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Applicant Reactions to Automated Assessments: Moderation by Applicant Quality
Get PDFApplicant Reactions to Automated Assessments: Moderation by Applicant Quality Caleb Pollard, Dr. Yalcin Acikgoz Organizations are beginning to implement technologies such as artificial intelligence with the intent to quickly identify qualified candidates (Wesche & Sonderegger, 2021). Artificial intelligence has recently been employed to automate the selection decision-making process within screening and job interviews (Jaser et al., 2022). Utilizing these automated selection processes allows employers to distill the applicant pool to include only qualified candidates at significantly quicker times (Noble et al., 2021). Since the use of automation is prevalent, it is important to consider how applicants may react. Links between applicant reactions and job acceptance intentions as well as job pursuit intentions have been established in the literature (Chapman et al., 2005, as cited in McCarthy et al., 2017). Overall, the current literature reports that applicants tend to have negative reactions toward implementing automation within the selection processes (Acikgoz et al., 2020). However, minimal research has examined moderating variables in this relationship. This brings us to the current study examining how applicant quality may impact reactions to automation in the selection process. It is expected that higher quality (conscientiousness, cognitive ability, education, etc.) applicants will be more confident in their selection and therefore will have more positive reactions to the use of automation. H1: Higher applicant quality will result in more positive applicant reactions. RQ1: Will demographic characteristics have any interaction effect on these relationships? The data for this study was collected recently for another manuscript examining applicant reactions. 635 prolific users were randomly assigned to receive a brief description of different selection procedures (automated and traditional) and were told to imagine an organization using this selection procedure. Reaction data was then collected using the selection procedural justice scale (SPJS) (Bauer et al., 2001). Additionally, measures of “invasion of privacy” and litigation intentions were collected on Likert-type items. Participant characteristics such as self-report IQ, education level, personality variables, experience, and demographics (race, age, gender) were collected. A correlational analysis will be conducted to examine if these variables correlate with reactions to automation. It is expected that applicants of higher quality will have more positive reactions to automation. If this is the case, then organizations looking to hire high-quality applicants may not need to be as concerned about the possibility of negative reactions to automation. This may add further support to the use of automation in the selection process. Future research should continue to search for moderating variables. References Acikgoz, Y., Davison, K. H., Compagnone, M., & Laske, M. (2020). Justice perceptions of artificial intelligence in selection. International Journal of Selection and Assessment, 28(4), 399–416. https://doi-org.proxy006.nclive.org/10.1111/ijsa.12306 Bauer, T. N., Truxillo, D. M., Sanchez, R. J., Craig, J. M., Ferrara, P., & Campion, M. A. (2001). Applicant reactions to selection: Development of the selection procedural justice scale (SPJS). Personnel Psychology, 54(2), 388–420. https://doi.org/10.1111/j.1744-6570.2001.tb00097.x Jaser, Z., Petrakaki, D., Starr, R., & Oyarbide-Magaña, E. (2022, January 27). Where automated job interviews fall short. Harvard Business Review. https://hbr.org/2022/01/where-automated-job-interviews-fall-short McCarthy, J. M., Bauer, T. N., Truxillo, D. M., Anderson, N. R., Costa, A. C., & Ahmed, S. M. (2017). Applicant perspectives during selection: A review addressing “So what?,” \u27What’s new?,’ and “Where to next?” Journal of Management, 43(6), 1693–1725. https://doi-org.proxy006.nclive.org/10.1177/0149206316681846 Noble, S. M., Foster, L. L., & Craig, S. B. (2021). The procedural and interpersonal justice of automated application and resume screening. International Journal of Selection & Assessment, 29(2), 139–153. https://doi-org.proxy006.nclive.org/10.1111/ijsa.12320 Wesche, J. S., & Sonderegger, A. (2021). Repelled at first sight? Expectations and intentions of job-seekers reading about AI selection in job advertisements. Computers in Human Behavior, 125. https://doi-org.proxy006.nclive.org/10.1016/j.chb.2021.10693
Advances in high-speed store separation for upward-ejected stores and dynamic cavity doors
Get PDFAs technology continues to evolve for aircraft-deployed weapons, computational approaches to store separation analysis face new challenges. Anticipating vehicle designs that require upward store ejection, this study uses computational fluid dynamics and 6DoF motion analysis to predict such store trajectories in high-speed flow. Several store designs are analyzed at various ejection velocities in Mach 4 and Mach 6 conditions. The trajectory results show that streamlined store geometries may not induce sufficient drag to clear the aircraft after ejection. However, store designs with drag-enhancing features show potential for safe separation trajectories. To account for the unsteady effects of a cavity door which opens just prior to store ejection, dynamic cavity door simulations are presented, comparing their results to a quasi-static approach. The results show that such cavity opening effects impact pressure loads on the store, which may be critical for accurate store trajectory predictions
The synthesis and characterization of 9,10-Bis-(iodoethynyl)anthracene for 2D molecular crystals from halogen-bonding
Get PDFTwo-dimensional crystals have unique properties, giving them the potential to develop practical items such as electronics, biomedicine, and sensors. Our goal is to use chemical principles to synthesize molecules that spontaneously form 2D crystals with designed patterns and properties. For this, we will exploit directional, non-covalent interactions to determine what pattern will form in 2D. In this project halogen-bonding will be utilized: halogen-bonding is the interaction between the electrophilic region of a halogen and a nucleophilic region of a Lewis base. We are functionalizing anthracenes with iodine and nitrogen to form halogen bonds that enable the molecules to pack more uniformly. The flat, stable, conjugated composition of anthracenes makes them good candidates for 2D molecular crystals. Our hypothesis is that halogen-bonded anthracenes will have an offset row tiling pattern in 2D
A unified algebraic framework extending from a 6-set discrete probability algebra and its application in deep learning
Get PDFThis thesis introduces a novel Unified Algebraic Framework, including an expandable Python Functions Package built upon an extensible 6-Set Discrete Probability Algebra. The motivation behind this research is to provide a unified, general, and extendible quantitative analysis tool that can be used to delve into the neuron-level deep neural network structure and aims at improving the transparency of how the black box works and making advancements in detailed applications. Our approach extends a 6-Set Discrete Probability Algebra to a more systematic quantitative framework that incorporates the analysis of the discrete probability distribution of neurons in deep neural network structure. Our methodology leverages the existing models and visualization of the application of the framework to quantitatively know how this algebra works and then implement the neuron-level application in classical scenarios. The key contribution of this research includes a mathematical 6-Set Discrete Probability Algebra that offers a more robust and reasonable foundation for how neurons play their role in deep learning networks and how the quantitative analysis of the probability distribution of the neurons provides plentiful evidence and knowledge to reduce the intuition and trial and error research pattern in the selection and design of neural networks. The thesis also provides an off-the-shelf expandible quantitative research tool that can be applied in the current domain and customized to expand to various fields. The thesis also demonstrates how the framework defines and measures dissimilarity between neurons to improve diversity in ensemble learning, similarity to achieve neuron-level knowledge transferring, the minimum distance perturbation to optimize the network structure with pruning, and entropy-based on differences of neurons to interpretability and explainability. This research provides a new approach that combines more sophisticated algebraic approaches in AI(Artificial Intelligence) and practical frameworks and tools that can be applied directly in deep learning applications to enhance effectiveness and efficiency. It will be helpful for researchers who are interested in this domain
College students\u27 perceptions of malingering attention deficit hyperactivity disorder
Get PDFThis study assessed college students’ knowledge and perceptions of attention deficit hyperactivity disorder (ADHD) to help identify patterns of behavior in those who malinger ADHD in a college environment. Specifically, I sought to determine what behaviors college students attribute to ADHD and how those behaviors are demonstrated when malingering the disorder. Participants in this study were neurotypical college students and those with a valid ADHD diagnosis. Half of the neurotypical participants were instructed to malinger ADHD on all study assessments. Participants who were instructed to malinger ADHD subjectively reported significantly more symptoms than their neurotypical peers, but not their valid ADHD counterparts. They also responded with a significantly different error pattern on experimental assessments. The findings from this study can inform future research regarding specific assessments that will capture discrepancies between individuals who malinger ADHD and legitimate cases
Effect of running cadence on tibial acceleration: implications for runners experiencing stress injuries
Get PDFI. Purpose The purpose of this study was to determine the influence of cadence modification on tibial acceleration (TA) in the interest of exploring potential methods to reduce the incidence of stress-related running injuries. II. Methods Eleven injury-free distance runners were recruited to run at 6 different cadences with acoustic pacing. An inertial measurement unit (IMU) containing an onboard triaxial accelerometer was mounted on the right medial distal tibia to record acceleration at each of these paces. A repeated-measures ANOVA was conducted to determine differences in tibial acceleration over varying cadences. Effect sizes (╖2 and Cohen’s d) were examined to determine meaningfulness of the results. Secondary analyses were conducted to determine potential covarying effects. III. Results The repeated measures ANOVA indicated that cadence significantly affected peak axial tibial acceleration (F=7.59, p\u3c0.001, ╖2=0.43). Post-hoc tests showed that peak axial TA was significantly lower at the fastest cadence compared to the slowest cadence (p\u3c0.001, Cohen’s d=0.813, mean difference=1.085 g). At lower cadences, females have exceptionally higher TA (p=0.01), and the difference in TA among females from their slowest to fastest cadence was significant (p\u3c0.001). The difference in TA among males from slowest to fastest cadence did not change significantly (p=0.78). IV. Conclusion The hypothesis was fully supported: TA decreases as cadence increases. Upon further examination, these differences were driven primarily by females. A decrease in TA is indicative of decreased external force being applied to the tibia. Results of this study suggest that increasing cadence while maintaining the same speed could result in potentially lowered risk of injury, and is especially important for females
A web application for comparing LLM and knowledge graph performance on cybersecurity queries
Get PDFThe evolution of cybersecurity has led to a spike in digital threats, both in frequency and complexity, necessitating advanced, intelligent solutions to protect sensitive information. Traditional defense mechanisms are increasingly inadequate, pushing cybersecurity professionals to seek innovative approaches for threat detection, response, and data analysis. This thesis investigates the integration of Large Language Models (LLMs) and Knowledge Graphs into cybersecurity workflows to address these challenges. Specifically, it explores the development of a web application that enables real-time, interactive use of state-of-the-art LLMs, such as OpenAI’s GPT-4 and similar models, for improved threat response and workflow efficiency. Built with a React frontend and FastAPI backend, the application allows for seamless interactions with multiple LLMs, offering tools to evaluate model responses, track performance, and handle cybersecurity-specific queries. The inclusion of Knowledge Graphs further improves the structured retrieval of information, providing cybersecurity professionals with a platform for managing complex cybersecurity efforts. Additionally, an automated performance evaluation system ensures response accuracy, crucial for sensitive cybersecurity tasks. This research demonstrates the potential of LLMs to benefit cybersecurity capabilities, showing their role in advancing threat detection, response generation, and comprehensive data analysis
Effects of experimenter behaviors on participants\u27 mood
Get PDFThis study investigated whether experimenter behaviors affected self-reported levels of state and trait anxiety, emotional valence memory, and projective interpretations of ambiguous stimuli. I hypothesized that participants exposed to anxious experimenters would report higher levels of state anxiety, recall more negative words, and render more negative interpretations while warm experimenters would lead participants to report lower levels of state anxiety, recall more positive words, and produce more positive interpretations. Participants (N = 98) were randomly assigned to either an anxious, flat, or warm experimenter condition and completed the State-Trait Anxiety Inventory (STAI; Spielberger et al., 1983), heard a list of 32 emotionally salient or neutral words, responded to ten Thematic Apperception Test (TAT; Murray, 1943) cards in a free-response format, completed an open recall of the previously read word list, retook the STAI, and evaluated their experimenter’s performance. Participants in all conditions reported significantly higher levels of state anxiety at the end of the study but did not significantly differ between conditions. Participants in the flat condition recalled significantly more negative words compared to those in the warm and anxious conditions, and the difference between the average number of positive and negative words recalled significantly differed by condition. Participant’s TAT responses were coded using the Linguistic Inquiry & Word Count (LIWC-22) software. Their responses were highly negative in tone but did not differ by experimenter condition. My primary hypotheses were not supported, and the flat experimenter exerted the most direct influence on participants. The laboratory environment appeared generally unsettling, suggesting further research on test anxiety and evaluative settings is necessary
Analysis of single event transients in arbitrary waveforms using statistical window analysis
Get PDFWindow functions are commonly used in data processing to detect transient events or for time-averaging of frequency spectra. A generalized window function is demonstrated using the Ionizing Radiation Effects Spectroscopy (IRES) technique to enhance the measurement of transient anomalies within arbitrary waveforms. The IRES filter convolves time data with a sliding window consisting of a moment-generating function. The resulting time-dependent statistical moments are used to eliminate any steady-state signatures, including noise, and extract transient behaviors. The IRES filter analyzes data from heavy-ion exposures of commercial off-the-shelf (COTS) operational amplifiers, laser-induced transients in Complementary Metal-Oxide-Semiconductor (CMOS) phase-locked loops, and simulated transients in digital and analog circuits.The performance of the IRES filter in noisy environments shows that transients can be measured with higher fidelity than standard amplitude thresholding. This statistical window analysis technique may remove the need for complex triggering mechanisms on instrumentation and doesn’t require a-prior knowledge of transient characteristics
Multidisciplinary Literary Review: The relationship between social media and empathy
Get PDFThis literary review examines the different psychological perspectives on the relationship between social media usage and empathy. Specifically, it discusses the association by expanding on the fields of cognitive psychology, neuropsychology, clinical psychology, and some evolutionary psychology. I define empathy and discuss its developmental journey, its cognitive functions, its neurobiological processes, its possible damage caused by social media usage, and its effects on physical and mental health. Lastly, I argue that research focusing on high levels of social media usage and its relationship with levels of empathy should focus on creating an elaborate longitudinal study to gain more information on the possible negative and positive consequences