My research explores the intricate relationship between metacognitive monitoring and control - the processes that allow learners to evaluate their own knowledge and regulate their study behaviors. I am fascinated by how these processes interact and how they can be optimized to improve learning outcomes. Across my work, I aim to uncover the cognitive cues that guide these judgments and decisions, and to identify strategies that promote effective self-regulated learning.
A central theme in my research is understanding how learners form judgments about their own learning and memory. In one line of research focused on these monitoring processes, I conducted multiple projects examining the role of processing fluency — the ease with which information is processed — in shaping judgments of learning (JOLs). For example, one series of experiments investigated whether fluency operates in an experience-based manner, revealing that fluency can bias learners’ monitoring judgments even without conscious awareness (read the full publication here). In follow-up work, I showed that the driving force behind this effect often lies in disfluent items, which decrease learners’ perceptions of future memory performance relative to baseline (read the full publication here). I also found that the impact of fluency is remarkably persistent, with perceptual learning producing long-lasting changes in metamemory judgments that endure well beyond the initial learning episode (read the full publication here). Furthermore, my research demonstrates that subtle forms of fluency can be overshadowed by more salient, performance-based cues, suggesting that learners prioritize certain types of information when forming metacognitive judgments. Together, these findings highlight the complexity of monitoring processes and the interplay between multiple cues in shaping learners’ self-assessments.
Beyond fluency, my research has also examined a range of non-fluency cues that influence metacognitive monitoring. One line of work investigated list composition effects, exploring how variations in item difficulty within a list shape judgments of learning. These studies revealed that learners often rely on relative differences in difficulty between items when forming monitoring judgments, even when these cues are not predictive of actual memory performance (read the full publication here). In an extension of this work, I have also examined the role of effort when monitoring our learning. Placing constraints on the well-established memorizing effort heuristic, my work showed that in the presence of relatively easier items the commonly observed negative relation between study time and JOLs for difficult items was absent. However, when learners were tasked with making predictions regarding others’ memory performance, they did not adapt their use of the memorizing effort heuristic in the same context-dependent manner as when they predicted their own memory performance (read the full publication here).
In addition to these projects, I have also explored whether other aspects of learning interact with or are influenced by judgments of learning (JOLs). This includes work examining how factors such as error generation shape metacognitive monitoring, and how such monitoring influences relational encoding. Further details on these projects can be found in the Publications section.