Enhancing contextualized learning via AR

Ming-Puu CHEN, Li-Chun WANG, Shu-Yuan LIN, Di ZOU, Haoran XIE, Chin-Chung TSAI

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

An AR-enhanced contextualized learning was developed to facilitate EFL learning for junior high school students. A preliminary study was conducted to examine the effects of levels of prior knowledge (low vs. high) on participants' learning effectiveness and attitude toward the implemented AR-enhanced theme-based contextualized learning. The analysis suggested that prior knowledge affected participants' learning from the experimental AR-enhanced learning. With the advantage in prior knowledge, the high prior knowledge learners outperformed the low prior knowledge learners both in comprehension and application performance and possessed higher degrees of confidence, preferences, deep learning and learning strategy but with lower degrees of anxiety. It was suggested that suitable learning supports need to be considered to adapt to EFL beginners' levels of prior knowledge in order to facilitate their learning. Copyright © 2019 IEEE.
Original languageEnglish
Title of host publicationProceedings of 2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI 2019)
Place of PublicationDanvers, MA
PublisherIEEE
Pages286-289
ISBN (Print)9781728126272
DOIs
Publication statusPublished - 2020

Citation

Chen, M.-P., Wang, L.-C., Lin, S.-Y., Zou, D., Xie, H., & Tsai, C.-C. (2020). Enhancing contextualized learning via AR. In 2019 Proceedings of 2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI 2019) (pp. 286-289). Danvers, MA: IEEE.

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