Accuracy Of Judgments Research Articles

How pedagogical content knowledge sharpens prospective teachers’ focus when judging mathematical tasks: an eye-tracking study

Teachers’ ability to accurately judge difficulties of mathematical tasks is an essential aspect of their diagnostic competencies. Although research has suggested that pedagogical content knowledge (PCK) is positively correlated with the accuracy of diagnostic judgments, experimental studies have not been conducted to investigate how PCK affects perception and interpretation of relevant task characteristics. In an intervention study with a control group, 49 prospective mathematics teachers judged the difficulty of 20 tasks involving functions and graphs while an eye tracker tracked their eye movements. Some of the tasks included characteristics well known to be difficult for students. Participants’ domain-specific PCK of typical student errors was manipulated through a three-hour intervention, during which they learned about the most common student errors in function and graph problems. We found that the process of perception (relative fixation duration on the relevant area in the tasks) was related to judgment accuracy. Pre-post comparisons revealed an effect of the intervention not only on participants’ domain-specific PCK of typical student errors but also on their perception and interpretation processes. This result suggests that domain-specific PCK of typical student errors allowed participants to focus more efficiently on relevant task characteristics when judging mathematical task difficulties. Our study contributes to our understanding of how professional knowledge makes teachers’ judgment processes of mathematical tasks more efficient.

FMRI evidence of movement familiarization effects on recognition memory in professional dancers.

Dual-process theories propose that recognition memory involves recollection and familiarity; however, the impact of motor expertise on memory recognition, especially the interplay between familiarity and recollection, is relatively unexplored. This functional magnetic resonance imaging study used videos of a dancer performing International Latin Dance Styles as stimuli to investigate memory recognition in professional dancers and matched controls. Participants observed and then reported whether they recognized dance actions, recording the level of confidence in their recollections, whereas blood-oxygen-level-dependent signals measured encoding and recognition processes. Professional dancers showed higher accuracy and hit rates for high-confidence judgments, whereas matched controls exhibited the opposite trend for low-confidence judgments. The right putamen and precentral gyrus showed group-based moderation effects, especially for high-confidence (vs. low-confidence) action recognition in professional dancers. During action recognition, the right superior temporal gyrus and insula showed increased activation for accurate recognition and high-confidence retrieval, particularly in matched controls. These findings highlighting enhanced action memory of professional dancers-evident in their heightened recognition confidence-not only supports the dual-processing model but also underscores the crucial role of expertise-driven familiarity in bolstering successful recollection. Additionally, they emphasize the involvement of the action observation network and frontal brain regions in facilitating detailed encoding linked to intention processing.

Vehicle Lateral Control Based on Dynamic Boundary of Phase Plane Based on Tire Characteristics

Lateral control is an essential safety control technology for autonomous vehicles, but the effectiveness of lateral control technology relies heavily on the precision of vehicle motion state judgements. In order to achieve accurate judgements of the vehicle motion state and to improve the control effectiveness of vehicle maneuverability and the stability controller, this paper starts with an analysis of phase plane stability. A simulation analysis is conducted to investigate the effect of the vehicle steering angle of the front wheels, the longitudinal velocity, and the tire–road adhesion coefficient on the boundary of the stability area. The stable area of the phase plane was partitioned using the proposed novel quadrilateral method, and we established a stability area regression model using machine learning methods. We analyzed the inherent connection between the lateral tire forces and the principles of vehicle maneuverability and stability control, indirectly combining the characteristics of tire forces with vehicle maneuverability and stability control. An allocation algorithm for maneuverability and stability control was designed. A co-simulation indicates that the vehicle stability controller not only accurately assesses the motion state of the vehicle but also demonstrates a considerably better performance in maneuverability and stability control compared to a controller using the traditional partitioning method of stable regions. The suggested allocation method enhances vehicle maneuverability and stability by enabling a seamless transition between the two and improving the effectiveness of stability control.

Systematic testing of three Language Models reveals low language accuracy, absence of response stability, and a yes-response bias.

Humans are universally good in providing stable and accurate judgments about what forms part of their language and what not. Large Language Models (LMs) are claimed to possess human-like language abilities; hence, they are expected to emulate this behavior by providing both stable and accurate answers, when asked whether a string of words complies with or deviates from their next-word predictions. This work tests whether stability and accuracy are showcased by GPT-3/text-davinci-002, GPT-3/text-davinci-003, and ChatGPT, using a series of judgment tasks that tap on 8 linguistic phenomena: plural attraction, anaphora, center embedding, comparatives, intrusive resumption, negative polarity items, order of adjectives, and order of adverbs. For every phenomenon, 10 sentences (5 grammatical and 5 ungrammatical) are tested, each randomly repeated 10 times, totaling 800 elicited judgments per LM (total n = 2,400). Our results reveal variable above-chance accuracy in the grammatical condition, below-chance accuracy in the ungrammatical condition, a significant instability of answers across phenomena, and a yes-response bias for all the tested LMs. Furthermore, we found no evidence that repetition aids the Models to converge on a processing strategy that culminates in stable answers, either accurate or inaccurate. We demonstrate that the LMs' performance in identifying (un)grammatical word patterns is in stark contrast to what is observed in humans (n = 80, tested on the same tasks) and argue that adopting LMs as theories of human language is not motivated at their current stage of development.

The richer, the better? Effects of combining seductive and interpretational visuals in computer‐based learning

AbstractBackgroundThere are two major types of pictures that have been the focus of multimedia learning research, namely, seductive and interpretational pictures. Despite an increasing body of literature documenting the effects of either seductive or interpretational pictures added to text‐based materials, there is a paucity of research explicitly comparing them in a multimedia learning environment.ObjectivesTo address this gap, this study manipulated the picture condition by designing seductive pictures (SPs), interpretational pictures (IPs), and seductive plus interpretational pictures (SIPs) and investigated the multimedia effects of SPs, IPs, and SIPs on several cognitive and affective‐motivational variables.MethodsTwo computer‐based experiments were conducted where a scientific text about the blood circulatory system was presented with SPs, IPs, or SIPs. Participants were randomly assigned to one of the three conditions, and completed a subsequent learning test (comprehension and transfer questions) as well as a survey measuring their learning experience.Results and ConclusionsThe results of the two experiments were consistent in showing that our experimental manipulation was unsuccessful in influencing the learning outcome variables. Nevertheless, learning with seductive plus interpretational pictures appeared to yield better judgement accuracy, as compared to learning with seductive or interpretational pictures only. Most educational practitioners still include decorative elements based on their impression of aesthetics of motivation; this study encourages them to use these elements within their learning materials.

Evaluating Graphical Perception of Visual Motion for Quantitative Data Encoding.

Information visualization uses various types of representations to encode data into graphical formats. Prior work on visualization techniques has evaluated the accuracy of perceived numerical data values from visual data encodings such as graphical position, length, orientation, size, and color. Our work aims to extend the research of graphical perception to the use of motion as data encodings for quantitative values. We present two experiments implementing multiple fundamental aspects of motion such as type, speed, and synchronicity that can be used for numerical value encoding as well as comparing motion to static visual encodings in terms of user perception and accuracy. We studied how well users can assess the differences between several types of motion and static visual encodings and present an updated ranking of accuracy for quantitative judgments. Our results indicate that non-synchronized motion can be interpreted more quickly and more accurately than synchronized motion. Moreover, our ranking of static and motion visual representations shows that motion, especially expansion and translational types, has great potential as a data encoding technique for quantitative value. Finally, we discuss the implications for the use of animation and motion for numerical representations in data visualization.

Research on Multi-parameter Interpretation Method of Advanced Exploration of Mine Transient Electromagnetic Method

To enrich the effective interpretation parameters of mine transient electromagnetic method (MTEM) and improve the accuracy of detection results, based on calculating the apparent resistivity and its depth of the whole period at each moment by dichotomy, combined with induced electromotive force, advanced detection fan diagrams of the apparent resistivity and the slope of the two parameters along depth direction are drawn respectively, and the imaging results of different parameters are compared and analyzed. It is found that there is an abnormal area with good roof and floor connectivity on the left side in the front of the roadway, and the four parameters have different degrees of abnormal reflection at this position. The later advanced drilling revealed that the water inflow was 12 m3/h, which verified that the multi-parameter interpretation results of the mine transient electromagnetic method were right. The above multi-parameter interpretation method for advanced exploration of the roadway not only enriches the interpretation way of the geological body but improves the accuracy of judgment of the geological anomaly body in front of the roadway.

Reasoning Through Narrative

AbstractA peculiar feature of our species is that we settle what to believe, value, and do by reasoning through narratives. A narrative is adiachronic, information-rich story that contains persons, objects, and at least one event. When we reason through narrative, we usenarrative to settle what to do, to make predictions, to guide normative expectations, and to ground which reactive attitudes we think areappropriate in a situation. Narratives explain, justify, and provide understanding. Narratives play a ubiquitous role in human reasoning. Andyet, narratives do not seem up to the task. Narratives are often unmoored representations (either because they are do not purport to referto the actual world, or because they are grossly oversimplified, or because are known to be literally false). Against this, I argue thatnarratives guide our reasoning by shaping our grasp of modal structure: what is possible, probable, plausible, permissible, required,relevant, desirable and good. Narratives are good guides to reasoning when they guide us to accurate judgments about modal space. Icall this the modal model of narrative. In this paper, I develop an account of how narratives function in reasoning, as well as an account ofwhen reasoning through narrative counts as good reasoning.

Efficient Visual Tracking Based on Fuzzy Inference for Intelligent Transportation Systems

Remote monitoring is an important application of intelligent transportation systems (ITSs). The combination of monitoring equipment and tracking algorithms can be used to automatically track moving targets. The tracking algorithm based on the Siamese network is both accurate and efficient, and its development potential is better than that of other algorithms. Its output is a detection map that reflects the probability that any position in the search area is the center of the target’s bounding box, and the maximum value of the detection map is the center of the target’s bounding box predicted by the algorithm. Owing to partial occlusion, target deformation, out-of-view, and background clutter, local maxima in the detection map may also be the center of the target’s bounding box. A tracker’s ability to make accurate judgments is currently limited. Furthermore, previous trackers extracted only the target features in the initial frame as the matching template. Although this matching template is highly reliable, it cannot effectively combine the target features available in the subsequent frames. Therefore, in this study, fuzzy inference is introduced into the tracking process to analyze the reliability of the detection map. When this map is reliable, the target feature of the search area is transformed into a substitute template; otherwise, multiple substitute templates are selected from the template pool for parallel matching as per the set rules. The optimal result is selected from multiple detection results, based on the priority of the detection results when the initial frame is used as the matching template. Experimental results on multiple datasets show that the proposed algorithm is superior to other similar algorithms in terms of multiple assessment metrics and can improve the robustness of remote monitoring tasks in ITSs.

Wind turbine blade damage detection and classification based on sound feature signal using machine learning

Wind turbine blades experience variable environmental conditions and are prone to failure due to fatigue and weather-induced damage. In this study, the aerodynamic sound signal of wind turbine blades is collected while in operation. Short-Time Fourier Transform method identified and used to analyze the periodic signal of the rotation of the wind turbine blades. The spectral centroid of the pulse signal and the variation of the corresponding three blades spectral centroid are extracted as the input features for supervised machine learning. Gaussian mixture model algorithm classified features and used with blades damage trend for structural health monitoring. Through the Gaussian mixture model established by using the mean value and standard deviation of the peak value of the spectral centroid, the results after the model test show the accuracy of the damaged blade judgment can reach 98 %. In addition, from the visual classification chart, it can be known that the blade will enter the damage state, and maintenance should be carried out in advance to avoid damage to the blade and maintain the stable operation of the wind turbine.

Using acoustic camera technology on inspection of noisy vehicles in Taiwan

In recent years, noise complaints on motor vehicles had shown an increasing trend and became an environmental concern issue in Taiwan. Since 2021, innovative acoustic camera technology used to inspect high-noise vehicles exceeding "Vehicle Noise Control Standard" would be fined. There are 111 sets of acoustic camera equipment using in 21 counties and cities in Taiwan, and local government issued 4,099 fines to violating vehicle owners. This environmental policy has been supported by people living near major road with ninety percent satisfaction. Currently, acoustic camera technology with sound radar adopted by some cities in France to locate noisy vehicles accurately and issue fines automatically. Array sound camera technology has been used to inspect noisy vehicles in Netherlands and Germany. Taiwan is the first country in Asia to use acoustic camera technology conducting inspections and law enforcement against noisy vehicles. The sound camera technology system is mainly composed of high-speed camera equipment, sound level meter and license plate recognition system. Fixed systems are prior to set on specific road in hot spots of public complaint to inspect and outlaw noisy vehicles. After implementation of acoustic camera technology in these years, some challenges need to overcome. First, people doubt with accuracy and fairness of law enforcement equipment. Second, noise judgment of multi-source vehicle with law enforcement. To improve accuracy of law enforcement and multi-sound source vehicle noise judgment, technology of combining sound photography with array microphones is developing in Taiwan. In the future, we plan to conduct research on multi-source vehicle noise judgment technology to improve inspection efficiency and ensure a peaceful environment.

Personality Comparison between Lethal and Non-lethal Intimate Partner Violence Perpetrators and Their Victims

Intimate partner violence against women (IPVAW) and femicide (intimate partner femicide, IPF), as a worldwide phenomenon, cannot be explained in a simple way. From an ecological point of view, there are individual factors contemplated. In the current studies, we consider personality as an individual factor to clarify what differentiates a non-lethal IPVAW situation from a femicide. Study 1 was designed to investigate the accuracy with which trained interviewers judged the personality of a group of IPVAW perpetrators during an interview. The target sample of study 1 was composed of 293 males who after being interviewed completed a measure of personality assessing the “Big Three” model of personality. The interviewers performed fairly accurate judgements about the personality of the target participants. Study 2 shows the differences in personality, using Eysenck’s personality model, between the IPF and IPVAW perpetrators and their victims. The total sample study 2 was formed of 551 participants distributed among IPF perpetrators, IPVAW perpetrators, and the victims of both groups. Differences in proportions were observed between both groups of perpetrators as well as between each group and their respective victims. With these findings, we propose personality as a femicide risk factor that should be taken into consideration by police officers and other practitioners when receiving an IPVAW report.

Coexistence of early gastric cancer and benign submucosal lesions mimic invasive cancer: a retrospective multicenter experience

ObjectiveTo present a study to identify the characteristics of coexisting early gastric cancer (EGC) and benign submucosal lesions, with the aim of reducing the adverse consequences of overdiagnosis and overtreatment.MethodsIn this retrospective study, we searched the endoscopic databases of three tertiary centers. We screened of patients suspected of early gastric cancer submucosal infiltration by conventional endoscopy and ultimately selected for endoscopic submucosal dissection treatment after endoscopic ultrasonography and magnifying endoscopy with narrow-band imaging examination. Patients with coexisting EGC and benign submucosal lesions in histological sections were included. Clinical data and endoscopic images were reviewed. To evaluate the precision of endoscopists’ diagnoses for this type of lesion, eight endoscopists with different experiences were recruited to judge the infiltration depth of these lesions and analyze the accuracy rate.ResultsWe screened 520 patients and retrospectively identified 18 EGC patients with an invasive cancer-like morphology. The most common lesion site was the cardia (12/18, 66.67%). The coexisting submucosal lesions could be divided into solid (5/18, 27.78%) and cystic (13/18, 72.22%). The most common type of submucosal lesion was gastritis cystica profunda (12/18, 66.67%), whereas leiomyoma was the predominant submucosal solid lesion (3/18, 16.67%). Ten (55.56%) patients < underwent endoscopic ultrasonography; submucosal lesions were definitively diagnosed in 6 patients (60.00%). The accuracy of judgement of the infiltration depth was significantly lower in cases of coexistence of EGC with benign submucosal lesions (EGC-SML) than in EGC (38.50% versus 65.60%, P = 0.0167). The rate of over-diagnosis was significantly higher within the EGC-SML group compared to the EGC group (59.17% versus 10.83%, P < 0.0001).ConclusionsWe should be aware of the coexistence of EGC and benign submucosal lesions, the most common of which is early cardiac-differentiated cancer with gastritis cystica profunda.

Evaluating and comparing bagging and boosting of hybrid learning for breast cancer screening

PurposeIn many fields, including bioinformatics, ensemble methods have been often employed to perform prediction tasks such as classification and regression due to their ability to improve the accuracy and robustness of machine learning models. Given that the most prevalent cancer and the primary cause of death for women is breast cancer, researchers have started using ensemble approaches to advance their studies in this area. Effectively, ensemble methods can be used to develop clinical decision support systems that can help healthcare providers make more accurate judgements. MethodsIn the present study, we construct and evaluate bagging and boosting ensemble methods for the binary classification of breast cancer screening images from the CBIS-DDSM dataset. To build the bagging ensembles, a hybrid architecture consisting of three feature extractors (Inception V3, MobileNet V2, DenseNet 201) and four classifiers (K-nearest neighbors, Multilayer perceptron, Support vector machine, Decision trees) was chosen. As for the boosting ensembles, the method consists of the same three feature extractors with a decision trees-based classifier and the four boosting methods (AdaBoost, GBM, XGboost, LightGBM). ResultsThe evaluation of both ensemble methods over the mammography dataset was made using four performance metrics (accuracy, sensitivity, F1-score, and recall), as well as the Skott–Knott statistical test and the Borda count voting system to rank all the possible model combinations. Results proved that bagging and boosting ensembles generally outperformed both their base learners and single models, and that the best performing ensemble overall was Gradient boosting with DenseNet 201 as feature extractor and 200 trees which scored an accuracy of 85.50 %. ConclusionsThe purpose of this research was to use hybrid learning based ensembles to maximize the potent performance of numerous models. It effectively illustrated the prospective potential of using ML approaches for the binary classification of mammography data used for breast cancer screening.

Identifying False Information in the Era of Big Data

The emergence and dissemination of false information in the era of big data has greatly affected people's lives, and identifying and correcting such false information is critical to the safety of personal information property and public health. To understand how the public is "influenced" by fake news, this paper surveyed 303 respondents from different ages. Controlled experiments were conducted based on which social platforms they were active on a daily basis, whether the information they often received could be identified as true or false, and whether they were willing to share this information with those around them. In each experiment, the study predicted the accuracy of different groups' judgments of true or false messages, as well as their willingness to share the messages with those around them. In both experiments, information from authoritative organizations or institutions significantly increased the accuracy of participants' judgments and their willingness to share the information with others. In addition, the results of the post-experiment questionnaire showed that participants would consider the authenticity and reliability of the corrected information sources and would confirm them by themselves.

Potency of teleophthalmology as a detection tool for diabetic retinopathy

In China, the prevalence of diabetic retinopathy (DR) is increasing, so it is necessary to provide convenient and effective community outreach screening programs for DR, especially in rural and remote areas. The purpose of this study was to use the results of ophthalmologists as the gold standard to evaluate the accuracy of community general practitioners' judgement and grading of DR to find a feasible and convenient DR screening method to reduce the risk of visual impairment and blindness in known diabetes patients. Retinal images of 1646 diabetic patients who underwent DR screening through teleophthalmology at Nanchang First Hospital were collected for 30 months (January 2020 to June 2022). Retinal images were collected without medication for mydriasis, stored by community general practitioner, and diagnosed by both community general practitioner and ophthalmologist of our hospital through teleophthalmology. The grading of ophthalmologist was used as a reference or gold standard for comparison with that of community general practitioner. A total of 1646 patients and 3185 eyes were examined, including 2310 eyes with DR. The evaluation by the community general practitioner had a Kappa value of 0.578, sensitivity of 80.58%, specificity of 89.94%, and accuracy of 83.38%% in 2020; a Kappa value of 0.685, sensitivity of 95.43%, specificity of 78.55%, and accuracy of 90.77% in 2021; and a Kappa value of 0.744, sensitivity of 93.99%, specificity of 88.97%, and accuracy of 92.86% in 2022. Teleophthalmology helped with large-scale screening of DR and made it possible for community general practitioner to grade images with high accuracy after appropriate training. It is possible to solve the current shortage of eye care personnel, promote the early recognition of disease and reduce the impact of diabetes-associated blindness.

Increasing accuracy motivations using moral reframing does not reduce Republicans’ belief in false news

In a pre-registered survey experiment with 2,009 conservative Republicans, we evaluated an intervention that presents having accurate beliefs as consistent with conservative political identity and values (e.g., patriotism, respect for tradition, and religious purity). The intervention caused participants to report placing greater value on accuracy, and placing greater value on accuracy was correlated with successfully rating true headlines as more accurate than false headlines. Yet, the intervention had no significant effect on accuracy judgments. These results suggest that moral reframing, and perhaps interventions based on connecting accuracy motivation with political identity more generally, may not be promising for combatting belief in misinformation.

Immediate post performance judgements about cognitive performance in schizophrenia and bipolar disorder: associations with test performance and subjective overall judgments regarding abilities

ABSTRACT Introduction: The study explored associations between the accuracy of post assessment judgements of cognitive performance with global self-assessments of psychosocial functioning compared to evaluations generated by observers in schizophrenia and bipolar disorder. Methods: An abbreviated cognitive assessment based on the MATRICS Consensus Cognitive Battery was administered to 122 individuals with schizophrenia and 113 with bipolar disorder. They provided self-estimates of their performance after each subtest. In addition, self-reports on cognition, social cognition, and everyday functioning were collected and compared to observer ratings. Results: Both groups overestimated their cognitive function, but in bipolar disorder, there was 30% shared variance between task performance and self-rated task performance (vs. 5% in schizophrenia). Significant correlations were found between self-reported everyday outcomes and both actual and self-assessed performance. In schizophrenia, immediate judgements were only related to self-rated functioning, not to observer rated functioning. In bipolar disorder, impairments in self-assessment of performance correlated with observer ratings of cognitive ability, which was not observed in schizophrenia. Conclusions: While both groups showed correlations between cognitive performance and introspective accuracy, individuals with bipolar disorder showed higher accuracy in assessing their cognitive performance and other outcomes. Notably, impairments in introspective accuracy were associated with observer-rated functioning exclusively in bipolar disorder.

Big Little Election Lies: Cynical and Credulous Evaluations of Electoral Fraud

Abstract The ‘Big Lie’ in American politics has sparked intense concern about the erosion of public confidence in the integrity of US elections—raising questions about the legitimacy of the authorities, institutions, and principles of democratic governance. Cynicism generated from misinformation about trustworthy elections has attracted a growing body of individual-level social-psychological research in America and Europe. Another common problem found around the world, however, which has received far less attention, concerns credulous citizens who express considerable faith and confidence in flawed contests. This study theorises that at macro-level, the accuracy of any public judgments about trustworthy elections is likely to be mediated by the information environment in open and closed societies, as well as by the type of regime. To understand these issues, Part I summarises the conceptual and theoretical argument about trust and trustworthiness. Part II describes the sources of evidence. To apply the theory, data on public opinion is drawn from around 85 societies around the globe included in Waves 6 and 7 of the World Values Survey (2010–2022), with measures of electoral trust and subjective perceptions of electoral integrity among ordinary citizens. Institutional electoral performance indices are drawn from the Varieties of Democracy project (V-Dem 12.0). Part III analyses how far these independent estimates match public judgments of the trustworthiness of elections in each country – and how far such relationships are conditioned by the type of information society as well as by the type of regime. Part IV highlights the key findings and considers their broader implications for understanding the macro-level conditions for trust and trustworthiness.

Reading and writing difficulties in third- and sixth-grade students: a cross-sectional survey.

In Southern Italy and, specifically, in the region of Campania, many surveys show that the average of students with reading difficulties is much higher than in northern Italy and abroad. On the other hand, specific learning disorders (SLDs) in Campania are much less certified. Since there are no etiological reasons that can explain this apparent inconsistency, an objective of this cross-sectional study was to evaluate the extent of reading/writing difficulties in students from a province of Campania and then to assess the ability of teachers to identify such difficulties in their students. Of a total of 241 enrolled students, 155 (64.31%), including 73 from primary school and 82 from secondary school, belonging to 5 schools in the province of Salerno (Italy), took part in the survey. Students' reading and writing skills were assessed through standardized tests. The tests results were then compared with teacher judgments and context-related variables. At the reading test, 28.7% of primary school and 13.4% of lower secondary school students fell below the 5th percentile for age. Results of the writing test were even more significant: almost half of the students of both levels of education performed below the 5th percentile. Teacher judgments showed higher agreement with standardized assessments in primary (88%, K of Cohen=0.68) than in secondary school (78%, K=0.23). Reading and writing difficulties were common in our sample. While reading skills tended to improve with age, writing difficulties apparently persisted to some extent in third and sixth-grade classes. The accuracy of teacher judgments on reading skills is relatively high, but teachers seem to hardly report reading difficulties "requiring attention." Although less "severe" than others, such difficulties should be considered, mainly because of their potential developmental trajectories.