Judgment Performance Research Articles

Exploring the Relation Between Metacognition, Gender, and Personality in Colombian University Students

In the present study, the relationship between objective and subjective measures of metacognition, personality traits of the Big Five (extraversion, agreeableness, conscientiousness, neuroticism, and openness) and gender were examined. A convenience sample of 352 university students completed the Metacognitive Awareness Inventory, the Adjectives to Evaluate Personality instrument, and completed 3 domain-specific tests (vocabulary, probabilities, paper folding) along with confidence in performance judgments for each item on these tests. Through a combination of descriptive statistics, zero-order bivariate correlations, simultaneous multiple regression, and a multivariate analysis of covariance, findings indicate that objective and subjective measures of metacognition are weakly related and that subjective measures of metacognition were more strongly related to personality traits. Conscientiousness and openness were the only personality traits that positively predicted metacognition. Gender affected both subjective and objective measures of metacognition, even after controlling for university type (private, public) and perceptions of academic performance (high, low) such that males were more accurate and less biased in their monitoring than females only in mathematical reasoning and they reported higher awareness of their knowledge and regulation of cognition than their female counterparts. Findings support the need to better understand how personality traits and gender affect self-regulated learning skills like metacognition to improve educational practices.

Malaysian Internal Auditor’s Risk Judgment Performance: Examining the Impact of ISA 610 “Using the Work of the Internal Auditor”

Effective from December 2016, the Malaysian external auditor is required under the revision of the International Standard on Auditing (ISA) to give comments on Key Audit Matters (KAM) in the audit client’s financial statement which indirectly increases the relevancy of ISA 610 “Using the Work of Internal Auditor”. This study aimed to explore the impact of two main aspects under ISA 610 namely “external auditor engagement quality (EX_QUAL)” and “external auditor reliance (EX_RELY)” on internal auditor’s risk judgment performance. The survey of 274 internal auditors in the Malaysian public and private sector found that internal auditors who experienced high EX_QUAL outperform risk judgment as a result of awareness that the judgment made must be reflective of their own competency, independence, work performance and due care. Unfortunately, internal auditors who experienced high EX_RELY did not perform as expected since internal auditor’s anxieties on the bad consequences of full disclosure risk faced by the company. EX_QUAL could be one of monitoring mechanism to improve internal audit’s risk judgment. Furthermore, mitigating action, such as external auditor involvement in internal audit annual risk assessment plan could deter internal auditor bias and increase objectivity, and thus induce a positive impact of EX_RELY on internal auditor’s risk judgment performance. Keywords: risk judgment, performance, reliance, internal auditor, external auditor

<p>Effects of Reading Motivation and Meta-comprehension on the Reading Comprehension of Students with Intellectual Disabilities</p>

Introduction. Reading comprehension is an essential skill to achieve autonomy and independence within our literate society. Unfortunately, several studies show that students with intellectual disabilities tend to achieve low reading levels. In normotypical students, the influence of reading motivation and metacomprehension habilities on reading comprehension has been extensively studied. In this sense, it is interesting and innovative to explore the influence of these variables on the population of students with IDs. Method. The present research had two main objectives: 1) to describe the level of reading motivation and meta-comprehension skills present in students with intellectual disabilities (N=27); and 2) to predict the impact of these variables on their performance in reading. A standardized reading comprehension test (LECTUM), the Motivation for Reading Questionnaire (MRQ), and different instruments to assess aspects of Metacomprehension (metacomprehension inventory, inconsistency detection test and confidence in performance judgments) were applied. Results. The analysis of the data through descriptive statistics allowed characterizing the performance of the students in each of the variables considered. In turn, the stepwise linear regression analysis showed that, together, the total number of inconsistencies detected as a measure of metacomprehension monitoring and two dimensions of metacognitive knowledge (knowledge about cognition and regulation after problematic understanding), predict 67% of the variability in participants’ reading comprehension performance. Discussion and Conclusion. Implications for special educational practice and reading comprehension theory are discussed.

An exploration of "real time" assessments as a means to better understand preceptors' judgments of student performance.

Clinical supervisors are known to assess trainee performance idiosyncratically, causing concern about the validity of their ratings. The literature on this issue relies heavily on retrospective collection of decisions, resulting in the risk of inaccurate information regarding what actually drives raters' perceptions. Capturing in-the-moment information about supervisors' impressions could yield better insight into how to intervene. The purpose of this study, therefore, was to gather "real-time" judgments to explore what drives preceptors' judgments of student performance. We performed a prospective study in which physicians were asked to adjust a rating scale in real-time while watching two video-recordings of trainee clinical performances. Scores were captured in 1-s increments, examined for frequency, direction, and magnitude of adjustments, and compared to assessors' final entrustability judgment as measured by the modified Ottawa Clinic Assessment Tool. The standard deviation in raters' judgment was examined as a function of time to determine how long it takes impressions to begin to vary. 20 participants viewed 2 clinical vignettes. Considerable variability in ratings was observed with different behaviours triggering scale adjustments for different raters. That idiosyncrasy occurred very quickly, with the standard deviation in raters' judgments rapidly increasing within 30s of case onset. Particular moments appeared to generally be influential, but their degree of influence still varied. Correlations between the final assessment and (a) score assigned upon first adjustment of the scale, (b) upon last adjustment, and (c) the mean score, were r = 0.13, 0.32, and 0.57 for one video and r = 0.30, 0.50, and 0.52 for the other, indicating the degree to which overall impressions reflected accumulation of raters' idiosyncratic moment-by-moment observations. Our results demonstrated that variability in raters' impressions begins very early in a case presentation and is associated with different behaviours having different influence on different raters. More generally, this study outlines a novel methodology that offers a new path for gaining insight into factors influencing assessor judgments.

Chemometrics validation of adsorption process economy: Case study of acetaminophen removal onto quail eggshell adsorbents

The potential of quail eggshells for acetaminophen (PCM) removal in aqueous solution was studied. Calcination greatly increased the surface area of the raw quail eggshell (RQES). Hence, surface area as determined by the Brunauer-Emmet-Teller (BET) surface and porosity analyzer are 680.80 m2/g for RQES while calcinated quail eggshell (CQES) had 927.30 m2/g. The scanning electron microscopic (SEM) analysis revealed pores useful for uptake of PCM. Adsorption process for the uptake of PCM onto RQES and CQES was pH-dependent with optimum pH of 7 and 6 respectively. The Freundlich adsorption isotherms suggested a multilayer adsorption of PCM unto RQES and CQES. The Dubinin Raduskevich (D-R) model best described the adsorption processes. The energy of adsorption obtained from the model for the two adsorption systems were 23.57 and 8.4515 kJ.mol−1 suggesting that chemisorption occurred within the systems. The maximum monolayer adsorption capacities were 10.00 and 15.15 mg/g for uptake of PCM unto RQES and CQES respectively. Pseudo-second-order model best explained the kinetics of the adsorption processes, adsorption process was established to be feasible and feasibility increased with temperature. The process economy validation by Ordinary Least Square (OLS) cum ridge estimator followed by model performance judgment using the test mean squared error (TMSE) revealed 32% and 22.8% in PCM quantity adsorbed per unit changes in time and temperature respectively. Hence, a valid justification for economy friendliness of the prepared adsorbents in acetaminophen removal.

Evaluation of direction judgements based on turn signal guide lamp and behavioural responses

Traffic crashes frequently occur at intersections because drivers or pedestrians cannot properly anticipate the direction towards which other vehicles are turning. A turn signal guide lamp was developed to improve the observer’s direction judgement of turn signals, and experiments were conducted to test the effect of the guide lamp based on behavioural responses. Our experimental results demonstrated that the turning direction judgement response time was reduced when both the turn signal indicators and turn signal guide lamps were used together compared with the case when only the turn signal indicators were used. Supplementary eye-tracking data also demonstrated that the gaze point frequently stayed on the light patterns on the ground marked by the turn signal guide lamps. Additional glare evaluation using the de Boer scale showed no significant difference between the turn signal indicator with a guide lamp and the turn signal indicator alone on dry or wet road surfaces. Therefore, it is expected that the newly developed turn signal guide lamp will increase the observer’s performance of direction judgement on the turn signalling function without causing an additional glare when the observer knows the function of the guide lamp.

Rapidly diminishing sensitivity and discrete sensitivity: Explaining people's sensitivity to outcomes across decisions.

Classic theories of perception, cognition, judgment, and decision making assert that people exhibit diminishing sensitivity to magnitude changes. For instance, according to the value function of prospect theory (Kahneman & Tversky, 1979), the pleasure of moving from 0 to $1000 is larger than the pleasure of moving from $1000 to $2000, whereas the pleasure of moving from $1000 to $2000 is larger than the pleasure of moving from $2000 to $3000. In this article, I call into question how much diminishing sensitivity actually impacts choice and the nature of the value function. I advance a special form of diminishing sensitivity that I have termed rapidly diminishing sensitivity, which postulates that people are sensitive to the presence versus the absence of outcomes but are less sensitive to the scope of the outcomes when the latter differ from zero. Rapidly diminishing sensitivity yields a value function that flattens out rapidly as values move away from zero. In the special case where the value function flattens out immediately after zero, rapidly diminishing sensitivity assumes a discrete form that I have termed discrete sensitivity. I propose that rapidly diminishing sensitivity and discrete sensitivity are typically observed in experimental studies that involve extensive manipulations of the size of the outcomes across decisions, holding everything else constant. I provide evidence for my hypothesis in eight well-powered preregistered experiments across a wide range of domains, such as financial decisions, valuations of human lives, purchase decisions, judgments of goal-related performance, intertemporal choices, and moral decisions. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Target drift discriminative network based on deep learning in visual tracking

In visual tracking, sometimes the target response value is high, but it is not the tracking result, which can result in the wrong judgment. Moreover, the threshold to decide the tracking result needs to be set artificially in the traditional discriminative methods. We propose a deep learning-based target drift discriminative network to judge whether the target is lost. We design a lightweight network without the threshold, using four convolutional layers, three full connection layers, and the Softmax function to judge the tracking results. When training the network, the established positive and negative samples are used, and we select difficult samples for further training to achieve a better target discriminative effect. Finally, a target drift discriminative network is introduced into the accurate tracking by overlap maximization. When it is judged that the target is lost, another search area is selected to quickly find the target. Numerous experiments show that our method achieves the best performance on datasets UAV123, UAV20L, and VOT2018-LT, especially on the UAV20L dataset, for which the tracking precision and tracking success rate are improved by 3.7% and 2.8%. Compared with several other classical threshold discriminative criteria, we do not need to set the threshold artificially and have better judgment performance.

Bilingual phonological awareness as a function of language proficiency

Aims and objectives: The present study examined whether phonological awareness reflects a stable construct or whether it varies by the different languages of bilingual speakers. In particular, the study tests to what extent language proficiency determines phonological awareness above and beyond language structural characteristics. Methodology: Bilingual adult speakers were tested as they afford within-participant comparisons to address this issue. Specifically, 29 Hebrew (L1)-English (L2) bilinguals were compared to 33 English (L1)-Hebrew (L2) bilinguals on a timed auditory rhyme judgment task including 270 word-pairs (90 English pairs, 90 Hebrew pairs, and 90 pseudo-Hebrew pairs). Data and analysis: Reaction times and dʹ on the rhyme judgment task were compared between the two bilingual groups to examine the role of language proficiency in predicting phonological awareness performance. Furthermore, rhyme judgments on Hebrew pairs were correlated with those on English pairs to provide within-participant index of phonological awareness stability. Findings: Rhyme judgment performance on the same set of words was affected by the strength of linguistic representations, as determined by language proficiency profile. English-Hebrew bilinguals performed better on English pairs, whereas Hebrew-English bilinguals performed better on Hebrew pairs. Moreover, within-group comparisons revealed that performance in the more proficient language was not correlated with performance in the less proficient language. Originality: By testing two groups of bilinguals who differ in their language dominance profile using the same set of materials (including both L1 and L2 pairs), the results reveal differences in phonological awareness abilities as a function of language proficiency that cannot be reduced to structural differences between the examined languages. Significance: The findings underscore the dynamic nature of phonological awareness abilities and carry implications for clinical diagnosis of bilingual populations, in that rhyme judgment performance in one language should not be taken to index expected abilities in the other language of bilingual speakers.

Performance of early warning and risk stratification scores versus clinical judgement in the acute setting: a systematic review

ObjectiveRisk stratification is increasingly based on Early Warning Score (EWS)-based models, instead of clinical judgement. However, it is unknown how risk-stratification models and EWS perform as compared with the clinical...

Investor Sentiment and Stock Market Return of Non-Financial Firms Listed on the Nairobi Securities Exchange

Investor sentiment is associated with attitude, thought, feeling, mood, belief, judgment, or expectation of market performance. The sentiment feeling is associated with investors' cognitive comparisons in their investment as well as their experience in making an investment decision. This study examined the effect of investor sentiment on stock market return of non-financial firms listed on the Nairobi Securities Exchange. The study adopted positivism as data collection and hypothesis development and testing was achieved. The study used quantitative research design to correlate study variables using mathematical analysis methods. The correlation results indicated that investor sentiment portrayed a positive association to stock market return. Regression of coefficients of the static model results indicate that investor sentiment and stock market return of non-financial firms listed on the Nairobi securities exchange is positively and significantly related. The results implied that there exist a positive and significant relationship between investor sentiment on stock market return since their coefficient values were positive. The regression coefficients result of lagged stock market return and stock market return was positively and significantly related. The regression of coefficients results indicate that investor sentiment and stock market return is positively and significantly related. The study concluded that investor sentiment has a positive and significant effect on stock market return in non-financial firms. These results imply that when investors are more optimistic about the market generating excess returns, their extreme optimism leads to more speculative activities that tempt them to invest even more. The study also shows that sentiment is relatively correlated with stock returns significantly over time. The study recommends that by taking the investor sentiment into account as a significant determinant of stock market volatility in asset price models, investors can enhance their stock returns. The results can inform on policymakers’ efforts to stabilize stock market volatility and uncertainty in order to protect investors’ wealth and attract more investors. Keywords: Investor Sentiment, Stock Market Return & Non-Financial Firms

Mitigating Information Ambiguity through TSM and Reflexivity for Team Judgment Performance

Part of the work of hierarchical temporary teams found in Professional Service Firms (PSF), is to form judgments based on ambiguous information. In this study, we propose that teams that hold a similar understanding of their client’s situation, in other words, have similar team situation models (TSM), achieve stronger team judgment performance. In addition, we investigate whether a reflexivity intervention helps teams cope with information ambiguity. To test our hypotheses, we collected data from 94 ad-hoc, hierarchical teams of financial auditors from a Big 4 firm, participating in a 2x2 experiment of a judgment task, varying information ambiguity and participation in the reflexivity intervention. We examined two types of TSMs relevant to the context. On the one hand, we looked at the teams’ similarity of perception of the relevant information (TSMinfo) and on the other, the similarity of perception of the judgment complexity (TSMjdm). Our results show that (1) information ambiguity is not directly related to team performance, (2) teams facing high information ambiguity have stronger TSMinfo, (3) teams achieve higher judgment performance with more similar TSMinfo and more dissimilar TSMjdm and (4) reflexivity helps the formation of TSMinfo when information ambiguity is moderate but hurts when it is high.

Does Reality Television-Style Singing Influence Singing Self-Concept?

Due to upward social comparison, we hypothesized that exposure to reality television singing (a technically demanding style of contemporary commercial music singing) would negatively influence singing self-concept compared to hearing amateur singers or plain, unembellished singing by professionals. A between-subjects, online experiment was used. A sample of 212 individuals (Mage=33.14; 69.30% female) participated in the study. After completing a background section, participants were randomly allocated into one of the experimental conditions (hearing one of four versions of a well-known song: a control version with piano and no singing, amateur singing, professional plain singing, and professional singing in the style of reality television singing). Participants were then asked to judge the performance they heard and to respond to items concerning their singing self-concept (including singing ability). A series of ANCOVAs was used to examine the impact of the experimental condition on the participants' performance judgments and singing self-concept. The amateur singing was judged as the lowest quality. While there was no significant difference by experimental condition regarding possessing good singing ability, the experimental condition did affect people's singing aspirations and perceived ability to sing along with the performers. The pattern of results suggests that exposure to reality television-style singing may have negative impacts on people's singing self-concept via upward social comparison. Self-concept has been identified as an important predictor of musical engagement and participation and plays a role in motivating action. These results encourage music educators, singing voice pedagogues, and community musicians seeking to promote musical and singing participation to be aware of cultural influences on an individual's singing self-concept.

Research on performance and dynamic competency evaluation of bid evaluation experts based on weight interval number.

In the past many years, some scholars have studied bid evaluation experts, such as the behavior of bid evaluation experts. However, previous research ignores the performance and competency of bid evaluation experts, so this paper aims to provide a theoretical basis for incentive and constraint mechanism and hierarchical or dynamic management of bid evaluation experts by implementing performance and dynamic competency evaluation of bid evaluation experts. Firstly, the evaluation index system of performance and dynamic competency of bid evaluation experts is preliminarily constructed by referring to relevant literature, and then the constructed evaluation index was modified and improved by consulting relevant stakeholders' experts. Secondly, considering the hesitation and consistency of expert weighting, the calculation method of expert weight coefficient and index score interval number is improved. Based on the theory of weight interval number, the corresponding mathematical optimization model is constructed to calculate the index weight according to the purpose of performance judgment and dynamic competency clustering of bid evaluation experts. Finally, the data of performance and dynamic competency of bid evaluation experts is obtained by questionnaire survey, and the empirical analysis was carried out by simulating the bid evaluation experts consistent with the actual situation. After improving the calculation method of index score interval number, and then calculating index weight interval number through index score interval number, the length of index weight interval number can be decreased and the calculation accuracy of index weight interval number can be increased. In addition, the index weight calculated by the constructed mathematical optimization model can make the intra-class discrimination smaller and the inter-class discrimination larger. Finally, some suggestions are also provided for the management of bid evaluation experts.

Acute pulmonary embolism: Appropriateness of emergency department management according to clinical guidelines

Background and aimsTo evaluate the frequency of acute pulmonary embolism, the use of clinical probability scores, and the appropriateness of the management of patients for whom computed tomography angiography (CTA) was requested from the emergency department for suspected acute pulmonary embolism. Materials and methodsThis was a retrospective observational study of CTA studies requested from the emergency department to rule out acute pulmonary embolism. We analyzed clinical variables and the explicit use of clinical probability scores. We determined the appropriateness of management according to the Wells Score and Geneva Score and the simplified versions of these two scores, calculated retrospectively. ResultsWe included 534 patients (52.8% women; mean age, 73 years). The frequency of acute pulmonary embolism was 23.0% and the Wells Score was explicitly used in 15.2%. The appropriateness of the management varied depending on the clinical probability score used to assess it (54.5%–75.8%) and on whether the standard d-dimer or age-adjusted d-dimer was used. ConclusionsThe failure to use the Wells Scores in all cases does not necessarily imply inappropriate management, and the performance of global clinical judgment can be similar to that of clinical probability scores; however, specific studies are necessary to confirm this hypothesis.

Harnessing Natural Language Processing to Support Decisions Around Workplace-Based Assessment: Machine Learning Study of Competency-Based Medical Education.

BackgroundResidents receive a numeric performance rating (eg, 1-7 scoring scale) along with a narrative (ie, qualitative) feedback based on their performance in each workplace-based assessment (WBA). Aggregated qualitative data from WBA can be overwhelming to process and fairly adjudicate as part of a global decision about learner competence. Current approaches with qualitative data require a human rater to maintain attention and appropriately weigh various data inputs within the constraints of working memory before rendering a global judgment of performance.ObjectiveThis study explores natural language processing (NLP) and machine learning (ML) applications for identifying trainees at risk using a large WBA narrative comment data set associated with numerical ratings.MethodsNLP was performed retrospectively on a complete data set of narrative comments (ie, text-based feedback to residents based on their performance on a task) derived from WBAs completed by faculty members from multiple hospitals associated with a single, large, residency program at McMaster University, Canada. Narrative comments were vectorized to quantitative ratings using the bag-of-n-grams technique with 3 input types: unigram, bigrams, and trigrams. Supervised ML models using linear regression were trained with the quantitative ratings, performed binary classification, and output a prediction of whether a resident fell into the category of at risk or not at risk. Sensitivity, specificity, and accuracy metrics are reported.ResultsThe database comprised 7199 unique direct observation assessments, containing both narrative comments and a rating between 3 and 7 in imbalanced distribution (scores 3-5: 726 ratings; and scores 6-7: 4871 ratings). A total of 141 unique raters from 5 different hospitals and 45 unique residents participated over the course of 5 academic years. When comparing the 3 different input types for diagnosing if a trainee would be rated low (ie, 1-5) or high (ie, 6 or 7), our accuracy for trigrams was 87%, bigrams 86%, and unigrams 82%. We also found that all 3 input types had better prediction accuracy when using a bimodal cut (eg, lower or higher) compared with predicting performance along the full 7-point rating scale (50%-52%).ConclusionsThe ML models can accurately identify underperforming residents via narrative comments provided for WBAs. The words generated in WBAs can be a worthy data set to augment human decisions for educators tasked with processing large volumes of narrative assessments.

Machine Learning-Based Evaluation on Craniodentofacial Morphological Harmony of Patients After Orthodontic Treatment.

Objectives: Machine learning is increasingly being used in the medical field. Based on machine learning models, the present study aims to improve the prediction performance of craniodentofacial morphological harmony judgment after orthodontic treatment and to determine the most significant factors. Methods: A dataset of 180 subjects was randomly selected from a large sample of 3,706 finished orthodontic cases from six top orthodontic treatment centers around China. Thirteen algorithms were used to predict the value of the cephalometric morphological harmony score of each subject and to search for the optimal model. Based on the feature importance ranking and by removing features, the regression models of machine learning (including the Adaboost, ExtraTree, XGBoost, and linear regression models) were used to predict and compare the score of harmony for each subject from the dataset with cross validations. By analyzing the prediction values, the most optimal model and the most significant cephalometric characteristics were determined. Results: When nine features were included, the performance of the XGBoost regression model was MAE = 0.267, RMSE = 0.341, and Pearson correlation coefficient = 0.683, which indicated that the XGBoost regression model exhibited the best fitting and predicting performance for craniodentofacial morphological harmony judgment. Nine cephalometric features including L1/NB (inclination of the lower central incisors), ANB (sagittal position between the maxilla and mandible), LL-EP (distance from the point of the prominence of the lower lip to the aesthetic plane), SN/OP (inclination of the occlusal plane), SNB (sagittal position of the mandible in relation to the cranial base), U1/SN (inclination of the upper incisors to the cranial base), L1-NB (protrusion of the lower central incisors), Ns-Prn-Pos (nasal protrusion), and U1/L1 (relationship between the protrusions of the upper and lower central incisors) were revealed to significantly influence the judgment. Conclusion: The application of the XGBoost regression model enhanced the predictive ability regarding the craniodentofacial morphological harmony evaluation by experts after orthodontic treatment. Teeth position, teeth alignment, jaw position, and soft tissue morphology would be the most significant factors influencing the judgment. The methodology also provided guidance for the application of machine learning models to resolve medical problems characterized by limited sample size.

Understanding German Consumers’ Intention to Adopt COVID-19 Infection Prevention Measures: A Moral Decoupling Perspective

Getting consumers to adopt infection prevention measures is important for society to overcome the coronavirus pandemic. This research adopts a moral decoupling perspective to examine how consumers in Germany respond to perceived transgressions of COVID-19 infection prevention regulations. Focusing on two nonpharmaceutical measures (mask wearing, social distancing) as well as a pharmaceutical one (vaccination), two empirical studies indicate that transgression relevance influences intention to adopt the measure (in parallel) through judgment of performance and judgment of morality. Type of transgression moderates the effect of transgression relevance on morality, but not on performance. In addition, effects weaken as a person’s fear of infection increases. Effects are robust, though, when controlling for moral decoupling and moral delegation (Study 1), and additionally for psychological reactance and political orientation (Study 2). Implications for research and practice evolve around new insights into how to get consumers to adopt infection prevention measures more effectively.

Effects of Blended Learning on Nursing Students’ Clinical Competence, Clinical Judgment, and Skill Performance Ability

Effects of Blended Learning on Nursing Students’ Clinical Competence, Clinical Judgment, and Skill Performance Ability

Confidence, accuracy judgments and feedback in schizophrenia and bipolar disorder: a time series network analysis.

Inaccurate self-assessment of performance is common among people with serious mental illness, and it is associated with poor functional outcomes independent from ability. However, the temporal interdependencies between judgments of performance, confidence in accuracy, and feedback about performance are not well understood. We evaluated two tasks: the Wisconsin Card Sorting Test (WCST) and the Penn Emotion recognition task (ER40). These tasks were modified to include item-by-item confidence and accuracy judgments, along with feedback on accuracy. We evaluated these tasks as time series and applied network modeling to understand the temporal relationships between momentary confidence, accuracy judgments, and feedback. The sample constituted participants with schizophrenia (SZ; N = 144), bipolar disorder (BD; N = 140), and healthy controls (HC; N = 39). Network models for both WCST and ER40 revealed denser and lagged connections between confidence and accuracy judgments in SZ and, to a lesser extent in BD, that were not evidenced in HC. However, associations between feedback regarding accuracy with subsequent accuracy judgments and confidence were weaker in SZ and BD. In each of these comparisons, the BD group was intermediate between HC and SZ. In analyses of the WCST, wherein incorporating feedback is crucial for success, higher confidence predicted worse subsequent performance in SZ but not in HC or BD. While network models are exploratory, the results suggest some potential mechanisms by which challenges in self-assessment may impede performance, perhaps through hyperfocus on self-generated judgments at the expense of incorporation of feedback.