National Science Foundation Research Experience for Teachers in Big Data and Data Science at the University of Louisville

An NSF RET site directed by faculty at the Speed School of Engineering and the College of Education and Human Development.

Download 2022 RET Application Form

The new RET 2022 brochure 

 

 

This project is supported by National Science Foundation grant NSF CNS-1801513
 
PI: Dr. Olfa Nasraoui, Knowledge Discovery & Web Mining Lab, Speed School of Engineering, University of Louisville
Co-PI: Dr. Stephanie Philipp, Department of Middle and Secondary Education, College of Education and Human Development, University of Louisville
Dr. Thomas Tretter, Department of Middle and Secondary Education, College of Education and Human Development, University of Louisville

 

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This award creates a new Research Experiences for Teachers (RET) Site focused on Big Data and data science at the University of Louisville. Each summer, ten high school Science/Technology/Engineering/Mathematics (STEM) teachers will participate in research activities with faculty in labs at the University of Louisville. The teachers will be recruited from Jefferson County Public Schools and the Ohio Valley Education Consortium. Teachers in this site will apply fundamental data science techniques and learn Big Data principles while investigating real world problems with social relevance. The fast pace of low-cost technological innovation and data-centered operations have led to an explosion of data that can be used to solve problems and provide new insights for the future. This includes projects involving areas such as human welfare, healthcare, smart cities, and robotics. The participating teachers will translate their research experiences and knowledge into classroom practice by developing instructional modules and course materials that they will introduce in their classrooms and share with other teachers in their school districts. These activities all contribute to the formation of a community of practice in partnership with the University of Louisville faculty mentors that has the potential to significantly enhance STEM education in the participating school districts.

 RET Site participants will participate in cutting-edge research projects with state-of-the-art data science tools and techniques. The RET Site features a unique combination of faculty mentors from the Department of Computer Engineering and Computer Science who have experience in both hardware and software, which is a synergistic combination in the field of Big Data. The goals include: providing quality research experiences in Big Data and data science for the high school teachers; strengthening the connection between the computing faculty and the school districts; enhancing high school teachers’ understanding of engineering research design and the principles of Big Data; enhancing high school teachers’ abilities to teach engineering and computer science concepts in a compelling way; and preparing engineering graduate students and university faculty to assist and support the high school teachers and their students. As Big Data permeates all sectors of society, Big Data problems often arise in diverse disciplines, not just the computing field. The data-enabled approach is revolutionizing the way scientists and engineers in many fields practice, understand, and make discoveries. Thus, Big Data can impact all STEM subjects and may become fundamental to a quality high school STEM education. This project will help develop a core group of teachers who can bring Big Data principles and methods into their classrooms and excite high school students about the potential of Big Data and data science and its relevance to many possible career paths of the future.

Goals

  1. Provide quality research experiences in Big Data and Data Science for the teachers.
  2. Strengthen the connection between the computing faculty and the school district.
  3. Enhance high school science teachers’ understanding of engineering research design and Computational Thinking through authentic research experiences in Big Data applications.
  4. Strengthen high school science teachers’ pedagogical understanding of how to teach students engineering design principles and the practice of Computational Thinking in alignment with Next Generation Science Standards.
  5. Support high school science teachers to strongly incorporate their engineering research experiences into their teaching, focusing on enhancing engineering design and Computational Thinking in the high school curriculum.
  6. Prepare and support engineering graduate students and university faculty to assist with the content needs of high school STEM teachers and to become aware of research-based pedagogies used with high school students in the context of the Next Generation Science Standards.