Using Meaningful Interpretation and Chunking to Enhance Memory: The Case of Chinese Character Learning Xiaoqiu Xu Pearson Knowledge Technologies Amado M. Padilla Stanford University Abstract: Learning and retaining Chinese characters are often considered to be the most challenging elements in learning Chinese as a foreign language. Applying the theory of meaningful interpretation, the chunking mnemonic technique, and the linguistic features of Chinese characters, this study examines whether the method of meaningful interpretation and chunking (MIC) can promote learners’ immediate learning and retention of Chinese characters. Mandarin Chinese learners at two high schools were randomized into a treatment group and a control group. Students in the treatment group learned Chinese characters with the MIC method, whereas their peers in the control group learned characters by the traditional method of rote repetition according to the stroke order. Four balanced character sets were introduced each day for four continuous days with three different interventions: teacher‐instructed method on Day 1, teacher‐cued method on Day 2, and students’ independent work on Day 3 and Day 4. Students’ learning outcomes of the characters were measured with (1) immediate quizzes given each day after instruction, (2) a retention test (after one week) that integrated all the immediate quizzes, and (3) an application test administered two months after the experiment. The findings suggest that MIC enhances learners’ immediate learning and retention of Chinese characters. In addition, the teacher‐cued method and familiar independent work were more effective for learning and retaining Chinese characters than the teacher‐ instructed method and unfamiliar independent work. Furthermore, the treatment effect also varied across the measurement components (meaning vs. perception), levels of instruction, and heritage versus non‐heritage groups. Key words: Chinese characters, chunking, meaningful interpretation, radical knowledge, teaching methods Xiaoqiu Xu (PhD, Stanford University) is a test development specialist at Pearson Knowledge Technologies, Sunnyvale, CA. Amado M. Padilla (PhD, University of New Mexico) is Professor of Psychological Studies in Education, Stanford University, Stanford, CA. Foreign Language Annals, Vol. 46, Iss. 3, pp. 402–422. © 2013 by American Council on the Teaching of Foreign Languages. DOI: 10.1111/flan.12039 402 FALL 2013