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The contribution of metamemory beliefs to the font size effect on judgments of learning: Is word frequency a moderating factor?

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Listed:
  • Tian Fan
  • Jun Zheng
  • Xiao Hu
  • Ningxin Su
  • Yue Yin
  • Chunliang Yang
  • Liang Luo

Abstract

Previous studies found that metamemory beliefs dominate the font size effect on judgments of learning (JOLs). However, few studies have investigated whether beliefs about font size contribute to the font size effect in circumstances of multiple cues. The current study aims to fill this gap. Experiment 1 adopted a 2 (font size: 70 pt vs. 9 pt) * 2 (word frequency (WF): high vs. low) within-subjects design. The results showed that beliefs about font size did not mediate the font size effect on JOLs when multiple cues (font size and WF) were simultaneously provided. Experiment 2 further explored whether WF moderates the contribution of beliefs about font size to the font size effect, in which a 2 (font size: 70 pt vs. 9 pt, as a within-subjects factor) * 2 (WF: high vs. low, as a between-subjects factor) mixed design was used. The results showed that the contribution of beliefs about font size to the font size effect was present in a pure list of low-frequency words, but absent in a pure list of high-frequency words. Lastly, a meta-analysis showed evidence supporting the proposal that the contribution of beliefs about font size to the font size effect on JOLs is moderated by WF. Even though numerous studies suggested beliefs about font size play a dominant role in the font size effect on JOLs, the current study provides new evidence suggesting that such contribution is conditional. Theoretical implications are discussed.

Suggested Citation

  • Tian Fan & Jun Zheng & Xiao Hu & Ningxin Su & Yue Yin & Chunliang Yang & Liang Luo, 2021. "The contribution of metamemory beliefs to the font size effect on judgments of learning: Is word frequency a moderating factor?," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-22, September.
    • Handle: RePEc:plo:pone00:0257547
    DOI: 10.1371/journal.pone.0257547
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    References listed on IDEAS

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    1. Bates, Douglas & Mächler, Martin & Bolker, Ben & Walker, Steve, 2015. "Fitting Linear Mixed-Effects Models Using lme4," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i01).
    2. Xiao Hu & Tongtong Li & Jun Zheng & Ningxin Su & Zhaomin Liu & Liang Luo, 2015. "How Much Do Metamemory Beliefs Contribute to the Font-Size Effect in Judgments of Learning?," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-11, November.
    3. Qing Cai & Marc Brysbaert, 2010. "SUBTLEX-CH: Chinese Word and Character Frequencies Based on Film Subtitles," PLOS ONE, Public Library of Science, vol. 5(6), pages 1-8, June.
    4. Tingley, Dustin & Yamamoto, Teppei & Hirose, Kentaro & Keele, Luke & Imai, Kosuke, 2014. "mediation: R Package for Causal Mediation Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 59(i05).
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