CSUF HSI Conference
April 25 – 27, 2018
Dissecting the STEM Education Ecosystem in Hispanic Serving Institutions:
Regional Insights from Southern California
Purposes: The three-day workshop (April 25-27, 2018) will discuss six topics relevant to and representing the ecosystem processes of undergraduate STEM education at HSIs:
- Preparing pre-college students – gaps in and opportunities for entering STEM majors;
- Transforming the First-Year College Experience - innovative educational technology and inclusive pedagogies for student learning and retention in STEM;
- Smoothing transitions from two- to four-year HSIs - opportunities and challenges for institutional partnerships;
- Building coalition among stakeholders in the undergraduate research experience - opportunities and challenges for student persistence;
- Removing academic barriers - gaps and opportunities for academic remediation; and
- Sustaining ecosystems on HSI campuses - social and cultural inclusiveness for student success.
Outcomes: The conference agenda will focus on the six topics covering HSI undergraduate STEM education ecosystems (see above). The outcomes will provide insights to improve undergraduate STEM education at HSIs in Southern California and result in a report that will:
- demystify factors impacting pre-college Hispanic and first-generation students on selecting STEM fields;
- identify feasible educational technology and innovative pedagogies for both first-year college and transferred community college students;
- provide mechanisms to leverage resources for the undergraduate student research experience at large regional urban comprehensive HSIs; and
- produce a general ecosystem model for our understanding of unique academic, social and cultural factors influencing STEM education of Hispanic and other underrepresented students at HSIs.
The report will also serve as an evidence-based synthesis to help CSUF establish a center for undergraduate STEM education at HSIs, one of its main missions and current strategic goals.
This material is based upon work supported by the National Science Foundation under Grant No. 1764323. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.