Advantages Of Computing Systems For Dyslexic Students: Techniques.

Write the Use of computing system for the dyslexic student.

Problems faced by Dyslexic Patients

In today’s world information technology and internet have provided solutions to a lot of problems related to health care and issues related to transport and communication. Information communication technology has become a huge platform for managing the issues like dyslexia and many more. Information technology has created a lot of advantages which can be utilized for human welfare. One of the most important inventions is the cloud computing in the field of information technology (Alghabban, Salama & Altalhi, 2016). Cloud computing is created to provide a powerful processing unit which is shared by several computers for analyzing data and making reliable decisions.

In this report all the advantages and disadvantages of cloud computing are discussed with the background of cloud computing. A model is first designed to understand the functioning of the computer system for helping the dyslexic patients. Then the issues and boundaries of the model related to the computer system are discussed and another model is designed further after overcoming the issues. Some features are added to the new model for making it more accurate.

Dyslexia is a disease which makes it hard for the patients to read and study the alphabets and drawings. Generally they have a vision problem which leads them to misunderstand the problems due to the dyslexic nature. Generally they see the deformed or opposite view of the characters and pictures (Mulfari et al., 2015). It is also a confusing issue for both the student as well as the teacher in the classroom. The teacher may not understand the problems related to the particular student and in some cases it is seen that the teacher is unable to identify the students. It is not so dangerous issue for them to understand the concept behind any subject. Several methods and techniques can be used for making the system more suitable for the dyslexic patients. It is also very hard for the students to familiarize with new technologies which can be used in this case (Alghabban, Salama & Altalhi, 2016). The main advantage of making the system more advanced in terms of the creating a platform for the student is that the interface designing is not only a easy topic but also it is a perfect job for them to make it more suitable for the system to understand the topic.

There are several techniques to help the dyslexic patients that can be used for the advancement of the interface which is used between the computer and the patient.

With the improvement of electronics and computer science various new technologies are developed that can be a very good platform the dyslexic patients. The main advantage of using the new technologies is that the student does not need to depend on any person for the understanding of the subject. The computer system can be more effectively used for the dyslexic students who are not able to read paragraphs or comprehension (Beacham & Duncan, 2017). The computers can increase the reading capability of the student up to 80% when the student has special cases related to the reading issues. The computer can also create a bigger view or image using the projectors which can help the dyslexic students to understand the problems in an easier way. The main advantage of using the computer system is that the students can use the resources repeatedly and whenever needed. They do not need to rely upon other persons to make them understood about the reading problems.

Techniques to Help Dyslexic Patients

Cloud computing is an important technology which can be used for the dyslexic students who are unable to study properly. The main issue related to the reading is that the students cannot identify the characters and alphabets properly (Mulfari, Celesti & Villari, 2015). An advanced computing system can be designed based on the cloud computing so that the machine can utilize all the data collected from the student and the main advantage of making the system more advanced in terms of computing is that the machines have the decision taking techniques which can be used by the users. The better data security, computing power, easy access of the cloud make it more advanced and suitable for the use of the dyslexic students.

In today’s world mobile phones are used in maximum and those have become almost a constant companion of our daily life. Mobile can be used in case of helping the dyslexic students who face several issues related to reading and pronouncing (Mili?, Simi? & Milutinovi?, 2014). The main advantage of using the mobile phone is that it can help the student anytime and with only a few touches of their fingers on the screen of the mobile. The mobile data can be also very useful in case of making the students understand about the new techniques which can be helpful for them to understand the problems.

This project has a lot of limitations which are discussed in this section in details. The main problem with this structure or the flowchart is that it can be used to determine the relations with many limitations. It is unable to provide the two sided communication and that is compulsory in case of solving the problems related to the students (Kraft et al., 2015). The main advantage of making this device is that it can help the dyslexic patients. But in this case the dyslexic patient cannot provide the issues related to his or her pronunciation and reading skill. The other important problems regarding this flowchart is that it cannot make the system more advanced in terms of accuracy and feedback from the point of view of the student only with respect to other factors taking the scenario into account which is stated in the above mentioned aspect (Johnson et al., 2014). The main problem of this system is that it does not ask the student for feedback. The student is only able to get the idea about the objects which are shown in the screen but specifically cannot convey his or her problem to the system (Pee et al., 2017). To get the new model main focus should be given to the student and the issues of the student which should be given to the system for the understanding of the difficulties of the student the student may not understand the characters or letters given in a paragraph. The main problem is that they are actually unable to make the differentiation between same kind of characters which look almost same (Jayapandian, 2014). The main disadvantage is that some numbers and calculations cannot be asked by the model to the student that they can understand those or not. The main problem regarding this problem is that the students are completely out of idea when they are not asked about the identification of the characters or sound. There are also many problems related to the system which are also not helpful for the guardians of the students who may assist their children in understanding the problems (Helland, 2016). That is why a new system is required which can help the students in understanding the characters and letters in more specific way. The main model is shown in below.

Use of Computing Systems for Dyslexic Students

This new model is more advanced in terms of making the student understand about the characters and numbers identification in a more precise way. This has become possible for adding a new part in the first model. A cloud computing feature is added to the system which can be utilized in terms of making the system more advanced in terms of accuracy and reliability from the point of view of the student. The main advantage of making the student more understood about the project is that it can be used in a larger aspect for the student to make it easier for them (Gómez & Ojala, 2014). The main problem in the previous model was that students were unable to make the identification and differentiation of the characters and several numbers from the data resources given by the system. The other important problems regarding this flowchart is that it cannot make the system more advanced in terms of accuracy and feedback from the point of view of the student only with respect to other factors taking the scenario into account. The main problem of this system is that it does not ask the student for feedback. The student is only able to get the idea about the objects which are shown in the screen but specifically cannot convey his or her problem to the system (Alghabban, Salama & Altalhi, 2017). To overcome this model the system is added with the cloud element which has a much more powerful processing unit for the analysis of the data given by the student in terms of making the problems from the point of student. The introduction of the cloud computing in the new model has created a platform for the student which actually asks them to verify about the objects which are shown in the display system of the computers (Beacham & Duncan, 2017). The main advantage of making the system more advanced in terms of making it more suitable to the student is that they can easily identify and compare their problems with respect to the standards.

Conclusion

From the above discussion it can be concluded that the students having dyslexia can reduce their difficulties to a greater extent by using the computing system in which the cloud computing features are implemented. The main advantages of this system are that the system is more powerful in terms of processing and decision making due to the use of the cloud computing feature. The main aspect of the system is that it asks the students repeatedly about the objects which they are actually watching in the screen and in this way the system try to understand the issues of the student. After understanding the issues the system actually implements it data analysis to recover the actual information related to the student for better understanding the student’s point of view. 

References

Alghabban, W. G., Salama, R. M., & Altalhi, A. (2016). Mobile Cloud Computing and M-Learning: State of Art.

Alghabban, W. G., Salama, R. M., & Altalhi, A. H. (2017). Mobile cloud computing: An effective multimodal interface tool for students with dyslexia. Computers in Human Behavior, 75, 160-166.

Beacham, N., & Duncan, R. (2017, February). Development of a Secure Cloud Based Learning Environment for Inclusive Practice in Mainstream Education. In Eighth International Conference on Cloud Computing, GRIDs, and Virtualization, 19 February 2017-23 February 2017, Athens, Greece. IARIA.

Gómez, J., & Ojala, T. (2014). A mobile navigation system based on visual cues for pedestrians with cognitive disabilities. Assistive Technologies for Physical and Cognitive Disabilities, 173-190.

Helland, T. (2016). Dyslexia identified early and persists into adolescence. The Journal of pediatrics, 170, 341-344.

Jayapandian, C. P. (2014). Cloudwave: a cloud computing framework for multimodal electrophysiological big data (Doctoral dissertation, Case Western Reserve University).

Johnson, E., Pardini, J., Sandel, N., & Lovell, M. (2014). C-45 Do Athletes with Dyslexia Differ at Baseline and/or at Concussion Post-Injury Assessment on a Computer-Based Test Battery?. Archives of Clinical Neuropsychology, 29(6).

Kraft, I., Cafiero, R., Schaadt, G., Brauer, J., Neef, N. E., Müller, B., ... & Skeide, M. A. (2015). Cortical differences in preliterate children at familiar risk of dyslexia are similar to those observed in dyslexic readers. Brain, 138(9), e378-e378.

Mili?, A., Simi?, K., & Milutinovi?, M. (2014). Cloud Computing Environment for e-Learning Services for Students with Disabilities. In Continued Rise of the Cloud (pp. 363-381). Springer London.

Mulfari, D., Celesti, A., & Villari, M. (2015). A computer system architecture providing a user-friendly man machine interface for accessing assistive technology in cloud computing. Journal of Systems and Software, 100, 129-138.

Mulfari, D., Celesti, A., Villari, M., & Puliafito, A. (2013, December). Using virtualization and Guacamole/VNC to provide adaptive user interfaces to disabled people in cloud computing. In Ubiquitous Intelligence and Computing, 2013 IEEE 10th International Conference on and 10th International Conference on Autonomic and Trusted Computing (UIC/ATC) (pp. 72-79). IEEE.

Mulfari, D., Celesti, A., Villari, M., & Puliafito, A. (2014, February). Using virtualization and noVNC to support assistive technology in cloud computing. In Network Cloud Computing and Applications (NCCA), 2014 IEEE 3rd Symposium on (pp. 125-132). IEEE.

Mulfari, D., Celesti, A., Villari, M., & Puliafito, A. (2015). Providing assistive technology applications as a service through cloud computing. Assistive Technology, 27(1), 44-51.

Pee, N. C., Mohtaram, S., Shibgatullah, A. S., Sulaiman, H. A., Othman, M. F. I., Rahim, Y. A., & Othman, M. A. (2017). The Framework of Mobile Dyslexia Screening Test Using Multiple-Deficit Theories. Advanced Science Letters, 23(5), 4000-4004.