Use of a Common Professional Language to Improve Neurodivergent STEM Scholar Sense of Belonging

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Monroe, C., Coplan, J., Sullivan, D., & Matte, R. W. (2025). Use of a Common Professional Language to Improve Neurodivergent STEM Scholar Sense of Belonging. New Directions for Higher Education, 2025(209), 27-33. https://doi.org/10.1002/he.20522

Publication date: 1 Mar 2025 Added to AutiHub: 7 Aug 2026 Type: Article Article language: English
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4
Publication authors identified as autistic
1 / 4 (25.0%)
  1. Christin Monroe *
  2. Jan Coplan
  3. Dylan Sullivan
  4. Rebecca W. Matte

Abstract

ABSTRACT In a 1‐credit evolving STEM Community and Identity course, low‐income and neurodivergent students participate in cohort activities to build community and develop their professional STEM portfolios. The strengths‐based Birkman Method personality survey is used to enhance STEM identity and clarify communication and work styles. This course involves collaboration between STEM faculty, education faculty, and career counselors. Many neurodivergent students entering college lack confidence and struggle to identify and communicate their strengths, which can affect their academic performance and professional growth. This study documents the benefits of using a common language, based on the Birkman Method, for students, mentors, and career counselors. The language is integrated into the course, mentoring sessions, and students' professional portfolios. As a result, students feel a stronger sense of belonging within their cohort and build more meaningful connections with mentors and career counselors. The Birkman Method also helps neurodivergent students take a more informed approach to job searching, improving their morale, mental health, and employment retention. This paper outlines activities designed to foster a community of scientific thinkers and support professional development at all academic levels of postsecondary education.

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Among occurrences linked to AutiHub author records: 1 / 15 (6.7%). Distinct cited authors identified as autistic: 1 / 43 (2.3%).
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Among linked cited-author occurrences only. Across all cited-author occurrences: 14 / 44 (31.8%). Distinct linked cited authors not identified as autistic: 13 / 14 (92.9%).
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