LA Summit

3rd Annual Learning Analytics Summit

Our summit is premised on the idea that faculty involvement with the use of learning analytics is critical to the establishment of a data-guided culture within higher education. With their expert knowledge about their students, disciplines, courses, and programs, instructors of all ranks are in the best position to take advantage of the new insights learning analytics can provide. And in many ways, they are also the ones most capable of making changes based upon those new insights. This can provide all higher education stakeholders with a better understanding of the challenges, opportunities, and choices students face as they travel on their individual pathways toward receiving a college degree.

Through keynote talks, presentations, and working sessions, we will address both the opportunities and barriers of providing learning analytics, data dashboards and predictive models to faculty at institutions of higher learning.

To view other videos from the Summit, visit our Kaltura Channel. 

Learning Analytic Summit Playlist

Opening Remarks

Opening remarks delivered by Kurt Zorn, Acting Vice Provost for Undergraduate Education (OVPUE) at Indiana University Bloomington.

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Learning Analytics and Complex Systems in Higher Ed

Kenote speech delivered by George Siemens, Professor at University of Texas Arlington.

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Ethical Learning Analytics: Do No Harm vs. Do Nothing

John Fritz and John Whitmer

Increasingly, when we observe the research and practice on learning analytics, it is difficult not to be overwhelmed about the ethical implications of using student data. While ethical concerns are raised through learning analytics, a misplaced trend is a “do nothing” approach as a way to assure we “do no harm.” We suggest that this  is a misplaced notion that reduces impact on student success and offer a middle ground approach as a viable solution. 

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Ideas to Action An Evolution of Learning Analytics Engagement at the University of Kansas

Caroline Bennett and Andrea Follmer Greenhoot

This keynote presentation is focused on exploring the evolution of faculty engagement with learning analytics data at the University of Kansas, including the initial and iterative development of a faculty learning community that leverages the strengths of departmental working groups and cross-departmental conversations.

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Learning Analytics for Long-term Faculty Culture Change

Michael Dennin

Much of the early applications of big data and learning analytics in education has been focused either changing individual courses or predicting and influencing student behavior. In this talk, I will discuss both structural and strategic elements that have come together to allow UCI to focus on the connection between learning analytics and faculty culture at the institutional level.

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Opportunities at Origin and Access to Higher Education: Revealing New Dimensions of Exclusions

Marco Molinaro and Stefano Fiorini

Over the past year the Sloan Equity and Inclusion in STEM Introductory Courses (SEISMIC) collaborative (www.seismicproject.org) has provided fertile ground for cross-institutional data exploration. Main data sources for this work derived from widely available student records. In this presentation we will show the potential for integrating this data with other important sources of information; namely opportunity and vulnerability indexes developed at the state level (such as the California Regional Opportunity Index- ROI) or national levels that use data from the US Census.

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A Pandemic of Busywork

Ben Motz, Joshua Quick, Julie Wernert, and Tonya Miles

In this study, we examine this relationship using data observed from a large-scale survey of undergraduate students, from logs of student activity in the online learning management system, and from students' estimated cumulative performance in their courses (n = 4,636). We find that there was a general increase in the number of assignments that students were expected to complete following the transition to remote instruction, and that students who spent more time and reported more effort carrying out this coursework generally had lower course performance and reported feeling less successful.

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Learning Analytics in the Context of COVID-19 A Case Study of Using Network Analysis to Guide Campus Course Offering Plans

Linda Shepard and Mark McConahay

The spread of COVID-19 has caused major disruptions in the higher education space, and colleges and universities faced difficult decisions on how to reopen their campuses. At IU-Bloomington student exposure to other students was reduced by strategically managing course enrollment networks. Evidence supporting effective decision making and reliance on data are provided.

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To view other videos from the Summit, visit our Kaltura Channel