This work investigates how innovations propagate through two professional networks (guilds): the Kern Entrepreneurial Engineering Network (KEEN) and the Consortium to Promote Reflection in Engineering Education (CPREE). Previous research has demonstrated that the adoption of pedagogical innovations is supported by the socialization of the innovation among potential adopters. In this work, we use social network analysis to explore the impact of professional connections on innovation adoption. Our research questions are: (1) How does overall social structure differ between guilds? (2) How do measures of social network structures relate to innovation adoption? A survey was distributed to members of KEEN and CPREE to capture the interactions respondents had while adopting the guild’s innovation. Social networks were generated for each guild and each respondent. These networks were analyzed to identify relationships between social network measures and the frequency of use of the innovation. Responses to open-ended questions were analyzed using thematic coding. The guilds’ overall structures impacted the formation and structure of distinct clusters/cliques, but these differing structures did not appear to affect sustained adoption. Individuals’ ego networks demonstrated a weak negative correlation between the frequency of adoption and the individual’s ego network density. Our results imply that having a diverse network exposes instructors to more ideas or allows them to see one idea from many perspectives.
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The social side of innovation
Abstract Innovation is fundamental to cumulative culture, allowing progressive modification of existing technology. The authors define innovation as an asocial process, uninfluenced by social information. We argue that innovation is inherently social – innovation is frequently the product of modifying others' outputs, and successful innovations are acquired by others. Research should target examination of the cognitive underpinnings of socially-mediated innovations.
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- Award ID(s):
- 1730678
- PAR ID:
- 10292199
- Date Published:
- Journal Name:
- Behavioral and Brain Sciences
- Volume:
- 43
- ISSN:
- 0140-525X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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