NEUROSCIENCE PSYCHOLOGY

3L03

ACTIVE VERSES PASSIVE LEARNING

FOR:

DR. SUN

DONE BY:

SHANNON SULLIVAN; 9640155

ABBY OVERDUIN; 9702104

CAROL BUCKING; 9809314

DIANA MAINA; 9640155

DUE DATE:

FRIDAY, APRIL 06, 2001

Abstract

The purpose of this experiment was to determine whether or not the memory of a task is affected whether or not an individual actively performs the task or passively observes the task. This has direct applications to virtual reality because often individuals are educated in a virtual reality environment and it is important to determine whether or not this should take place in an active or a passive manner. In this experiment we designed a virtual reality maze and then taught individuals to go through the maze by pairing a subject who actively went through the maze with a subject who passively watched the former go through the maze. It was hypothesized that when both the active and passive subjects were tested for their memory of the correct route through the maze, the active subjects would have fewer number of errors and would take less time to complete the maze. When results were analyzed though, it was determined that neither the number of errors made nor the time to completion indicated any statistically significant differences between the active and passive groups of subjects. Nonetheless, there did appear to be a trend towards better memory of the maze in active subjects compared to active subjects when the time variable was examined. This led us to conclude that if a number of methodological flaws in our study design were corrected then a significant improvement in memory of the maze might be observed in active subjects compared to passive subjects.

Introduction:

Living in an era where technology rules the world, it has become increasing important to understand the implications that this has on learning. This study concerns the specific technology of virtual reality, and is aimed at exploring the most effective way that virtual reality can be used as a teaching tool. Virtual reality is defined as an artificial environment experienced through sensory stimuli, such as sight and sound, provided by a computer, and in which one’s own actions determine what occurs in the virtual reality environment (VRE). To the individual, it appears that they are immersed in this computer-generated environment. In this experiment, subjects were immersed in a virtual reality maze, and their actions determined how they navigated through this VRE.

To determine if VREs are effective teaching tools, we must first determine if the skills acquired in the VRE are transferable to the world outside of it. While research is not entirely conclusive, it does appear to show strong evidence that the individuals are capable of transferring the tasks that are learned in a VRE to real life situations. For example, Johnson and Wignman, 1995 showed that when pilots were trained to fly helicopters in a VRE, they were able to transfer this knowledge to the real world, and were able to fly actual helicopters.

There are great advantages to being able to learn tasks in a VRE. For example, it is much cheaper and safer to train astronauts to fly shuttles in a VRE instead of in space. In fact this strategy is implemented in NASA training not only to fly shuttles but also to use the Canadarm. Another potential field for the use of VREs is in the medical field. Cadavers are in short supply, expensive to keep and there is an intrinsic problem with them. For the people to have died, there has to be something wrong with them, therefore all of the cadavers will be inherently flawed. With a virtual reality cadaver, there could be nothing wrong with it, or different problems can be created for the medical students to see, all in one “cadaver”. Pilots could learn to fly planes or young adults could master the skills required to control an automobile with far less danger to the rest of society.

With such an enormous potential market for VREs, the best way to utilize them should be explored. For example, would the students learn more by actively interacting with the program, or will students who passively watch the program learn the same? If active role of exploring and manipulating the VRE produces better learning, one on one programs should be developed. But if actively exploring does not confer an advantage over passively watching the VRE, programs should be developed that enables groups of students to learn all at the same time.

The question of active versus passive learning has been explored outside of a VRE for many years. An example of this research reveals that a car driver remembers the route that was taken much more accurately than the passenger, who was passively following the driver’s routes (Apple Yard, 1970). This result has been revealed to be controversial, however, with some data not supporting this conclusion (Ito and Matsunaga, 1990). Active versus passive research has also produced such controversial evidence.

Peruch et al 1995, designed an experiment to test active verses passive learning in a VRE. Subjects either actively explored an environment, locating hidden objects, or passively watched the exploration. The subjects were then placed randomly in the VRE and asked to find the shortest route to a certain, randomly chosen object. The error rate of the paths taken to the object was then compared between the active and passive subjects. Peruch et al’s hypothesis was supported by the evidence that the active subjects performed better at locating the objects, and hence had lower errors in their way finding, when tested than the passive subjects did.

A recreation of this experiment by Wilson et al in 1997 revealed contradictory results to those found by Peruch et al. They, in fact found no evidence of superior way finding in the active participants. Wilson et al, 1997, also performed an orientation study in conjunction with the way finding study, to compare active versus passive effects on orientation. The subject, either actively or passively, explored a VRE to learn the location of objects hidden from view, just as in Peruch et al’s experiment. The subjects were then tested by placing them in the VRE and asking them to point to a randomly chosen object from where they were situated, even though the objects were hidden from view. Contrary to their hypothesis, the evidence found there to be no difference between the active and passive groups and their ability to orient themselves in the VRE.

Another study performed by Wilson in 1999 provided more evidence that there is no difference between active and passive learning on orientation. When Wilson recreated his orientation experiment of 1997, the same results were found. In a parallel experiment, Wilson also tested the memory differences of subjects for objects encountered within the VRE. Subjects explored a maze, again actively or passively, and were required to remember the identity of objects encountered. There was found to be no difference between active and passive groups and the number of items remembered.

In summary, there is contradictory evidence on the role of active versus passive learning on way finding, and no difference between active and passive activities and their effects on orientation and on memory for objects.

The purpose of this study is to examine the effects of active versus passive learning on way finding through a virtual reality maze. It is hypothesized that the active participant will have a faster time when tested on way finding through a maze than a passive subject.

Methods

Subjects

Participants in this experiment were six women, who were associated with the experimenters and were undergraduate students at McMaster University from random programs. None of the participants had any previous experience with the equipment used or the software employed.

Apparatus

The subjects rode a stationary mountain bike, brand Super cycle, which was connected to the computer to explore the environment. Every move that was made on the bike was experienced on the computer screen through two sensors. One attached on the steering column controlled turning in the VRE. The other was attached to the rear wheel and controlled the speed of movement in the VRE. The computer was an SGI 02.

Figure 1 displays an aerial view of the practice maze, and Fig 2 displays an aerial view of the training/testing maze.

Insert Fig 1 Here.

Procedure

The six participants were divided into three groups of two and the groups were tested at separate times. Each participant began the experiment with a five-minute practice period in the practice maze to become accustomed to using the bike, making turns etc. From the two participants, one was randomly chosen to become an active subject while the other became a passive subject. The active subject then rode the bike through the training/testing maze for four trials, exploring the maze on a computer screen. They were timed and their errors recorded. The passive person watched the progress and activities of the active subject on the same computer screen as the active person, as the active person performed the task. There was a five-minute time limit on each training trial. If the subjects were unable to complete the maze before the five minutes were over, five minutes was counted as their time, and a new trail began. This was known as the training phase. The testing phase took place after the four training trials were completed. One subject was asked to leave the room. The other subject then went through the maze two times. The time to completion and the number of errors that occurred in this test trial are used as the basis for analyzing the results. In order to rule out the order effect, the experimenters switched between testing the active or passive person first.

Results

This experiment was conducted to determine whether or not there were differences in the ability of active versus passive subjects in learning a virtual reality maze. It was hypothesized that after four training trials the active earners would perform better than the passive learners. Data were collected on two outcome measures, time to complete the maze and the number of errors made, and time was considered the main endpoint.

The success of the active subjects ability to learn was assessed as a measure of the time to complete the maze [Insert Figure 2]. By conducting an ANOVA, it was determined that there was a significant change in performance across training sessions [t(df) = 3, p = 0.000336]. Although data were not statistically analyzed according to number of errors made, because this wasn’t our main endpoint, a similar trend was observed, where the number of errors appeared to decrease near the end of the training period [Insert Figure 3]. This set of results indicated that the active subjects had learned the maze by the end of the four training trials.

It was determined that during the testing phase, the mean time to complete the maze for active learners was M = 134.6 seconds, SD = 87.7 and the mean number of errors made among active learners was M = 0.75, SD = 0.957. In contrast, the mean time to complete the maze for passive learners during the test phase was M = 172.3 seconds, SD = 83.0 and the mean number of errors made among passive learners during the test phase was M = 0.75, SD = 0.957. This evidence shows that the active subject was considerably faster but did not tend to make fewer errors. Observation of the error rates indicates there are no significant differences between the ability of the active and the passive learners to remember the correct route through the maze [Insert Figure 4]. Similarly, a paired t-test revealed that the active learners did not perform significantly better than the passive learners in the test phase when time to completion of maze was measured [t(df)=3, p=0.0632, two-tailed]. Thus, despite the fact that a trend favoring better memory in the active subjects was observed; these results were not statistically significant. [Insert Figure 5 and Figure 6]. These results indicated that there was no significant difference in memory of the maze between the active and the passive learners.

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 1. This is the bird’s eye view of the test maze; it includes a subject’s path

Figure 2. The number of errors made by making a wrong turn in the virtual reality test maze by active subjects over four trials during the learning phase of the experiment.

Figure 3. The time needed to complete the virtual reality test maze for active subjects over four trials during the learning phase of the experiment.

Figure 4. The time needed to complete the virtual reality maze of each of the eight subjects in this experiment, where each passive subject is paired with the active subject that they watched complete the maze.

Figure 5. The number of errors made by making a wrong turn in the virtual reality test maze for each of the eight subjects in this experiment, where each passive subject is paired with the active subject that they watched complete the maze.

Figure 6. Differences between active and passive subjects in mean time to completion of maze.

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Ito, H., and Matsunaga, K. (1990). Relative Distance Perception through

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Information in Walking. Ecological Psychology, 2, 113-120.