The 2021 Symposium will take place on two afternoons. Ten speakers from around the U.S. will give 15-minute presentations about a range of topics, including:
- Day 1 – Tuesday, March 16: Attendees will hear about the ethical challenges of using data science to inform interventions, reforms that are happening in the hiring and retention of women in academia, and data science approaches to increase enrollment and graduation of students, particularly from underrepresented groups.
- Day 2 – Wednesday, March 17: Attendees will hear about how a variety of institutions, including Penn State, are using data to inform innovative approaches for increasing diversity, the importance of growth mindsets for student success, considerations for ensuring health equity, and a new Penn State collaboration with the NSF National Center for Engineering Statistics.
View the full agenda, including abstracts for each talk, below.
Day 1 Agenda (Tuesday, March 16)
|Time (ET)||Title (Click the title to view the abstract)||Presenter|
|1:00 p.m.||Welcoming Remarks||Jenni Evans, Director of ICDS and Professor of Meteorology and Atmospheric Science|
|Session Chair: Roderick Lee, Associate Professor of Information Systems, Penn State Harrisburg|
|1:10 p.m.||Data, Ethics, and Social Values: A Brief Tour||Daniel Susser, Assistant Professor of Information Sciences and Technology, Penn State|
|1:30 p.m.||The Cosmetic Side of Quantification: Exploring Institutional Demographic Data||Ashley Patterson, Assistant Professor of Education, Penn State|
|1:50 p.m.||Equity-Minded Approaches to Faculty Evaluation||KerryAnn O’Meara, Professor of Higher Education and Special Assistant to the President for Strategic Initiatives, University of Maryland|
|2:10 p.m.||Measuring Undergraduate Success Trajectories to Support Improving Higher Education Equity and Inclusion||Richard Arum, Dean of the School of Education and Professor of Sociology and Education, University of California Irvine|
|2:30 p.m.||Eliminating Equity Gaps through Data and Analytics||Timothy Renick, Professor of Religious Studies and Executive Director of the National Institute for Student Success at Georgia State University|
|2:50 p.m.||Panel Discussion with Day 1 Presenters||Moderated by Vasant Honavar, Professor and Edward Frymoyer Chair of Information Sciences and Technology|
Day 2 Agenda (Wednesday, March 17)
|Time (ET)||Title (Click the title to view the abstract)||Presenter|
|1:00 p.m.||Welcoming Remarks||Lora Weiss, Senior Vice President for Research, Penn State|
|Session Chair: Lynette Yarger, Associate Professor of Information Sciences and Technology, and Assistant Dean for Equity and Inclusion, Schreyer Honors College|
|1:10 p.m.||ImPACT IT: Increasing the Participation and AdvanCemenT of Women in Information Technology||Adriane Randolph, Professor of Information Systems, Kennesaw State University|
|1:30 p.m.||Using Internal and Peer Student Data to Drive Equity||Jeff Adams, Associate Vice President and Associate Dean for Undergraduate Education, Penn State, and
David Smith, Associate Dean for Advising and Executive Director Division of Undergraduate Studies, Penn State
|1:50 p.m.||Science of Science: Big Data and AI for understanding the research ecosystem||Sarah Rajtmajer, Assistant Professor of Information Sciences and Technology, Penn State|
|2:10 p.m.||Creating Growth Mindset Cultures that Support Diversity in Science||Mary Murphy, Professor of Psychological and Brain Sciences, Indiana University|
|2:30 p.m.||Stop Blaming the Data - Health Equity in the Age of AI||Fay Cobb Payton, Professor of Information Technology and Business Analytics, North Carolina State University|
|2:50 p.m.||Remarks||Kathleen Bieschke, Vice Provost for Faculty Affairs, Penn State|
|3:00 p.m.||Panel Discussion with Day 2 Presenters||Moderated by Amulya Yadav, PNC Career Development Assistant Professor of Information Sciences and Technology|
Abstracts – Day 1
Data, Ethics, and Social Values: A Brief Tour
Presented by Daniel Susser
Data science can be a powerful force for good, but it can also do harm—to individuals and to society. In this talk, I outline significant ethical issues that data scientists must navigate in their work, from concerns about privacy, fairness, and accountability, to emerging questions about data and democratic oversight. As we increasingly rely on data-driven technologies to advance scientific knowledge, inform policymaking, and automate decision-making and intervention, we must ensure that these systems reflect and enact our shared ethical and social values.
The Cosmetic Side of Quantification: Exploring Institutional Demographic Data
Presented by Ashley Patterson
Universities are under pressure to represent the ethno-racial diversity of their students bodies in the most favorable light possible. Websites and marketing materials are often the sites where this pressure is played out. Through an analysis of demographic data portrayed on 158 college and university websites, we identified three practices higher ed institutions undertake when enhancing the appearance of diversity on campus. These findings have subsequently led to a framing inquiry that can be utilized to analyze the presence of what we title ‘cosmetic diversity.’
Equity-Minded Approaches to Faculty Evaluation
Presented by KerryAnn O’Meara
In this presentation, Dr. O’Meara will share lessons learned from research, practice and funded projects on equity-minded approaches to faculty evaluation. Current funded projects examine equity in hiring, workload, promotion and tenure policy reform, and other discretionary spaces in academic affairs. She will highlight the conditions, and routine practices and policies that shape equity in faculty affairs.
Measuring Undergraduate Success Trajectories to Support Improving Higher Education Equity and Inclusion
Presented by Richard Arum
The Next Generation Undergraduate Success Measurement Project at the University of California, Irvine (UCI) is a pilot demonstration project to develop and implement a state-of-the-art measurement project to improve our understanding of the value of undergraduate educational experiences and promote evidence-based models of undergraduate student success. One central goal of the project is to inform efforts to improve institutional practices and performance to advance educational equity and success. The project includes the use of administrative data and college record data, data from the learning management system Canvas (LMS data), survey data, and data from performance assessments. Survey data and performance assessments are being collected on two cohorts of each 1,200 undergraduate students. The first cohort started in the academic year 2019/20 and the second cohort started in the academic year 2020/21. Both cohorts participate in the study over the course of two years and complete up to 40 surveys per year. These surveys include questions about educational attitudes, aspirations, motivation, behavior and experiences at college, including discrimination, micro-aggression and support from faculty, staff and peers. A few preliminary findings from the project will be shared and implications for promoting equity and inclusion will be discussed.
Eliminating Equity Gaps through Data and Analytics
Presented by Timothy Renick
For the past decade, Georgia State University has been at the leading edge of demographic shifts in the southeast. While doubling the numbers of non-white and low-income students it enrolls, the university has simultaneously raised graduation rates by 23 percentage points and closed all equity gaps based on race, ethnicity, and income-level. It now awards more bachelor’s degrees to African Americans than any other non-profit college or university in the nation. Through a discussion of s series of data-informed, scaled innovations including chat bots, predictive-analytics-based advising, and micro grants, the session will cover lessons learned from Georgia State’s transformation and outline several practical and low-cost steps to improve outcomes for underserved students.
Abstracts – Day 2
ImPACT IT: Increasing the Participation and AdvanCemenT of Women in Information Technology
Presented by Adriane Randolph
Currently, only 20% of Information Systems faculty at the rank of Full Professor are women. There lacks enough granularity in the data to understand how these percentages apply to women from traditionally-underrepresented groups like African-Americans, Native Americans, and Latinx. In conjunction with the Information Systems academic field’s professional society, the Association for Information Systems, a team of investigators across five institutions are working to promote the advancement of women in the Information Systems field, with an emphasis on increasing transitioning women to “Full.” A three-year, million-dollar grant awarded by the National Science Foundation Organizational Change for Gender Equity in STEM Academic Professions (ADVANCE) program titled, “ImPACT: Increasing the Participation and AdvanCement of Women in Information Technology” (Award # 2017130) is currently underway. This NSF ADVANCE Partnership grant aims to address the lack of gender equity within the Information Systems academic field; increase the number of women, especially at the rank of Full Professor; and catalyze action and foster accountability around supporting women’s efforts to advance to Full.
Using Internal and Peer Student Data to Drive Equity
Presented by Jeff Adams and David Smith
Penn State is engaged in two university-level initiatives explicitly focused on improving the educational outcomes for non-advantaged students in specific higher education sectors. The American Talent Initiative (ATI) strives to increase the number of low-income students graduating from the nation’s top institutions while the APLU’s Powered by Publics (PxP) initiative focuses on eliminating the achievement gap for low-income, minority, and first-generation students. Both projects provide opportunities for Penn State to benchmark student data against select peers. Further, in a joint effort between Teaching and Learning with Technology (TLT) and the Division of Undergraduate Studies (DUS), Penn State is piloting innovative approaches to using institutional data to facilitate proactive outreach to students. As part of this data-informed approach to student success, this initiative is developing training materials for the academic advising community around the ethical use of data. This presentation will provide broad overviews of these projects to support further discussion of how data can be used to drive equity.
Science of Science: Big Data and AI for understanding the research ecosystem
Presented by Sarah Rajtmajer
This presentation will provide an overview a Penn State-led effort to develop computational approaches to extract and evaluate information from published academic work. Dr. Rajtmajer will discuss the implications of this work and, more broadly, emerging work in the science of science for understanding the research ecosystem. Within this ecosystem, researchers are looking to understand the impact of scientific investment, particularly as it relates to diversity, equity and inclusion. The work Dr. Rajtmajer will outline includes outcomes from the Penn State-led DARPA SCORE program and a new collaborative effort with the NSF National Center for Engineering Statistics (NCSES).
Creating Growth Mindset Cultures that Support Diversity in Science
Presented by Mary C. Murphy
In this talk, I will define what growth mindset cultures are and how they are communicated to students. I will present research on how growth mindset cultures reduce identity threat and belonging uncertainty among people from underrepresented backgrounds. Drawing on several of our recently published studies, I will show how we harness many forms of data to examine how faculty mindset beliefs and behaviors create a context of identity safety or identity threat for people from structurally disadvantaged groups—with downstream consequences for interest, persistence, and performance. I will discuss a new project, called the Student Experience Project, that harnesses technology to help STEM faculty across 6 universities create growth mindset cultures in their classes, and show new evidence about how these practices shape students’ experiences in class. I will end with thoughts about what individuals and institutions can do to harness data and different methodological approaches to build and maintain learning environments that support diversity in science.
Stop Blaming the Data: Health Equity in the Age of AI
Presented by Fay Cobb Payton
My earlier research used interorganizational theory focused on information sharing and the impacts on health organizations and patients given the increased needs to share clinical and financial information. This work shifted to include health disparities via comorbid conditions (including breast cancer, mental health, HIV), data modeling and constructing user experience artifacts. While technology enabled organizations to change the point of care delivery, AI has extended how providers and payors manage, diagnosis, treat and evaluate patient populations and the associated health conditions. A central thread of my research is leveraging, creating and using information to assess society (community) needs and implications. Yet, much of this research rests on health datasets which are inherently bias. Dataset bias, however, does not exist in a vacuum. Health data creation and curation can acerbate biases in analyses, treatment and hence, care decision-making and delivery. I will discuss how my research continues to examine disparities within and across the stove piles of disciplinary silos, and why health equity in the age of AI requires researchers to stop singularly blaming the data for the biases that exist.