What Makes One Intrinsically Interested in IT? An Exploratory Study on Influences of Autistic Tendency and Gender in the U.S. and India
通过两项调查，发现自闭倾向是影响IT兴趣的重要因素，且控制该因素后，美国男女的IT兴趣差异不再显著，而印度则无显著性别差异。
To increase diversity and inclusion in IT enrollment and employment, we must first answer the question: What makes one intrinsically interested in technology in the first place? To the extent that one’s choice of an IT education and career is driven by such intrinsic interest, the answer to this question will inform the various educational and organizational efforts to enhance social inclusion through increasing neurodiversity and gender diversity. Building on prior literature on the empathizing-systemizing (E-S) theory of autism, we employ two studies to explore the influences of autistic tendency and gender on intrinsic interest in IT. In Study 1, survey data from a U.S. sample provide support for autistic tendency as an antecedent of IT interest. The data also show that after controlling for individual variations in autistic tendency, the seemingly higher IT interest exhibited by U.S. men versus women becomes nonsignificant, demonstrating autistic tendency as an underlying mechanism by which differences in IT interest manifest between men and women. In Study 2, we replicate the model with respondents from India. Survey results again provide support for autistic tendency as an antecedent of IT interest and further show that there exists no significant gender difference in IT interest in India, regardless of whether autistic tendency is controlled for. This research offers a belated academic acknowledgment of the autism-IT linkage for the IS field and a comprehensive introduction of the E-S theory as a theoretical lens for multiple areas of IS research, including social inclusion, adoption, neuroIS, and evolutionary theory building. The finding of a nonsignificant difference in IT interest between men and women in the U.S. and India dispels a gender stereotype and demonstrates that collective-level gender labels may yield misleading results when individual-level factors, such as autistic tendency, masquerade as gender differences. Implications for IS practice are also discussed.