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Faculty members and their corresponding academic fields at the University of Puerto Rico at Bayamón are classified with regard to grading practices over time. Based on the effects on the intercept of the equations that predict the GPA and the proportion of student withdrawals observed in each of the 39,337 courses offered during 41 consecutive terms, faculty members and academic fields are scaled from the easiest to the most difficult. Evidence points to the conclusion that the courses of the most difficult academic fields are offered primarily by the hardest grading faculty members and attended by the most academically able students, while the courses of the easiest academic fields are offered primarily by the easiest grading faculty members and attended by less academically able students. The conclusion of such self-sorting processes is reinforced by evidence from maximum likelihood models demonstrating that the probability that a randomly selected faculty member behaves like a high-grader or a low-grader is highly and significantly related to the cluster of academic fields to which the faculty member belongs. Such a probability is also strongly and significantly influenced by the heterogeneity of student academic ability distribution. Hence, faculty members are very responsive to signals sent by their students' characteristics. This empirical result deserves further detailed analysis given that it implies a scenario in which faculty members and students engage in a shopping-around process in which both parties free-ride from each other, altering institutional norms and academic standards.

Deregulation of for-profit colleges led to a precipitous rise in enrollments from 1990 to 2010. Since 2010, regulation, investigations, and sanctions have led to enrollment declines in for-profit postsecondary institutions. Initially barred from receiving Title IV federal funds, in the form of Pell Grants and Stafford Loans, for-profit colleges gained access to Title IV funds in 1972 on the grounds that these institutions were educationally equivalent to, or more economical than public and non-profit institutions. This paper examines Beginning Postsecondary Student longitudinal data from 2012/17, utilizing regression analyses to determine whether the for-profit college sector produces similar educational outcomes and student loan debt compared to the public higher education sector. Findings indicate that degree-seeking students enrolling in 2-year programs at for-profit colleges have approximately half the odds of degree attainment as demographically similar students at public colleges; students entering 4-year, for-profit programs have approximately a quarter the odds of achieving a bachelor's degree as their public college counterparts. Students at for-profit colleges, moreover, take on significantly greater student loan debt than demographically similar students at public colleges. Federal funds might better be spent subsidizing under-funded, overcrowded public colleges than enabling America's most disadvantaged students to incur debt at for-profit colleges that are neither educationally nor economically equivalent.

Organizational change is a phenomenon that must be faced and carried out by every individual in the organization to achieve organizational goals. Embodiments of organizational change often occur not because it suits the needs of the organization but because of personal interests and power. This study aimed to determine the main factors that can create change, namely the relationship of leadership and political pressure of school principals that influence organizational change in the Public Secondary School in Madura, East Java, Indonesia. This research used a quantitative approach to survey methods. Based on the achievement of its objectives, this study included causal explanation research, the analysis of this study using Structural Equation Modeling (SEM) and a sample of about 650 people collected from 1000 respondents taken from 130 schools through probability sampling techniques using AMOS software. The results showed that the leadership and political pressure of regional heads were the main factors of organizational change at SMPN (Public Secondary School) in Madura, East Java. Organizational Change depends very much on the role of the political pressure of the regional head through education policy, as well as the role of the principal's leadership in running the wheels of the organization so that the school's goals can be achieved. This study also showed that the principal's leadership as an intermediary variable from political pressure shows no influence because the political pressure of the regional head is directly related to organizational change.

Computer programming MOOCs attract people who have different motivations. Previous studies have hypothesized that the motivation declared before starting the course can be an important predictor of distinctive dropout rates. The aim of this study was to outline the main motivation clusters of participants in a computer programming MOOC, and to compare how these clusters differed in terms of intention to complete and actual completion rate. The sample consisted of 1,181 respondents to the pre-course questionnaire in the "Introduction to Programming" MOOC. A validated motivation scale, based on expectancy-value theory and k-means cluster analysis, was used to form the groups. The four identified clusters were named as Opportunity motivated (27.7%), Over-motivated (28.6%), Success motivated (19.6%) and Interest motivated (24.0%). Comparison tests and chi-square test were used to describe the differences among the clusters. There were statistically significant differences among clusters in self-evaluated probability of completion. Also, significant differences emerged among three clusters in terms of percentages of respondents who completed the MOOC. Interestingly, the completion rate was the lowest in the Over-motivated cluster. A statistically significant higher ratio of completers to non-completers was found in the Opportunity motivated, Success motivated, and Interest motivated clusters. Our findings can be useful for MOOC instructors, as a better vision of participants' motivational profiles at the beginning of the MOOC might help to inform the MOOC design to better support different needs, potentially resulting in lower dropout rates.

In this study, it was aimed to reveal the opinions of mathematics teacher candidates about the use of the GeoGebra program, which is dynamic geometry software, in the teaching of probability, which is among the concepts that we generally use in the decision-making process in uncertain situations that we encounter in the teaching process by teachers and students. Within the scope of this purpose, a total of 65 elementary mathematics teacher candidates, who have taken statistics and probability courses at a state university, were given GeoGebra training for 4 weeks and made applications. After the training, a semi-structured opinion questionnaire consisting of 5 questions developed by the researchers was applied to the pre-service teachers. Besides, each participant was interviewed. The study is a case study, and the content analysis method was used in the analysis of the data. It has been determined that it is difficult to write equations in the subject of probability processed through GeoGebra and although it provides result-oriented solutions, it provides good and permanent learning in the context of reaching more sample solutions in a short time, it provides a pleasant, non-monotonous and interesting lesson opportunity by concretizing the subject. Also, it was concluded that dynamic elements provide permanence, but there may be difficulties in applications due to the lack of knowledge of computer use by teachers and students.

Epidemics and pandemics are difficult periods for the affected community, specifically in the proliferation of mental health issues. In such adverse times, factors of psychological vulnerability such as propensity to worry and low emotional stability might have a detrimental effect on the mental health of the individuals. To investigate the impact of such factors on mental health, this study examined the impacts of propensity to worry and fear of COVID-19 on anxiety depending on the individuals' levels of emotional stability. As a means of such investigation, this study was conducted based on quantitative data, and the research sample was selected using a convenient sampling method. Participants included 304 university students (71.6% were women and 28.4% were men; M[subscript Age] = 22.37 ± 3.04) and responded to the Penn State Worry Questionnaire, Fear of COVID-19 Scale, Symptom Checklist-90 Revised, and 10-Item Personality Inventory. The moderated mediation analysis using PROCESS macro (Model 14) was performed to examine the study hypotheses. Results revealed that propensity to worry was associated with anxiety symptoms. Fear of COVID-19 mediated this link and emotional stability moderated the relationship between propensity to worry and anxiety. The findings showed that trait worry, trait emotional stability, and fear of COVID-19 are determinants of anxiety symptoms, suggesting that such factors are important in understanding these issues.

Learning about probability can pose difficulties for students at all levels. Performing probability experiments using games can encourage students to develop understandings of probability grounded in real events. In this reflective paper, we explore the thinking of a group of students and teachers as they reasoned about experimental and theoretical probabilities in a game context. We designed a probability lesson based on the game LuLu (McCoy et al., 2007). In this article we share the activity and describe the kinds of explorations that can be facilitated in any secondary school mathematics classroom. We were particularly interested in investigating whether students could construct a bidirectional link between experimental probability and theoretical probability. Overall, the lesson enabled students to gain hands-on experience in data collection and analysis and better comprehend affordances of culturally diverse games.

Contrary to the overall tendency to increase student participation in the financing of higher education, Estonia abolished student tuition fees in 2013. We study the effects of this reform on the students' access to and progress in higher education, concentrating mostly on the changes in probabilities of rural and remote students being admitted (extensive margin) and graduating within a nominal time (intensive margin). We distinguish between four different outcomes: admission in general, admission to vocational education, admission to high-rank curricula, and graduation within nominal time. We confirm the tendency that a high socioeconomic status increases the probability of being admitted to high-rank curricula and reduces the probability of choosing an applied curriculum, and the 2013 reform did not change that. While the reform weakly improved rural students' tendency to graduate on time, it diminished the probability that they were admitted to high-rank curricula. So, paradoxically and contrary to the intention of the reform, higher state involvement in higher education financing has not improved the equity in university admission in Estonia in terms of either socioeconomic background or regional disparities. We claim that part of the explanation of that paradox lies in the conditionality of this reform and the combination of a scarce needs-based and a competitive merit-based student support system in Estonia. We see our broader contribution in emphasising the important role of support systems in the future analysis of the potential to improve students' access.

There is increasing attention on the retention of international students, with many stakeholders desiring to keep international students for long-term economic growth. This study examined the factors affecting international students choosing to stay in Finland 5 years after initial enrollment, with particular focus on the role graduation plays in students staying or leaving. Tracking 11 years of entering cohorts for 5 years across national (Finland) data registries, we found evidence of an inverse relationship between graduation, degree type, and the probability of staying: The higher the degree level, the less likely an international student is to stay after graduation. We conclude that while graduation is a key metric and discussion point in national and institutional policy, our findings suggest focusing on improving international students' ability to integrate into a host country's labor market and promotion of an environment conducive for international students' families, more than graduation, would produce higher stay rates of international students.

Propensity score methods account for selection bias in observational studies. However, the consistency of the propensity score estimators strongly depends on a correct specification of the propensity score model. Logistic regression and, with increasing popularity, machine learning tools are used to estimate propensity scores. We introduce a stacked generalization ensemble learning approach to improve propensity score estimation by fitting a meta learner on the predictions of a suitable set of diverse base learners. We perform a comprehensive Monte Carlo simulation study, implementing a broad range of scenarios that mimic characteristics of typical data sets in educational studies. The population average treatment effect is estimated using the propensity score in Inverse Probability of Treatment Weighting. Our proposed stacked ensembles, especially using gradient boosting machines as a meta learner trained on a set of 12 base learner predictions, led to superior reduction of bias compared to the current state-of-the-art in propensity score estimation. Further, our simulations imply that commonly used balance measures (averaged standardized absolute mean differences) might be misleading as propensity score model selection criteria. We apply our proposed model -- which we call GBM-Stack -- to assess the population average treatment effect of a Supplemental Instruction (SI) program in an introductory psychology (PSY 101) course at San Diego State University. Our analysis provides evidence that moving the whole population to SI attendance would on average lead to 1.69 times higher odds to pass the PSY 101 class compared to not offering SI, with a 95% bootstrap confidence interval of (1.31, 2.20).

Transition metrics, which quantify the propensity for one event to follow another, are often utilized to study sequential patterns of behaviors, emotions, actions, and other states. However, little is known about the conditions in which application of transition metrics is appropriate. We report on two experiments in which we simulated sequences of states to explore the properties of common transition metrics (conditional probability, D'Mello's "L," lag sequential analysis, and Yule's "Q") where results should be null (i.e., random sequences). In experiment 1, we found that transition metrics produced statistically significant results with non-null effect sizes (e.g., "Q" > 0.2) when sequences of states were short. In experiment 2, we explored situations where consecutively repeated states (i.e., loops, or self-transitions) are impossible -- e.g., in digital learning environments where actions such as hint requests cannot be made twice in a row. We found that impossible loops affected all transition metrics (e.g., "Q" = 0.646). Based on simulations, we recommend sequences of length 50 or more for transition metric analyses. Our software for calculating transition metrics and running simulated experiments is publicly available.

The COVID-19 pandemic generated a new scenario in education, where technological resources mediate teaching and learning processes. This paper presents the development of a virtual teacher training experience aimed at promoting inferential reasoning in practicing and prospective mathematics teachers using inference problems on the Chi-square statistic. The objective of this article is to assess the implemented or intended institutional meanings and the degree of availability and adequacy of the material and temporal resources necessary for the development of the training experience. For this purpose, we use theoretical and methodological notions introduced by the Ontosemiotic Approach to Mathematical Knowledge and Instruction (OSA), among which are the notions of practice and suitability criteria. The participants of this experience were divided into three groups; one of them was comprised of practicing teachers and the other two of prospective teachers. The intervention used different virtual modalities that enabled the development of the participants' inferential reasoning in a similar way.

Education expansion has prompted an extensive body of literature on the issue of overeducation, particularly in developed countries. However, as is the case for many developing countries, little, if any, empirical evidence from Saudi Arabia has emerged on this topic. Using cross-sectional survey data, this study examined the prevalence and possible determinants of overeducation among Saudi graduates in the labour market on the basis of two different self-assessment measures. Results indicated that nearly 50% of Saudi graduates in the study were considered overeducated based on each measure, while about 41% were consistently considered overeducated based on both measures. Using logistic regression models, several individual and job characteristics were deemed as major determinants of the probability of being overeducated across both measures. Furthermore, the two measures largely overlapped and yielded somewhat similar conclusions in terms of both the estimates and determinants of overeducation among graduates. The plausible implications of the results for education and labour market policies are discussed.

Studies revealed that college readiness promotes college success and higher education student learning outcomes. This study opted to 1) analyze the total effect and the conditional effect of college readiness on college success by university generations and departments; 2) analyze the differences in the probability of college success across departments and university generations; 3) describe the quality of university generations in terms of the conditional effects and the probabilities of college success. The study is an ex post facto research. The Ethiopian 1st, 2nd, and 3rd generation universities; and the National Educational Assessments and Evaluations Agency officers were the population of the study. The total sample size was 551. The Ethiopian General Education School Leaving Certificate Examination Grade Point Average, the Ethiopian Higher Education Entrance Examination score, and the College Cumulative Grade Point Average of the students were sources of the data. Using the Process Procedure for Software Package for Social Sciences, the binomial logistic regression was conducted. Maintaining the highest total conditional effect of college readiness on college success while heightening the probability of college success at a value of college readiness has been interpreted as a trait of the high performing university generation.

Evaluating the effects of the Coronavirus (COVID-19) pandemic on distance education applications in higher education is important for future practice. In this context, the aim of the study is to determine preservice mathematics teachers' conceptual-procedural knowledge level competencies and general thoughts about distance education in the distance education probability course in the department of mathematics teaching. In the study, a questionnaire consisting of 18 questions was prepared in the light of the literature as a data collection tool for 52 preservice mathematics teachers who took the probability course with distance education in the 2020-2021 academic year. After the implementations, one-to-one interviews were made with the lecturer conducting the course. The data of the study were analysed with the descriptive analysis method. As a result, it was determined that the conceptual-operative knowledge of the preservice mathematics teachers in the probability course in the distance education process was at a medium level. Although it was determined that the participation in online lessons was quite low compared to the lessons taught face-to-face, the preservice teachers mostly followed the lessons from asynchronous recordings, but there was no low performance or unwillingness in the preservice teachers who attended the lessons online. It has been determined that the biggest problem with distance education is the internet access and the low reliability of evaluation process. To increase the reliability, it has been determined that the transition to camera-controlled exams and the use of the safe exam browser (SEB) have been introduced.

The objective of this development research is to create an android application of probability theory of the same element permutation material based on RME as a learning medium, as well as to assess the quality of the apps created for utilize in learning mathematics. This research used research and development (R&D) method with the 4D development paradigm. There are four steps to the process: define, design, develop, and disseminate. The information analysis approach utilized is a media achievability test conducted by media specialist and material specialists, and a media quality test was conducted by students as responders. The feasibility test results show that the android application of the probability theory of the same element permutation material based on RME is feasible with good criteria, based on an assessment of 87.50 percent by media specialist and an assessment of 84.93 percent by two material specialists. The results of media quality test of 60 students from partner schools showed good criteria, based on an assessment of 80.20 percent by students as responders. The data from the tests suggest that the android application of the probability theory of the same element permutation material based on RME is possible to use as a source of mathematics learning.

Educational assessment tests are designed to measure the same psychological constructs over extended periods. This feature is important considering that test results are often used for admittance to university programs. To ensure fair assessments, especially for those whose results weigh heavily in selection decisions, it is necessary to collect evidence demonstrating that the assessments are not biased and to confirm that the scores obtained from different test forms have statistical equality. Therefore, test equating has important functions as it prevents bias generated by differences in the difficulty levels of different test forms, allows the scores obtained from different test forms to be reported on the same scale, and ensures that the reported scores communicate the same meaning. In this study, these important functions were evaluated using real college admission test data from different test administrations. The kernel equating method under the non-equivalent groups with covariates design was applied to determine whether the scores that were obtained from different periods and measured the same psychological constructs were statistically equivalent. The non-equivalent groups with covariates design was specifically used because the test groups of the admission test are non-equivalent and there are no anchor items. Results from the analyses showed that the test forms had different score distributions and that the relationship was non-linear. Thus, the equating procedure was adjusted to eliminate these differences and thereby allowing the tests to be used interchangeably.

Interpreting phenomena under uncertainty stands as a substantial cognitive activity in our daily life. Furthermore, in probability education research, there is a need for developing a unified model that involves several probabilistic conceptions. From this aspect, a central inquiry has been raised through this study: how do preservice mathematics teachers (PSMTs) reason under uncertainty? A multiple case study design was operated in which a purposive sample of PSMTs was selected to justify their reasoning in two probabilistic contexts while their responses were coded by NVivo, and corresponding categories were developed. As a result, PSMTs' probabilistic reasoning was classified into mathematical (M), subjective (S), and outcome-oriented (O). Besides, several biases emerged along with these modes of reasoning. While M thinkers shared equiprobability and insensitivity to prior probability, the prediction bias and the belief of Allah's willingness were yielded among S thinkers. Also, the causal conception spread among O thinkers.

This study builds on previous research investigating management organizations (MOs), charter school locations, and closure by examining the effects of MO type (EMO, CMO and freestanding schools), racial enrollment, student achievement, and the community characteristics surrounding each charter school in Ohio's eight largest counties with the largest urban school districts on the likelihood of closure between 2009 and 2018. We conducted a discrete-time survival analysis using life tables and binary logistic regression. Findings indicated that freestanding charter schools experience higher risks of closure than EMO and CMO managed charter schools in those counties. Although they are more likely to close, freestanding schools have higher student achievement in math and reading. Higher math proficiency reduces the likelihood of closure by 2.8%. However, community and enrollment characteristics are not statistically significant predictors of closure.

This research is aimed to describe a learning trajectory for probability through game-based learning. The research employed design research consisting of three stages: preparing for the experiment, design experiment, and retrospective analysis. A hypothetical learning trajectory (HLT) using Sudoku and Snake-and-ladder games was developed by collecting data through documentation, interviews, and classroom observations. The HLT was implemented in the classroom to investigate students' actual learning trajectory. The results of this research indicate that the games helped students understand the concept of probability. The learning trajectory for probability based on game-based learning is seen from the perspective of four levels of emergent modeling. In the first level -- 'situational level' -- Sudoku and Ladder-and-Snake games were played by students. The second level is the 'referential level' where the rules of the games were used as a starting point to learn the concept of probability. Communication during game playing stimulated students' knowledge about random events, sample spaces, sample points, and events. At the third level -- 'general level' -- students used tree and table diagrams to generalize possible outcomes of an experiment and develop an understanding of sample spaces and sample points. Lastly, at the 'formal level' students developed their informal knowledge into formal concepts of probabilities.

Using data from two Toronto student cohorts that entered high school five years apart, this study uses descriptive and multivariate techniques to examine short-term change in the predictors of four possible pathways after high school: confirming a place in university, confirming a place in college, applying but no admittance, or not applying at all. From a comparative cohort perspective, the analysis considers various overlapping ascriptive and school experience factors that contribute to unequal transitions--from race, gender, and immigration background to early achievement, attendance, and suspensions. Even across a short time period, there is change in transition patterns. The results highlight that a comparative cohort approach provides insight into how the transition to post-secondary education in an urban environment changes even over relatively short periods of time.

There is limited research available that examines students with disabilities' participation rates and perceptions of Work-Integrated Learning (WIL) while in post-secondary. This is problematic as universities in Canada are growing their WIL programs to improve school to work transition rates. This research finds that 23% of students who are registered with the Disability Services Office for academic accommodations have engaged in WIL. For those who have not engaged in WIL, almost 50% strongly or somewhat agreed that their disability was a factor. Furthermore, students with mental health disorders are 3.3 times less likely to have had a WIL experience. Participation in WIL increases students with disabilities' probability of reporting more positively that they understand the accommodations they may need in WIL. However, only 17% of students with disabilities in a cooperative education program reported requesting accommodations in a co-op work term.

The concept of probability is an important concept to learn in school. That is why teachers and preservice teachers should learn how to teach this concept effectively. It is important and necessary to know the attitudes of teachers towards the subject of and the teaching of probability. For this reason, a scale related to the attitudes towards probability and probability teaching is adapted in this study. A quantitative research model was adopted as the research method, and data was collected from 265 prospective elementary mathematics teachers of different grade levels. After language translation of the scale items, necessary statistical analysis was conducted for the adaptation process. At the end of the study, a seven-factor scale with 27 items was obtained. There were four items in all dimensions, as in the original scale, but only three items in the behavioral component towards the teaching of probability dimension remained after the adaptation process.

Many problems in real life are full of uncertainty. Probabilistic thinking is one way to solve this uncertainty problem. The personality abilities that are interesting to examine include how independent the students are in facing probabilistic solutions. For this reason, it is necessary to study the probabilistic thinking profile of prospective mathematics teachers in solving probabilistic problems in terms of learning the self-regulation. The research method used in this research is qualitative research. In this study, the researcher conducted an analysis of students' probabilistic thinking with the scope of the probability material related to the sample space, the probability of events, and the probability of the random variable space. The profile of the level of probabilistic thinking is influenced by cognitive factors in the form of probabilistic knowledge obtained by students and personality in the form of self-regulated learning. Student learning self-regulated influences the mental activity in decision making. By studying the profile of probabilistic thinking, students are better prepare to face uncertainty with various aspects that influence it.

Although Goodman-Kruskal gamma (G) is used relatively rarely it has promising potential as a coefficient of association in educational settings. Characteristics of G are studied in three sub-studies related to educational measurement settings. G appears to be unexpectedly appealing as an estimator of association between an item and a score because it strictly indicates the probability to get a correct answer in the test item given the score, and it accurately produces perfect latent association irrespective of distributions, degrees of freedom, number of tied pairs and tied values in the variables, or the difficulty levels in the items. However, it underestimates the association in an obvious manner when the number of categories in the item is more than four. Towards this, a dimension-corrected G (G2) is proposed and its characteristics are studied. Both G and G2 appear to be promising alternatives in measurement modelling settings, G with binary items and G2 with binary, polytomous and mixed datasets.

While school choice has been well studied, there is little existing research exploring the role of transportation, in general, and school buses, in particular, to school choice decisions. We examine the effect of school buses on school choice decisions using data on kindergarten students and their eligibility for transportation assistance in New York City public schools in 2017. Using both conditional logit school choice models and regression discontinuity designs, we provide both descriptive and credibly causal evidence on the impact of school proximity, bus eligibility, and their interaction on school choice decisions. Our results indicate that proximity and buses both matter. Specifically, while distance significantly deters choice, school bus eligibility increases the likelihood of choosing a school by 1.4-4 percentage points (or 12-30 percent). Compared to a high-quality school, we find that bus eligibility has twice as large an impact on reducing the negative distance effect in the 0.5 to 1 mile range from school (27 versus 12 percent). These results will be useful for policy makers looking to leverage school transportation policy to improve school choice decisions, and ultimately student outcomes.

Data science has maintained its popularity for about 20 years. This study adopts a bottom-up approach to understand what data science is by analyzing the descriptions of courses offered by the data science programs in the United States. Through topic modeling, 14 topics are identified from the current curricula of 56 data science programs. These topics reiterate that data science is at the intersection of statistics, computer science, and substantive fields.

The study determined the problem-solving performance and skills of prospective elementary teachers (PETs) in the Northern Philippines. Specifically, it defined the PETs' level of problem-solving performance in number sense, measurement, geometry, algebra, and probability; significant predictors of their problem-solving performance in terms of sex, socio-economic status, parents' educational attainment, high school graduated from, and subject preference; and their problem-solving skills. The PETs' problem-solving performance was determined by a problem set consisting of word problems with number sense, measurement, geometry, algebra, and probability. A mixed-method research design was employed. Senior PETs purposively served as a sample where they mostly preferred to teach other subjects than mathematics. PETs who preferred math performed satisfactorily, while prospective teachers who opted for other subjects performed unsatisfactorily. The PETs' unsatisfactory output indicates the need for remediation to advance the mathematical material skills and enrich the problem-solving abilities of these primary schools' potential teachers. Besides, results showed that subject preference strongly affected and predicted the problem-solving success of the PETs. PETs who preferred to teach mathematics performed significantly better than their counterparts; hence, mathematics as a field of specialization in the Bachelor of Elementary Education program may be considered by teacher education institutions. Further, most PETs displayed lack of problem-solving skills; thus, a Problem-Solving course is recommended for them.

This study aimed to test the reliability of the Perceived Severity and Response to Bullies and Victims of Bullying Questionnaire (PSRBVBQ) for middle school teachers (N=322 teachers), using exploratory factor analysis and reliability analysis. PSRBVBQ assesses teachers' responses to bullying using situational scenarios. It includes two vignettes for each type of bullying (physical, verbal and relational) to analyze the perceived severity, likelihood of responding to the bully, likelihood of responding to the victim. Exploratory factor analysis indicated a three-factor solution: perceived severity ([alpha] = 0.73), the likelihood of responding to the bully ([alpha] = 0.84), the likelihood of responding to the victim ([alpha] = 0.89). These results indicate a good internal consistency of the items in each scale, especially for the likelihood of responding to the victim and for the likelihood of responding to the bully scales. The results show that the PSRBVBQ has good psychometric properties and can be successfully used in research regarding Romanian teachers' perceptions and their response to bullying. Also, more than one-third of teachers perceive verbal aggression as serious, while much less perceive relational aggression as very serious. At the same time, we found that the perceived severity predicts the probability of the teacher's reaction to the incidents of aggression.