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Supervised practice teaching is an inseparable part of the higher education of future teachers and is perceived as the bridge between theoretical and practical preparation. It is also a tool for the development of professional competences of future teachers, therefore it is inevitable to pay attention to it in terms of theory, research and practice. This article introduces the position of self-reflection in the process of evaluating the implementation of supervised practice teaching done by students themselves. Through the analysis of self-reflecting evaluation of the implemented practice done by students, it presents various possibilities how to improve the supervised practice teaching in higher education of future teachers itself.
This paper discusses the use of student-produced videos to improve speaking skills in EFL classrooms, with emphasis on their use in preparatory classes at Kocaeli University, School of Foreign languages. The use of student-produced videos as a learning and teaching tool may greatly enhance the quality of students’ oral skills in many ways. They have the chance of reviewing their own performances, evaluating their speaking skills and becoming more self-critical of their abilities. The perspectives of using the student-created videos for the development of oral skills in language classrooms are presented.
A case of mobile apps in the Lithuanian and English language pair
Gilvilė Stankevičiūtė, Ramunė Kasperavičienė and Jolita Horbačauskienė
Machine translation (MT) is still a huge challenge for both IT developers and users. From the beginning of machine translation, problems at the syntactic and semantic levels have been faced. Today despite progress in the development of MT, its systems still fail to recognise which synonym, collocation or word meaning should be used. Although mobile apps are very popular among users, errors in their translation output create misunderstandings. The paper deals with the analysis of machine translation of general everyday language in Lithuanian to English and English to Lithuanian language pairs. The results of the analysis show that more than two thirds of all the sentences were translated incorrectly, which means that there is a relatively small possibility that a mobile app will translate sentences correctly. The results are disappointing, because even after almost 70 years of MT research and improvement, researchers still cannot offer a system that would be able to translate with at least 50% correctness.