Faculty Adopters

The objective of the faculty adopter award is to build/enhance data science capacity at WSSU. The awardees formed a partnership with PI Dr. Deb in order to persistently and meaningfully infuse data literacy and management skills into a variety of disciplines using a modular approach.

Dr. Muztaba Fuad
Department of Computer Science
Winston-Salem State University

Dr. Fuad collaborated in designing and deploying a module that was integrated into the “Computer Architecture” (CSC 3332) class for CS/IT majors during the Spring 2018 semester. The module was designed to expose students to virtualization and cloud computing fundamentals and to provide students with hands-on experiences in using AWS cloud. Specific learning outcomes were 1) to recognize the key properties, techniques, strengths and challenges of cloud computing, and 2) to develop hands-on experience with AWS web interface for virtual machine (VM) provisioning and management. The module contains lecture notes, detailed tutorial to use AWS cloud and a hand-on project where students create two EC2 instances with different hardware and software configurations, analyze instance performances by benchmarking them with CPU- and IO-bound applications and determine how performance scales with the different VM types. The module is available here link. The results of this intervention were published in ACM SIGSE 2019.

Dr. Keith Irwin
Associate Professor
Department of Computer Science
Winston-Salem State University

Dr. Irwin helped developing and implementing a module for the Database Management (CSC 3325) course for CS/IT majors during spring of 2018 with the goal of exposing students to the various types of big data systems and to integrate the study of SQL within these systems. The learning outcomes were 1) to recognize the key properties, strengths, and limitations of important big database management system (BDBMS) such as MapReduce, No-SQL, and New-SQL, and 2) to develop hands-on experience in using SQL within Apache Spark framework to load and query big datasets. The module contains lecture note, a detailed tutorial to use Spark-SQL and a take home project that allows the students to create a Spark application that loads historical Facebook stock prices and uses Spark SQL to query the data. The module is available here link. The results of this intervention were published in ACM SIGSE 2019.

Dr. Russell M. Smith,
Professor of Geography
Faculty Lead for the Spatial Justice Studio @ CDI
Winston-Salem State University

Dr. Smith explored CS+X intervention model that integrates data science literacy into discipline-specific undergraduate courses through faculty partnerships. During the Fall of 2018, Dr. Smith and Dr. Deb jointly designed and piloted a module to a general education course titled as “Environmental Justice and Sustainability” at WSSU. The course was mostly attended by social science majors and examines critical perspectives on social justice and geography. The learning outcomes of the module are 1) to understand how advances in technology enable the field of data science, 2) to be familiar with the sources of data relevant to the discipline, 3) to analyze a data set using spreadsheet and pivot table, and 4) to convey meaningful insights from a data analysis through visualizations. The take home project requires the students to explore the census and environmental data of NC counties, to use their spreadsheet and pivot table manipulation skills to answer ten queries, and to visually represent their findings. The module is available here link. The results of this intervention were published in ACM ITiCSE.

Dr. Greg Taylor
Associate Professor
Department of Management and Marketing
Winston-Salem State University

Dr. Taylor infused data literacy into his Business Analytics (QBA 3370) course, taken mostly by Business Administration and Accounting majors, during Fall of 2019 at WSSU. The goal of this infusion was to build quantitative reasoning and critical thinking skills related to applications of artificial intelligence and data science for business-related majors. Along with the lecture notes and necessary tutorials to use R and Rapid Miner frameworks, the module also offerred four Canvas discussion forums and related classroom discussions exploring future business uses of artificial intelligence, ethical issues, and neural network-based systems. As part of the hands-on project students explored 1) Boston Home Price data set and made predictions using R and caret, and 2) Email data set to detect Spams using Rapid Miner and R. The developed module is available here link.

Dr. Tiffany Adams
Clinical Assistant Professor
Department of Physical Therapy
Winston-Salem State University

Dr. Adams incorporated a data science module into her graduate course Administration and Management I (DPT 8212), taken by Doctor of Physical Therapy (DPT) students, during the Fall of 2019 at WSSU. The goal was to examine the benefits of adding data science into PT and PTA curricula for enhanced student/clinician, patient, and organizational outcomes. As part of the module, the students were taught the necessary data analytics skills using spreadsheet and pivot table, and utilized these new skills to evaluate the quality of PT services being provided at an affiliated pro bono clinic. In the project, students cleaned the data from PT notes for 141 patients of a pro bono clinic to gather information regarding student and clinician compliance in these areas: vital signs assessment, utilization of the Oswestry Disability Index and Neck Disability Index, documentation of patient medications, and functional goal writing. Students then used their data analytics skills to analyze the gathered patients and quality of PT service data and identified any trends and patterns associated with them. The developed resources are available here link

Dr. M. Dee Guillory
Associate Professor of Marketing
Management, Marketing and MIS Department
Winston-Salem State University

Dr. Guillory infused data science concepts to her Social Media Marketing (MKT 4372) class typically taken by business administration majors during the spring of 2020. The learning outcomes are is 1) to understand the importance of marketing analytics with the collection of social media big data, 2) to perform necessary data transformation and cluster analysis, and 3) to measure return on investment (ROI) and to make recommendations due to marketing analytics. Students performed a Social Media Marketing Campaign project by utilizing simulation tool Stukent and gained hand-on experience on data transformation, customer analysis and segmentation, and measuring ROI.