictheory.

6 Conclusion

In this paper, I have argued for the importance of rooting learning in experience. Too much of traditionaleducation proceeds entirely at the more abstract, conceptual level of talk. This traditional method of teachinghas resulted in an emphasis on students acquiring and possessing knowledge without having a deep, robustunderstanding of the subject matter. This kind of outcome is particularly pervasive and well-known in thedomain of science learning, especially in physics.

I have argued that both experiential learning and discourse-based learning that is grounded in experience arerequired if students are to master subject matter at the level of understanding. Understanding focuses onapplication and on knowledge-in-action; it offers the best potential for knowledge transfer, the creativeapplication of knowledge, and the construction of new knowledge. I have shown how, following this line ofthinking, technology can be designed to support learning and collaborative meaning co-construction betweenlearners rather than being used to always support explicit instruction.

The field of networked virtual environments offers many opportunities for continued exciting research. Welearned from an initial pilot study that, as a collaborative learning environment, students using the environmentmay not always possess the knowledge and understanding to advance the learning-based discourse in a directionthat leads to coherent, scientific, knowledge building. To address this difficulty, we are actively working on theintroduction of autonomous pedagogical agents into the learning environment. These agents will be embodied asavatars, like other users in the environment; they will also be able to communicate with other users either via


textual messages or via spoken messages using a text-to-speech engine. Our longer term goal is to support aform of mixed reality in the virtual worlds, where the real and the synthetic begin to merge in a seamlessfashion.

References

diSessa, A. (1986). Artificial worlds and real experience. Instructional Science, 14, 207–227.

diSessa, A. (2000). Changing Minds: Computers, Learning, and Literacy. Cambridge, MA: MIT Press.

Edelman, G. M. (1992). Bright Air, Brilliant Fire: On the Matter of the Mind. NY: Basic Books.

Gardner, H. (1991). The Unschooled Mind: How Children Think and How Schools Should Teach. NY: BasicBooks.

Kolb, D. A. (1984). Experiential Learning: Experience as the Source of Learning and Development . EnglewoodCliffs, NJ: Prentice-Hall.

Laurillard, D. (1993). Rethinking University Teaching: A Framework for the Effective Use of EducationalTechnology. London: Routledge.

McCloskey, M. (1983). Intuitive physics. Scientific American, 248 (4), 114–122.

Singhal, S., & Zyda, M. (1999). Networked Virtual Environments: Design and Implementation. NY: ACMPress.

virtual reality in education: rooting learning in experience · 2015-07-29 · virtual reality in...

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