How font size affects judgments of learning: Simultaneous mediating effect of item-specific beliefs about fluency and moderating effect of beliefs about font size and memory

Abstract

Numerous studies have provided experience-based or theory-based frameworks for the basis of judgment of learning (JOL). However, few studies have directly measured processing experience and beliefs related to the same cue in one experiment and examined their joint contribution to JOLs. The present study focused on font-size effects and aimed to examine the simultaneous contribution of processing fluency and beliefs to the effect of font size on JOLs. We directly measured processing fluency via self-paced study time. We also directly measured participants’ beliefs via two approaches: pre-study global differentiated predictions (GPREDs) as an indicator of preexisting beliefs about font size and memory and ease of learning judgments (EORs) as online generated item-specific beliefs about fluency. In Experiment 1, EORs partially mediated the font-size effect, whereas self-paced study time did not. In Experiments 2a and 2b, EORs mediated the font-size effect; at the same time, beliefs about font size and memory moderated the font-size effect. In summary, the present study demonstrates a major role of beliefs underlying the font-size effect.

Using Multilevel Mediation Model to Measure the Contribution of Beliefs to Judgments of Learning

“…The Belief ij is the belief-based prediction of memory performance for each trial. When beliefs are measured with global predictions, each participant only gives one belief-based prediction of memory performance for each level of the cue (Hu et al, 2015;Frank and Kuhlmann, 2017;Su et al, 2018;Schaper et al, 2019). Thus, for each participant, all of the items within the same level of the cue have the same value of belief-based prediction.…”

“…Here we fix the slope a j as the same value for all participants [i.e., a in Equation 3] and does not add the random slope. This is because, in many previous studies (and in the hypothetical dataset), the predictor variable Cue only contains two levels (e.g., large and small font size) and the mediator variable Belief is the same within each level of the cue for a participant (Hu et al, 2015;Frank and Kuhlmann, 2017;Su et al, 2018;Schaper et al, 2019). In this case, the random effect for slope a j is perfectly confounded with the residual error, which can make the model fail to converge (Singmann and Kellen, 2020) (see section "Further Explanation About the Random Slope of Path a When We Regress Beliefs on the Cue in Multilevel Mediation Model" in the Supplementary Material for further explanation on this topic).…”

“…The results revealed that participants had a priori beliefs that large words are easier to remember than small ones, suggesting that such beliefs may contribute to the font-size effect on JOLs. Following studies indicate that beliefs play an important role in the effect of different cues on JOLs, including font size, volume, semantic relatedness, word frequency, concreteness, and so on (Mueller et al, 2013(Mueller et al, , 2016Hu et al, 2015;Jia et al, 2016;Frank and Kuhlmann, 2017;Li et al, 2017;Witherby and Tauber, 2017;Su et al, 2018).…”

“…To further examine the effect of beliefs on JOLs within the same participants, some previous studies have asked one group of participants to first make global belief-based predictions about their memory and then to provide JOLs to study items (Ariel et al, 2014;Hu et al, 2015;Frank and Kuhlmann, 2017;Su et al, 2018;Schaper et al, 2019). In these studies, participants predict how many items they will recall in a future test before they start learning the items.…”

“…To quantify the contribution of processing fluency to JOLs at the item level, previous studies often employed a multilevel linear model to delineate the relationship between fluency and JOLs (Undorf and Erdfelder, 2015;Undorf et al, 2017;Yang et al, 2018). Thus, it should be better to also explore the role of beliefs in the JOL process at the item level if we want to compare the contribution of beliefs and processing fluency to JOLs (Frank and Kuhlmann, 2017;Su et al, 2018;Schaper et al, 2019). Researchers should use appropriate statistical methods to examine to what extent cues affect item-by-item JOLs through global beliefs about memory performance, and quantitatively compare the effect of beliefs and fluency on JOLs at the item level.…”