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EVALUATION OF THE USE OF VIRTUAL ENVIRONMENTS (VE) IN SPECIAL EDUCATION

PJ Standen & J Cromby
Department of Learning Disabilities
University of Nottingham Medical School
South Block
E Floor
QMC
Clifton Boulevard
Nottingham NG7 2UH
UK
Tel: 0115 970 9247
Fax: 0115 978 1598
e-mail: mvzpjs@mvn1.nottingham.ac.uk
john.cromby@nottingham.ac.uk

Web Posted on: December 12, 1997


Introduction

Our work is designed to explore the benefits for people with learning disabilities of using virtual environments (Cromby et al 1996). Since everyone uses different terminology when talking about this client group it is necessary to begin with some definitions. In this paper, the term "people with learning disabilities" is used to refer to adults, whilst "students with learning difficulties" is used to refer to younger people. In other countries, these people might be described as "mentally retarded", "mentally handicapped", "developmentally disabled" or "intellectually disabled".

People with severe learning disabilities are defined as having an IQ of less than 50. In the United Kingdom about three or four people in every thousand fall into this category. They are an extremely heterogenous group with about 80% having some additional physical impairment such as mobility problems, sensory impairments, neurological problems and heart defects. Some have no speech, and must use signing systems to communicate.

Since the acceleration in the closure of long stay hospitals in the early 1980's many of these people have been moved to the community living either independently, in residential units or the family home and attending day centres. Young people growing up with learning disabilities can now expect a much greater degree of independent living with less support and more responsibility for their daily lives. There is an urgent need to find effective ways of helping them acquire the skills to cope with this.

Our group in Nottingham have been investigating the use of desktop virtual environments in this task as they possess several characterisitics which make them highly appropriate in the training and education of people with learning disabilities.

First, they encourage active involvement in learning because if the learner does nothing, nothing happens yet every action they make is responded to in predictable ways. Active involvement has been identified as an important component of learning (Wood, 1988) and may need even more encouragement in people with learning disabilities as they typically have little control over things that others take for granted (Kuh et al, 1988) and tend to assume a passive role (Sims, 1994). Evidence that students with severe learning difficulties take this opportunity was found in an earlier study (Standen and Low, 1996) where ratings were made of video tapes of teacher-student pairs using desktop virtual environments. Over successive sessions students with a wide range of abilities showed a significant increase in activities performed independently of their tutor's help.

Secondly, virtual environments create the opportunity for people with learning disabilities to learn by making mistakes but without suffering the real humiliating or dangerous consequences of their errors. Most young people will learn how to shop by first accompanying their parents and gradually helping with the task until they are allowed to go out unaccompanied maybe somewhere nearby for just one or two items. Young people with learning disabilities rarely accompany their parents on shopping trips either because of mobility problems, difficult behaviour or fear of others' reactions. Because of the fear of their vulnerability to danger they are overprotected (Shakespeare, 1975) and have fewer opportunities for independent outings . Accompanied visits to a real environment sufficient to learn a skill may be impossible to arrange. However, in the virtual environment they can go where they like even if they have a mobility problem. They can make as many mistakes as they like without hurting themselves or irritating others and the computer will not tire of the learner attempting the same task over and over again, nor get impatient because they are slow or engrossed in particular details (Salem-Darrow, 1995).

Thirdly a virtual environment can be manipulated in ways that the real version could not be. For a novice a simple world can be constructed and as the user becomes more familiar with the task the world can be made more complex (Middleton, 1992). So for example, an environment designed to help a new wheelchair user negotiate a building could omit closed doors until the user has mastered moving through narrow gaps.

Lastly, in virtual environments rules and abstract concepts can be conveyed without the use of language or other abstract symbols. This is because the learner can discover the qualities of objects by direct interaction with them (Bricken, 1991) for example, a shopping trolley will cease to move smoothly when obstructed by a shelving unit. This is especially important for people with learning disabilities who often have very limited language.

In evaluating the use of VE with students with severe learning difficulties we started with some of the claims made for its appropriateness. To illustrate our approach this presentation will deal with two of these claims: that virtual environments encorage self-directed activity and that learning in a virtual environment will transfer to the real world.

The value of self-directed activity has been highlighted by both developmental and cognitive psychologists. It may be even greater for people with learning disabilities. As with all people with disabilities, children with learning difficulties have less control over things that other children take for granted and assume they will play a passive role all the time (Sims, 1994).

Much of our work so far has been carried out in a school for students with severe learning disabilities. Catering for 160 students aged from 3 to 19 years it is the largest of its kind in the UK. Teachers at the school are faced with classes including a wide range of abilities, much more so than in main stream schools, and many of their students will have additional disabilities and disruptive behaviour.

The first study to be reported set out to investigate whether VE did promote self-directed activity, or whether teachers were using them in a more conventionally didactic manner.


Method

Participants: 18 teacher-student pairs took part. They ranged in age from 3 to 15 years and half were male. All had scores on the Vineland Adaptive Behaviour communication subdomains of receptive and expressive behaviour well below age-group norms indicating levels of low to adequate communicative ability.

Procedure: Each pair had between 4 and 10 twice weekly sessions using the Makaton programme. Each session was recorded on videotape. After repeated viewing of the tapes, teachers' activity was coded into 8 categories:

  • 1. Non 3D Instruction: any verbal instruction given by the teacher to direct child's attention back to the screen or to make a movement which was not through three-dimensional space eg move the arrow to the phone, click the mouse, look at the screen, press this button.
  • 2. Non 3D Suggestion: any verbal suggestion (can be in the form of question) given by the teacher to make a movement which was not through three- dimensional space. Unlike 1 above it does not tell the student how to accomplish a task but simply prompts the student eg let's see what the man does, would you like to turn the pages of this book? what do you think the doors can do? shall we have a look at another room?
  • 3. 3D Instruction: any verbal instruction given by the teacher to make a movement through three-dimensional space eg find the pencils, move to the right, press this button on the joystick to bring yourself up.
  • 4. 3D Suggestion: any verbal suggestion (can be in the form of a question) by the teacher to make a movement through three-dimensional space.eg would you like to move closer? Would you like to see what else is in the room?
  • 5. Pointing: this is when the teacher points to the screen to direct the student's attention, to instruct the student to move the arrow from one place to another. It often accompanies other behaviours (eg a question) but will be scored as a separate category.
  • 6. Physical Guidance: teacher physically guides the student in using the joystick, mouse or keyboard eg puts hand over student's hand to move mouse. As with pointing often accompanied by suggestion or instruction.
  • 7. Teaching Questions: questions and comments made by teacher that give meaning to student's experience. Could include comments made to put student's actions into context. eg everyone's gone out, maybe that's why the doors are shut; what is that? what colour are the pencils?
  • 8. Teacher's Move: teacher moves mouse or joystick or uses keyboard.

Students' activity was coded into three categories:

  • 9. Spontaneous 3D Movement: any movement made by student using joystick.
  • 10. Spontaneous Non 3D Movement: any movement made by student using mouse or keyboard.
  • 11. Student's Initiative Completed by Teacher: student starts an action which is completed by teacher.

As sessions differed in length, frequencies of behaviour categories were converted to rates (frequency of category divided by duration of session). As very few pairs completed more than 7 sessions, analysis was carried out on these only.


Results

  • 1. Teachers' behaviours. Using regression analysis, significant decreases in rate over repeated sessions was found for all of the teacher's behaviours with the more didactic categories (e.g. instruction and physical guidance) decreasing at a faster rate than suggestion and pointing.
  • 2. Students' behaviours. Regression analysis could not be used for the students' results because the data were slightly skewed and so rates for the first and last sessions were compared using a Wilcoxon one tail test. A significant increase in rate was found for spontaneous 3D movement (p<0.03) and spontaneous non 3D movement (p<0.04) but rates remained the same over sessions for Student's Initiative Completed by Teacher.
  • 3. If a composite score is formed for all teacher categories and then all student categories and these figures are plotted against session, teacher activity can be seen to decrease as student activity increases.

The second study to be reported investigated whether any learning which takes place in a virtual environment will transfer to environments where these skills are needed. People with learning disabilities are often described as concrete thinkers unable to use in another setting skills and knowledge learned in training.

In an earlier study we described how students with severe learning disabilities (Standen and Cromby, 1995) get better at using a real supermarket after practicing in a virtual supermarket on a desktop system. The real world task involved finding four items on a shopping list, putting them into a trolley and taking this to the checkout. All subjects carried out this task before half went on to have twice weekly sessions practicing the same task in a virtual supermarket while the rest, the control group, had twice weekly sessions with other virtual environments. On returning to the real supermarket the group with experience of the virtual supermarket were significantly faster and more accurate than the control group.

As evidence for transfer of learning the odds were somewhat stacked against the control group whose intervening activity was not structured in the same way as was the experimental group's and, apart from playing a game with the shopping lists, they had little opportunity to practice any of the component skills of shopping.

With this in mind we carried out another study with the same group of students, comparing learning using a virtual environment with learning the same task in the real world. One challenge facing the students when they start school is how to find their way around the complicated one storey building. Even after they have been at the school some time many of the students have never visited some parts without being taken there passively by someone else. To prepare them for this, teachers run sessions showing them how to use a map and then accompanying them while they attempt to find, with the help of the map, flags placed at intervals around the school. This practice is very time consuming, staff intensive and extremely challenging for children with mobility problems. Our study intended to compare this method of learning how to navigate the school with a virtual version.


Method

Participants: 22 students aged between 7 and 19 years who were scheduled to join a course as described above took part. They were randomly assigned to either an experimental or control group ensuring that the two groups were matched for age, sex, and ability as measured using the Vineland Adaptive Behaviour Scales.

Design: The task to be learnt was how to find flags placed around their school. For each flag a map was drawn indicating its location. The control group learnt this task in the real school while the experimental group learnt in the virtual school.

Virtual environment: The virtual school was built using the architect's plans for the real school, included all the areas from the real school and was to the same scale. It lacked some of the detail of the real school ie gym equipment, pictures but a n earlier study had shown that the students recognised it as a model of their school and could identify all the rooms. There were 16 flags placed around the it in the same positions as they are in the real school.

Procedure: All participants underwent a preliminary course to learn how to use a map. Then they had seven sessions (in the real school for the control group, the virtual school for the experimental). In each session the student had to find as many flags as possible and was limited to twenty minutes. After the first, sessions started with the students having to find the flags they had found on previous sessions before attempting to find new ones. When finding a flag they were given the appropriate map and the only clues given were those laid down according to a protocol. The final test was in two parts. First, the same tutor who had conducted all the previous sessions took all the students through an eighth session but for both groups this was in the real school. Secondly, a teacher who did not know to which group the participants belonged tested the students in the real school in their attempt to find eight of the flags randomly selected from those that all students had found on at least three sessions.


Results

  • 1. Time spent in training: There was no difference between the two groups in the total time spent with the tutor over the seven training sessions so neither group had the advantage of more of the tutor's time nor was the experimental group more expensive in teaching time.
  • 2. Number of flags found in training: the experimental group found significantly (p<0.05) more flags by the last session than did the control group. Eight of the experimental group but only 4 of the control group had found all 16 flags by the last trial but this difference did not reach significance.
  • 3. Performance in eighth session: as not all students found the same number of flags in this session, time taken was divided by the number of flags found. Although the experimental group had a lower mean time per flag (39.94 seconds) than the control group (47.55) this difference did not reach significance. Neither was there any difference between the groups in the number and types of clues given once these figures were adjusted for the number of flags found.
  • 4. Performance in teacher's assessment: although the experimental group had a lower mean time (499.00 seconds) than the control group (546.11) this difference did not reach significance. Neither was there any difference between the groups in the number and types of clues given.

While there were no significant advantages of the experimental group over the control group in the eighth session and the teacher's assessment there were suggestions of differences favouring the experimental group. They also learnt significantly more in the training sessions and appeared to reach a plateau earlier so that a test of their ability after fewer training sessions might have favoured the experimental group. However the fact that the experimental group was no worse than the control group is evidence that the learning they experienced in the virtual environment transfers to the real world analogue.


References

Bricken, W. (1991) "Virtual reality learning environments: potentials and challenges" Computer Graphics 25, 3.

Cromby JJ, Standen PJ and Brown DJ (1996) "The potentials of virtual environments in the education and training of people with learning disabilities" Journal of Intellectual Disability Research 40 (6), 489-501.

Kuh D, Lawrence C, Tripp J, Greber C (1988) "Work and work alternatives for disabled young people" Disability, Handicap and Society 3, 3-26

Middleton T (1992) "Advanced technologies for enhancing the education of students with disabilities" Journal of Microcomputer Applications January. 1-7

Salem-Darrow M (1995) "Virtual reality's increasing potential for meeting needs of persons with disabilities: what about cognitive impairments?" Proceedings of the Third International Conference on Virtual Reality and Persons with Disabilities. HJ Murphy (ed) Northridge CA: California State University Center on Disabilities.

Shakespeare, R. (1975) "The Psychology of Handicap" London, Methuen

Sims, D. (1994) "Multimedia camp empowers disabled kids" IEEE Computer Graphics and Applications January 13-14

Standen PJ, and Cromby JJ (1995) "Can children with developmental disabilities use virtual reality to learn skills which generalsie to the real world?" Proceeding of the Third International Conference on Virtual Reality and Persons with Disabilities HJ Murphy (ed) Northridge CA: California State University Centre on Disabilities.

Wood, D.J. (1988) "How Children Think and Learn" Oxford, Blackwells