Language and Communication Evidenced Based Practice

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Social Language Development Test

The Social Language Development Test is a test that is meant to measure one’s language-based skills of interaction with friends and social interpretation skills. These skills are known to be the best predictors of social language. The Social Language Development Test helps teachers gain insight on the competency of their students when it comes to language tests as well as their social understanding. While most children do well on traditional language tests, their social language skill might be inadequate. This test has the ability to substantiate the influence that a language disorder has on social disorders and determine whether they should be placed in therapy or not. The tasks incorporated in this test tend to reflect the development of social language expression and comprehension. The Social Language Development Test has numerous subtests that entail verbal expressions, question-answering tasks, verbal explanations, and interpretations of photographed scenes (Moon, Cho, Lim, Roh, Koh, Kim, & Nam, 2019). Subtest A is all about making inferences as the pupil is expected to infer what another person is thinking. In subset B, interpersonal negotiations take place where the pupil pretends to be having a conflict with peers and they must identify the problem and propose a solution. Subtest C is about multiple interpretations where the pupil demonstrates flexible thinking. In Subtest D, student supports their peers by pretending to be in similar situations as them. Validity of the subtests is established using the construct of group validity. Reliability, on the other hand, is established through test-retest, inter-rater reliability and reliability, which is based on the homogeneity of each item. Without a doubt, I would use the social language development test as an assessment method in the classroom. I would find it helpful especially since it can give me a hint about my students’ abilities. It will help me learn my students better and this way I can help them meet their needs.

Speech Generated Devices

Speech-generated devices are tablet-like devices that make it possible for people that can con longer speak to communicate their thoughts using electronic voice generation. Speech-generated devices are uniquely programmed and highly personalized to perform their functions, and without them, most people would be isolated and tapped into a body without the ability to communicate. The devices tend to be hand-held, and users use them by pressing keys or buttons. Some devices even read words out loud as a person types on a keyboard. Speech-generating devices are common for people that do have a difficult time pronouncing words owing to a physical disability like acquired brain injury or cerebral palsy (He, Sainath, Prabhavalkar, McGraw, Alvarez, Zhao, & Gruenstein, 2019). Autistic children also use speech-generating devices to develop their language and speech. Undoubtedly, speech-generating devices are of help to autistic children. Research has demonstrated that autistic children tend to prefer speech-generating devices to other argumentative and alternative communication devices. Worth noting, that speech-generating devices cannot prevent children from speaking if they cannot speak. Additional and large-scale research is required to figure out the system that best suits children and the best way that children can put to use speech-generating devices. Parents that choose to buy their children speech-generated devices should be involved in the use of the device with the child. Parents should also ensure that every person in the child’s environment is conversant with the device. I would use speech-generating devices in the classroom as it would help children with communication issues to improve them. Additionally, the speech-generating device is the perfect teaching intervention for children that have autism as well as learning disabilities. It is an easier way to help students communicate better and improve their pronunciation capacities.

References

He, Y., Sainath, T. N., Prabhavalkar, R., McGraw, I., Alvarez, R., Zhao, D. & Gruenstein, A. (2019). Streaming end-to-end speech recognition for mobile devices. In ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 6381-6385). IEEE.

Moon, J. H., Cho, S. Y., Lim, S. M., Roh, J. H., Koh, M. S., Kim, Y. J., & Nam, E. (2019). Smart device usage in early childhood is differentially associated with fine motor and language development. Acta Paediatrica, 108(5), 903-910.