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Employment outcomes for autistic 1 individuals are often poorer relative to their neurotypical (NT) peers, resulting in a greater need for other forms of financial and social support. While a great deal of work has focused on developing interventions for autistic children, relatively less attention has been paid to directly addressing the employment challenges faced by autistic adults. One key impediment to autistic individuals securing employment is the job interview. Autistic individuals often experience anxiety in interview situations, particularly with open-ended questions and unexpected interruptions. They also exhibit atypical gaze patterns that may be perceived as, but not necessarily indicative of, disinterest or inattention. In response, we developed a closed-loop adaptive virtual reality (VR)–based job interview training platform, which we have named Career Interview Readiness in VR (CIRVR). CIRVR is designed to provide an engaging, adaptive, and individualized experience to practice and refine interviewing skills in a less anxiety-inducing virtual context. CIRVR contains a real-time physiology-based stress detection module, as well as a real-time gaze detection module, to permit individualized adaptation. We also present the first prototype of the CIRVR Dashboard, which provides visualizations of data to help autistic individuals as well as potential employers and job coaches make sense of the data gathered from interview sessions. We conducted a feasibility study with 9 autistic and 8 NT individuals to assess the preliminary usability and feasibility of CIRVR. Results showed differences in perceived usability of the system between autistic and NT participants, and higher levels of stress in autistic individuals during interviews. Participants across both groups reported satisfaction with CIRVR and the structure of the interview. These findings and feedback will support future work in improving CIRVR’s features in hopes for it to be a valuable tool to support autistic job candidates as well as their potential employers.
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Design and Validation of a Stress Detection Model for Use with a VR Based Interview Simulator for Autistic Young Adults
Studies show that young autistic adults are under- or unemployed, with almost half never holding a paying job in their 20’s. Unemployment within this population leads to decreased personal growth and increased dependence on caregivers. Research suggests that the interview process is one of the largest barriers to employment for this population. Autistic individuals often struggle with emotion regulation, which can be exacerbated by the interview process. To address this, we propose the use of a stress detection model in conjunction with a virtual reality interview simulator. This combination will allow for the interview to adapt to the state of the participant to improve the skills and engagement of the user and positively influence their comfort level. Data regarding negative affective responses to categories of questions can also be used to inform employers on better interviewing techniques. A model was designed using data obtained from neurotypical participants completing a modified Computerized Paced Serial Addition Task (PASAT-C) and evaluated on a dataset obtained from Autistic participants who took part in a simulated interview. Agreement between the model and ground truth was compared based on Pearson correlation coefficients. It was found that was r(289) = 0.28, which was statistically significant (p < .001; CI: 0.17 to 0.38). Our preliminary results provide evidence for the validity of observer-based labeling of data captured using a wrist-worn physiological sensor.
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- PAR ID:
- 10293119
- Date Published:
- Journal Name:
- International Conference on Human-Computer Interaction (HCII)
- Volume:
- 12768
- Page Range / eLocation ID:
- 580-588
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Antona, M; null (Ed.)Employment of autistic individuals is strikingly low in relation to the skill level and capabilities of this population. Roughly 65% of autistic adults are either unemployed or underemployed relative to their abilities but there is increasing recognition that this number could be greatly improved through empowering autistic individuals while simultaneously providing a boost to the economy. Much of this disparity can be attributed in part to the lack of awareness and understanding among employers regarding behavior of autistic individuals during the hiring process. Most notably, the job interview—where strong eye contact is traditionally expected but can be extremely uncomfortable for autistic individuals—presents an unreasonable initial barrier to employment for many. The current work presents a data visualization dashboard that is populated with quantitative data (including eye tracking data) captured during simulated job interviews using a novel interview simulator called Career Interview Readiness in Virtual Reality (CIRVR). We conducted a brief series of case studies wherein autistic individuals who took part in a CIRVR interview and other key stakeholders provided lived experiences and qualitative insights into the most effective design and application of such data visualization dashboard. We conclude with a discussion of the role of information related to visual attention in job interviews with an emphasis on the importance of descriptive rather than prescriptive interpretation.more » « less
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Computer-based job interview training, including virtual reality (VR) simulations, have gained popularity in recent years to support and aid autistic individuals, who face significant challenges and barriers in finding and maintaining employment. Although popular, these training systems often fail to resemble the complexity and dynamism of the employment interview, as the dialogue management for the virtual conversation agent either relies on choosing from a menu of prespecified answers, or dialogue processing is based on keyword extraction from the transcribed speech of the interviewee, which depends on the interview script. We address this limitation through automated dialogue act classification via transfer learning. This allows for recognizing intent from user speech, independent of the domain of the interview. We also redress the lack of training data for a domain general job interview dialogue act classifier by providing an original dataset with responses to interview questions within a virtual job interview platform from 22 autistic participants. Participants’ responses to a customized interview script were transcribed to text and annotated according to a custom 13-class dialogue act scheme. The best classifier was a fine-tuned bidirectional encoder representations from transformers (BERT) model, with an f1-score of 87%.more » « less
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This Work in Progress (WIP) paper will present an interview protocol development that leverages social media analysis for capturing narratives of neurodivergent (e.g., ADHD, autistic, dyslexic) engineering students. The work presented in this WIP is part of a larger mixed-methods sequential research project which aims to capture neurodivergent engineering student narratives that describe their engineering experiences in terms of strengths and challenges. Through social media analysis, we identified key language used by the neurodivergent community (e.g., neurodivergent, spoon, forget). We developed a few initial themes such as multiple pathways to recognizing one’s identity of being neurodivergent, multiple ways in which neurodivergence symptoms are experienced, and the ways in which an individual internally and outwardly interacts with their own symptoms. To capture neurodivergent narratives, we plan on conducting semi-structured interviews with neurodivergent engineering students three times over the semester (beginning, middle, end). Initial interview protocols for each interview will be developed and adjusted throughout the interview data collection process. An initial compilation of relevant interview questions was compiled from previous research and from the objectives of the research study. This initial pool of questions will then be refined based on our thematic findings and using the nuanced language identified on the social media platforms TikTok, Reddit, and Twitter. Results of this work will be presented in this paper as an interview protocol that will continue to be adapted as part of this larger research study, but can also be used as a starting point for researchers exploring similar topics in capturing the experience of neurodivergent engineering students.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1007/978-3-030-78092-0_40
