Date of Award

2020

Degree Type

Dissertation

Degree Name

Doctor of Philosophy in Education

Department

Education

First Advisor

Wayne He

Abstract

Research has shown that memorizing a character by its strokes is perhaps the most difficult aspect of learning the Chinese language, particularly for beginning students. Since learners can handwrite Chinese characters without knowing the meaning or the pronunciation, emphasizing drawing the characters from the beginning is not an efficient way of learning Chinese characters. Meanwhile, character recognition, grammar pattern drills, and memorization are not enough for college Chinese language learning. Currently, there is a gap in the literature about Chinese language acquisition research from classroom contexts to naturalistic settings, from an acquisition metaphor to a participation metaphor, and from Chinese language to Chinese language use.

The goal of this study was to investigate the learners’ perceptions about Computer Assisted Chinese Character Learning (CACCL) in a proficiency oriented professionally focused program in the U.S. and to examine if the CACCL works for Chinese language learners in the program. When the data is followed by in-depth exploratory surveys, learning sessions with both CACCL and non-CACCL, read-aloud assessments, typing assessments, and handwriting assessments with CACCL and non- CACCL, this study focuses on Chinese learners whose proficiency is both at the novice and intermediate levels.

Findings from this study indicated that one possible approach may involve the use of bridging the pronunciation and the character so that digital tools can offer support and improvement of existing Chinese teaching instructions. Quality Chinese language education may fundamentally depend on language learning interaction but also computer assisted language learning curriculum design. My data also suggest that there is a need to understand how students can best apply self-regulated learning strategies to achieve academic success in a virtual environment so that they can be more effective with the provided online resources as virtual Chinese language learning continues to increase.

Available for download on Thursday, December 15, 2022

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