Based on the Big Data Program Language Learning Website Generation System

We transformed the existing learning program Language Shower, which is used in some Norwegian day-care centers in the Grorud district of Oslo municipality, into a digital solution using an app for smartphone or tablet with the option for further enhancement of presentation by a NAO robot. The solution was tested in several iterations and multiple day-care centers over several weeks. Measurements of the children’s progress across learning sessions indicate a positive impact of the program using a robot as compared to the program without robot. In-situ observations and interviews with day care center staff confirmed the solution’s many advantages, but also revealed some important areas for improvement. In particular, the speech recognition needs to be more flexible and robust, and special measures have to be in place to handle children speaking simultaneously.

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

Cognition ◽

10.1016/j.cognition.2019.104056 ◽

2020 ◽

Vol 194 ◽

pp. 104056 ◽

Cited By ~ 2

Author(s):

Job Schepens ◽

Roeland van Hout ◽

T. Florian Jaeger

Keyword(s):

Big Data ◽

Language Learning

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USING A LANGUAGE GENERATION SYSTEM FOR SECOND LANGUAGE LEARNING

Computer Assisted Language Learning ◽

10.1080/0958822960090208 ◽

1996 ◽

Vol 9 (2-3) ◽

pp. 181-189 ◽

Cited By ~ 1

Author(s):

Michael Levison ◽

Greg Lessard

Keyword(s):

Second Language ◽

Language Learning ◽

Second Language Learning ◽

Generation System ◽

Language Generation

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The Study of Learner Autonomy in Foreign Language Learning in Big Data Era

Proceedings of the 2018 International Conference on Big Data and Education - ICBDE '18 ◽

10.1145/3206157.3206184 ◽

2018 ◽

Author(s):

Cao Shaosen

Keyword(s):

Big Data ◽

Foreign Language ◽

Language Learning ◽

Foreign Language Learning ◽

Learner Autonomy

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Bigsecurity'16: 2016 IEEE conference on computer communications workshops (INFOCOM WKSHPS): BigSecurity 16: The fourth international workshop on security and privacy in big data - program

2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) ◽

10.1109/infcomw.2016.7562001 ◽

2016 ◽

Keyword(s):

Big Data ◽

International Workshop ◽

Security And Privacy ◽

Computer Communications ◽

Data Program

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Achieving academic control in two languages: Drawing on the psychology of language learning in considering the past, the present, and prospects for the future

Studies in Second Language Learning and Teaching ◽

10.14746/ssllt.2015.5.2.7 ◽

2015 ◽

Vol 5 (2) ◽

pp. 327-345

Author(s):

Andrew D. Cohen

Keyword(s):

Language Learning ◽

Language Learners ◽

Dual Language ◽

First Language ◽

Language Program ◽

Language Programs ◽

The Past ◽

Dual Language Program ◽

Program Language ◽

Academic Control

This paper first considers what it means to become truly proficient in a language other than the native one. It then looks briefly at the evolution of dual language programs. Next, it focuses on the issue of whether the first language (L1) or the second language (L2) serves as the language of mediation. Other dual language program issues are then discussed, such as how proficient learners actually become in academic and social language in the L2, their proficiency in grammar and pronunciation, and possible administrative constraints in the design and execution of such programs. Finally, attention is given to a guidebook written directly for dual language learners and for their teachers in which learners are encouraged to take a proactive role to ensure that they make the most of their dual program language learning and use experiences.

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Second Language Learning Convergence System Based on Big Data

Indian Journal of Science and Technology ◽

10.17485/ijst/2016/v9i26/97329 ◽

2016 ◽

Vol 9 (26) ◽

Author(s):

Jae-il Yi

Keyword(s):

Big Data ◽

Second Language ◽

Language Learning ◽

Second Language Learning ◽

Convergence System ◽

Learning Convergence

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Measuring political legitimacy with Twitter: Insights from India’s Aadhaar program

New Media & Society ◽

10.1177/14614448211033493 ◽

2021 ◽

pp. 146144482110334

Author(s):

Laura C Mahrenbach ◽

Jürgen Pfeffer

Keyword(s):

Big Data ◽

Political Legitimacy ◽

Cost Benefit ◽

Biometric Data ◽

Theoretical Approaches ◽

Twitter Data ◽

Social Measurement ◽

Normative Factors ◽

Data Program ◽

Emerging Powers

As emerging powers forge ahead with big data initiatives, questions arise regarding the implications of these programs for governance in the Global South more broadly. One understudied aspect deals with how actors attribute legitimacy to governments’ big data activities. We explore actors’ agency in one crucial case: the world’s largest demographic and biometric data program, India’s Aadhaar. Analyzing roughly 250,000 tweets collected in the first 10 years of Aadhaar’s operation, we find that both normative acceptance and cost–benefit calculations are crucial for legitimacy attribution. This finding challenges mainstream theoretical approaches, which prioritize normative factors and often fail to examine how normative and material factors interact during legitimacy attribution. In addition, our study demonstrates a new, mixed-methods approach to measuring legitimacy attribution using Twitter data, which overcomes traditional challenges. As such, we underline the viability of Twitter data as a tool for social measurement.

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