Waves of intensity in language learning: Polyglot Alan Bigulov’s project “10 Languages in 1000 days”

Signo Pub Date : 2022-01-03 DOI:10.17058/signo.v47i88.17394
D. Nikulicheva
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引用次数: 3

Abstract

The study aims at identifying individual language learning strategies that allow a polyglot to effectively communicate with unfamiliar native speakers on spontaneous topics within a short learning period of 1000 days. The study was conducted from September 2018 up to June 2021 observing Alan Bigulov’s performance (the polyglot from Vladikavkaz, Russia) in the process of learning ten new, typologically different languages. The study theoretical framework was the psycholinguistic expert performance modeling – in this case, the psycholinguistic monitoring of a person, especially effective in the time management of language learning. Methodologically, the study focused on close monitoring of daily video recordings of Alan Bigulov's communication in the target language, weekly correspondence between the researcher's questions and the subject's answers, and respective linguistic analysis of the subject’s evaluative predicates during the whole 1000-day Project. The research main results have elicited the following patterns: consistent focus on one language; three-level model of a spiral entry into a communicative situation; the effectiveness of the super-intensive start; deliberate wave-like variation of classes intensity; the importance of flexible language classes algorithms aimed at avoiding routine and reaching a new intensity level.
语言学习的高潮:Polyglot Alan Bigulov的项目“1000天内的10种语言”
该研究旨在确定个人语言学习策略,使精通多种语言的人能够在1000天的短学习期内与不熟悉的母语人士就自发的话题进行有效沟通。这项研究于2018年9月至2021年6月进行,观察了Alan Bigulov(来自俄罗斯弗拉迪卡夫卡兹的多语者)在学习十种新的、类型不同的语言过程中的表现。研究的理论框架是心理语言学专家表现模型——在这种情况下,是对一个人的心理语言学监测,在语言学习的时间管理方面尤其有效。在方法论上,该研究侧重于密切监测Alan Bigulov用目标语言交流的每日视频记录,研究人员的问题和受试者的答案之间的每周通信,以及在整个1000天的项目中对受试者评价谓词的各自语言分析。研究的主要结果引出了以下模式:对一种语言的一贯关注;螺旋式进入交际情境的三级模型;超密集启动的有效性;类强度的有意波动;灵活的语言类算法的重要性旨在避免例行公事并达到一个新的强度水平。
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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24 weeks
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