A bilingual/L2 hybrid intervention model: combining human and machine intelligences

Chen, Carol

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https://hdl.handle.net/2142/113897 Copy

Description

Title

A bilingual/L2 hybrid intervention model: combining human and machine intelligences

Author(s)

Chen, Carol

Issue Date

2021-12-03

Director of Research (if dissertation) or Advisor (if thesis)

Cope, William

Doctoral Committee Chair(s)

Cope, William

Committee Member(s)

• Kalantzis, Mary
• Pak, Yoon Kyung
• Montebello, Matthew
• You, Yu-ling

Department of Study

Educ Policy, Orgzn & Leadrshp

Discipline

Educ Policy, Orgzn & Leadrshp

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ed.D.

Degree Level

Dissertation

Date of Ingest

2022-04-29T21:34:46Z

Keyword(s)

Education

Language

eng

Abstract

Most Taiwanese English language learners have been exposed to traditional approaches to acquiring English as a second or foreign language. Studies demonstrate current/traditional teaching practices are not the most effective for struggling English language learners, and the rate of improvement has been limited. Therefore, this study explores current hybrid environments that integrate a combination of advanced computer-assisted technologies that are operated with artificial intelligence technologies to deliver more effective English language teaching, as well as using translanguaging, a current bilingual teaching method, to support the language acquisition process. To push English language teaching and learning to a more effective and efficient level, artificial intelligence-powered tools providing interventional support have been identified as the integral technological innovations to be leveraged with other tools (reading platforms, formative platforms, on-screen share tools, etc.). Specifically, the use of machine translation tools operating with artificial intelligence technologies have been identified in the literature as a vital computer-assisted tool in supporting learners with their English or second language development via translingualism. However, due to the limitations of artificial intelligence in which causality is lacking, machine translation tools operated on artificial intelligence continue to make errors in translation. Therefore, human intervention is needed in facilitating the teaching and learning process by leveraging other intelligent computer-assisted tools, namely writing assistant software and voice recognition/evaluation software, to make the intervention model more effective in the overall language learning process. Hence, combining machine and human intelligences in deploying machine translation tools, as well as other artificial intelligence-operated tools, serves as an integral approach to addressing learning progression limitations and moving the teaching and learning process into a more innovative hybrid zone based on extending the transtheoretical model for hybrid learning in assisting struggling English language learners. This research will explore how humans can interact with machines by training image-bilingual text translation models via Google's Teachable Machine, as well as utilizing other artificial intelligence-powered tools, namely a writing assistant and a voice recognition or evaluation software, to fill the gaps in current literature regarding integrating intelligent computer-assisted tools for English language learning amongst struggling nonnative English speakers in a hybrid learning environment.

Graduation Semester

2021-12

Type of Resource

Thesis

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http://hdl.handle.net/2142/113897

Copyright and License Information

Copyright 2021 Carol Chen

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