We present initial structural validity evidence for a serious game designed for personnel selection and classification for cybersecurity roles in the US Air Force (USAF).Based on literature review and input from USAF cybersecurity subject-matterexperts, we targeted six constructs for assessment. We describe the development process used to build a game to assess individual differences in these constructs, while also being engaging and motivating for players. We attend to the challenge of avoiding an overall game performance factor that dominates variance of multiple constructs scored from the same gameplay episodes and report steps taken to enhance discriminant validity of the scores. We apply factor analysis and item response theory models to develop scores that are reliable, show discriminant validity, and show modest education/gender group differences.
Progress of technology and processing power has enabled the advent of sophisticated technology including Artificial Intelligence (AI) agents. AI agents have penetrated society in many forms including conversation agents or chatbots. As these chatbots have a social component to them, is it critical to evaluate the social aspects of their design and its impact on user outcomes. This study employs Social Determination Theory to examine the effect of the three motivational needs on user interaction outcome variables of a decision-making chatbot. Specifically, this study looks at the influence of relatedness, competency, and autonomy on user satisfaction, engagement, decision efficiency, and decision accuracy. A carefully designed experiment revealed that all three needs are important for user satisfaction and engagement while competency and autonomy is associated with decision accuracy. These findings highlight the importance of considering psychological constructs during AI design. Our findings also offer useful implications for AI designers and organizations that plan on using AI assisted chatbots to improve decision-making efforts.
In the latest salvo in the century-long lexical-dimensionality-reduction debate (Galton, 1884), Ashton and Lee (2020) argue their HEXACO model is superior to Big Five models. We argue that debates comparing alternative low-dimensional personality structures no longer advance personality science or practice. Instead, researchers should embrace the inherent complexity and high dimensionality of human individual differences. If a low-dimensional model is used, investigators should choose a model based on its coherent representation of traits they deem meaningful for the research domain, rather than its alignment with a specific factor analysis solution.
Yarkoni highlights patterns of overgeneralization in psychology research. In this comment, we note that such challenges also pertain to applied psychological and organizational research and practice. We use two examples – cross-cultural generalizability and implicit bias training – to illustrate common practices of overgeneralization from narrow research samples to broader operational populations. We conclude with recommendations for research and practice.
This paper takes an exploratory approach to analyze reactions to game-based assessments (GBAs) by examining users' reviews of GBA mobile applications. In this study, we explore 3146 user reviews and 1253 comments from 10 GBA applications found on the two most popular mobile application distribution platforms using a natural language processing tool. Findings suggest that candidates generally perceive GBAs as novel and have varying reactions to specific game, assessment, and application elements. As this study contributes to the limited body of research available on candidates' reactions to GBA mobile applications, findings and research directions are discussed to expand our understanding of this growing area of assessment.game-based assessment, mobile applications, natural language processing, reactions Practitioner points• Game-based assessment (GBA) mobile applications are generally viewed by applicants as novel and interesting, and as a favorable method of assessment.• However, some users are hesitant to place full trust in GBA mobile applications, perceiving them as less face-valid than traditional assessment methods.• Users also react negatively to technical issues such as mobile application glitches or crashes.• Organizations seeking to use GBA mobile applications in their employee selection system should carefully design the assessment by selecting psychometrically valid and useful game elements, and should also incorporate user-tested feedback. | INTRODUCTIONEmployee selection has experienced several changes over its more than 100-year history (Ryan & Ployhart, 2014). Technology has driven this evolution in many ways and is often considered one of the biggest influences on how we recruit, select, train, and evaluate employees (Tippins, 2015). While validating and assessing employee selection systems is critical, many organizations have been increasingly concerned with the usability of employee selection procedures and applicants' engagement with the process. Applicant reactions are important to employers because of influences on the applicants' perceptions of the organization, validity, and utility of the procedures, influences on the employee selection process, and potential ethical and legal issues (Smither et al., 1993).Recently, game-based assessments (GBAs) have been promoted for use in employee selection as a potential method to improve the user experience (Chamorro-Premuzic et al., 2017). A scan of the literature reveals that research on applicant reactions to GBAs is
Yarkoni (2020) highlights patterns of overgeneralization in psychology research. In this comment, we note that such challenges also pertain to applied psychological and organizational research and prac-tice. We use two examples—cross-cultural generalizability and implicit bias training—to illustrate common practices of overgeneralization from narrow research samples to broader operational popula-tions. We conclude with recommendations for research and practice.
Highway toll accumulation frameworks. It is utilized as a part of India. Some of these comprising Manual toll accumulation, RF labels, Barcodes and Number plate acknowledgment. Every one of these frameworks have inconveniences that prompt a few blunders in the relating framework. This paper exhibits a brief audit of toll gathering frameworks present in India, their points of interest and impediments furthermore expects to outline and add to another proficient toll accumulation framework which will be a decent minimal effort elective among every other framework. This framework in light of Computer Vision vehicle discovery utilizing OpenCV library as a part of Embedded Linux stage. The framework is outlined utilizing Embedded Linux advancement kit(ARM7).In this framework, a camera catches pictures of vehicles going through toll corner in this way a vehicle is recognized through camera. Contingent upon the territory involved by the vehicle, order of vehicles as light and overwhelming is finished. Further this data is gone to the Raspberry pi which is having web server set up on it. At the point when raspberry pi comes to know the vehicle, then it get to the web server data and as per the kind of the vehicle, fitting toll is charged. This framework can likewise made the most of two moving vehicles from pre-recorded recordings or put away recordings by utilizing the same calculation and methodology that we follow in this paper.
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