Targeted Infusion Project: Infusing Machine Learning in Cognitive Psychology and Cognitive Bias Analysis: Enhancement of the Computer Science and Psychology Curricula

菲斯克大学的目标注入项目（TIP）旨在实施计算机科学和心理学课程的新注入。这个项目将提高心理学学生？理解人工学习和认知的能力。该项目还将开发一门以社会科学为重点的机器学习课程。该提案的新颖方面包括：介绍机器学习（ML）和社会科学应用，以实现平衡的算法开发;提供理解与人工智能（AI）协议相关的学习和偏见的经验;创建与ML和AI中的偏见和学习相关的计算机科学和社会科学课程模块;并在HBCU提供这方面的经验，使代表性不足的学生进入STEM研究生院和职业。该提案将纳入定量方法，并将研究纳入社会科学和计算机科学课程的讲座和实验室部分。该项目的目标是创新课程，以便更好地为社会科学和计算机科学的学生提供越来越多学科的世界观：1）为社会科学开发一门机器学习入门课程，在核心机器学习概念以及对社会科学的应用和影响之间取得平衡，2）开发一门心理学课程，重点关注学习和认知中的深度学习范式，3）为其他计算机科学和心理学课程开发模块，加强计算机科学和心理学之间的联系。这些目标将为核心科学技能提供坚实的基础，特别是计算，认知发展，算法评估和解决问题的定量技能。这个跨学科的方法将与菲斯克大学正在进行的几项举措协同作用，并对学生的培训，学习和STEM学科的职业生涯产生变革性的影响。这个奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

The Targeted Infusion Project (TIP) at Fisk University seeks to implement a novel infusion of the computer science and psychology curriculum. This project will enhance psychology students? abilities to understand artificial learning and cognition. This project will also develop a course in machine learning focused on social sciences. Novel aspects of this proposal include: providing an introduction to machine learning (ML) and applications to social science for balanced algorithm development; offering an experience of understanding learning and bias related to artificial intelligence (AI) protocols; creating computer science and social science curriculum modules relating to bias and learning in ML and AI ; and offering this experience at a HBCU, so that underrepresented students are funneled into STEM graduate schools and careers.This proposal will incorporate quantitative methods and include research into lecture and laboratory components of social science and computer science courses. The goal of this project is to innovate the curriculum in order to better prepare students in the social sciences and computer sciences for an increasingly multidisciplinary worldview: 1) develop an introductory machine learning course for social sciences which balances between core machine learning concepts as well as application and implication to the social sciences, 2) develop a psychology course that focuses on deep learning paradigms in learning and cognition, 3) develop modules for other computer science and psychology courses which reinforce the connections between computer science and psychology. Together the objectives will provide a strong foundation in core scientific skills, particularly quantitative skills in computation, cognitive development, algorithm assessment, and problem solving. This interdisciplinary approach will synergize with several ongoing initiatives at Fisk University and have a transformative effect on student training, learning and careers in STEM disciplines.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.