Applying Science Methodology of Artificial Intelligence on School Students in Writing Skills Testing Education
Dr Nong Shim Ningbo University China Abstract This study explored the use of AI in a foreign language (FL) writing by foreign language majors at Faculty of languages and translation, King Khalid University. The role of translation, and specifically online translation tools (OLT). The present study tried to document students’ existing use free online translation (FOT) tools, and their views about these tools. The tools of the study involved video observations and questionnaires regarding FOT use. Twenty-one university students enrolled in a writing course. Follow-up interviews were done with the students who were observed using FOT tools widely on the video recordings. Results indicated those students have a primarily positive attitude toward FOT tools. In addition, most of students said that they use such tools frequently. Results are discussed in the context of the continuing debate over whether and how translation technology should be used in FL classrooms. These findings show the importance of providing teachers and students with instruction on (FOL), as well as the need for additional research on the effects of AI on writing acquisition. Keywords Artificial Intelligence, Elementary School Students,Free Online Tools, Translation, Writing Skill The Development of Artificial Intelligence Artificial Intelligence (AI) had appeared a long way since the presence of AI research in the 1950s when Turing developed the well-known Turing Test to inspect whether machines could think. Early trends in AI research displayed a philosophical difference between Weak AI and Strong AI. The vision of AI as a building system that can think like humans was known as Strong AI. Interchangeably, allowing systems to work without figuring out the difficulties of human thinking was seen as Weak AI (Marr, 2018). Strong AI has been thought as a threatening perception, since it aims to reproduce human intelligence and take over control from humans. The definition of twenty-first-century of AI has been reformed as follows: AI is “a science and a number of computational technologies that are inspired by—but usually operate quite differently from—the ways people use their nervous systems and bodies to sense, learn, reason, and take action.” (Stone et al., 2016). We do not have enough knowledge about the complications of human cognition to approximate it via machines. That being said, as research has progressed, it has moved beyond the perspectives of Strong and Weak AI. A third objective of AI is to build models based on human cognitive without the end goal of reproducing difficult human thinking (Marr, 2018). One such new development related to this third objective is the “partnership on AI to benefit people and society.” This partnership was cofounded in 2016 by Amazon, IBM, Google, Facebook, and Microsoft to study how AI is being used, and to examine AI’s influence on people and society. (Hern, 2016). By creating an open platform for discussions, this partnership sets up a type of transparency for studying the big influence of AI. Stanford University showed a “100-year report on AI” in 2016. By providing historical documentation and future directions, this report released to examine eight factors related to AI, containing the factor of education. While AI provided great promise for language learning, the early work of AI lessened because of its limited ability to promote deep learning. Today, AI has permeated many aspects of everyday lives, from smart applications on our mobile devices to self-driving cars. (Stone et. al, 2016). For a long time translation and language learning developed together as the grammar translation model used to teach languages, mainly for reading and writing knowledge was applied to the teaching and learning of languages. The separation between grammar-translation models and theories of foreign language acquisition resulted to the development of communicative teaching methods to language learning and teaching during the last half of the 20th century. This does not mean translation has disappeared from the classroom, however. Wilkerson (2018) shows that even when the instructor aims to use the target language, English is frequently used to translate classroom dialogue. While the place of the native language in the classroom language is the subject of continuing debate–see, for example, Rell (2015)– ,mentioned that “the activities and teaching strategies outlined here are intended to encourage student reflection on the translation method and on the changes between languages and not to replace communicative learning and teaching in the target language”. While translation is inattentive from modern teaching methods, the training and profession of translation are alive. With globalization has come a bad need to translate texts ranging from employee handbooks to television programs. Also, advances in natural language processing and the increasing of the Internet have presented into the world of translation a new tool: Web-based machine translation (WBMT). The automatic online translators, including Google Translate, and FreeTranslation.com, were originally designed to give customers a basic translation of Web pages or short texts written in another language; and most center on the translation of English writings into other languages. Recently, however, WBMT has found a new user in the foreign language student. Williams (2016) The Role of Translation in Language Teaching and Learning Laviosa (2014) declares the reintroduction of translation as an educational tool in the FL classrooms in academic settings. She believes that the re-emergence of translation in the FL classrooms is easily justified in light of the current changes in FL teaching and learning methods and Applied Linguistics. According to her, cultural variety in today’s globalized world and multicultural educational schemes has changed the relationship between culture— as a unified individual personality— and language learning. The use of L1 in FL learning environments is becoming more of a traditional method than two or three decades ago. Web-based Machine Translation (WBMT) in the English Language Classes: Problems and Solutions Language specialists are conscious of the deficiencies of all types of machine translation (MT), as expressed briefly in Barreiro and Ranchhod (2015): “the most clear failure of MT is that it is unable to render publication-ready text” (p. 3). Williams (2016) quotes various examples of incorrect English-French translations produced by WBMT, all associated with problems of