Initial Beliefs Research Articles

Testing a mindset intervention as a resilience factor among Latino/a students in science

ABSTRACTLatinos/as experience underachievement and underrepresentation in science. Mindset beliefs contribute to positive academic outcomes among students generally, but are understudied among Latinos/as in science. In this quasi-experimental study, Latino/a students expressed initial mindset-related beliefs shown to be less generative of success in science than their non-Latino/a classmates. A six-week mindset intervention positively influenced Latinos/as’ mindset beliefs and self-perceptions compared to a control group. Gains were generally similar in magnitude for Latino/a and non-Latino/a students, suggesting that mindset may be compensatory rather than protective among Latino/a youth. Gender differences in initial mindset beliefs and response to the intervention are discussed.

Preschoolers' Development of Theory of Mind: The Contribution of Understanding Psychological Causality in Stories.

This study investigated the relationship between children’s abilities to understand causal sequences and another’s false belief. In Experiment 1, we tested 3-, 4-, 5-, and 6-year-old children (n = 28, 28, 27, and 27, respectively) using false belief and picture sequencing tasks involving mechanical, behavioral, and psychological causality. Understanding causal sequences in mechanical, behavioral, and psychological stories was related to understanding other’s false beliefs. In Experiment 2, children who failed the initial false belief task (n = 50) were reassessed 5 months later. High scorers in the sequencing of the psychological stories in Experiment 1 were more likely to pass the standard false belief task than were the low scorers. Conversely, understanding causal sequences in the mechanical and behavioral stories in Experiment 1 did not predict passing the false belief task in Experiment 2. Thus, children may understand psychological causality before they are able to use it to understand false beliefs.

A new hierarchical belief-rule-based method for reliability evaluation of wireless sensor network

With the wide applications of wireless sensor network (WSN), its reliability evaluation has been attracted more attention. The reliability of a WSN is affected mainly by internal and external factors, which include internal faults and external attacks. In this paper, a reliability evaluation method based on a hierarchical belief rule base (BRB) method is proposed for the reliability evaluation of the WSN. First, the factors affecting the reliability of a WSN are analysed, and the reliability evaluation process that considers the WSN fault evaluation and WSN security evaluation is described. Second, the reliability evaluation model is constructed based on the hierarchical BRB model. The qualitative knowledge is used by the BRB model to build initial belief rules, and the quantitative data are used to optimize the initial parameters of the BRB model, which can utilize various types of uncertainty information effectively. Therefore, the proposed method can be applied to the WSN reliability evaluation, which is a complex and uncertain problem. Finally, a simulation case study and an actual case study of wellhead blowout monitoring are conducted to verify the effectiveness of the proposed method. The reliability results of actual WSN are obtained by the standard testing method, where the loss and accuracy rates of the collected data are treated as the observation factors for obtaining the actual reliability values. The estimated results of hierarchical BRB model are very close to the actual reliability values, which shows that the proposed method can be used for evaluating the reliability of the actual WSN accurately.

Willingness to revise own testimony: 3- and 4-year-olds’ selective trust in unexpected testimony from accurate and inaccurate informants

Prior work has shown that young children trust single accurate and inaccurate individuals to a similar extent in their endorsement of novel information. However, it remains unknown to what extent children trust a credible or noncredible individual when given information that is pitted against their own beliefs. The current study examined whether children, when given unexpected testimony that contradicted their initial beliefs but was not completely unbelievable, would selectively revise their beliefs depending on the informant’s past history of accuracy. The participants (3- and 4-year-olds; N = 100) were familiarized with an informant who labeled a series of common objects either accurately or inaccurately. Following that, all children saw a picture of an ambiguous hybrid artifact that consisted of features of two typical common artifacts and were asked to identify the hybrid object with their own label. Subsequently, children watched the previously accurate or inaccurate informant give the same hybrid object a different but plausible label. Children expressed a greater tendency to override their initial judgments and endorse the unexpected testimony from a previously accurate informant than from someone who had consistently made naming errors. The findings provide novel understandings of the circumstances under which 3- and 4-year-old preschoolers may or may not rely on the informant’s prior reliability in their selective learning.

Constructivism and personal epistemology development in undergraduate chemistry students

Students' beliefs about knowledge, or their personal epistemologies, are critical components of the learning process. Researchers and educators need to understand how portrayals of knowledge in the classroom shape personal epistemology development. Using a quasi-experimental design, an organic chemistry instructor taught a traditional, lecture-based course and a constructivist-based interactive-learning course. Students (N = 270) completed three surveys assessing personal epistemology and perceptions of constructivism in the classroom. Although the interactive-learning classroom did not seem to affect personal epistemology, evidence suggested that perceptions of a complex learning environment predicted changes in personal epistemology. Students' initial epistemic beliefs predicted how they perceived the classroom environment. Results also supported an epistemic alignment hypothesis: students performed better on the final exam when their beliefs matched the course structure. Findings support an interactive model between students' personal epistemologies and epistemic climate and highlight the challenges of changing beliefs through single-semester classroom interventions.

Physical education preservice teachers’ perceptions of the subject and profession: development during 2005–2016

ABSTRACTBackground: During the socialization process when becoming a physical education (PE) teacher, the knowledge, perceptions and expectations of what it means to work as a teacher are developed. In this socialization, the initial acculturation phase is shown to be of the most importance, since individual PE teachers’ experiences during this phase are shown to have a long-lasting influence on their approach to and perception of the subject and the profession. Furthermore, research shows that most physical education teacher education (PETE) programmes are ineffective in altering these initial perceptions and beliefs during the programme. This inertia to change may resemble Bourdieu’s concept of habitus.Purpose: The purpose of this study was to analyse the background of PE preservice teacher students (PSTs) and examine their embodied perceptions and beliefs related to the subject and profession when they enrol. Specifically, the study focuses on their background characteristics, perceptions of PE and PE teachers, and whether their background and perceptions changed between 2005 and 2016.Method: This study draws on a web-based questionnaire completed by 224 students (90 women and 134 men) enrolled in the PETE programme at a major university in Sweden between 2005 and 2016. The questionnaire used in this study addressed the PSTs’ experiences, views, beliefs and perceptions of PE and the PE profession, and it was completed during the first semester of respective students’ PE subject studies.Findings: PE PSTs are a homogeneous group of students with similar backgrounds, experiences and perceptions of PE and their future profession as PE teachers. Participants suggested that important characteristics for a good PE teacher include possessing subject knowledge, having pedagogical competence and being considerate. A good PE lesson should be fun and inspiring, consist of physical activity and be adapted to all. Important goals for PE are to develop pupils’ character and promote healthy behaviours. The PSTs’ background characteristics and perceptions do not seem to have changed during the studied period, in spite of the fact that the structure of the PETE programme did change.Conclusions: The homogeneous background among PSTs, with vast experience of sport and physical activity, implies that they will interact and engage with students with similar backgrounds and perceptions (i.e. habitus) during PETE. This may limit the potential influence of PETE and fail to prepare PSTs for the demands of their future profession. However, if the influences of acculturation were accounted for during PETE, the programmes could be better designed and better prepare PSTs for their future profession.

BELIEF-TWISTING SHOCKS AND THE MACROECONOMY

I study the role of shocks to beliefs combined with Bayesian learning in a standard equilibrium business cycle framework. In particular, I examine how a prior belief arising from the Great Depression may have influenced the macroeconomy during the last 75 years. In the model, households hold twisted beliefs concerning the likelihood and persistence of recession and boom states that are affected by the Great Depression. These initial beliefs are substantially different from the true data generating process and are only gradually unwound during subsequent years. Even though the driving stochastic process for technology is unchanged over the entire period, the nature of macroeconomic performance is altered considerably for many decades before eventually converging to the rational expectations equilibrium. This provides some evidence of the lingering effects of beliefs-twisting events on the behavior of macroeconomic variables.

The Underwater Acoustic Target Recognition Algorithm Based on Evidence Clustering

In underwater acoustic target recognition, the target signal is usually complex and the samples which are difficult to obtain also have some uncertain information. In order to effectively solve these problems, the evidence clustering recognition algorithm (TECRA) is presented. In this new method, the k-nearest neighbor are first determined by using the feature distance between the object and its neighbors in each class of the training set, and a reasonable initial basic belief assignments (bba's) for each target data are constructed by the improved k-nearest neighbor classification algorithm. Then the final global bba's of the target is obtained by optimizing the objective function of the algorithm. Finally the object can be recognized by the fusion result and the classification rule presented in the paper. Several experiments based on real underwater acoustic data sets are made to test the effectiveness of TECRA in comparison with some other methods. The results indicate that TECRA can effectively improve the recognition accuracy.

Path-dependent behavior and information leakage in financial markets

I develop a new mechanism that exploits the leakage of information in financial markets to deliver herding and contrarian behavior, which I label “path-dependent behavior.” The mechanism is related to the role of word-of-mouth communication in transmitting information about stocks among traders. In practice, this occurs via dealing interactions and a notable phenomenon called “the broker’s ear.” I find that, for a suitably long trading history, path-dependent behavior is more likely the better the quality of traders’ private information. Herding in the direction of the true state of the world occurs almost surely for any initial beliefs, and it improves price informativeness. An external observer who underestimates/overestimates the rate of information leakage will always overestimate/underestimate the quality of private information. I also show that when the quality of private information is very high and the asymmetry of information between traders and market maker is pronounced, the market is expected to herd 50% of the time. Nonetheless, this has little impact on order imbalance, excluding cases exhibiting catastrophic price behavior.

Addressing Physical Education Teacher Socialization Through Standards-based Reform of Physical Education Teacher Education

ABSTRACTResearch suggests that progress in the physical education profession is slowed by a cycle of nonteaching and dominance of traditional methodologies. Socialization factors operate to preserve and perpetuate the status quo of the profession, which is rooted primarily in team sport content. Teacher education programs are challenged to persuade pre-service teachers to question their initial belief structures while also preparing them for the sociopolitical realities of schools. There is not, however, a formal mechanism through which to accomplish these goals, because current accreditation standards do not include an emphasis on socialization. As a result, the purpose of this article is to stimulate further discussion by reviewing relevant research related to socialization, describe evidence-based practices for overcoming these challenges, and propose an addition to the Society of Health and Physical Educators America (2017) standards for initial physical education teacher education to specifically focus attention on socialization issues.

Poor metacognitive awareness of belief change.

When people change beliefs as a result of reading a text, are they aware of these changes? This question was examined for beliefs about spanking as an effective means of discipline. In two experiments, subjects reported beliefs about spanking effectiveness during a prescreening session. In a subsequent experimental session, subjects read a one-sided text that advocated a belief consistent or inconsistent position on the topic. After reading, subjects reported their current beliefs and attempted to recollect their initial beliefs. Subjects reading a belief inconsistent text were more likely to change their beliefs than those who read a belief consistent text. Recollections of initial beliefs tended to be biased in the direction of subjects' current beliefs. In addition, the relationship between the belief consistency of the text read and accuracy of belief recollections was mediated by belief change. This belief memory bias was independent of on-line text processing and comprehension measures, and indicates poor metacognitive awareness of belief change.

A Flexible Bridge Rating Method Based on Analytical Evidential Reasoning and Monte Carlo Simulation

Several bridge inspection standards and condition assessment practices have been developed around the globe. Some practices employ four linguistic expressions to rate bridge elements while other practices use five or six, or adopt numerical ratings such as 1 to 9. This research introduces a condition rating method that can operate under different condition assessment practices and account for uncertainties in condition assessment by means of the Evidential Reasoning (ER) theory. The method offers flexibility in terms of using default elements and their weights or selecting alternative set of elements and condition rating schemes. The implemented ER approach accounts for uncertainties in condition rating by treating the condition assessments as probabilistic grades rather than numerical values. The ER approach requires the assignment of initial basic beliefs or probabilities, and typically these initial beliefs are assigned by an expert. Alternatively, this research integrates the Monte Carlo Simulation (MCS) technique with the ER theory to quantitatively estimate the basic probabilities and to produce robust overall bridge condition ratings. The proposed method is novel to the literature and has the following features: (1) flexible and can be used with any number of bridge elements and any standard of condition grades; (2) intuitive and simple paired comparison technique is implemented to evaluate weights of the bridge elements; (3) the MCS technique is integrated with the ER approach to quantify uncertainties associated with the stochastic nature of the bridge deterioration process; (4) the method can function with limited data and can incorporate new evidence to update the condition rating; (5) the final rating consists of multiple condition grades and is produced as a distributed probabilistic assessment reflecting the condition of the bridge elements collectively. The proposed method is illustrated with a real case study, and potential future research work is identified.

Knowing-it-all but still learning: Perceptions of one's own knowledge and belief revision.

Lay theories suggest that people who are overconfident in their knowledge are less likely to revise that knowledge when someone else offers an alternative belief. Similarly, one might assume that people who are willing to revise their beliefs might not be very confident in their knowledge to begin with. Two studies with children ages 4-11 years old and college students call these lay theories into question. We found that young children were simultaneously more overconfident in their knowledge (e.g., believing they knew what chartreuse meant) and more likely to revise their initial beliefs (e.g., choosing another color after seeing a peer choose a different color) than older children and adults. These results bridge the metacognitive and epistemic trust literatures, which have largely progressed independently from each other. We discuss the potential causes and functions of the dissociation between the confidence with which beliefs are held and the revision of those beliefs across development. (PsycINFO Database Record

Individual’s Resistance Regarding BPM Initiative: Case Study of the Insurance Company

Abstract Though the individual’s resistance is very often considered a significant barrier to BPM success, the literature on that topic is quite scarce. With the aim to shed light on this topic, we have conducted research of a Croatian insurance company. We examined the impact of individual’s resistance regarding BPM initiative using the theory of reasoned action. Structural equation model was developed using the data collected by the survey among company employees. The results indicate that subjective norms are positively related to the individual’s resistance regarding BPM initiative, while positive initial belief regarding BPM initiative tends to decrease the probability of resistance to change.

Escenarios Electorales para México 2006: el Juego de Simón

<p>A partir del enfoque de la elección racional, este trabajo analiza el papel que juegan las empresas en los procesos electorales. Desde el plano teórico, encuentra que los repetidos ciclos de encuestas tenderán a llevar a los electores a un “equilibrio duvergiano”, guiándolos a coordinarse a partir de sus creencias iniciales, con evidencia empírica, muestra cómo este efecto se da realmente durante el proceso de elección presidencial en México de 2000, y sugiere posibles escenarios para la disputa del Ejecutivo Federal en 2006.</p>

Language complexity, belief-consistency, and the evaluation of policies

ABSTRACTPolicy proposals often contain complex legal, technical, or scientific jargon, making it difficult for people to evaluate their favorability toward the policy. We proposed one experiment testing the effect of language complexity on people’s evaluation of a policy proposal as moderated by their initial policy beliefs. We hypothesized that when a policy was consistent with one’s beliefs or if participants had no policy preference, they would evaluate it more favorably when it was simple than when it was complex; when a policy was inconsistent with one’s beliefs, they would evaluate it less unfavorably when it was complex than when it was simple. Results confirmed our hypotheses. This demonstrates that complex information does not always make people judge policies more negatively but rather cause people to weigh complex information less heavily in their judgments.

Health information and consumer learning in the bottled water market

This paper examines the impact of health information in different media outlets on bottled water consumption through consumer learning. We develop a random coefficient discrete choice model with Bayesian learning process to capture consumers’ learning of health information and changes in their beverage choices over time. Consumers are assumed to have initial prior beliefs about the health effect of different beverages and to update their beliefs using health information received from different media types. Empirical results show that consumers’ perceived quality of bottled water kept increasing during our sample period, and this learning process accounted for 24.44% of the industry’s revenue, which is about 4.8 billion dollars per year. Comparing the effectiveness of different media outlets, we find that the sales impact of traditional media (TV and radio) is greater than online sources. Our findings highlight the contribution of health information to the bottled water industry and provide policy makers with a new direction to reduce high-calorie food consumption and improve public health.

Organizational Learning Supported by Machine Learning Models Coupled with General Explanation Methods: A Case of B2B Sales Forecasting

AbstractBackground and Purpose:The process of business to business (B2B) sales forecasting is a complex decision-making process. There are many approaches to support this process, but mainly it is still based on the subjective judgment of a decision-maker. The problem of B2B sales forecasting can be modeled as a classification problem. However, top performing machine learning (ML) models are black boxes and do not support transparent reasoning. The purpose of this research is to develop an organizational model using ML model coupled with general explanation methods. The goal is to support the decision-maker in the process of B2B sales forecasting.Design/Methodology/Approach:Participatory approach of action design research was used to promote acceptance of the model among users. ML model was built following CRISP-DM methodology and utilizes R software environment.Results:ML model was developed in several design cycles involving users. It was evaluated in the company for several months. Results suggest that based on the explanations of the ML model predictions the users’ forecasts improved. Furthermore, when the users embrace the proposed ML model and its explanations, they change their initial beliefs, make more accurate B2B sales predictions and detect other features of the process, not included in the ML model.Conclusions:The proposed model promotes understanding, foster debate and validation of existing beliefs, and thus contributes to single and double-loop learning. Active participation of the users in the process of development, validation, and implementation has shown to be beneficial in creating trust and promotes acceptance in practice.

First-Year Students' Initial Motivational Beliefs at University: Predicted by Motivational Beliefs Derived from Within and Out-of-School Experience and Malleable Regardless of the Extent of Students' Out-of-School Experience.

The present study tested how academic self-concept of ability (ASC) and intrinsic task value (ITV) transpose onto novel university programs that depart from traditional subject areas within the framework of expectancy-value theory. The study focused on two potential sources of information used to anticipate one’s ASC and ITV regarding new learning content (here: business administration). First, students’ experiences from secondary school, especially their ASCs and ITVs established in a school subject they consider similar to business administration—mathematics—should predict their business administration-specific ASC and ITV. Second, students may have gained relevant experience in out-of-school settings such as internships with business companies or commercial vocational training prior to entering higher education. ASC and ITV developed from out-of-school experiences was hypothesized to predict students’ business administration-specific ASC and ITV as well. However, the likely mismatch between anticipated and actual experience with new contents should lead to revisions of ASC and ITV after entering university reflected in a presumably lower stability compared to secondary school settings. In addition, the extent of students’ out-of-school experience might act as a moderator. Data were collected from 341 first-year students in higher education in Germany before they began their study program and again 3–4 months later. Confirmatory factor analyses support the discriminant validity of the measures used in the study. Results from structural equation modeling show that students’ ASC/ITV derived from relevant out-of-school experience make an important contribution to their initial business administration-specific ASC and ITV beyond their mathematics-specific ASC/ITV. Furthermore, both business administration-specific ASC and ITV showed significantly lower stability coefficients over the initial study phase than research from secondary school indicating revisions to them via experience. Multiple-group structural equation modeling showed no moderating effect of the extent of students’ out-of-school experience. The discussion focuses on interpretations of the expectancy-value theory that explicitly include motivational beliefs derived from out-of-school settings as antecedents of expectancy and value. With respect to practical implications, results are discussed in the light of student counseling and support to help students develop an adequate picture of a study program’s learning contents and overcome initial motivational setbacks.

Integration of individual and social information for decision-making in groups of different sizes.

When making judgments in a group, individuals often revise their initial beliefs about the best judgment to make given what others believe. Despite the ubiquity of this phenomenon, we know little about how the brain updates beliefs when integrating personal judgments (individual information) with those of others (social information). Here, we investigated the neurocomputational mechanisms of how we adapt our judgments to those made by groups of different sizes, in the context of jury decisions for a criminal. By testing different theoretical models, we showed that a social Bayesian inference model captured changes in judgments better than 2 other models. Our results showed that participants updated their beliefs by appropriately weighting individual and social sources of information according to their respective credibility. When investigating 2 fundamental computations of Bayesian inference, belief updates and credibility estimates of social information, we found that the dorsal anterior cingulate cortex (dACC) computed the level of belief updates, while the bilateral frontopolar cortex (FPC) was more engaged in individuals who assigned a greater credibility to the judgments of a larger group. Moreover, increased functional connectivity between these 2 brain regions reflected a greater influence of group size on the relative credibility of social information. These results provide a mechanistic understanding of the computational roles of the FPC-dACC network in steering judgment adaptation to a group’s opinion. Taken together, these findings provide a computational account of how the human brain integrates individual and social information for decision-making in groups.