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I have had just one job interview in my life and it was for the position of Biology Instructor at Catonsville Community College. Having just completed my M.S. Degree at Northern Illinois University, I knew I needed employment because I was moving to Maryland prior to September 1970. After enquiring about the possibility of a teaching position at 4 Maryland community colleges, I was granted an interview at Catonsville Community College. On May 4, 1970, I found myself driving from Illinois to Maryland for a real job interview. I remember the date because I was listening on my car radio to the aftermath of the Kent State shooting earlier that day. The interview apparently went well because I was offered the position beginning in September for the amazing salary of $10,000! My professional life had begun. Armed with little more than a love of microbiology and a lot of patience and desire, I began the journey to hopefully become the best microbiology educator of which I am capable. Fifty-one years later I am still striving for that goal.

The present study pursued a dual purpose: the primary aim of the study was to test the role of non-verbal cues in eliciting emotions; the second aim was to verify if the participants’ ability in communication decoding was related to an unconscious coherent emotional activation. Participants were invited to observe a mute video with a job interview. Three different conditions were considered: one clip where the interview was characterized by racial prejudice, one with sexual prejudice and a control condition. An ad hoc questionnaire was administered to test participant’s observations. Participants’ facial expressions were also recorded. Results evidenced a great participants’ ability in detecting emotional content of a communication by concentrating only on non-verbal signals and a corresponding unconscious emotional activation. Both evidences will be framed in the most recent theoretical debates.

The study investigated the vocational education students’ pronunciation problems, especially on English consonant sounds. More specifically, this study looked at 1) what are the students’ problems on English consonant sound, 2) what are the dominant problems affecting and 3) how do they resolve their pronunciation problems. The participants were 69 vocational higher education freshmen in Indonesia. The qualitative description approach was used to collect the data. Field observation, questionnaire, and job interview video practice were conducted in the study. The study revealed that most students had problem on the consonants sounds such as: /θ/, /ð/, /dʒ/, / tʃ/, /ʃ/, /j/, etc. Three factors affecting their pronunciation were mother tongue influence, non-corresponding spelling, and age. The most dominant factor was the mother tongue influence. After discussing their partner’s feedback, the students said to have a willingness to resolve their difficulties. The results can be used as a reference in making pronunciation instructions to minimize students’ pronunciation errors.

During recruitment, human resource departments face two challenges: finding the right people for the job and attracting talent. Therefore, the hiring process requires both the ability to communicate a good company brand image and to understand the characteristics and potential of candidates. In this study, we used a neuroscientific approach to measure the experience of candidates during a job interview. The experiment involved 30 participants that individually took part in a job interview lasting 40 min. During the experiment, their engagement and stress levels were measured in real-time with skin conductance and electroencephalographic (EEG) data. From the results, we identified both the most stressful phases (the second and the fourth parts, relating to the explanation of the job and remuneration) and the most engaging phases (the first and the third phases, relating to the presentation of the company and the explanation of the career process) of the interview, suggesting implications for the assessment process. This study is a contribution to the field of neuromanagement, as a neuroscientific approach was applied to management issues in light of work and organizational psychology.

Research has shown that hiring discrimination is a barrier for older job candidates in many OECD countries. However, little research has delved into why these job candidates face discrimination. Therefore, we have con-ducted an online scenario experiment involving recruiters to empirically investigate 15 potential stigmas related to older age drawn from a systematic review of the literature. We found that older age particularly signals to recruiters that the applicant has lower technological skills, flexibility, and trainability levels. Together, these per-ceptions explain about 41% of the effect of age on the probability of being invited to a job interview. Additionally, we found that the negative association between age and the invitation to interview probability is smaller when recruiters work for firms with a higher percentage of older employees.

This study sought to determine whether two situational factors within a job interview could impact applicant interview anxiety. More specifically, the study investigated whether providing interview questions to applicants before officially beginning the interview or attempting to mimic a feelings elicited from rapport building using a script could reduce applicant interview anxiety. We also investigated whether applicants’ intolerance of uncertainty would moderate the relation between question provision and interview anxiety. After conducting real selection interviews for a research assistant position, applicants (N = 205) completed a questionnaire asking about their interview anxiety and intolerance of uncertainty. Ultimately, our hypotheses were not supported, as interview anxiety did not differ across conditions and intolerance of uncertainty did not moderate the relation between question provision and interview anxiety. Thus, we did not find any evidence to suggest that the situational factors we identified have an impact on interview anxiety.

Nowadays the number of students studying abroad increases rapidly. Migrant students represent a highly motivated and achieving category and contribute a lot to the economies of the host countries. Coming to the host country they face different challenges, one of them being employment. Previous studies reveal that migrant students during the period of their acculturation undergo various difficulties, and even after graduation, there are such hurdles as pressure, immigration policies, and an uncertain future. If they want to pursue a career in the host country, new barriers such as documentation requirements, problems with language and discrimination could appear. The necessity to create a safe environment that can help them acquire the necessary skills needed at a job interview made the research authors consider the use of a VR tool. Virtual reality simulators make it possible to repeat actions as many times as necessary to achieve the desired result and proved their efficiency applied to other vulnerable categories of citizens. In this study, a needs analysis was conveyed to depict the barriers migrant students face while seeking a job in a host country and to discuss the most useful architecture of an effective computer simulator “Employment navigator”. 171 migrant students took part in it. The outcome of the research resulted in the architecture design of the ‘Employment Navigator’ virtual reality simulator that can be used as a tool to assess the readiness of a migrant student to undergo a job interview successfully.

An Interview with ALEX is a 12-minute interactive experience that engages the participant in a job interview with ALEX, a powerful artificial intelligence HR employed by a speculative tech giant called "Open Mind Corporation." Through a science-fiction lens, the experience reveals how artificial intelligence (AI) and the gamification of work can be used as subtle tools of control in the interest of those in power.

Background The incidence of autism spectrum disorders (ASD) is on the rise. Currently, 1 in 59 children are identified with ASD in the United States. ASD refers to a range of neurological disorders that involve some degree of difficulty with communication and interpersonal relationships. The range of the spectrum for autism disorders is wide with those at the higher functioning end often able to lead relatively independent lives and complete academic programs even while demonstrating social awkwardness. Those at the lower functioning end of the autism spectrum often demonstrate physical limitations, may lack speech, and have the inability to relate socially with others. As persons with ASD age, options such as employment become increasingly important as a consideration for long‐term personal planning and quality of life. While many challenges exist for persons with ASD in obtaining and maintaining employment, some research shows that, with effective behavioral and social interventions, employment can occur. About 37% of individuals with ASD report having been employed for 12 months or more, 4 years after exiting high school. However, several studies show that individuals with ASD are more likely to lose their employment for behavioral and social interaction problems rather than their inability to perform assigned work tasks. Although Westbrook et al. (2012a, 2013, 2015) have reviewed the literature on interventions targeting employment for individuals with ASD, this review is outdated and does not account for recent developments in the field. Objectives The objective of this review is to determine the effectiveness of employment interventions in securing and maintaining employment for adults and transition‐age youth with ASD, updating two reviews by Westbrook et al. (2012a, 2013). Search Methods The comprehensive search strategy used to identify relevant studies included a review of 28 relevant electronic databases. Search terminology for each of the electronic databases was developed from available database thesauri. Appropriate synonyms were used to maximize the database search output. Several international databases were included among the 28 databases searched. In addition, the authors identified and reviewed gray literature through analysis of reference lists of relevant studies. Unpublished dissertations and theses were also identified through database searches. The programs of conferences held by associations and organizations relevant to ASD and employment were also searched. In sum, the search strategy replicated and expanded the prior search methods used by Westbrook et al. (2012a, 2013). Selection Criteria Selection criteria consisted of an intervention evaluation using a randomized controlled trial or quasi‐experimental design, an employment outcome, and a population of individuals with ASD. Data Collection and Analysis We updated the search from Westbrook et al., replicating and broadening the information retrieval processes. Our wide array of sources included electronic databases, gray literature, and conference and organization websites. Once all potentially relevant studies were located, pairs of coders evaluated the relevance of each title and abstract. Among the studies deemed potentially relevant, 278 were subjected to full‐text retrieval and screening by pairs of coders. Because many intervention studies did not include employment outcomes, only three studies met our inclusion criteria. Given the small number of included studies, meta‐analytic procedures were not used; rather, we opted to use more narrative and descriptive analysis to summarize the available evidence, including an assessment of risk of bias. Results The systematic review update identified three studies that evaluated employment outcomes for interventions for individuals with ASD. All three studies identified in the review suggest that vocation‐focused programs may have positive impacts on the employment outcomes for individuals with ASD. Wehman et al. indicated that participants in Project SEARCH had higher employment rates than control participants at both 9‐month and 1‐year follow‐up time points. Adding autism spectrum disorder supports, Project SEARCH in Wehman et al.'s study also demonstrated higher employment rates for treatment participants than control participants at postgraduation, 3‐month follow‐up, and 12‐month follow‐up. Smith et al. found that virtual reality job interview training was able to increase the number of job offers treatment participants received compared to control participants. Authors' Conclusions Given that prior reviews did not identify interventions with actual employment outcomes, the more recent emergence of evaluations of such programs is encouraging. This suggests that there is a growing body of evidence regarding interventions to enhance the employment outcomes for individuals with ASD but also greater need to conduct rigorous trials of vocation‐based interventions for individuals with ASD that measure employment outcomes.

Face serves as the primary source of contact for humans while interacting with each other. Facial Expressions fall under the bucket of non-verbal type of communication and plays a vital role in understanding the emotional state of a person. Identifying emotions through Facial Expressions can be used in various fields like revealing the Behavior of a candidate in a Job Interview, Understanding the comprehension level of the candidates in a classroom, Healthcare, Electoral campaign etc.; In additions to images fed to the Neural Network, Open Face tool is also used to extract the Facial Action Units of the subject in the dataset which contributes in training a neural network. We have designed and built a model-based technique with a high accuracy to classify the Facial based emotions. The data is trained on a Temporal Relations based Neural Network. Emotions can help us make decisions and it has a wide use case.

Mental health problems are associated with poor labour market outcomes. Based on data from a field experiment, this article investigates the extent to which hiring discrimination limits the job opportunities of young applicants who disclose a history of mental health problems. From September 2019 to December 2020, 1398 job applications were sent in pairs to 699 employers with job openings in a broad selection of occupations in the Norwegian labour market. The applicants were equally qualified except that, in each pair, one applicant informed about mental health problems as an explanation for a past employment break. The results show that applicants who disclose mental health problems are discriminated against in hiring processes. Applicants with mental health problems have about 27% lower probability of receiving an invitation to a job interview and about 22% lower probability of receiving any positive employer response. These results do not seem to have been driven by the COVID-19 crisis that unfolded during the course of the study. As such, the study provides suggestive evidence that uncertain economic times might not necessarily increase the level of discrimination against applicants with mental health problems. This paper is part of the HIRE project at Norwegian Social Research, Oslo Metropolitan University, funded by The Research Council of Norway (grant number: 273745).

Do apparatuses and eyestrain have effects on learning performances and quality of experience? Materials and Methods: 42 participants played a serious game simulating a job interview with a Samsung Gear VR Head-Mounted Display (HMD) or a computer screen. Participants were randomly assigned to 3 groups: PC, HMD biocular, and HMD stereoscopy (S3D). Participants played the game thrice. Eyestrain was assessed pre- and post-exposure with six optometric measures. Learning performances were obtained in-game. Quality of experience was measured with questionnaires. Results: eyestrain was higher with HMDs than PC based on Punctum Proximum of accommodation but similar between biocular and S3D. Knowledge gain and retention were similar with HMDs and PC based on scores and response time. All groups improved response time but without statistically significant differences between HMDs and PC. Visual discomfort difference was statistically significant between PC and HMDs (biocular and S3D). Flow difference was statistically significant between PC and HMDs (biocular and S3D), with the PC group reporting higher Flow than HMD-S3D. Conclusion: short-term learning is similar between PC and HMDs. Groups initially using HMDs continued improving during long-term learning but without statistically significant difference compared to PC. Eyestrain and visual discomfort were higher with HMDs than PC. Flow was higher with the PC group. Our results show that eyestrain does not seem to decrease learning.

People with psychosis can experience social functioning impairments. Virtual reality (VR) has been used to assess and treat these difficulties. This systematic review (Prospero CRD42015026288) provides an evaluation of these VR applications. PsycINFO, MEDLINE, Embase, Web of Science, Cochrane Library, and Scopus were searched until May 2020. The Effective Public Health Practice Project (EPHPP) Quality Assessment Tool was used to assess studies. Database searching identified 3810 titles. Fifty-eight studies (published 2005-2020; N = 2,853), comprising twenty-six head-mounted display studies (20 assessment, 6 treatment) and thirty-two immersive 2D screen studies (23 assessment, 9 treatment), were included. There were forty-eight observational studies and ten randomised controlled trials, with 1570 participants (of which, 185 were at ultra-high risk of psychosis) in VR test groups. Nearly half the studies were published since 2016. Assessments targeted cognitive and behavioural indicators of social functioning, e.g. paranoia, eye gaze, or interpersonal distance. Treatments promoted cognitive-behavioural social skills or job interview training. Studies indicate feasibility, acceptability, and effectiveness of VR for social functioning impairments in psychosis. Limitations of studies include the narrow scope of social functioning, small sample sizes, and limited randomised controlled trials and standardised interventions. Findings suggest VR has potential to be integrated with existing psychological approaches. ispartof: INTERNATIONAL REVIEW OF PSYCHIATRY vol:33 issue:3 pages:337-362 ispartof: location:England status: published

The paper built on First Impression Challenge from Chalearn V2 Workshop on Explainable Computer Vision Multimedia and Job Candidate Screening Competition CVPR17 by focusing solely on Textual Input in contrast to other Challenge’s participants who considered video or audio modalities. Therefore, the paper aims to develop a new deep learning architecture capable of predicting human personality traits and job interview from the video transcripts. Several feature representations that involve statistical and deep learning have contrasted. Our approach achieved the best score when text modality alone were employed, yielding an average of 89% score in human personality traits and 89.10% value for job interview. The research results will help companies and other organization studying human personality to assess a human personality using a minimum textual resources from the job candidates

There has always been pressure on higher education institutions to enhance the employability of graduates and to instil knowledge, skills, and attributes that will be beneficial to future employers. The impact of Covid‑19 on a global, national, and local level is placing even more pressure on the topic of employability. Graduates are uncertain about job availability and there is a need for career guidance. After a national and local shutdown of university campuses in 2015 and 2016 due to #FeesMustFall, Career Services staff at the University of the Free State designed and created online work readiness programmes in order for students to continue with work preparations, no matter what the circumstances. In 2018, the first topics on CV‑writing and job interview skills were rolled out online and made available to all registered students; each semester, two additional topics were added. By the time Covid‑19 led to a national lockdown in South Africa in March 2020, the transition to online work readiness programmes was fairly easy. The purpose of this study is to determine the impact of the online work readiness programmes offered on the Blackboard platform from April to June 2020 during the Covid‑19 pandemic and national lockdown. This article will provide an analysis of a questionnaire conducted with willing participants who have engaged and worked through the online work readiness programmes from April to June 2020, to investigate the impact on graduates’ readiness for the world of work. Through the survey, students shared their learning experiences and the influence it has had on their career planning. It is believed that the findings of this research study will create a deeper understanding of how career services, as a particular functional area in student affairs, can reposition itself during uncertain times to remain responsive to the needs of students.

We report the results of an empirical study on gaze aversion during dyadic human-to-human conversation in an interview setting. To address various methodological challenges in as- sessing gaze-to-face contact, we followed an approach where the experiment was conducted twice, each time with a different set of interviewees. In one of them the interviewer’s gaze was tracked with an eye tracker, and in the other the interviewee’s gaze was tracked. The gaze sequences obtained in both experiments were analyzed and modeled as Discrete-Time Markov Chains. The results show that the interviewer made more frequent and longer gaze contacts compared to the interviewee. Also, the interviewer made mostly diagonal gaze aversions, whereas the interviewee made sideways aversions (left or right). We discuss the relevance of this research for Human-Robot Interaction, and discuss some future research problems.

Deceptive impression management (i.e., faking) may alter interviewers’ perceptions of applicants’ qualifications and, consequently, decrease the predictive validity of the job interview. In examining faking antecedents, research has given little attention to situational variables. Using a between-subjects experiment, this research addressed that gap by examining whether organizational culture impacted both the extent to which applicants faked and the manner in which they faked during a job interview. Analyses of variance revealed that organizational culture did not affect the extent to which applicants faked. However, when taking into account applicants’ perceptions of the ideal candidate, organizational culture was found to indirectly impact the manner in which applicants faked their personality (agreeableness and honesty-humility). Overall, the findings suggest that applicants may be able to fake their personality traits during job interviews to increase their person–organization fit.

Design of appropriate assessment tools to measure student achievement of program learning outcomes (PLOs) represents a challenge to higher education institutions. Typical outcome-based assessment tools examine student outcomes at the course level, i.e. course learning outcomes (CLOs), and are then mapped to PLOs. The validity of this approach depends on the correctness and accuracy of the mapping between CLOs and PLOs. To directly evaluate student achievement of PLOs, curriculum-based exit exams have been developed and adopted by engineering programs. Such exams play a critical role in the assessment and improvement of engineering programs. Yet, their validity as a direct measure of PLOs is uncertain. This paper aims to fill this gap by assessing the appropriateness of using curriculum-based exit exams to evaluate student attainment of PLOs at the time of graduation. A student survey was developed to obtain the perceptions of 92 senior civil engineering students over the course of three semesters. Findings revealed that students generally did not believe that the exit exam was an appropriate tool to evaluate their attainment of PLOs nor did it improve their knowledge in civil engineering disciplines. However, it helped prepare them for a job interview. Student performance in various disciplines was attributed to the level of preparedness, interest in the topics, and difficulty of exam questions. Additionally, students believed having more sample questions or increasing the contribution of the exit exam to their grade point average would help improve the overall performance. The results also showed that the majority of students prepared for the exit exam by studying and solving questions from previous exit exam samples. A continuous improvement process was proposed to enhance the overall exit exam experience. Remedial actions were also suggested to render it a more valid direct assessment tool and inspire a positive attitude in students towards it.

Background The marijuana purchase task (MPT) is a commonly used behavioral economic measure of relative cannabis value (i.e. demand) that presents specific methodological concerns due to non-standardized measurement, variability in modality of use, and evolving legalization policies. Refinement of the task is critical to improve task ecological validity and accurate measurement of cannabis demand. The present study examined the construct validity of an adaptive MPT that allowed for participant selection of their preferred cannabis-based product and unit of measurement and the effect of next-day responsibilities on demand. Methods Participants reporting at least monthly cannabis use (N = 186, 40.3 % women, Mage = 33.59) were recruited via Amazon Mechanical Turk and completed the original MPT and our adaptive form with 2 next-day responsibilities scenarios (no responsibilities vs. morning job interview) for each MPT. Cannabis use motives, problems, and risk for cannabis use disorder were also assessed. Results Cannabis demand was sensitive to next-day responsibility, with higher hypothetical consumption observed in the no responsibilities condition. Responsibility-related decreases in Omax (F(1,185) = 4.83, p = .029, η2p = .03) were significantly greater on the adaptive MPT than the original MPT. Demand indices derived from the adaptive MPT were significantly correlated with cannabis problems (rbreakpoint = .19, rPmax = 0.18, relasticity=-0.18) and motives (rrange=-.32−.25), and demand metrics from the original MPT. Conclusions Results provide preliminary support for the construct validity of an adaptive MPT and suggest that early-morning work responsibilities may reduce cannabis demand. Continued research is needed to further refine this task and determine implications for cannabis use disorder intervention and prevention approaches.

Gaze and language are major pillars in multimodal communication. Gaze is a non-verbal mechanism that conveys crucial social signals in face-to-face conversation. However, compared to language, gaze has been less studied as a communication modality. The purpose of the present study is 2-fold: (i) to investigate gaze direction (i.e., aversion and face gaze) and its relation to speech in a face-to-face interaction; and (ii) to propose a computational model for multimodal communication, which predicts gaze direction using high-level speech features. Twenty-eight pairs of participants participated in data collection. The experimental setting was a mock job interview. The eye movements were recorded for both participants. The speech data were annotated by ISO 24617-2 Standard for Dialogue Act Annotation, as well as manual tags based on previous social gaze studies. A comparative analysis was conducted by Convolutional Neural Network (CNN) models that employed specific architectures, namely, VGGNet and ResNet. The results showed that the frequency and the duration of gaze differ significantly depending on the role of participant. Moreover, the ResNet models achieve higher than 70% accuracy in predicting gaze direction.

This research examines the perceived fairness of two types of job interviews: robot-mediated and face-to-face interviews. The robot-mediated interview tests the concept of a fair proxy in the shape of a teleoperated social robot. In Study 1, a mini-public (n=53) revealed four factors that influence fairness perceptions of the robot-mediated interview and showed how HR professionals’ perception of fair personnel selection is influenced by moral pragmatism despite clear moral awareness of discriminative biases in interviews. In Study 2, an experimental survey (n=242) conducted at an unemployment center showed that the respondents perceived the robot-mediated interview as fairer than the face-to-face interview. Overall, the studies suggest that HR professionals and jobseekers exhibit diverging fairness perceptions and that the business case for the robot-mediated interview undermines its social case (i.e., reducing discrimination). The paper concludes by addressing key implications and avenues for future research.

Autistic transition age youth struggle with obtaining employment, and interviewing is a critical barrier to getting a job. We adapted an efficacious virtual reality job interview intervention to meet the needs of autistic transition age youth, called the Virtual Interview Training for Transition Age Youth. This study evaluated whether Virtual Interview Training for Transition Age Youth can be feasibly delivered in high school special education settings and whether Virtual Interview Training for Transition Age Youth improves job interview skills, job interview self-efficacy, job interview anxiety, and access to employment. Forty-eight autistic transition age youth received school-based pre-employment services as usual with Virtual Interview Training for Transition Age Youth, while 23 autistic transition age youth received services as usual only. Local teachers trained and supervised autistic transition age youth using Virtual Interview Training for Transition Age Youth. Participants reported Virtual Interview Training for Transition Age Youth was highly acceptable. Participants receiving services as usual and Virtual Interview Training for Transition Age Youth, compared to participants receiving services as usual only, had better job interview skills and lower job interview anxiety as well as greater access to jobs. Overall, Virtual Interview Training for Transition Age Youth appears to be effective at teaching job interview skills that are associated with accessing competitive jobs. Moreover, youth enjoyed Virtual Interview Training for Transition Age Youth and teachers feasibly implemented the tool within special education pre-employment transition services. Future research needs to better understand how autistic transition age youth from culturally diverse backgrounds and different social, behavioral, or mental health challenges may respond to Virtual Interview Training for Transition Age Youth. Lay abstract Autistic transition age youth struggle with obtaining employment, and interviewing is a critical barrier to getting a job. We adapted an efficacious virtual reality job interview intervention to meet the needs of autistic transition age youth, called the Virtual Interview Training for Transition Age Youth. This study evaluated whether Virtual Interview Training for Transition Age Youth can be feasibly delivered in high school special education settings and whether Virtual Interview Training for Transition Age Youth improves job interview skills, job interview self-efficacy, job interview anxiety, and access to employment. Forty-eight autistic transition age youth received school-based pre-employment services as usual with Virtual Interview Training for Transition Age Youth, while 23 autistic transition age youth received services as usual only. Local teachers trained and supervised autistic transition age youth using Virtual Interview Training for Transition Age Youth. Participants reported Virtual Interview Training for Transition Age Youth was highly acceptable. Participants receiving services as usual and Virtual Interview Training for Transition Age Youth, compared to participants receiving services as usual only, had better job interview skills and lower job interview anxiety as well as greater access to jobs. Overall, Virtual Interview Training for Transition Age Youth appears to be effective at teaching job interview skills that are associated with accessing competitive jobs. Moreover, youth enjoyed Virtual Interview Training for Transition Age Youth and teachers feasibly implemented the tool within special education pre-employment transition services. Future research needs to better understand how autistic transition age youth from culturally diverse backgrounds and different social, behavioral, or mental health challenges may respond to Virtual Interview Training for Transition Age Youth.

The development of new technologies influences all sectors of activity, including human resources and particularly the recruitment process. The emergence of pre-recorded video interviews makes it possible to organize asynchronous interviews with candidates and evaluate them. Candidates connect to a platform and record themselves while they answer questions defined in advance by recruiters. The platform then allows several recruiters to evaluate the candidate, share notes and possibly invite the candidate to a face-to-face interview. However, the number of such video applications is becoming increasingly large and difficult to process "manually" by one or two recruiters. It is therefore becoming necessary to consider assistance for the recruiter, who sometimes has to process several hundred video interviews. In addition, the development of such tool could also allow candidates to train the practice of asynchronous video interview thanks to an automatic evaluation. As part of a project with an industrial partner, we collected two corpus of more than 5000 asynchronous video interviews for real jobs. This thesis studies the task of predicting the performance of candidates during asynchronous video interviews using three modalities (verbal content, prosody and facial expressions) using data from real interviews that take place in non-laboratory conditions. We propose a new multimodal hierarchical attention model called HireNet that aims to predict the employability of candidates as assessed by recruiters. In HireNet, an interview is viewed as a sequence of questions and answers containing salient social cues. In a second step, we discuss the influence of non-verbal behavior in a hiring decision. It is important to study this issue because it may provide a better understanding of how to train candidates for job interviews and make recruiters aware of these influential behaviors. Subsequently, we focus on the study of influential social signals in asynchronous video job interviews that are discovered through deep learning methods. A special feature of HireNet is the use of attention mechanisms that aim to identify the most relevant parts of a response. Thus, information at a finite temporal level could be extracted using global annotations (at the interview level) on the candidate's hirability. While most deep learning systems use attention mechanisms to provide a quick visualization of slices when an increase in attention values occurs, we perform an in-depth analysis to understand what happens at these moments. Thus, we study the content of these moments by comparing them with randomly sampled moments in order to study their differences. Overall, this method aims to improve the interpretability of such systems and to question their use as an exploratory tool. Our third contribution concerns biases in automatic video interview analysis systems. We propose a first approach that uses adversarial training to learn a representation that ignores the gender and ethnicity of the candidates. We show experimentally that it ensures a better representation without significant loss of efficiency on the main task. We then study the use of this adversarial training without the need to collect sensitive information about the candidates. In this way, we aim to improve the fairness of future automatic systems for processing job interview videos for equal job selection.; Le développement des nouvelles technologies influence tous les secteurs d’activités, y compris celui des ressources humaines et notamment le processus de recrutement. L’émergence des entretiens vidéo différés permet d’organiser en asynchrone des entretiens avec des candidats et de les évaluer. Les candidats se connectent à une plateforme et se filment pendant qu’ils répondent à des questions définies en amont par les recruteurs. La plateforme permet ensuite à plusieurs recruteurs d’évaluer le candidat, de partager des notes et d’inviter éventuellement le candidat à un entretien en face-à-face. Le nombre de telles candidatures vidéo devient cependant de plus en plus volumineux et difficile à traiter « manuellement » par un ou deux recruteurs. Il devient donc nécessaire d’envisager une aide pour le recruteur qui doit traiter parfois plusieurs centaines d’entretiens vidéo. De plus, le développement d'une telle aide pourra aussi permettre aux candidats de s'entraîner à l'exercice de l'entretien vidéo différé grâce à une évaluation automatique. Dans le cadre d'un projet avec un partenaire industriel, nous avons recueilli deux corpus de plus de 5000 entretiens d'embauche vidéo asynchrones pour des postes réels. Cette thèse étudie la tâche consistant à prédire les performances des candidats lors d'entretiens vidéo asynchrones en utilisant trois modalités (contenu verbal, prosodie et expressions faciales) grâce à des données provenant d'entretiens réels qui se déroulent dans des conditions hors laboratoires. Nous proposons un nouveau modèle multimodal d'attention hiérarchique appelé HireNet qui vise à prédire l’employabilité des candidats tels qu'ils sont évalués par les recruteurs. Dans HireNet, un entretien est considéré comme une séquence de questions et de réponses contenant des signaux sociaux saillants. Dans un second temps, nous abordons la question de l’influence du comportement non verbal dans une décision d'embauche. Il est important d'étudier cette question car elle pourrait permettre de mieux comprendre comment former les candidats aux entretiens d'embauche et sensibiliser les recruteurs à ces comportements influents. Par la suite, nous nous concentrons sur l'étude des signaux sociaux influents dans les entretiens vidéo d'embauche asynchrones qui sont découverts par les méthodes d'apprentissage profond. Une particularité de HireNet est l'utilisation de mécanismes d'attention qui visent à identifier les parties les plus pertinentes d'une réponse. Ainsi, des informations à un niveau temporel fin pourraient être extraites en utilisant des annotations globales (au niveau de l'entretien) sur la convocabilité du candidat. Alors que la plupart des systèmes d'apprentissage profond utilisent des mécanismes d'attention pour offrir une visualisation rapide des tranches lorsqu'une augmentation des valeurs d’attention se produit, nous effectuons une analyse approfondie pour comprendre ce qui se passe lors de ces moments. Ainsi, nous étudions le contenu de ces moments en les comparant avec des moments échantillonnés de manière aléatoire afin d’étudier leurs différences. Dans l’ensemble, cette méthode vise à améliorer l’interprétabilité de tels systèmes et à s’interroger sur leur utilisation comme outil exploratoire. Notre troisième contribution concerne les biais dans les systèmes d'analyse automatique des entretiens vidéo. Nous proposons une première approche qui utilise un entraînement adversaire pour apprendre une représentation ignorant le sexe et l'ethnicité des candidats. Nous montrons expérimentalement qu'elle assure une meilleure représentation sans perte significative d'efficacité sur la tâche principale. Nous étudions ensuite l'utilisation de cet entraînement adversaire sans qu'il soit nécessaire de recueillir des informations sensibles sur les candidats. Ainsi, nous visons à améliorer l'équité des prochains systèmes automatiques de traitement des vidéos d'entretiens d'embauche pour une égalité dans la sélection des emplois.

This article deals with the future of work. It addresses the challenges posed by digitization and the use of artificial intelligence in employment. Digitalisation is changing the world of work and the demands on employees. Lifelong learning becomes a central topic. Computer programs play an important role in more and more decisions. For example, when it comes to the question of whether an applicant is suitable and is even invited to a job interview. Personnel decisions are to be solved more efficiently and in a more time-saving way by using AI. However, this bears the danger of disadvantaging individuals or groups of individuals. It is shown where AI is already used and where known problem areas exist. The dependence of supposedly objective data on the quality of data input is discussed. Fields with discrimination potential are shown.

Thanks to the success of goal-oriented negotiation dialogue systems, studies of negotiation dialogue have gained momentum in terms of both human-human negotiation support and dialogue systems. However, the field suffers from a paucity of available negotiation corpora, which hinders further development and makes it difficult to test new methodologies in novel negotiation settings. Here, we share a human-human negotiation dialogue dataset in a job interview scenario that features increased complexities in terms of the number of possible solutions and a utility function. We test the proposed corpus using a breakdown detection task for human-human negotiation support. We also introduce a dialogue act-based breakdown detection method, focusing on dialogue flow that is applicable to various corpora. Our results show that our proposed method features comparable detection performance to text-based approaches in existing corpora and better results in the proposed dataset.

International audience

The article describes the procedures of faculty recruitment and selection in the Russian higher education system with a focus on unique characteristics of certain universities. A particular emphasis is made on how this process is shaped by institutions’ regulatory framework. В статье представлен опыт подбора и отбора педагогических работников в Российском государственном профессионально-педагогическом университете. Дана характеристика основным особенностям этого процесса с учетом специфики образовательного учреждения. Проанализирован комплекс локальной нормативной базы организации.

В статье рассматриваются основные аспекты обучения студентов деловому иностранному языку на базе электронной информационно-образовательной среды с интеграцией программного продукта Rosetta Stone. In this article we discuss main aspects of studying business foreign language at University. The educational process is based on electronic information-educational system with the integration of the Rosetta Stone program.

Assessment and evaluation methods in a job interview have always been very much focused on a person’s performance, knowledge, and experience. However, excelling at a challenging job often requires skills that go beyond the skills and background of a person. And while psychometrics in the evaluation process is nothing new, gamifying the interview process is still considered a novel approach to candidate evaluation. As part of exploring new potentialities for Chemistry’s innovative card game, BossUP!, a study was conducted with the purpose of prototyping a new format of interview engagement and evaluation for the organization. In combination with a pre- and post-questionnaire, coupled with face-to-face gameplay during the interview process, this study explores the boundaries of how interviews can break free of traditional methods, by not only making it a fun and engaging experience via gamification, but to also enhance the evaluation method beyond performance, knowledge, and experience.

We demonstrate a job interview dialogue with the autonomous android ERICA which plays the role of an interviewer. Conventional job interview dialogue systems ask only pre-defined questions. The job interview system of ERICA generates follow-up questions based on the interviewee’s response on the fly. The follow-up questions consist of two kinds of approaches: selection-based and keyword-based. The first type question is based on selection from a pre-defined question set, which can be used in many cases. The second type of question is based on a keyword extracted from the interviewee’s response, which digs into the interviewee’s response dynamically. These follow-up questions contribute to realizing natural and trained dialogue.

An essential component of the job recruitment process involves conducting interviews, during which decision is made on the appropriateness of a candidate for a particular job. An important challenge faced by interviewers during the recruitment process relates to determining whether or not selected candidates will attend the job interview. Candidates failing to attend interviews because of various reasons lead to time wasting and as such, effective prediction is needed by human resource managers about whether or not a candidate will attend an interview. In other words, if the human resource department knows exactly whether or not the job seeker is attending the interview, a more efficient interview invitation strategy could be worked upon. However, even though different machine learning techniques are available for prediction, limited work has been undertaken to address this recruitment process related issue. Taking cognizance of this problem, this paper investigates, analyzes, and predicts candidate attendance during interviews in order to optimize recruitment process within businesses. For this, C4.5 algorithm was applied on an open dataset related to job interview attendance. Following generation of a classification tree, results showed some insightful patterns on when candidates do not attend job interviews.

In this chapter, I will show you how to create a network force graph. We will create a network visualization chart with mechanical spring behavior to represent interview questions you may want to review before your next React job interview. Let’s get started.

With the increasing presence in our lives of interactive and technological items, the concept of “experience” becomes crucial in both the design and the evaluation phases. When aiming to measure such experience, researchers typically adopt self-report methodology. However, it has been established that also unconscious motives (i.e., emotions, implicit attitudes) - which people are not always aware of - need to be taken into account in understanding users’ perception, by means of indirect measures. The present study investigates the possibility of measuring UX by both implicit and explicit attitudes measures. In an experimental study (N = 36), we asked participants to evaluate a conversational chatbot prototype, which had the fictional goal of pre-selecting candidates for a job, and to fix a date for the job interview. We manipulated between-participants the chatbot’s gender (male vs. female) and the tone of voice (formal vs. informal). Explicit user experience’s evaluation (i.e., UEQ) and implicit attitudes towards the chatbot (i.e., IAT) were the dependent variables, as well as self-reported measures of chatbot’s efficacy and emotional experience. Our findings showed an implicit preference towards the informal version of the chatbot, as revealed by the IAT scores, whereas no differences emerged on explicit measures of the UEQ. Results are discussed in light of the effect of implicit attitudes on overall experience, and on the importance of comparing implicit and explicit measures, as well as objective usability measures, when evaluating the UX.

In this work, a prototype of a job interview training application in virtual reality is evaluated. This paper explores the factors affecting the usability and embodiment of an avatar and how they related to job interviews in a virtual reality setting. A between-group study was conducted (n=15) to measure the effect on the embodiment of an avatar that creating and customizing an avatar had compared to picking from pre-defined ones. Participants had to undergo a job interview in virtual reality with their avatars. A mixed-method approach was followed with data collection using both post-experiment questionnaires and recorded semi-structured interviews. No significant results could be established between the avatar selection process and the embodiment towards the avatar. The thematic analysis of the interview data and the quantitative data analysis resulted in design guidelines for future job interview training applications. Critical aspects of the design guidelines outline the need to promote and enable users to use hand gestures, allow basic customization of their avatars, and put special attention to the design and behavioral fidelity of the interviewer. I det här arbetet, utvärderas en prototyp av en träningsapplikation för jobbintervjuer. Det här arbetet utforskar faktorer som påverkar användbarheten och förkroppsligandet av en avatar och hur dessa faktorer relaterar till jobbintervjuer i virtuell verklighet. En studie utfördes med två olika grupper (n=15) för att mäta effekten av förkroppsligande av avatarer som processen av att skapa och anpassa en avatar hade jämfört med att enbart välja bland förvalda avatarer. Deltagarna fick delta i jobbintervju i virtuell verklighet med sina avatarer. En blandad metod användes med datainsamling genom både formulär och inspelade intevjuer. Inga statistisk signifikanta resultat kunde erhållas mellan urvalsprocessen av avataren och förkroppsligande av avataren. Den tematiska analysen av intervjudatan resulterade i designriktlinjer som utlyser behovet av att möjliggöra användare att fritt använda händerna, göra enkla modifikationer av sina avatarer och lägga extra mycket fokus på designen av intervjuaren.

PurposeThe purpose of this paper is to explore the relationship between general self-efficacy (GSE), job search self-efficacy (JSSE), extraversion and job search success within a sample of new entrants in the labour market. It is hypothesised that JSSE acts as a mediator between GSE and job search success. Evaluation of the hireability – made by expert interviewers – of new entrants involved in a job interview simulation is proposed as a job search success criterion. Moreover, the moderating role of extraversion on the relationship between JSSE and job search success is explored.Design/methodology/approachData were collected on 177 graduates from an Italian university. Participants were involved in a simulation of an interview conducted by experts of the personnel selection process, who gave an evaluation. Macro PROCESS for SPSS was used to test the hypotheses.FindingsGSE has an indirect effect on job search success via JSSE. Moreover, extraversion has a moderating effect on the JSSE–job search success relationship for more extraverted job seekers.Practical implicationsJob search and counselling practitioners should consider extraversion and personal differences to improve the effectiveness of interventions aimed at fostering new entrants' self-regulatory resources and behaviours during the job search.Originality/valueThis study contributes to the existing research about the job search process by testing a new and important job search success criterion, showing that GSE could help new graduates in establishing a specific self-efficacy, such as JSSE, and demonstrating that extraversion interacts with JSSE.

Objectives: The involvement of patient and family representatives in job interview panels is sparsely documented. This study was conducted at a newly established university hospital in Denmark. The aim was to identify different perspectives on attitudes and experiences associated with involving patient and family representatives in the recruitment process for senior staff. Furthermore, the aim was to highlight considerations and reservations related to the subsequent implementation process. Methods: Inspiration was drawn from formative evaluation research. Data Sources: Seventeen telephone interviews with applicants, 49 e-mail responses from staff, and unsolicited e-mails to the researcher. Analysis Strategy: Interpretive description. Results: Learnings from the study showed among other things that the participating staff experienced widespread skepticism before participation in the job interview panels, but their experience in the panels led them to consider the patients’ and families’ input to be beneficial to the entire recruitment process. The considerations and reservations raised were divided into 5 themes. Conclusions: The results provide a relevant starting point to negotiate and refine the aims of collective patient involvement related to a given situation—such as health-care recruitment processes.

Job interview is one of the stages that must be passed by job applicants before getting a job. However, the manual interview process resulted in a large amount of cost and time of selection, so we need a system that can provide recommendations of which applicants are qualified. Currently there are many studies of text classification using the Naive Bayes method, K-Nearest Neighbor, Support Vector Machine, and Deep Learning. Therefore, algorithms that are used less frequently will be tested in this study, such as the Decision Tree. Then the Swarm Intelligence method, Particle Swarm Optimization, is implemented to improve the performance of the method. So that this research focuses on testing and comparing ordinary Decision Tree and Decision Tree methods that are optimized with Particle Swarm Optimization. From the test results, the accuracy of the optimized model increased by 7.1%, and the highest accuracy achieved was 74.3%.

A job interview is a domain that takes advantage of an android robot's human-like appearance and behaviors. In this work, our goal is to implement a system in which an android plays the role of an interviewer so that users may practice for a real job interview. Our proposed system generates elaborate follow-up questions based on responses from the interviewee. We conducted an interactive experiment to compare the proposed system against a baseline system that asked only fixed-form questions. We found that this system was significantly better than the baseline system with respect to the impression of the interview and the quality of the questions, and that the presence of the android interviewer was enhanced by the follow-up questions. We also found a similar result when using a virtual agent interviewer, except that presence was not enhanced.

The Software Engineering (SE) curriculum in undergraduate computer science (CS) education is designed to train students in the process of software and systems development. Traditionally, topics such as software development methodologies, industry nomenclatures, and solution analysis are delivered through lectures and group projects. We propose a novel approach in teaching SE that we call MACROVR: MAchine learning to select project team members; Cloud technologies required for project control, code versioning, and team communications; ROtational schedules in Agile/Scrum roles; an individual Video of the team project story board; and Rubrics for all presentations. Our teaching strategy with this approach utilizes the latest technologies currently employed in industry and corresponds to soft skills commonly assessed in interviews. The goal of our study is to measure if using the MACROVR approach contributes to preparedness for a computing job interview. Most often, this course is taken towards the end of a four-year CS degree program while students are job hunting or seeking an internship in the computing industry. We use an anonymous, fifteen question survey instrument sent to volunteers that indicated they are seeking a computing job and have successfully completed the SE course. The sample is comprised of three sections of the SE course using the MACROVR approach (135 students) and four sections that did not use all of the required strategies and technologies, which we call MACROVR-lite (184 students). Our two cohorts, MACROVR and MACROVR-lite, are each given the same survey questions. We analyze their Likert scale data responses using non-parametric methods. Our findings indicate the MACROVR approach better prepares students with the skills and highly valued qualities for success in computing industry interviews.

Part 2 of the Transitions to Adulthood Center for Research's An Interview Tale Comic depicts questions in an interview that a young adult may encounter. Please see our tip sheet, Do I Tell My Boss?: Disclosing My Mental Health Condition at Work for more information. Part 1 of An Interview Tale is here.