Targeted Infusion Project: Infusion of Computational Science Based Data Analytics Coursework and Research to Strengthen and Enrich the Lane College Undergraduate Chemistry Program

历史黑人学院和大学本科项目(HBCU-UP)通过有针对性的灌输项目，支持基于证据的创新模式和方法的开发、实施和研究，以改善HBCU本科生的准备和成功，使他们能够攻读STEM研究生课程和/或职业。莱恩学院的这个项目将通过引入计算化学和数据分析、研究机会和学术参与/传播机会，为学生提供在整个入学过程中以及在学士学位学习之后受益的技能培养技术。多年来，人们对STEM专业的兴趣与日俱增，因此需要为攻读学士学位的学生做好非传统、跨学科的准备。该项目的总体目标是提高化学领域，特别是计算化学和相关领域中代表性不足群体的学生的兴趣、准备和参与程度。这一目标将通过以下方式实现：1)向学生展示和培训计算科学技术；2)通过有指导的研究经验增加进行科学研究的学生人数；3)鼓励本科生参与科学话语和数据传播；4)增加化学相关学科研究生的人数。该项目将作为一个案例研究，帮助那些历史上没有接触过STEM教育或研究机会的学生做好准备。这些努力还将增加计算化学和数据科学领域的科学知识体系。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The Historically Black Colleges and Universities Undergraduate Program (HBCU-UP) through Targeted Infusion Projects supports the development, implementation, and study of evidence-based innovative models and approaches for improving the preparation and success of HBCU undergraduate students so that they may pursue STEM graduate programs and/or careers. The project at Lane College will provide students with exposure to skill-building techniques that will benefit them throughout their matriculation as well as beyond their baccalaureate studies through introduction to computational chemistry and data analytics, research opportunities and scholarly engagement/dissemination opportunities. As the interest in STEM majors has grown over the years, so has the need for non-traditional, interdisciplinary preparation of students working towards the baccalaureate. The overall goal of the project is to increase the interest, preparation and inclusion of students from groups underrepresented in the field of chemistry, specifically computational chemistry and related areas. This goal will be accomplished by 1) exposing and training students in computational science techniques; 2) increasing the number of students conducting scientific research through mentored research experiences; 3) encouraging the engagement of undergraduate students into scientific discourse and dissemination of data and 4) increasing the number of students attending graduate school for a chemistry-related discipline. This project will serve as a case study on the preparation of students who, historically, have not been exposed to STEM education or research opportunities. These efforts will also increase the body of scientific knowledge in the areas of computational chemistry and data science.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.