Cross-disciplinary Challenges: Navigating Power Dynamics in Advocating an Entrepreneurial STEM Curriculum.
Saved in:
| Title: | Cross-disciplinary Challenges: Navigating Power Dynamics in Advocating an Entrepreneurial STEM Curriculum. |
|---|---|
| Authors: | Ho, Chun Sing Maxwell1 (AUTHOR) hocs@eduhk.hk |
| Source: | Research in Science Education. Feb2025, Vol. 55 Issue 1, p11-39. 29p. |
| Subject Terms: | *Social exchange, *Social norms, *School principals, *Science teachers, Power (Social sciences) |
| Abstract: | Entrepreneurial STEM, an interdisciplinary approach blending STEM and entrepreneurship education, has become a new trend for cross-subject collaboration that aims to instill an entrepreneurial mindset in students, enabling them to apply their STEM knowledge across various contexts. In this study, we investigate the challenges and corresponding strategies of head science teachers who initiated an entrepreneurial STEM (Science, Technology, Engineering, Mathematics) curriculum in their schools. Grounded in social exchange theory, we explore how head science teachers with entrepreneurial attributes navigated asymmetrical power distribution presented by principals and other subject heads. This collective case study focuses on three schools in Hong Kong that successfully implemented a renowned entrepreneurial STEM curriculum. The findings reveal a common trajectory among head science teachers: initial enthusiastic promotion of the curriculum while meeting resistance; a downscaling and team reform struggles; and a handover and scale-up. This study illuminates the intricate process of balancing power dynamics and stakeholder perceptions through reciprocal negotiation, which were in turn shaped by societal norms. [ABSTRACT FROM AUTHOR] |
| Copyright of Research in Science Education is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
|
Full text is not displayed to guests.
Login for full access.
|
|
Be the first to leave a comment!