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. 2025 Oct;32(5):2090-2103.
doi: 10.3758/s13423-025-02646-0. Epub 2025 Mar 17.

High variability orthographic training: Learning words in a logographic script through training with multiple typefaces

Affiliations

High variability orthographic training: Learning words in a logographic script through training with multiple typefaces

Eric Pelzl. Psychon Bull Rev. 2025 Oct.

Abstract

We tested whether naturally occurring visual variability-specifically, typefaces-would help people generalize word learning to typefaces they had never seen before. In Chinese, thousands of unique written characters must be learned item by item, and differentiated from similar-looking characters. Participants (n = 190) with no previous Chinese experience learned 24 Chinese characters in one of two training groups: the Single-Typeface group trained using only one of three Chinese typefaces; the Variable-Typeface group trained using all three. Everyone completed two training and testing phases. During Definition Training, they saw each character six times and learned to associate it with an English definition (-water). After training, participants were tested on their accuracy in providing definitions for the characters. During Form Training, participants chose the characters they had previously learned from a display that included a trained character and a visually similar distractor ( vs ). After training, they were tested on their speed/accuracy in choosing the learned characters. At testing in both phases, half of the words were presented in a familiar typeface; half in a novel typeface. Results showed significant interactions between training and testing conditions in both phases, with a significant effect of training in the Form Testing phase: Single-Typeface training resulted in faster responses for familiar typefaces, but much slower responses for novel typefaces; in comparison, Variable-Typeface training resulted in better generalization to novel typefaces. These results suggest that typeface variability can influence how effectively people generalize knowledge during the initial stages of learning a logographic script.

Keywords: Desirable difficulty; High variability training; Orthography; Vocabulary learning.

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Conflict of interest statement

Declarations. Ethics approval: The ethical components of this research were approved by The Pennsylvania State University Office for Research Protections (Protocol: STUDY00018208, “Online Investigation of Written Language Processing”). Consent to participate: All participants provided informed consent prior to participation. Consent for publication: All participants provided informed consent for their data to be published. Open practices statement: All stimuli used in the experiments are included in the paper and its appendices. Data and associated R code for the statistical analyses, as well as supplementary materials are available at: https://osf.io/5b7yn/ Competing interests: None to declare.

Figures

Fig. 1
Fig. 1
English definitions along with the 24 target Chinese characters displayed in each of the three training and two testing typefaces
Fig. 2
Fig. 2
English definitions along with the 24 target Chinese characters and their lures used in Form Training and Testing
Fig. 3
Fig. 3
Progression of training and testing phases. The use of typefaces for Single-Typeface and Variable-Typeface groups differed during training phases, but was the same for both groups during testing phases
Fig. 4
Fig. 4
Trial structure and parameters for Definition Training. The structure of Definition Testing was the same except that the character’s definition was not presented (no feedback)
Fig. 5
Fig. 5
Trial structure and parameters for Form Training. The structure of Form Testing was the same, except that there was no feedback
Fig. 6
Fig. 6
Raw accuracy of definitions across blocks of Definition Training and the Test phase. Error bars depict standard error. (For more detailed figures showing individual participant variability, see the Supplementary Materials)
Fig. 7
Fig. 7
Accuracy by testing typeface for Definition Testing. Single-Typeface group results are pictured on the left, Variable-Typeface on the right. Large black dots indicate group means; smaller dots indicate individual participant means. Lines connect scores for participants/groups in the two testing conditions (Familiar vs Novel Typeface). Colored lines indicate increases in score; dashed lines indicate decreases in score. The distribution of scores is shown in the shaded area for each testing condition, along with boxplots that capture the median score (thick center line) and interquartile range of scores
Fig. 8
Fig. 8
Raw accuracy across blocks of Form Training and Testing. Error bars depict standard error. (For more detailed figures showing individual participant variability, see the Supplementary Materials)
Fig. 9
Fig. 9
Raw RT across blocks of Form Training and Testing. Error bars depict standard error. (For more detailed figures showing individual participant variability, see the Supplementary Materials)
Fig. 10
Fig. 10
RTs by testing typeface for Form Testing. Single-Typeface group results are pictured on the left; Variable-Typeface on the right. Large black dots indicate group means; smaller dots indicate individual participant means. Lines connect scores for participants/groups in the two testing conditions (Familiar vs Novel Typeface). Colored lines indicate speed-up in RTs; dashed lines indicate slowdown in RTs. The distribution of scores is shown in the shaded area for each testing condition, along with boxplots that capture the median score (thick center line) and interquartile range of scores

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