Presentations and Resources can be downloaded by clicking on links for the presenter(s). The 8 DASI sessions had an average attendance of 21.

1:30 PM Wednesday, Teaching Statistics to Generation Z and Providing a Foundational Understanding for Analytics
Abstract: This session will mainly focus on HOW statistics are taught rather than on WHAT statistical procedures should be taught. Good instruction communicates effectively with the students taking the class and prepares them to be able to effectively use what was taught when they have the need to use the statistical procedures in the future. Generation Z students are quite different from other generations. A discussion will address these differences and explore ideas about how to engage generation Z students in statistics learning. Analytics has permeated decision making in almost all areas. A second discussion will also explore presenting statistics learning with an analytics perspective.
Session chair: Bob Andrews, Virginia Commonwealth University
Presenters:
Ping Wang, James Madison University Presentation on Generation Z students
Bob Andrews, Virginia Commonwealth University Excel file: Analytics oriented presentation of typical statistics procedures

3:00 PM Wednesday, What Resources Would be Most Useful to a Data, Analytics or Statistics Instructor?
Abstract:Panel lead discussion of what types of resources would provide the most help to instructors of courses in data, analytics and statistics. The panel includes representatives from potential providers of resources (leaders from the DSI DASI SIG, publishers of text material and software providers). The publishers and software providers strive to provide resources that will assist with instruction and the goal is for the Data, Analytics and Statistics Instruction Specific Interest Group to provide resources on the DSI website, such as a list of databases that could be used for instruction.
Session chair: Bob Andrews, Virginia Commonwealth University
Panel Members:
Bill Miller, Georgia College & State University PowerPoint Presentation and Excel file with list of databases
Kellie Keeling, University of Denver Issues of importance
Aaron Arnsparger, Cengage; Nicole DeFazio, MINITAB; Ruth Hummel, JMP; Quinton Nottingham, Virginia Tech & Hawkes Learning Author

8:45 AM Thursday, Workshop on the Use JMP & R Software for Analytics Instruction
Abstract:Workshop will compare a "point and click" environment versus a programming environment; JMP versus SAS Enterprise Miner and SPSS Modeler and "for profit" versus "open source" software from both an instructor and student perspective. It will also provide recommended approaches to using the popular, open-source, statistical programming environment R (in conjunction with R Studio) in an undergraduate business analytics course with a focus on implementation issues, challenges, and lessons learned.
Session chair: Bob Andrews, Virginia Commonwealth University
Presenters:
Barry Wray & Stephen Hill, UNC-Wilmington; JMP & R Presentation

10:15 AM Thursday, Prescription for Prescriptive Analytics Course Content & a Case Study for Prescriptive Modeling
Abstract: After a discussion of confusion in the marketplace (and academia) around the definition of prescriptive analytics, a proposed set of topics will be specified with the purpose of providing students with a solid background in this area of analytics. This will be followed by a case study to illustrate an intuitive approach to teaching classification trees using JMP. It introduces interactive tools for exploring potential bivariate and multivariate relationships and uses insights gained through exploratory analysis and logistic regression to motivate the introduction of tree-based methods. It will demonstrate how to build and interact with decision trees, how to interpret decision tree models, and how to extend tree-based models using bootstrapping (bootstrap forest) & boosting (boosted trees).
Session chair: Bob Andrews, Virginia Commonwealth University
Presenters:
Jeff Camm, Wake Forest Prescription for Prescriptive Analytics Course Content
Ruth Hummel, JMP Finding Love in a Classification Tree

1:30 PM Thursday, Teaching Data Strategy & Governance and Demo of the use of Minitab Software for Data Analysis Instruction
Abstract: (This has been adjusted to what actually happened in the sesssion when Rose Sebastianelli, University of Scranton was not able to present due to the flu.)
Session has two segments: 1. Presentation of opportunities and challenges in teaching a course on data strategy and governance so that students understand the tools, techniques, and frameworks to help an organization improve the collection, storage, sharing, and using of data plus governing these activities to ensure the usability, accuracy, integrity, and security of data throughout the data lifecycle.
2. Demonstration of MINITAB capabilities that are useful for statistics and data analysis instruction.
Session chair: Bob Andrews, Virginia Commonwealth University
Presenters:
Uma Gupta, State University of New York - Buffalo State College Teaching Data Strategy & Governance
Nicole DeFazio, MINITAB Presentation follow up information

3 PM Thursday, Experiences with Innovative Instruction: Methods that Move Away from Pure Lecture
Abstract: Report on faculty efforts to improve the learning experience in individual classes at their respective institutions. These efforts involve: flipping the classroom, online software for interacting with students such as Piazza and BlueJeans, presenting dynamic (algorithm generated) examples for the students to work in class, and using principles of Ignatian Pedagogy (IPP) that make the student aware of the context they bring to the subject and require a significant of amount of reflection. Attendees will be encouraged to discuss ideas presented.
Session chair: Bob Andrews, Virginia Commonwealth University
Presenters:
Bob Stine, Wharton School of the University of Pennsylvania; Impact of Analytic Emphasis
Mary Malliaris, Loyola University Chicago; Teaching with Ignatian Pedagogy
Jerry "Buddy" Bilbrey, Lander University; Algorithm Problems Comparison

4:30 PM Thursday, Content and Delivery of Analytics Instruction for Undergraduate and MBA Students
Abstract: Instructional faculty will share their experiences in creating undergraduate courses and an undergraduate minor in analytics, as well as delivering an online analytics course to MBA students. Challenges addressed during the session will include software used, course content, student capabilities, faculty expertise, and limited resources. Time will be allotted for discussion and feedback from those attending the session.
Session chair: Bob Andrews, Virginia Commonwealth University
Presenters:
Ina Markham, James Madison University; Analytics at JMU
Dmitriy Shaltayev, Christopher Newport University; Analytics at CNU
Binshan Lin, Louisiana State University in Shreveport; Experience at LSU-Shreveport

10:15 AM Friday, Course Redesign and Restructuring to Improve the Quality of Instruction
Abstract: Session will have three reports: 1. redesign efforts for an undergraduate statistics course motivated a self-study of high rates for D, F & W grades for the course; 2. pros and cons of attempts to improve student learning in the introductory statistics class by using cooperative learning methods (flipped classrooms, POGIL and others); 3. best practices developed by teaching introductory analytics using both a Windows platform and a Mac platform. Attendees will be encouraged to discuss ideas presented.
Session chair: Bob Andrews, Virginia Commonwealth University
Presenters:
Gisela Bardossy, University of Baltimore; Statistics Course Redesign
Ping Wang, James Madison University; Redesign at JMU
Eric Tucker, U.S. Air Force Academy; Teaching across the Windows and Macintosh Platforms