=Paper=
{{Paper
|id=Vol-2533/paper22
|storemode=property
|title=Multimedia Educational Technologies for Teaching Students with Autism
|pdfUrl=https://ceur-ws.org/Vol-2533/paper22.pdf
|volume=Vol-2533
|authors=Vasyl Andrunyk,Volodymyr Pasichnyk,Nataliia Kunanets,Tetiana Shestakevych
|dblpUrl=https://dblp.org/rec/conf/dcsmart/AndrunykPKS19
}}
==Multimedia Educational Technologies for Teaching Students with Autism==
https://ceur-ws.org/Vol-2533/paper22.pdf
Multimedia Educational Technologies for Teaching
Students with Autism
Vasyl Andrunyk [0000-0003-0697-7384], Volodymyr Pasichnyk [0000-0002-5231-6395],
Nataliia Kunanets [0000-0003- 3007-2462], Tetiana Shestakevych [0000-0002-4898-6927]
Lviv Polytechnic National University, Lviv, 79000, Ukraine
Vasyl.A.Andrunyk@lpnu.ua, Tetiana.V.Shestakevych@lpnu.ua
Abstract. Visualization of educational materials in the education of students
with autism is a useful and convenient learning tool. At the same time, choosing
the most useful and effective multimedia educational technology to support
such learning is a problem, as there is a wide range of developed technologies,
and each participant in the process of education of children with autism assesses
such technologies subjectively. Each participant of IT-support of education of
students with autism, i.e. inclusive school teacher, psychologist, parents, IT
specialist has its own criteria how to assess such multimedia technology, and
development of objective criteria for evaluating such technologies will become
the basis for developing an appropriate system that will form a complex
information technology of education of a student with autism in an inclusive
classroom. Applying the analytic hierarchy process, allows to make reasoned
decisions.
Keywords: Multimedia Educational Technologies, Teaching Students with
Autism, Information Technology, Analytic Hierarchy Process
1. Introduction
Combining different forms of information provision in educational content is an
integral characteristic of modern educational technologies. The use of audio, graphical
and video signals is of particular importance for the teaching of students with autism.
Moreover, the theory and practice of teaching students with autism is developing
through the ability to use multimedia educational technologies.
The use of visual tools in teaching such students has proven effective [1, 2]. The
reason for this is the peculiarities of the autism spectrum disorders, often students
with such nosology have communication difficulties, it is problematic for them to
establish social bonds [3]. Developed information technologies to support the learning
of students with autism, in addition to the presentation of academic knowledge,
should be able to improve social and communication skills.
In Ukraine, one of the regional training and rehabilitation centers for children with
autism uses augmented and virtual reality (AR and VR) ICTs to study specific topics in
the training course. For example, the Social and everyday orientation course is
Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License
Attribution 4.0 International (CC BY 4.0)
2019 DCSMart Workshop.
supported with augmented reality technology (fig. 1а, 1b shows the road crossing
with a traffic signal scenario, 1c, 1d shows the computer class behavior scenario).
a) b)
c) d)
Fig. 1а-1b. A fragment of a Road crossing with a traffic signal scenario, 1c, 1d. A fragment of
a Computer class behavior scenario
Such visualization of the processes of daily activity enables students with autism to
learn and improve social skills in safe situation, providing the necessary number of
repetitions of such activities for better memorization.
Modern, actual ICTs for students with autism are developed using virtual,
augmented and mixed reality technologies [1, 4, 5] (Fig. 2). Such technologies are
very useful to improve the social and communication skills of students with
autism.
Fig. 2. Types of educational information technologies for education of students with autism
Modern professionals, who work with students with autism have access to a wide
range of multimedia educational technologies. A large amount of such ICTs is publicly
available. At the same time, such multimedia educational technologies developed by
enthusiasts (inclusive teachers, psychologists, parents, and IT professionals) are
disparate, mutually unrelated technologies, and are used to teach a specific topic or a
special, personalized social or communication skill. Therefore, the use of such
multimedia educational technology by a third-party paraprofessional is almost
impossible. The selection of appropriate information technology could be remedied by
the existence of a common pool of accessible multimedia technologies that could be
used by inclusive education professionals. But even then, the search for the right ICT
that would meet the requirements of the specialist, and also take into account the
characteristics and abilities of the student with autism, involves a complete search of
such information technologies. It will be a complete waste of time. In other hand, if
such technologies were characterized, it would save time for teachers. Currently, various
paraprofessionals publish reviews of available ICTs and evaluate them for certain
subjective characteristics [7].
The standard ISO / IEC40500: 2012, created by World Wide Web Consortium
(W3C) is an objective tool for assessing the IT-support of autistic student education
[8]. This standard recommends that the developers of ICTs for persons with
disabilities should take into account the responsiveness, efficiency, comprehensibility
and reliability of the created software [9]. One can check automatically the level of
website compliant to such demands by using the Achecker service [10]. The Achecker
detects various types of errors, and for the average standard compliance level (AA
level) there are 61 types of such errors.
The Fig. 3 shows a snippet of the Achecker, displaying the results of a review of the
Inclusive Education website (https://education-inclusive.com/), created by by the All-
Ukrainian public association The National Assembly of People with Disabilities of
Ukraine. Six errors of two types were identified, these were related to distinction (to
facilitate the visual and auditory perception of information by users, including
distinguishing of the front and back of the site), as well as sufficient time to read and
use the content. For comparison, the site of the All-Ukrainian public association
National Assembly of People with Disabilities of Ukraine (https://naiu.org.ua/) has 48
errors of five types (related to non-text elements of the site, adaptability of its content,
the distinguishability of the content, site navigation, assistance with data entry). The
website of the National Committee for Sport of Disabled People of Ukraine
(https://new.paralympic.org.ua/, version for the visually impaired), has 29 errors of
five types.
Fig. 3. Fragment of Achecker application window with web site analysis results
The Achecker application has proven to be a useful tool for analyzing the websites of
regional psychological, medical, and pedagogical institutions of Ukraine [9], the
websites of regional libraries [1], etc. However, this application is only useful for
website analysis, it cannot be used to test for compliance with the ISO requirements of
other types of ICTs. The variety of multimedia educational technologies available to
students with autism does not systematically support the learning of such students.
According to the authors, it is advisable to develop a recommendation system that
would allow the design of information technology for the training of a student with
autism, taking into account his or hers abilities, as well as the psychophysical
characteristics of such a student, his educational characteristics. And of course, we need
to consider the available hardware, i.e. computers, VR-glasses, video projector, etc.
The development of such a recommendation system involves evaluating the available
multimedia education technologies for students with autism on a variety of dimensions.
The characteristics of assessing of educational multimedia for students with autism will
allow not only to comprehensively select and combine existing educational
technologies, but also to develop appropriate ICTs that would meet the needs of all
participants in the educational process of students with autism.
As it was mentioned above, the modern process of education of students with autism
involved psychologists, inclusive education teachers, parents of students with autism, IT
specialists [7]. According to the Ministry of science and education of Ukrainian, in the
Letter Regarding the duties of a teaching assistant [11], the teaching assistant teacher in
the inclusive classroom must perform a number of functions. Multimedia educational
technologies can help such a specialist to perform these functions. Therefore, the criteria
for evaluating such technologies for a assisting teacher are the ability to use such
technologies to assist in the fulfillment of their functions in an inclusive classroom. For
example, to support organizational function, the assisting teacher may use multimedia
educational technologies to organize the educational process, to monitor the child in
order to study his individual characteristics, inclinations, interests and needs, etc.
(appropriate criterion for evaluating educational we call organizational).
To support the educational and development function, multimedia educational
technologies are used to provide educational services, to promote the development of
children with special educational needs, to improve their psychological and emotional
state, to stimulate the development of their social activity, to facilitate the identification
and disclosure of their abilities, talents, and gifts (training criterion). The diagnostic
function is to participate in the development of an individual curriculum, evaluation of
students' educational achievements, etc. (diagnostic criterion). The prognostic function
is to create an individual development program based on an analysis of the actual and
potential development of the child (prognostic criterion). And finally, the counseling
function involves, among other things, constant communication with parents and
informing them and the class teacher about the student's achievements (consultation
criterion).
The criteria of educational multimedia, relevant to each participant of the educational
process of a student with autism, are presented at Fig. 4 [8, 9, 11, 12].
Fig. 4. Relevant criteria of educational multimedia for students with autism
To support the decision about the components of such complex information
technology, various methods can be used. For example, a analytic hierarchy process can
be implemented.
2. An Analytic Hierarchy Process for Choosing Multimedia
Educational Technology
Decision-making problems are constantly emerging and solved in biological, ecological,
social, and economic systems, various processes and phenomena. The decision is a
reasonable set of actions by the decision maker aimed at the object or control system,
which gives the opportunity to bring the object or system to the desired state or to
achieve its goal. Decision making is the process of choosing the most preferential
decision from the set of valid decisions or ordering the set of decisions. Decision-
making is possible on the basis of knowledge about the object of management, the
processes that take place in it and can happen over time, as well as in the presence of
many indicators that characterize the effectiveness and quality of the decision.
Any decision-making process is carried out in several basic stages.
Stage of the problem statement. It consists of phases of analysis and diagnosis of the
problem and determination of the goals of the solution.
Stage of decision making. It consists of the phases of formulating constraints and
decision-making criteria and identifying alternatives to the decision.
Stage of decision selection. It consists of phases of evaluation of alternatives and final
decision selection. At this final stage, the options from the set of feasible alternatives are
evaluated according to the criteria chosen and the final decision is made.
The analytic hierarchy process (AHP), proposed by the T. Saati [13] is one of the
well-known approaches for determining the optimal solution in multicriteria conditions.
This method has several advantages over other methods as it allows to take fully into
account all the criteria offered to select the best multimedia educational technology for
teaching students with autism.
To implement the method of analytic hierarchy process it is necessary to create a
hierarchical three-level structure. The goal is the upper level and the decision is taken
about this goal, the second level is the set of criteria by which alternative multimedia
educational technologies for training students with autism are selected. Next, the
alternatives form the third level of the hierarchy. Decision-making is about choosing one
of the possible alternatives based on a set of priorities. We shall illustrate the method of
analytic hierarchy for choosing a multimedia educational technologies for teaching
students with autism – from the point of view of an assistant teacher (the criteria and
attributes are above). A diagram illustrating from the perspective of an inclusive
classroom assisting teacher is shown in Fig. 5.
Matrixes of judgments are constructed based on the results of pairwise comparison.
Each matrix defines a priority vector that reflects the weights of the criteria and
alternatives. The alternative with the greatest global weight is considered to be the
choice of multimedia educational technology.
Fig. 5. Scheme of the AHP method for selecting multimedia educational technologies for
teaching students with autism from the perspective of an inclusive classroom assisting teacher
The AHP method uses an expert rating scale of paired comparisons of one object
over another, with values from 1 to 9. The general content of these estimates is given
in Table 1 [15].
Table 1. The importance scale for pairwise comparison matrices
Importance scale Value
Equal 1
Weak 3
Strong 5
Very strong 7
Absolute 9
Intermediate value 2, 4, 6, 8
Let us consider the features of using the AHP to determine the best multimedia
educational technology for teaching students with autism, which should be used by
assistant teacher. As mentioned above, such technologies can be used by the teacher in
terms of being able to assist in the performance of his functions. For each such
criterion (organizational, diagnostic, prognostic, training, and consultation), we set a
scale of importance for the four multimedia technologies, find the weight of the
respective alternatives.
The matrix of pairwise comparisons of the alternative multimedia according to the
diagnostic criterion is given in table 2.
Table 2. The matrix of pairwise comparisons for the diagnostic criterion
Alternatives М1 М2 М3 М4
М1 1,00 3,00 5 9,00
М2 0,33 1,00 3 7,00
М3 0,20 0,33 1 3,00
М4 0,11 0,14 0,33 1,00
Sum 1,64 4,47 9,33 20
The results of the calculation of the weights of alternatives by the diagnostic
criterion are given in Table. 3. The calculation was performed according to method 3
(see [14]), after which each column was normalized, and then priority column vector
found.
Table 3. Weight of alternatives by the diagnostic criterion
Alternatives М1 М2 М3 М4 Sum Weight of alternative
М1 0,60 0,70 0,50 0,50 2,26 0,56
М2 0,20 1,20 0,30 0,40 1,09 0,27
М3 0,10 0,10 0,10 0,20 0,45 0,11
М4 0,10 0,0 0,0 0,10 0,18 0,46
We calculate the priority vector as an estimate of the principal eigenvector of the
pairwise comparison matrix. The elements of this vector are the weights of
alternatives, which are calculated as the algebraic sum of the elements of the
corresponding row of the table 3, divided by the total number of alternatives.
Therefore, by diagnostic criterion, Multimedia 1 is the best alternative because it
has the highest weight value of 0,56.
For pairwise comparison matrix for the diagnostic criterion, the following
parameters were calculated:
the estimation of the largest eigenvalue, which is calculated by the formula
n
max wi si , where wi is a weight of the alternative with number i, si is a
i 1
sum of elements of column number i from pairwise estimation matrix, n is
the number of alternatives;
n;
consistency index CI max
n 1
CI
index of ratios sequence CR .
RI
Here and after, RI 0,9 an index for n = 4 alternatives.
After calculating for the pairwise comparison matrix constructed by the diagnostic
criterion, these parameters take the following values:
max 1,64·0,56 + 4,47·0,27 + 9,33·0,11 + 20·0,46 = 4,142;
n
– consistency index CI max = (4,142-4)/4-1 = 0,047;
n 1
CI
– index of ratios sequence CR = 0,047/0,9 = 0,053.
RI
Because the CR = 5,30% < 10%, then we consider the matrix of pairwise
comparisons for the diagnostic criterion as agreed.
Similar calculations are made for the other criteria (organizational, diagnostic,
prognostic, training, consultation). The calculated weights of the alternatives are
given in Table 4.
Table 4. Weights of alternatives
Organizational Diagnostic Prongostic Training Consultation
0,566009 0,504974 0,411548 0,634582 0,54394568
0,274384 0,320422 0,41774 0,17624 0,20693193
0,113308 0,133113 0,110652 0,117988 0,18572699
0,046299 0,041492 0,060061 0,07119 0,0633954
Diagram of the distribution of weight coefficients presented at in Fig. 6.
Fig 6. The scales of alternative multimedia educational technologies for students with autism
According to the results, Multimedia 1 is the best alternative for assisting teacher
in fulfilling his demands to help in an inclusive class. The AHP can be a helpful tool
in educational decision making. To make the method more accurate, we shall detail
the assessment of each of criteria by specifying its attributes.
The criterion Support and correction of communication skills can be evaluated by
such attributes:
Types of educational influences,
The degree of interactivity of the training environment,
Need for communication,
Variation of types and forms of dialogue,
Types of interaction,
Formation of skills of correct dialogue.
The criterion Improving social skills can be evaluated by such attributes:
Taking into account the individual abilities and characteristics of the student
with ASD,
Individualization of training,
New types of educational activity,
Organizational forms of the lesson,
Design of educational material.
The criterion Organizational can be evaluated by such attributes:
Monitor changes in a student's psychological and emotional state of a student
with ASD,
Multilevel training material,
Academic mobility,
Organizational forms of the lesson,
The structure of the learning algorithm,
The degree of interactivity of the learning environment.
The criterion Diagnostic can be evaluated by such attributes:
Educational success,
Taking into account the initial level of student`s skills.
The criterion Prognostic can be evaluated by such attributes:
Consideration of individual abilities and characteristics of the student with
ASD,
Individualization of education.
The criterion Consultation can be evaluated by such attributes:
Academic mobility,
Informing students about their achievements.
The criterion Training can be evaluated by such attributes:
Individualization of learning,
Capability development,
Structure of educational goals,
Quality of educational material,
Design of educational material,
Performance of the educational task,
Types of educational influences,
The degree of interactivity of the learning environment,
Development of professional independence,
New types of educational activity,
Type of dialogue.
The criterion Software can be evaluated by such attributes:
Software quality,
Methods and means of access to educational material,
Additivity,
Availability of multimedia,
Type of environment management,
Programming technologies used.
The criterion Interaction between objects can be evaluated by such attributes:
The degree of interactivity of the learning environment,
Compliance with the requirements of universal design,
Compliance with ISO requirements,
Overall composition of the website,
A harmonious combination of color schemes,
Feedback.
The criterion Individualization of training can be evaluated by such attributes:
Taking into account the individual abilities and characteristics of the student
with ASD,
Capabilities development,
Monitoring changes in the psycho-emotional state of a student with ASD.
The criterion Feedback available can be evaluated by such attributes:
Type of environment management,
Learning success.
The proposed attributes of each criterion will form the basis of a complex multi-
criteria assessment of multimedia educational technologies for children with autism.
After assessment of each attribute, the final assessment of the criterion will be
calculated, and only then the AHP will be conducted. Adding attributes assessment into
the AHP will enable more specific, personalized evaluation of each criterion.
3. Conclusions
The multimedia educational technologies are of great support in training students with
autism. It is difficult to choose an appropriate media from the existing, each teacher,
psychologist or parent of such a student is doing this on his own. The system of
decision support might help to choose the best alternative multimedia, but that
requires the existence of a range of characteristics, that might be assessed for each
multimedia. The difficulty is that such set of characteristics should take into account
needs of all the participants of education of students with autism. Authors proposed
such set of characteristics and showed how decision can be taken using the analytic
hierarchy process. To enable taking into account more detailed assessment of
multimedia educational technology, we suggested a set of attributes as a specification of
each attribute. In the future researches, we shall develop a system, that will evaluate the
effects of multimedia implementation into educational process of a student with autism.
References
1. Andrunyk, V., Shestakevych, T., Pasichnyk, V.: The technology of augmented and virtual
reality in teaching children with ASD. Econtechmod. Vol. 7 (4), 59-64 (2018).
2. Drigas, A., Vlachou, J.: Information and Communication Technologies (ICTs) and Autistic
Spectrum Disorders (ASD). International Journal of Recent Contributions from
Engineering, Science & IT (iJES). 3 (2016).
3. Tsiopela, D., Jimoyiannis, A.: Pre-vocational Skills Laboratory: Development and
Investigation of a Web-based Environment for Students with Autism. Procedia Computer
Science. Vol. 27, pp. 207–217. (2014).
4. Lytvyn, V., Vysotska, V., Mykhailyshyn, V., Rzheuskyi, A., Semianchuk, S.: System
Development for Video Stream Data Analyzing. In: Lytvynenko V., Babichev S., Wójcik
W., Vynokurova O., Vyshemyrskaya S., Radetskaya S. (eds) Lecture Notes in
Computational Intelligence and Decision Making. ISDMCI 2019. Advances in Intelligent
Systems and Computing, vol 1020, pp. 315-331. Springer, Cham (2020).
5. Zdebskyi, P., Vysotska, V., Peleshchak, R., Peleshchak, I., Demchuk, A., Krylyshyn, M.:
An Application Development for Recognizing of View in Order to Control the Mouse
Pointer. In: Modern Machine Learning Technologies and Data Science, Vol. 2386, pp. 55-
74 (2019).
6. Pasichnyk, V., Shestakevych, T., Kunanets, N., Rzheuskyi, A., Andrunyk, V.:
Accessibility Analysis of Scientific Libraries Web Resources. Econtechmod. Vol. 8(2), pp
9-16 (2019).
7. Andrunyk, V., Shestakevych, T., Pasichnyk, V., Kunanets, N.: Information Technologies
for Teaching Children with ASD. In: Hu Z., Petoukhov S., Dychka I., He M. (eds)
Advances in Computer Science for Engineering and Education II. ICCSEEA 2019.
Advances in Intelligent Systems and Computing, vol 938. Springer, Cham (2020).
8. ISO Homepage. Available online: https://www.iso.org/standard/58625.html, last accessed
2019/10/09.
9. Pasichnyk, V., Shestakevych, T., Kunanets, N., Andrunyk, V.: Analysis of completeness,
diversity and ergonomics of information online resources of diagnostic and correction
facilities in Ukraine. In: 14th International Conference on ICT in Education, Research and
Industrial Applications. Integration, Harmonization and Knowledge Transfer (ICTERI),
vol. I, pp. 193-208 (2018.)
10. Youngblood, S., Youngblood, N.: Usability, content, and connections: how county-level
Alabama emergency management agencies communicate with their online public.
Government Information Quarterly, vol. 35, iss. 1, pp. 50-60 (2018).
11. Regarding the duties of a teaching assistant, https://zakon.rada.gov.ua/rada/show/v-
675736-12, last accessed 2019/10/21.
12. Hrytsiuk, Yu., Andrushakevych, O.: A tool for determining the quality of software by
metric analysis methods. Scientific bulletin NLTU of Ukraine. Vol. 28 (6), pp. 159-171
(2018).
13. Saaty, Thomas L.: Mathematical Principles of Decision Making (Principia Mathematica
Decernendi) Pittsburgh: RWS. (2009).
14. Kolyada, M., Bugayeva, T.: Making pedagogical decisions based on the analysis of
hierarchies by the Saati method. Educational technologists and society. No. 2(18) (2015).
http://ifets.ieee.org/russian/periodical/V_182_2015EE.html, last accessed 2019/11/01.