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"Sticky and Complicated": Towards Re...
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Rodier, Robert C.
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"Sticky and Complicated": Towards Removing Inequity in Academic Program Design.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
"Sticky and Complicated": Towards Removing Inequity in Academic Program Design./
作者:
Rodier, Robert C.
其他作者:
Bowman, Brandy S.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2024,
面頁冊數:
133 p.
附註:
Source: Dissertations Abstracts International, Volume: 85-12, Section: A.
Contained By:
Dissertations Abstracts International85-12A.
標題:
Higher education. -
電子資源:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31238965
ISBN:
9798382816012
"Sticky and Complicated": Towards Removing Inequity in Academic Program Design.
Rodier, Robert C.
"Sticky and Complicated": Towards Removing Inequity in Academic Program Design.
- Ann Arbor : ProQuest Dissertations & Theses, 2024 - 133 p.
Source: Dissertations Abstracts International, Volume: 85-12, Section: A.
Thesis (Ed.D.)--Western Carolina University, 2024.
The researchers believe that post-secondary education can provide a greater number of Black students with degrees in the fields of Science, Technology, Engineering, and Math (STEM). Using improvement science, this research aims to test whether providing scaffolded learning and awareness modules around success in STEM programs for faculty and staff can improve curricular design efforts and influence how a cohort discusses and addresses curricular complexity discussions. Black student success in Science, Technology, Engineering, and Math programs in Colleges and Universities has lagged behind White students despite decades of efforts by philanthropy and the U.S. Government. The research used a mixed-methods approach with a pre-/post-survey and a pulse survey, but it leans toward qualitative methods, using discussion boards, interviews, and class discussions. We also used the improvement science framework to test our intervention. We believe the improvement science methodology of faster cycles provides a better way to test ideas and ensures that there are multiple measures for the process along the way.The results are promising. The participants' discussion patterns shifted from the beginning to the end of the intervention, so their discussions became about what they could do to address issues affecting Black student success in their institutions instead of what their institutions should do.The findings show that this is a complex issue that is changing rapidly at the local and national levels. While there are language issues, the academy participants are already addressing these so that their work focuses on "all" students instead of using Diversity, Equity, and Inclusion language. In addition to the language, data disaggregation is critical to identifying subpopulations within the larger group that might need nuanced support.This study offers recommendations on how education leaders can increase an equity lens on curricular complexity work at their institution by scaffolding and integrating learning for faculty, staff, and administrators involved in student learning. The recommendations for next research areas are around considering language - it will be interesting to see how the shift towards "all" students helps or hurts sub-population success with the shift away from social consciousness that was heightened during the COVID-19 pandemic. Political and social issues are also always moving, which affect both language. The undercurrent in creating change at an institution to increase student success for different sub-populations, Black students in particular, is creating awareness about an institutions implicit biases, which is essential across campus and in a review of policies and practices. A third recommendation includes data-informed decision-making. Becoming more data-informed in decision-making goes beyond the Institutional Research office creating reports and publishing them on a website or creating a dashboard; it includes training and use of data to support faculty and staff to do their own analysis and understand who is at the institution and how they can support those students. Data-informed decision-making means allowing institutions to disaggregate their data to have transparent discussions about who is succeeding or not succeeding at their institution and not leaving data questions only in the hands of some at the institution.
ISBN: 9798382816012Subjects--Topical Terms:
641065
Higher education.
Subjects--Index Terms:
Curricular complexity
"Sticky and Complicated": Towards Removing Inequity in Academic Program Design.
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The researchers believe that post-secondary education can provide a greater number of Black students with degrees in the fields of Science, Technology, Engineering, and Math (STEM). Using improvement science, this research aims to test whether providing scaffolded learning and awareness modules around success in STEM programs for faculty and staff can improve curricular design efforts and influence how a cohort discusses and addresses curricular complexity discussions. Black student success in Science, Technology, Engineering, and Math programs in Colleges and Universities has lagged behind White students despite decades of efforts by philanthropy and the U.S. Government. The research used a mixed-methods approach with a pre-/post-survey and a pulse survey, but it leans toward qualitative methods, using discussion boards, interviews, and class discussions. We also used the improvement science framework to test our intervention. We believe the improvement science methodology of faster cycles provides a better way to test ideas and ensures that there are multiple measures for the process along the way.The results are promising. The participants' discussion patterns shifted from the beginning to the end of the intervention, so their discussions became about what they could do to address issues affecting Black student success in their institutions instead of what their institutions should do.The findings show that this is a complex issue that is changing rapidly at the local and national levels. While there are language issues, the academy participants are already addressing these so that their work focuses on "all" students instead of using Diversity, Equity, and Inclusion language. In addition to the language, data disaggregation is critical to identifying subpopulations within the larger group that might need nuanced support.This study offers recommendations on how education leaders can increase an equity lens on curricular complexity work at their institution by scaffolding and integrating learning for faculty, staff, and administrators involved in student learning. The recommendations for next research areas are around considering language - it will be interesting to see how the shift towards "all" students helps or hurts sub-population success with the shift away from social consciousness that was heightened during the COVID-19 pandemic. Political and social issues are also always moving, which affect both language. The undercurrent in creating change at an institution to increase student success for different sub-populations, Black students in particular, is creating awareness about an institutions implicit biases, which is essential across campus and in a review of policies and practices. A third recommendation includes data-informed decision-making. Becoming more data-informed in decision-making goes beyond the Institutional Research office creating reports and publishing them on a website or creating a dashboard; it includes training and use of data to support faculty and staff to do their own analysis and understand who is at the institution and how they can support those students. Data-informed decision-making means allowing institutions to disaggregate their data to have transparent discussions about who is succeeding or not succeeding at their institution and not leaving data questions only in the hands of some at the institution.
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https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31238965
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