Preparing Autistic Students for the AI Workforce

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Jang, J., Butler, R., McDaniel, R., San, A., Boyer, D. M., Asadi, S., Kubina, R., Mishra, T., & Begel, A. (2025). Preparing Autistic Students for the AI Workforce. Proceedings of the 33rd ACM International Conference on the Foundations of Software Engineering, 760-771. https://doi.org/10.1145/3696630.3727233

Publication date: 23 Jun 2025 Added to AutiHub: 21 Oct 2026 Type: Other Article language: English
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Authors

Publication authors
9
Publication authors identified as autistic
0 / 9 (0.0%)
  1. JiWoong Jang
  2. Ren Butler
  3. Rory McDaniel
  4. Aidan San
  5. D. Matthew Boyer
  1. Somayeh Asadi
  2. Richard Kubina
  3. Taniya Mishra
  4. Andrew Begel

Abstract

Software project courses too often focus instruction on technical skills but leave necessary communication and teamwork skills as an exercise for the learner. When autistic students take these courses, they often find difficulty fitting into teams with non-autistic students because of their different styles of communication. To explore how to help autistic students adapt to non-autistic normative software engineering environments, we designed and taught a first-of-its-kind online project course on AI, explicitly teaching communication and teamwork skills with purposefully designed scaffolds. After the course, students were matched with professional, online summer internships in which they could apply the skills they learned. We detail the course structure, including the pedagogical strategies employed and the specific challenges encountered. Our experiences reveal key elements that contributed to the course's success, such as the importance of adaptive teaching methods and the need for carefully considered instructor training for teaching neurodivergent learners in software engineering. We share this report to provide guidance for educators, researchers, and advocates seeking to develop effective computing education programs that include autistic students.

Bibliography cited by this reference

Cited references are imported from external metadata sources when they are available. The list may be partial.

Cited bibliography overview

These indicators describe the bibliography cited by this publication. An author name is counted each time it appears in one cited reference, so the same person can be counted more than once. Names not yet linked to an author already present in AutiHub are treated as unknown, not as non-autistic. Last computed: 28 Oct 2026 01:01.

Cited references
54
With a DOI
25
Without a DOI, from raw bibliography text
29
1 / 54 (1.9%) cited references include at least one author identified as autistic.
References with data to complete
8 / 54 (14.8%)
References with detected author names
46 / 54 (85.2%)
Without detected author names
8
Without a structured title
8
Without a stable identifier
28
References with raw author names still to review
8
References with external metadata lookup issues
0
These indicators apply to cited references displayed on this page, after technical duplicates have been merged. A reference without a DOI can still support author statistics when a title and author names are available.
Author names detected in the cited bibliography
97
From DOI or external metadata
97
From validated raw bibliography text
0
Raw names already validated
0
Raw names still to review
8
27 / 97 (27.8%) names are linked to an author already present in AutiHub. 70 / 97 (72.2%) names are not yet linked.
Names linked to a person identified as autistic
1 / 97 (1.0%)
Calculated across all author names detected in the cited bibliography. Among names linked to an author already present in AutiHub: 1 / 27 (3.7%). Distinct people identified as autistic: 1 / 93 (1.1%).
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