ATU receives a $99K grant to advance the study of data science

OCT 06, 2021

Credit: ATU

Arkansas Tech University received a nearly $100K grant to help advance the study of data science.

RUSSELLVILLE, Ark — Arkansas Tech University (ATU) has received a $99,760 grant from the Arkansas National Science Foundation Established Program to Stimulate Competitive Research (NSF EPSCoR) to advance the study of data science.

The Supporting Effective Educator Development (SEED) grant is a two-year grant led by Dr. Weijia Jia, assistant professor of statistics at ATU and director of the university's applied statistics degree program.

"The objective of this research is to collect series of datasets from different disciplines related to the research of faculty members at Arkansas Tech University and preparing data science course projects, practicum courses, capstone projects, and senior design projects for college-level data science education," said Dr. Jia. "The projects and designs would open the door of the data life cycle to the students in data science-related classes, instill curiosity about the data, motivate the students and better prepare them to enter the workforce."

The grant project research committee also includes ATU faculty colleagues, Dr. Jacob Grosskopf, assistant professor of geology, Dr. Christopher Kellner, professor of wildlife science, Dr. Matthew Wilson, assistant professor of agriculture, Dr. Wan Wei, assistant professor of economics, and Dr. Xinli Xiao, assistant professor of mathematics.

The grant is part of the Arkansas NSF EPSCoR Data Analytics that are Robust and Trusted (DART) program.

The Arkansas Economic Development Commission (AEDC), says DART is looking to "address fundamental barriers to practical application and acceptance of modern data analytics" and overcome any barriers that could "derail or impede its full development and contributions."

Some possible barriers to the application and acceptance of modern data analytics that are defined by AEDC are:

  • Big data management
  • Security and privacy
  • Model interpretability

"The data science team of this research also plans to recruit and lead undergraduate students at ATU to participate in data visualization, wrangling, and pre-processing, which provide students a starting point of understanding the vitality, diversity, and complexity of data," said Dr. Jia. "This project will benefit the data science program course designs by easing the burden of the course project preparation and supporting development of data science education at different educational institutions in Arkansas."

For more information about the study of data science at Arkansas Tech, visit or click here.

Credit: ATU

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