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Situational judgment tests (SJTs) are personnel selection instruments that present job applicants with work‐related situations and possible responses to the situations. There are typically 2 types of instructions: behavioral tendency and knowledge. Behavioral tendency instructions ask respondents to identify how they would likely behave in a given situation. Knowledge instructions ask respondents to evaluate the effectiveness of possible responses to a given situation. Results showed that response instructions influenced the constructs measured by the tests. Tests with knowledge instructions had higher correlations with cognitive ability. Tests with behavioral tendency instructions showed higher correlations with personality constructs. Results also showed that response instructions had little moderating effect on criterion‐related validity. Supplemental analyses showed that the moderating effect of response instructions on construct validity was not due to systematic differences in item content. SJTs have incremental validity over cognitive ability, the Big 5, and over a composite of cognitive ability and the Big 5.

Background Good technical skills are crucial for surgeons. Yet although surgical training programs strive to assess technical aptitude when selecting surgical residents, valid assessments of such aptitude are still lacking. Surgical simulators have been proposed as a potentially effective tool for this purpose. The current study aims to develop a technical aptitude test using a virtual reality surgical simulator, and to validate its use for the selection of surgical residents. Methods The study had three phases. In Phase 1, we developed an initial version of the technical aptitude test using the Lap-X-VR laparoscopic simulator. In Phases 2 and 3 we refined the test and collected empirical data to evaluate four main sources of validity evidence (content, response process, internal structure, and relationships with other variables), and to evaluate the feasibility and acceptability of the test. Specifically, Phase 2 comprised a review of the test by 30 senior surgeons, and in Phase 3 a revised version of the test was administered to 152 interns to determine its psychometric properties. Results Both the surgeons and interns rated the test as highly relevant for selecting surgical residents. Analyses of the data obtained from the trial administration of the test supported the appropriateness of the score calculation process and showed good psychometric properties, including reliability (α = 0.83) and task discrimination (mean discrimination = 0.5, SD = 0.1). The correlations between test scores and background variables revealed significant correlations with gender, surgical simulator experience, and video game experience ( p s < 0.001). These variables, however, explained together only 10% of the variance in test scores. Conclusions We describe the systematic development of an innovative virtual reality test for assessing technical aptitude in candidates for surgical training, and present evidence for its validity, feasibility and acceptability. Further validation is required to support the application of the test for selection, as well as to discern the impact of gender, surgical simulator experience, and video game experience on the fairness of test results. However, the test appears to be a promising tool that may help training programs assess the suitability of candidates for surgical training.

Success in higher education is associated with both students' capacity for self-regulation and the ability to understand assessment processes. The Assessment Literacy Module (ALM) is an interactive online tool designed to promote development of students' own academic judgement and assessment literacy. Students act as assessors of work samples; they use the assessment rubric and are guided by expert marker feedback that relates the marking standards to the assessment outcome. In this study, we evaluated perceptions of ALM impact on the student learning experience by surveying staff (N = 18) and students (N = 416) involved in 18 undergraduate subjects. Students reported that after completing the ALM they had a better understanding of the assessment criteria (94%); they felt the module helped them prepare for their assessments (90%) and were more confident about their assessment quality (86%). Staff perceptions of the benefits of the ALM closely aligned with those reported by students. We recommend this tool for enhancing assessment literacy and developing academic judgement in undergraduate students of all levels. The ALM is of greatest utility in large cohort subjects as a sustainable approach for providing all students access to expert feedback. Future research will explore how the ALM benefits teaching practices. [Author abstract]

This study examines the phenomena of complex threat syndrome (CTS) in the Sahel from the standpoint of the increasing dysfunctionality of the states in this area. The study posits that the CTS in the Sahel reflects the logic of a conflict-crime-terror conundrum in the context of rising state fragility. The crisis of legitimacy and governability in the Sahel, instantiated by the weaknesses of the states to facilitate governance, security, and development effectively and sustainably, has brought about conditions that exacerbate anti-state militantism and extremism. The inability of governments to demonstrate requisite competencies in the face of these threats bolsters and reproduces widespread criminal indulgence, impunity, and opportunism. Critical indicators of this include rising jihadist insurgencies, banditry, communal conflicts, and other forms of violence. The consequence has been a complex threat situation where violent conflicts and crimes reinforce each other to engender an enduring climate of insecurity and crisis. Mitigating such a complex security scenario requires a deliberate effort by the authorities in the Sahel to optimize statecraft through effective state-building, security governance reforms, and functional state-society synergy.

Work sample tests have been used in applied psychology for decades as important predictors of job performance, and they have been suggested to be among the most valid predictors of job performance. As we examined classic work sample literature, we found the narrative review by Asher and Sciarrino (1974) to be plagued by many methodological problems. Further, it is possible that data used in this study may have influenced the results (e.g., r= .54) reported by Hunter and Hunter in their seminal work in 1984. After integrating all of the relevant data, we found an observed mean correlation between work sample tests and measures of job performance of .26. This value increased to .33 when measures of job performance (e.g., supervisory ratings) were corrected for attenuation. Our results suggest that the level of the validity for work sample tests may not be as large as previously thought (i.e., approximately one third less than previously thought). Further, our work also summarizes the relationship of work sample exams to measures of general cognitive ability. We found that work sample tests were associated with an observed correlation of .32 with tests of general cognitive ability.

Costello wants to continue to build on his introduction to mathematical modeling. First, he will provide a brief overview distinguishing mathematical modeling from traditional problem-solving approaches used in classrooms. Second, he will dive into the four components of mathematical modeling and share an example of student thinking within each component. Using concrete examples of student thinking for each of four components provides an opportunity to demonstrate the finer points of mathematical modeling and highlight how students must take an active, independent stance to their learning.

Costello previously explored the problems assign to students and questioned whether students would find such problems relevant and meaningful. It was during this exploration that he highlighted that often, defined problems are assigned in many classrooms. While there are benefits to defined problems, they must be cognizant to provide students with opportunities to tackle alternative types of problems, problems that are more reflective of the world they live in, and the complexities that are associated with such problems. This is where they started their discussion on ill-defined problems. Ill-defined problems are missing one or more of the three characteristics of a problem (initial state, goal state, stumbling blocks (i.e., what assumptions and restrictions may be required)). Missing one or more of these characteristics removes much of the structure that is found in traditional defined problems. And, without the structure, ill-defined problems are messy and resemble the problems that they tend to encounter in their experiences outside of school. It is through this messiness that they broaden perspective of problem solving to include mathematical modeling.

Work sample exams are generally thought to have either low or comparatively low levels of ethnic group differences when used for personnel selection. Such exams are sometimes called “simulation exercises” and involve having applicants perform a set of tasks that are similar to those performed on the job. The nearly ubiquitous meta‐analytic value of Black–White subgroup differences in the literature is d= .38. Unfortunately, this estimate is plagued by a variety of problems (e.g., range restriction, inclusion of nonwork sample tests). Further, there are virtually no analyses that examine how the saturation of different constructs influence work sample tests. We gathered available data for Black–White ethnic group differences and found that overall work sample differences were markedly larger for samples of job applicants (d= .73) than previously thought. We also examined how different exercises and saturation of different constructs influenced work sample ds. For example, work sample test ratings of cognitive and job knowledge skills were associated with a mean observed d= .80, whereas ratings of various social skills were associated with mean observed ds that varied from .21 to .27. We urge scientists and practitioners to consider both the method and the constructs that are targeted when forecasting predictor ds.

The teacher work sample (TWS) is considered to be an effective method to provide evidence of what preservice teachers know and can do (Ward, 2010). Many teacher education programs use the TWS as a key assessment to provide evidence for meeting the National Council for the Accreditation of Teachers standards. At the unit level, however, the TWS is designed for teachers of all subjects and therefore lacks depth and specificity to address the National Association for Sport and Physical Education (NASPE) Initial Physical Education Teacher Education Standards. Therefore, physical education teacher education (PETE) programs must refine the TWS to meet the NASPE accountability requirements. The purpose of this study was to compare a modified and nonmodified TWS among preservice physical education teachers. Participants were 60 randomly selected preservice physical education teachers from a university located in the Southwestern United States. The TWS used in this study was developed by the Renaissance Group and consisted of the following 7 components: (a) contextual factors, (b) learning objectives, (c) assessment plan, (d) design for instruction, (e) instructional decision making, (f) analysis of student learning, and (g) reflection and selfevaluation. The PETE faculty where the study was conducted made the modifications to the TWS and scoring guide. Modifications and standard alignments were made based on the requirements established by the NASPE 2008 Initial PETE Standards. Thirty preservice teachers completed the modified TWS and 30 completed the nonmodified TWS during their student-teaching experiences. Independent t tests were used to compare the mean scores between the modified and nonmodified TWS for each component of the assessment. In general, preservice teachers who completed the modified TWS exhibited slightly lower mean scores for each component of the assessment compared with those who completed the nonmodified TWS. The t test analysis revealed that preservice teachers who completed the modified TWS scored significantly lower on the instructional decision-making component of the assessment, t(58) = 2.55, p , .05. No significant differences between the modified and nonmodified TWS were found for the rest of the components. These results suggest that the modifications made on the TWS may have made the components of the assessment more specific and thus improved objectivity. Consequently, this would make the assessment better able to distinguish among levels of teacher candidate

Purpose Statistical methods for identifying response shift (RS) at the individual level could be of great practical value in interpreting change in PRO data. Guttman errors (GE) may help to identify discrepancies in respondent's answers to items compared to an expected response pattern and to identify subgroups of patients that are more likely to present response shift. This study explores the benefits of using a GE-based method for RS detection at the subgroup and item levels. Methods The analysis was performed on the SatisQoL study. The number of GE was determined for each individual at each time of measurement (at baseline TO and 6 months after discharge M6). Individuals showing discrepancies (with many GE) were suspected to interpret the items differently from the majority of the sample. Patients having a large number of GE at M6 only and not at TO were assumed to present RS. Patients having a small number of GE at TO and M6 were assumed to present no RS. The Response Shift ALgorithm in Item response theory (ROSALI) was then applied on the whole sample and on both groups. Results Different types of RS (non-uniform recalibration, reprioritization) were more prevalent in the group composed of patients assumed to present RS based on GE. On the opposite, no RS was detected on patients having few GE. Conclusions Guttman errors and item response theory models seem to be relevant tools to discriminate individuals affected by RS from the others at the item level.