Development of English Learning System by Using NFC Tag

Aizawa, Shogo; Yoshimura, Motohide

doi:10.2991/jrnal.k.210713.015

Cited by 2 publications

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“… Aizawa and Yoshimura (2021) created an English learning system using the Near Field Communication (NFC) tag. The research analysis uses the Raspberry Pi and NFC readers to analyze the learning efficiency.…”

Section: Related Workmentioning

confidence: 99%

Design of network English autonomous learning education system based on human-computer interaction

Wang

Smith

2022

Front. Psychol.

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The continuous development of Human-Computer Interaction (HCI) and information technologies impact the digital learning environment. The network and multimedia technologies change the Autonomous Learning System (ALS) structure. The learning process uses several techniques; however, the interactive function requires continuous improvement to enhance autonomous learning. Therefore, Optimized Deep Learning Network (ODNN) is introduced to build the Autonomous English Learning System (AELS) in this work. The ODNN system uses the learning and activation functions that derive the student’s learning capabilities and gives the proper training to the student. The HCI-based created autonomous learning process provides the guidelines to the student for making independent learning. The ALS improves the student’s learning ability and skills compared to classroom-based learning. The discussed ODNN-based AELS system effectiveness is evaluated using the Japanese-English Bilingual Corpus with a set of assessment questionaries. Then the HCI-based autonomous English learning is a quantitative analysis with the classroom-based learning. The discussed system is implemented using the Python tool, in which the AELS system ensures 98.51% learning efficiency compared to classroom learning.

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Section: Related Workmentioning

confidence: 99%