Innovative Dynamic Matrix-Type Learning Environment Based on the Example of the St. Petersburg School of Conference Interpreting and Translation, Herzen University, Russia

I. Alekseeva, A. Antonova
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Abstract

The paper examines an innovative cluster-type matrix model for training interpreters and translators, based on recent developments in text and pragmatics theory, as well as on the scenario approach in education. The aim is to create a single, multifaceted space for open interpreter and translator training with an anthropological focus, drawing on the achievements in Russian teaching culture and best world practices, including a system of feedback from employers, to enable a flexible response to the needs of the society. To achieve the aim, an innovative interactive system of intensive interpreter and translator training has been developed based on a cluster principle and continuous education quality monitoring. At the heart of the system are a scenario strategy and a text typology approach. What is unique about the St Petersburg School of Conference Interpreting and Translation (SCIT)’s project is the fact that it is not just an educational programme or a system or an algorithm, but a dynamic matrix-type learning environment.It is a flexible model for professional retraining that presupposes a range of basic skills and can fill any gaps in the general translators’ competence and current performance by applying the professional environment matrix. The cluster approach provides a combination of in-person, distant and independent learning components, as well as increased transparency of the educational and professional spaces, opening up future employment prospects.The ‘diffuse matrix’ version of the innovative matrix principle in education underlies the diversity of methods employed by SCIT: methodological pluralism, dominant in the process of training, implies a combination of diverse techniques developed by different authors for the matrix, making it most flexible and the whole approach – customer tailored. It should be pointed out that the external diversity is strictly regulated and targeted by the project’s creators by means of a monitoring mechanism.The future of the model is seen in its use in Russia and other countries to train highly professional interpreters and translators in other spheres (for example, audiovisual translation). It could also be used at the final stage of higher vocational training; as a standard mechanism for improving professional skills and retraining; as well as a social harmonising element (creating new links among academic, educational, and professional activities).
创新动态矩阵式学习环境——以俄罗斯赫尔岑大学圣彼得堡会议传译学院为例
本文基于语篇和语用学理论的最新发展,以及教育中的情景方法,探讨了一种用于口译和笔译员培训的创新集群型矩阵模型。其目的是为开放的口译和笔译培训创造一个单一的、多方面的空间,以人类学为重点,借鉴俄语教学文化的成就和世界最佳实践,包括雇主反馈系统,以灵活应对社会需求。为了实现这一目标,基于集群原则和持续教育质量监测,开发了一种创新的互动式口译和翻译强化培训系统。系统的核心是场景策略和文本类型学方法。圣彼得堡会议口译与翻译学院(SCIT)项目的独特之处在于,它不仅仅是一个教育项目、一个系统或一个算法,而是一个动态的矩阵式学习环境。这是一种灵活的专业再培训模式,它以一系列基本技能为前提,可以通过应用专业环境矩阵来填补一般翻译人员在能力和当前表现方面的任何空白。集群方法提供了面对面,远程和独立学习组件的组合,以及增加教育和专业空间的透明度,开辟了未来的就业前景。创新矩阵原则在教育中的“扩散矩阵”版本是工商及科技局采用多样化方法的基础:方法多元化,在培训过程中占主导地位,意味着由不同作者为矩阵开发的各种技术的组合,使其最灵活和整体方法-客户量身定制。需要指出的是,外部多样性是由项目的创造者通过一种监测机制来严格规范和针对性的。该模式的未来是在俄罗斯和其他国家用于培训其他领域(例如视听翻译)的高度专业的口译和笔译员。也可用于高等职业培训的最后阶段;作为提高专业技能和再培训的标准机制;以及社会和谐元素(在学术、教育和专业活动之间建立新的联系)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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