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Abstract PurposeAn increasing number of autistic students in the United States are seeking post-secondary education. In response, some post-secondary institutions have established Autism Support Programs (ASP) to address the comprehensive needs of this population. There is little up-to-date, comprehensive information about which institutions host these programs, what types of services they offer, and what is required to access them. MethodsExpanding on previous research, we introduce a new method, which utilizes established data science techniques, to identify ASPs at post-secondary institutions in the U.S. Our technique also allows us to identify the characteristics of the ASPs, including admissions requirements, cost, structure, and supports offered. ResultsResults highlight our method is more efficient and more robust than previous methods from the literature. For example, we identify 49 schools hosting ASPs that were not identified in past literature searches. We report on the characteristics of identified ASPs such as application process, most common supports and program cost. ConclusionThe bi-directional change in the number of ASPs shows that this is an evolving field, requiring automated tools to enable regular updates to data. Although it is promising that a relative handful of U.S. schools have established these programs, a large majority of post-secondary institutions have not, and for those that host them, barriers to access exist, including the necessity of an ASD diagnosis, coupled with up-front and ongoing costs. 

Background When transitioning from high school, autistic job seekers often navigate three different pathways to employment: University, Job Coaching, and Self-Directed (defined as those job seekers who independently complete the job search process, without formal support). Assistive technology may aid job seekers throughout the job seeking process. The aim of this study is to learn more about the challenges and assistive technology that autistic job seekers encounter while navigating these three different employment pathways. Methods Qualitative semi-structured interviews were conducted with fifteen stakeholders in the United States, autistic job seekers and support personnel, within each pathway of the hiring process to gather information regarding the challenges autistic job seekers encounter, and the assistive technology they use to address those challenges. Results From a thematic analysis of these interviews, we found that autistic job seekers along each pathway commonly move through the following, phases of the hiring process or “checkpoints”: resume building, networking, job search, job application, and interviews. Autistic job seekers also face challenges within each checkpoint, such as knowing when and what to disclose; self-efficacy, anxiety, and communication challenges; and a lack of communication from potential employers. We also learned that some self-directed autistic job seekers, when compared to those in the University and Job Coaching pathways, may not be using assistive technologies available in the job search process. From our interviews, we also learned the types of assistive technology that autistic job seekers and assistants use in the job seeking process which can be classified as organizational tools, connectivity tools, and visual media tools. Conclusion and implications Our findings revealed a necessity to connect self-directed autistic job seekers to assistive technology available. Based on these results, we present suggestions for future research and design suggestions for developing assistive technology for autistic job seekers. What this paper adds? We define three career pathways for autistic job seekers: University, Job Coaching and Self Directed. To learn more about the hiring process for autistic job seekers and the assistive technology used within each pathway, we conducted a need-finding study. As a contribution of this study, we discovered challenges along each checkpoint in the hiring process, as well as various forms of assistive technology used to support autistic job seekers when encountering those challenges. For our second contribution, we use the information from these interviews to provide suggestions for the design of future assistive technology within the hiring process, potentially supporting the self-efficacy of autistic job seekers, during this process. 

Successful job search results from job seekers’ well-shaped social communication. While well-known differences in communication exist between people with autism and neurotypicals, little is known about how people with autism collaborate with their social surroundings to strive in the job market. To better understand the practices and challenges of collaborative job seeking for people with autism, we interviewed 20 participants including applicants with autism, their social surroundings, and career experts. Through the interviews, we identified social challenges that people with autism face during their job seeking; the social support they leverage to be successful; and the technological limitations that hinder their collaboration. We designed four probes that represent major collaborative features found from the interviews–executive planning, communication, stage-wise preparation, and neurodivergent community formation–and discussed their potential usefulness and impact through three focus groups. We provide implications regarding how our findings can enhance collaborative job seeking experiences for people with autism through new designs. 

For more than four decades, researchers have used meta‐analyses to synthesize data from multiple experimental studies often to draw conclusions that are not supported by individual studies. More recently, single‐case experimental design (SCED) researchers have adopted meta‐analysis techniques to answer research questions with data gleaned from SCED experiments. Meta‐analyses enable researchers to answer questions regarding intervention efficacy, generality, and condition boundaries. Here we discuss meta‐analysis techniques, the rationale for their adaptation with SCED studies, and current indices used to quantify the effect of SCED data in applied behavior analysis.