Big data suggest strong constraints of linguistic similarity on adult language learning

What is it? Using corpora to teach languages is nothing new and, while the term corpus linguistics hails from the 1940s, most language learning before the 20th century adopted a corpus approach – using a series of texts in the language under study as a type of corpus on which to base acquisition. With the advent of widespread computing in the latter half of the 20th century, corpora began to be digitised, rendering interrogation of large amounts of data a much simpler and more appealing prospect. Today, languages in all forms (written, spoken, performed, formal, informal, etc.) are captured all the time through online and digital platforms, apps, etc. meaning that the wealth of language data literally at our fingertips is enormous. This has triggered the development of appropriate tools to explore these vast data sets.

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The Application of Big Data to Improve Pronunciation and Intonation Evaluation in Foreign Language Learning

Advances in Intelligent Systems and Computing - Advances in Harmony Search, Soft Computing and Applications ◽

10.1007/978-3-030-31967-0_18 ◽

2019 ◽

pp. 160-168

Author(s):

Jin-Wei Dong ◽

Yan-Jun Liao ◽

Xiao-Dan Li ◽

Wei-bo Huang

Keyword(s):

Big Data ◽

Foreign Language ◽

Language Learning ◽

Foreign Language Learning

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Learning Analytics: The next frontier for computer assisted language learning in big data age

SHS Web of Conferences ◽

10.1051/shsconf/20151702013 ◽

2015 ◽

Vol 17 ◽

pp. 02013 ◽

Cited By ~ 2

Author(s):

Qinglan Yu

Keyword(s):

Big Data ◽

Language Learning ◽

Learning Analytics ◽

Computer Assisted ◽

Computer Assisted Language Learning

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Exploration of the Compilation of English Learning Materials for Chinese College Students Based on Big Data under the Guidance of Complex Dynamic Theory

International Journal of Linguistics Literature & Translation ◽

10.32996/ijllt.2021.4.3.3 ◽

2021 ◽

Vol 4 (3) ◽

pp. 22-32

Author(s):

Mao Feng ◽

Li Quan ◽

Wu Biyu

Keyword(s):

Big Data ◽

Language Learning ◽

Teaching And Learning ◽

Knowledge Map ◽

English Learning ◽

Complex Dynamic ◽

Learning Materials ◽

Chinese College Students ◽

College English ◽

English Teaching

With the help of big data and Citespace software, this research makes a statistical analysis of the journals and dissertations on College English teaching and learning materials collected by CNKI from 2011 to 2020. This paper, based on the knowledge map drawn by the visualized analysis of literatures volume, authors, research institutions and keywords clustering, analyzes the current research status and hotspots in the compilation of China’s College English textbooks. It is found that there are six problems in the compilation. Because of the complexity of teaching and learning materials and the dynamic progress of language learning, the nature of English teaching and learning materials is bound to turn from a learning tool to learning resources. Thus, this research, from the perspective of Complex Dynamic System Theory, attempts to develop big data-based College English learning materials with digital, individual and multi-dimensional characteristics by three paths: the establishment of big data-based English learning behaviors index system, the development of big data-based College English learning materials and the application of big data-based College English learning materials. This paper will explore a new way of developing China’s College English learning materials, improve and optimize the compilation and development of College English learning materials in China.

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With great data comes great (theoretical) opportunity

10.31234/osf.io/42rza ◽

2018 ◽

Author(s):

Michael C. Frank

Keyword(s):

Big Data ◽

Language Learning ◽

Critical Period ◽

Cognitive Models ◽

The Relationship

Is there a “critical period” for language? Using a viral online grammar test, Hartshorne, Tenenbaum, and Pinker (2018) collected a new massive dataset on the relationship between age and language learning. Their data highlight both the importance – and the challenges – of creating quantitative theories linking “big data” to cognitive models.

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The Application of Big Data Analytics in Online Foreign Language Learning among College Students : Empirical Research on Monitoring the Learning Outcomes and Predicting Final Grades

2020 2nd International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI) ◽

10.1109/mlbdbi51377.2020.00056 ◽

2020 ◽

Author(s):

Shao Chunzi ◽

Wang Xuanren ◽

Liu Ling

Keyword(s):

College Students ◽

Big Data ◽

Foreign Language ◽

Language Learning ◽

Learning Outcomes ◽

Empirical Research ◽

Data Analytics ◽

Big Data Analytics ◽

Foreign Language Learning ◽

Final Grades

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On Computer and Foreign Language Teaching and Learning in Big Data Era

International Journal of Emerging Technologies in Learning (iJET) ◽

10.3991/ijet.v13i05.7717 ◽

2018 ◽

Vol 13 (05) ◽

pp. 236 ◽

Cited By ~ 1

Author(s):

Ji-Hua Fan

Keyword(s):

Big Data ◽

Foreign Language ◽

Language Learning ◽

Teaching And Learning ◽

Language Teaching ◽

Foreign Language Learning ◽

Foreign Language Teaching ◽

Language Resources ◽

Learning And Teaching ◽

Authentic Language

The purpose of this paper is to explore the application of computer to foreign language learning in Big Data era. Combining the properties of language learning and teaching theories, we analyze the potential uses of computer in foreign language learning. We find that the main potential of computer-based foreign language learning lies in making authentic language resources accessible to learners, providing Big Data analysis for foreign language teaching and triggering the new online learning and teaching models. As for foreign language learning in Big Data era, we propose that the application of computer should be based on the learners’ need and teachers’ instruction.

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