The process of metacognitive monitoring refers to one’s ability to incorporate rapid in-the-moment self-assessments of their cognitive performance. An area of interest within this literature concerns metacognitive accuracy (MA), or the extent to which an individual can discern when their own judgments are incorrect/correct. Much of the work in this area has either focused on school-aged samples or clinical samples, with findings of impairment in metacognitive processes associated with traumatic brain injury, Schizophrenia, cerebrovascular accidents, and Alzheimer’s disease. Notably, decreased working memory and executive functioning are frequently reported in samples with low MA, suggesting a possible reliance on basic cognitive resources in the facilitation of metacognitive processes. Thus, the goal of this investigation was to elucidate potential relationships between individual domains of cognition and higher-order MA. We hypothesized that performance on measures of working memory and executive function would be positively associated with measures of MA.

Data from 87 undergraduate students who volunteered in research for class credit were used. All participants completed a computerized metamemory task where six lists of 12 words each paired with varying point values were first presented to the participants. After each list, participants were instructed to score as many points as possible by recalling words they could remember. After a brief delay, participants completed a recognition task using the words presented earlier and provided a retrospective confidence judgement (RCJ) following each item. A metric for MA, meta d', was calculated using signal-detection theory analysis from the reported RCJs and recognition task performance. Participants also completed neuropsychological tests of attention (Trails A), working memory (WM; Backward Digits), executive function (EF; Trails B), mental flexibility (MF; Trails B/A Ratio), and processing speed (Symbol Digit Modalities). A sequential multiple regression was performed with meta d’ serving as the criterion, with education, age, and performance on neuropsychological measures entered as predictors.

The model indicated that a moderate percentage of the variability (R2 = .201) in metacognitive accuracy could be attributed to the combination of predictors in the model (F (7,79) = 2.843, p = .011). Examination of the regression coefficients indicated that only measures of attention (ß = .638, p = .01), MF (ß = .473, p = .041), and WM ß = .244, p = .024) were significantly related to MA after controlling for all other variables in the model.

The model suggests that working memory, attention, and mental flexibility increased in a linear fashion as MA increased. Our hypotheses were partially supported, while working memory predicted MA, its contribution to the overall model was the smallest among the significant predictors. While executive function was not a significant contributor to the model, MF (a component of EF) was. The largest contributor to the model was attention, which supports prior findings in the literature. This outcome would suggest that while separate from EF, metacognitive processes in neurotypical students may rely on other, more basic cognitive processes. These results may prove beneficial in guiding the development of rehabilitative interventions for MA in clinical samples.